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1. Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies

Author: Munn-Chernoff, MA, Johnson, EC, Chou, YL, Coleman, JRI, Thornton, LM, Walters, RK, Yilmaz, Z, Baker, JH, Hübel, C, Gordon, S, Medland, SE, Watson, HJ, Gaspar, HA, Bryois, J, Hinney, A, Leppä, VM, Mattheisen, M, Ripke, S, Yao, S, Giusti-Rodríguez, P, Hanscombe, KB, Adan, RAH, Alfredsson, L, Ando, T, Andreassen, OA, Berrettini, WH, Boehm, I, Boni, C, Boraska Perica, V, Buehren, K, Burghardt, R, Cassina, M, Cichon, S, Clementi, M, Cone, RD, Courtet, P, Crow, S, Crowley, JJ, Danner, UN, Davis, OS, Zwaan, M, Dedoussis, G, Degortes, D, DeSocio, JE, Dick, DM, Dikeos, D, Dina, C, Dmitrzak-Weglarz, M, Docampo, E, Duncan, LE, Egberts, K, Ehrlich, S, Escaramís, G, Esko, T, Estivill, X, Farmer, A, Favaro, A, Fernández-Aranda, F, Fichter, MM, Fischer, K, Föcker, M, Foretova, L, Forstner, AJ, Forzan, M, Franklin, CS, Gallinger, S, Giegling, I, Giuranna, J, Gonidakis, F, Gorwood, P, Gratacos Mayora, M, Guillaume, S, Guo, Y, Hakonarson, H, Hatzikotoulas, K, Hauser, J, Hebebrand, J, Helder, SG, Herms, S, Herpertz-Dahlmann, B, Herzog, W, Huckins, LM, Hudson, JI, Imgart, H, Inoko, H, Janout, V, Jiménez-Murcia, S, Julià, A, Kalsi, G, Kaminská, D, Karhunen, L, Karwautz, A, Kas, MJH, Kennedy, JL, Keski-Rahkonen, A, Kiezebrink, K, Kim, YR, Klump, KL, Knudsen, GP, La Via, MC, Le Hellard, S, Levitan, RD, Li, D, Lilenfeld, L, Lin, BD, Lissowska, J, Luykx, J, Magistretti, PJ, Maj, M, Mannik, K, Marsal, S, Marshall, CR, Mattingsdal, M, McDevitt, S, McGuffin, P, Metspalu, A, Meulenbelt, I, Micali, N, Mitchell, K, Monteleone, A M, Monteleone, P, Nacmias, B, Navratilova, M, Ntalla, I, O'Toole, JK, Ophoff, Roel, Padyukov, L, Palotie, A, Pantel, J, Papezova, H, Pinto, D, Rabionet, R, Raevuori, A, Ramoz, N, Reichborn-Kjennerud, T, Ricca, V, Ripatti, S, Ritschel, F, Roberts, M, Rotondo, A, Rujescu, D, Rybakowski, F, Santonastaso, P, Scherag, A, Scherer, SW, Schmidt, U, Schork, NJ, Schosser, A, Seitz, J, Slachtova, L, Slagboom, PE, Slof-Op't Landt, MCT, Slopien, A, Sorbi, S, ?wi?tkowska, B, Szatkiewicz, JP, Tachmazidou, I, Tenconi, E, Tortorella, A, Tozzi, F, Treasure, J, Tsitsika, A, Tyszkiewicz-Nwafor, M, Tziouvas, K, van Elburg, AA, van Furth, EF, Wagner, G, Walton, E, Widen, E, Zeggini, E, Zerwas, S, Zipfel, S, Bergen, AW, Boden, JM, Brandt, H, Crawford, S, Halmi, KA, Horwood, LJ, Johnson, C, Kaplan, AS, Kaye, WH, Mitchell, J E, Olsen, CM, Pearson, JF, Pedersen, NL, Strober, M, Werge, T, Whiteman, DC, Woodside, DB, Grove, J, Henders, AK, Larsen, J T, Parker, R, Petersen, LV, Jordan, J, Kennedy, MA, Birgegård, A, Lichtenstein, P, Norring, C, Landén, M, Mortensen, PB, Polimanti, R, McClintick, JN, Adkins, AE, Aliev, F, Bacanu, SA, Batzler, A, Bertelsen, S, Biernacka, JM, Bigdeli, TB, Chen, L S, Clarke, TK, Degenhardt, F, Docherty, AR, Edwards, AC, Foo, JC, Fox, L, Frank, J, Hack, LM, Hartmann, AM, Hartz, SM, Heilmann-Heimbach, S, Hodgkinson, C, Hoffmann, P, Hottenga, JJ, Konte, B, Lahti, J, Lahti-Pulkkinen, M, Lai, D, Ligthart, L, Loukola, A, Maher, BS, Mbarek, H, McIntosh, AM, McQueen, MB, Meyers, JL, Milaneschi, Y, Palviainen, T, Peterson, RE, Ryu, E, Saccone, N L, Salvatore, JE, Sanchez-Roige, S, Schwandt, M, Sherva, R, Streit, F, Strohmaier, J, Thomas, N, Wang, JCY, Webb, BT, Wedow, R, Wetherill, L, Wills, AG, Zhou, H, Boardman, JD, Chen, D, Choi, D S, Copeland, WE, Culverhouse, RC, Dahmen, N, Degenhardt, L, Domingue, BW, Frye, MA, Gäebel, W, Hayward, C, Ising, M, Keyes, M, Kiefer, F, Koller, G, Kramer, J (John), Kuperman, S, Lucae, S, Lynskey, MT, Maier, W, Mann, K, Männistö, S, Müller-Myhsok, B, Murray, AD, Nurnberger, JI, Preuss, U, Räikkönen, K, Reynolds, MD, Ridinger, M, Scherbaum, N, Schuckit, MA, Soyka, M, Treutlein, J, Witt, SH, Wodarz, N, Zill, P, Adkins, DE, Boomsma, DI, Bierut, LJ, Brown, S, Bucholz, KK, Costello, EJ, Wit, HJ, Diazgranados, N, Eriksson, JG, Farrer, LA, Foroud, TM, Gillespie, NA, Goate, AM, Goldman, D, Grucza, RA, Hancock, DB, Harris, KM, Hesselbrock, V, Hewitt, JK, Hopfer, CJ, Iacono, WG, Johnson, E O, Karpyak, VM, Kendler, KS, Kranzler, HR, Krauter, K, Lind, PA, McGue, M, MacKillop, J, Madden, PA, Maes, HH, Magnusson, PKE, Nelson, EC, Nöthen, MM, Palmer, AA, Penninx, BWJH, Porjesz, B, Rice, JP, Rietschel, M, Riley, BP, Rose, RJ, Shen, PH, Silberg, J, Stallings, MC, Tarter, RE, Vanyukov, MM, Vrieze, S, Wall, TL, Whitfield, JB, Zhao, H, Neale, BM, Wade, TD, Heath, AC, Montgomery, GW, Martin, NG, Sullivan, PF, Kaprio, J, Breen, G, Gelernter, J, Edenberg, HJ, Bulik, CM, Agrawal, A, Munn-Chernoff, MA, Johnson, EC, Chou, YL, Coleman, JRI, Thornton, LM, Walters, RK, Yilmaz, Z, Baker, JH, Hübel, C, Gordon, S, Medland, SE, Watson, HJ, Gaspar, HA, Bryois, J, Hinney, A, Leppä, VM, Mattheisen, M, Ripke, S, Yao, S, Giusti-Rodríguez, P, Hanscombe, KB, Adan, RAH, Alfredsson, L, Ando, T, Andreassen, OA, Berrettini, WH, Boehm, I, Boni, C, Boraska Perica, V, Buehren, K, Burghardt, R, Cassina, M, Cichon, S, Clementi, M, Cone, RD, Courtet, P, Crow, S, Crowley, JJ, Danner, UN, Davis, OS, Zwaan, M, Dedoussis, G, Degortes, D, DeSocio, JE, Dick, DM, Dikeos, D, Dina, C, Dmitrzak-Weglarz, M, Docampo, E, Duncan, LE, Egberts, K, Ehrlich, S, Escaramís, G, Esko, T, Estivill, X, Farmer, A, Favaro, A, Fernández-Aranda, F, Fichter, MM, Fischer, K, Föcker, M, Foretova, L, Forstner, AJ, Forzan, M, Franklin, CS, Gallinger, S, Giegling, I, Giuranna, J, Gonidakis, F, Gorwood, P, Gratacos Mayora, M, Guillaume, S, Guo, Y, Hakonarson, H, Hatzikotoulas, K, Hauser, J, Hebebrand, J, Helder, SG, Herms, S, Herpertz-Dahlmann, B, Herzog, W, Huckins, LM, Hudson, JI, Imgart, H, Inoko, H, Janout, V, Jiménez-Murcia, S, Julià, A, Kalsi, G, Kaminská, D, Karhunen, L, Karwautz, A, Kas, MJH, Kennedy, JL, Keski-Rahkonen, A, Kiezebrink, K, Kim, YR, Klump, KL, Knudsen, GP, La Via, MC, Le Hellard, S, Levitan, RD, Li, D, Lilenfeld, L, Lin, BD, Lissowska, J, Luykx, J, Magistretti, PJ, Maj, M, Mannik, K, Marsal, S, Marshall, CR, Mattingsdal, M, McDevitt, S, McGuffin, P, Metspalu, A, Meulenbelt, I, Micali, N, Mitchell, K, Monteleone, A M, Monteleone, P, Nacmias, B, Navratilova, M, Ntalla, I, O'Toole, JK, Ophoff, Roel, Padyukov, L, Palotie, A, Pantel, J, Papezova, H, Pinto, D, Rabionet, R, Raevuori, A, Ramoz, N, Reichborn-Kjennerud, T, Ricca, V, Ripatti, S, Ritschel, F, Roberts, M, Rotondo, A, Rujescu, D, Rybakowski, F, Santonastaso, P, Scherag, A, Scherer, SW, Schmidt, U, Schork, NJ, Schosser, A, Seitz, J, Slachtova, L, Slagboom, PE, Slof-Op't Landt, MCT, Slopien, A, Sorbi, S, ?wi?tkowska, B, Szatkiewicz, JP, Tachmazidou, I, Tenconi, E, Tortorella, A, Tozzi, F, Treasure, J, Tsitsika, A, Tyszkiewicz-Nwafor, M, Tziouvas, K, van Elburg, AA, van Furth, EF, Wagner, G, Walton, E, Widen, E, Zeggini, E, Zerwas, S, Zipfel, S, Bergen, AW, Boden, JM, Brandt, H, Crawford, S, Halmi, KA, Horwood, LJ, Johnson, C, Kaplan, AS, Kaye, WH, Mitchell, J E, Olsen, CM, Pearson, JF, Pedersen, NL, Strober, M, Werge, T, Whiteman, DC, Woodside, DB, Grove, J, Henders, AK, Larsen, J T, Parker, R, Petersen, LV, Jordan, J, Kennedy, MA, Birgegård, A, Lichtenstein, P, Norring, C, Landén, M, Mortensen, PB, Polimanti, R, McClintick, JN, Adkins, AE, Aliev, F, Bacanu, SA, Batzler, A, Bertelsen, S, Biernacka, JM, Bigdeli, TB, Chen, L S, Clarke, TK, Degenhardt, F, Docherty, AR, Edwards, AC, Foo, JC, Fox, L, Frank, J, Hack, LM, Hartmann, AM, Hartz, SM, Heilmann-Heimbach, S, Hodgkinson, C, Hoffmann, P, Hottenga, JJ, Konte, B, Lahti, J, Lahti-Pulkkinen, M, Lai, D, Ligthart, L, Loukola, A, Maher, BS, Mbarek, H, McIntosh, AM, McQueen, MB, Meyers, JL, Milaneschi, Y, Palviainen, T, Peterson, RE, Ryu, E, Saccone, N L, Salvatore, JE, Sanchez-Roige, S, Schwandt, M, Sherva, R, Streit, F, Strohmaier, J, Thomas, N, Wang, JCY, Webb, BT, Wedow, R, Wetherill, L, Wills, AG, Zhou, H, Boardman, JD, Chen, D, Choi, D S, Copeland, WE, Culverhouse, RC, Dahmen, N, Degenhardt, L, Domingue, BW, Frye, MA, Gäebel, W, Hayward, C, Ising, M, Keyes, M, Kiefer, F, Koller, G, Kramer, J (John), Kuperman, S, Lucae, S, Lynskey, MT, Maier, W, Mann, K, Männistö, S, Müller-Myhsok, B, Murray, AD, Nurnberger, JI, Preuss, U, Räikkönen, K, Reynolds, MD, Ridinger, M, Scherbaum, N, Schuckit, MA, Soyka, M, Treutlein, J, Witt, SH, Wodarz, N, Zill, P, Adkins, DE, Boomsma, DI, Bierut, LJ, Brown, S, Bucholz, KK, Costello, EJ, Wit, HJ, Diazgranados, N, Eriksson, JG, Farrer, LA, Foroud, TM, Gillespie, NA, Goate, AM, Goldman, D, Grucza, RA, Hancock, DB, Harris, KM, Hesselbrock, V, Hewitt, JK, Hopfer, CJ, Iacono, WG, Johnson, E O, Karpyak, VM, Kendler, KS, Kranzler, HR, Krauter, K, Lind, PA, McGue, M, MacKillop, J, Madden, PA, Maes, HH, Magnusson, PKE, Nelson, EC, Nöthen, MM, Palmer, AA, Penninx, BWJH, Porjesz, B, Rice, JP, Rietschel, M, Riley, BP, Rose, RJ, Shen, PH, Silberg, J, Stallings, MC, Tarter, RE, Vanyukov, MM, Vrieze, S, Wall, TL, Whitfield, JB, Zhao, H, Neale, BM, Wade, TD, Heath, AC, Montgomery, GW, Martin, NG, Sullivan, PF, Kaprio, J, Breen, G, Gelernter, J, Edenberg, HJ, Bulik, CM, and Agrawal, A
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotyp
Published: 2021

2. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

Author: Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, Borglum, AD, Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, and Borglum, AD
Abstract: BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
Published: 2020

3. Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Author: Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, Sullivan, PF, Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, and Sullivan, PF
Abstract: Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.
Published: 2020

4. Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy

Author: Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, Sullivan, PF, Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment-resistant depression; disorder severity and unfavorable treatment outcomes are shown to be influenced by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment and response/nonresponse are associated with an increased genetic burden for major depression (MD) using polygenic risk score (PRS), which summarize the contribution of disease-related common risk variants. Fifty-one psychiatric inpatients suffering from a major depressive episode underwent ECT. MD-PRS were calculated for these inpatients and a separate population-based sample (n = 3,547 healthy; n = 426 self-reported depression) based on summary statistics from the Psychiatric Genomics Consortium MDD-working group (Cases: n = 59,851; Controls: n = 113,154). MD-PRS explained a significant proportion of disease status between ECT patients and healthy controls (p = .022, R2 = 1.173%); patients showed higher MD-PRS. MD-PRS in population-based depression self-reporters were intermediate between ECT patients and controls (n.s.). Significant associations between MD-PRS and ECT response (50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate that ECT cohorts show an increased genetic burden for MD and are consistent with the hypothesis that treatment-resistant MD patients represent a subgroup with an increased genetic risk for MD. Larger samples are needed to better substantiate these findings.
Published: 2019

5. Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Author: Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, Macintyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, ASD, Sullivan, PF, Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, Macintyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, ASD, and Sullivan, PF
Abstract: Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.
Published: 2019

6. Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia

Author: Harold, D, Connolly, S, Riley, BP, Kendler, KS, McCarthy, SE, McCombie, WR, Richards, A, Owen, MJ, O'Donovan, MC, Walters, J, Donnelly, P, Bates, L, Barroso, I, Blackwell, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Hopkins, L, Pirinen, M, Pearson, R, Strange, A, Su, Z, Vukcevic, D, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Ripke, S, Neale, BM, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M-L, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chan, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Lee, J, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Muller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Buxbaum, JD, Borglum, AD, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, Harold, D, Connolly, S, Riley, BP, Kendler, KS, McCarthy, SE, McCombie, WR, Richards, A, Owen, MJ, O'Donovan, MC, Walters, J, Donnelly, P, Bates, L, Barroso, I, Blackwell, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Hopkins, L, Pirinen, M, Pearson, R, Strange, A, Su, Z, Vukcevic, D, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Ripke, S, Neale, BM, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M-L, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chan, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Lee, J, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Muller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Buxbaum, JD, Borglum, AD, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, and Sullivan, PF
Abstract: Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.
Published: 2019

7. Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Author: Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, Sullivan, PF, Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Published: 2019

8. Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

Author: Bigdeli, T. B, Ripke, S, Bacanu, Sa, Lee, S. H, Wray, Nr, Gejman, P. V, Rietschel, M, Cichon, S, St Clair, D, Corvin, A, Kirov, G, Mcquillin, A, Gurling, H, Rujescu, D, Andreassen, O. A, Werge, T, Blackwood, D. H. R, Pato, C. N, Pato, M. T, Malhotra, A. K, O'Donovan, M. C, Kendler, K. S, Fanous, A. H, Neale, Bm, Walters, Jt, Farh, Kh, Holmans, Pa, Lee, P, Bulik Sullivan, B, Collier, Da, Huang, H, Pers, Th, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Begemann, M, Belliveau, Ra, Bene, J, Bergen, Se, Bevilacqua, E, Bigdeli, Tb, Black, Dw, Børglum, Ad, Bruggeman, R, Buccola, Ng, Buckner, Rl, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, Rm, Carr, Vj, Carrera, N, Catts, Sv, Chambert, Kd, Chan, Rc, Chen, Ry, Chen, Ey, Cheng, W, Cheung, Ef, Chong, Sa, Cloninger, C, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, Jj, Curtis, D, Davidson, M, Davis, Kl, Degenhardt, F, Del, Favero, J, Delisi, Le, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott Price, V, Essioux, L, Fanous, Ah, Farrell, Ms, Frank, J, Franke, L, Freedman, R, Freimer, Nb, Friedl, M, Friedman, Ji, Fromer, M, Genovese, G, Georgieva, L, Gershon, Es, Giegling, I, Giusti Rodríguez, P, Godard, S, Goldstein, Ji, Golimbet, V, Gopal, S, Gratten, J, Grove, J, Haan, De, L, Hammer, C, Hamshere, Ml, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, Am, Henskens, Fa, Herms, S, Hirschhorn, Jn, Hoffmann, P, Hofman, A, Hollegaard, Mv, Hougaard, Dm, Ikeda, M, Joa, I, Julìa, A, Kahn, Rs, Kalaydjieva, L, Karachanak Yankova, S, Karjalainen, J, Kavanagh, D, Keller, Mc, Kelly, Bj, Kennedy, Jl, Khrunin, A, Kim, Y, Klovins, J, Knowles, Ja, Konte, B, Kucinskas, V, Kucinskiene, Za, Kuzelova Ptackova, H, Kähler, Ak, Laurent, C, Keong, Jl, Lee, S, Legge, Se, Lerer, B, Li, M, Li, T, Liang, Ky, Lieberman, J, Limborska, S, Loughland, Cm, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, Pk, Maher, Bs, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, Mccarley, Rw, Mcdonald, C, Mcintosh, Am, Meier, S, Meijer, Cj, Melegh, B, Melle, I, Mesholam Gately, Ri, Metspalu, A, Michie, Pt, Milani, L, Milanova, V, Mokrab, Y, Morris, Dw, Mors, O, Mortensen, Pb, Murphy, Kc, Murray, Rm, Myin Germeys, I, Müller Myhsok, B, Nelis, M, Nenadic, I, Nertney, Da, Nestadt, G, Nicodemus, Kk, Nikitina Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, F, Sy, Oh, Olincy, A, Olsen, L, Jv, Os, Pantelis, C, Papadimitriou, Gn, Papiol, S, Parkhomenko, E, Pato, Mt, Paunio, T, Pejovic Milovancevic, M, Perkins, Do, Pietiläinen, O, Pimm, J, Pocklington, Aj, Powell, J, Price, A, Pulver, Ae, Purcell, Sm, Quested, D, Rasmussen, Hb, Reichenberg, A, Reimers, Ma, Richards, Al, Roffman, Jl, Roussos, P, Ruderfer, Dm, Salomaa, V, Sanders, Ar, Schall, U, Schubert, Cr, Schulze, Tg, Schwab, Sg, Scolnick, Em, Scott, Rj, Seidman, Lj, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, Jm, Sim, K, Slominsky, P, Smoller, Jw, Hc, So, Spencer, Cc, Stahl, Ea, Stefansson, H, Steinberg, S, Stogmann, E, Straub, Re, Strengman, E, Strohmaier, J, Stroup, T, Subramaniam, M, Suvisaari, J, Svrakic, Dm, Szatkiewicz, Jp, Söderman, E, Thirumalai, S, Toncheva, D, Tooney, Pa, Tosato, Sarah, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, Bt, Weiser, M, Wildenauer, Db, Williams, Nm, Williams, S, Witt, Sh, Wolen, Ar, Wong, Eh, Wormley, Bk, Jq, Wu, Hs, Xi, Zai, Cc, Zheng, X, Zimprich, F, Stefansson, K, Visscher, Pm, Adolfsson, R, Andreassen, Oa, Blackwood, Dh, Bramon, E, Buxbaum, Jd, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, Pv, Gill, M, Hultman, Cm, Iwata, N, Jablensky, Av, Jönsson, Eg, Kendler, Ks, Knight, J, Lencz, T, Levinson, Df, Qs, Li, Liu, J, Malhotra, Ak, Mccarroll, Sa, Moran, Jl, Mowry, Bj, Nöthen, Mm, Ophoff, Ra, Owen, Mj, Palotie, A, Pato, Cn, Petryshen, Tl, Posthuma, D, Riley, Bp, Sham, Pc, Sklar, P, Clair, Ds, Weinberger, Dr, Wendland, Jr, Daly, Mj, Sullivan, Pf, O'Donovan, Mc, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Bigdeli, Tim B, Ripke, Stephan, Bacanu, Silviu-Alin, Lee, Sang Hong, Fanous, Ayman H, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Psychosis Endophenotype International Consortium, Wellcome Trust Case-Control Consortium 2, Other departments, Adult Psychiatry, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Psychiatrie (3), MUMC+: Hersen en Zenuw Centrum (3), and Del-Favero, Jurgen
Subjects: 0301 basic medicine, Multifactorial Inheritance, Bipolar Disorder, Inheritance Patterns, Genome-wide association study, Single-nucleotide polymorphism, polygenic, heritability, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, medicine, Humans, SNP, GWAS, Family, Genetic Predisposition to Disease, Family history, Allele, Genetics (clinical), Genetic association, Genetics & Heredity, Psychiatry, Genetics, Depressive Disorder, Major, family history, Models, Genetic, Case-control study, medicine.disease, 3. Good health, schizophrenia, Psychiatry and Mental health, 030104 developmental biology, Schizophrenia, Case-Control Studies, Human medicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N=978), cases reporting no such family history (N=4,503), and unscreened controls (N=8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R-2=0.0021; P=0.00331; P-value threshold
Published: 2016
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9. Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

Author: Arnau-Soler, A., Adams, M. J., Hayward, C. (Caroline), Thomson, PA, Porteous, D, Campbell, A. (Archie), Smith, B.H. (Blair), Black, C., Padmanabhan, S. (Sandosh), Mcintosh, A.M. (Andrew), Wray, N.R. (Naomi), Ripke, S. (Stephan), Mattheisen, M. (Manuel), Trzaskowski, M., Byrne, E.M. (Enda), Abdellaoui, A. (Abdel), Agerbo, E, Air, T.M., Andlauer, T.F.M., Bacanu, SA, Bækvad-Hansen, M., Beekman, A.T.F. (Aartjan), Bigdeli, TB, Binder, E.B. (Elisabeth), Blackwood, D.H.R. (Douglas), Bryois, J., Buttenschøn, H.N., Bybjerg-Grauholm, J., Cai, N., Castelao, E, Christensen, J.H., Clarke, T.-K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N.J. (Nick), Crawford, G.E., Davies, G. (Gail), Deary, I.J. (Ian), Degenhardt, F., Derks, E.M. (Eske), Direk, N., Dolan, C.V. (Conor), Dunn, EC, Eley, T.C. (T.), Escott-Price, V, Kiadeh, F.F.H., Finucane, HK, Forstner, A.J. (Andreas), Frank, J. (Josef), Gaspar, H.A., Gill, M. (Michael), Goes, F.S., Gordon, S.D., Grove, J. (Jakob), Hall, L.S., Hansen, C.S., Hansen, T.F. (Thomas F), Herms, S. (Stefan), Hickie, I.B. (Ian), Hoffmann, P. (Per), Homuth, G. (Georg), Horn, C., Hottenga, JJ, Hougaard, D.M. (David), Ising, M. (Marcus), Jansen, R, Jorgenson, E, Knowles, J.A. (James A), Kohane, IS, Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z. (Zoltán), Li, Y. (Yuwen), Lind, P.A. (Penelope), Macintyre, D.J. (Donald J), MacKinnon, D.F., Maier, R.M., Maier, W. (Wolfgang), Marchini, J. (Jonathan), Mbarek, H, McGrath, P., Mcguffin, P. (Peter), Medland, S.E., Mehta, D, Middeldorp, CM, Mihailov, E. (Evelin), Milaneschi, Y. (Yuri), Milani, L. (Lili), Mondimore, F.M., Montgomery, G.W. (Grant), Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R. (Dale), O'Reilly, P.F. (Paul), Oskarsson, H. (Hogni), Owen, M.J., Painter, JN, Pedersen, CB, Pedersen, M.G., Peterson, R.E., Pettersson, E, Peyrot, W.J. (Wouter ), Pistis, G. (Giorgio), Posthuma, D., Quiroz, J.A., Qvist, P., Rice, J.P. (John), Riley, B.P. (Brien), Rivera, M., Mirza, S.S., Schoevers, R. (Robert), Schulte, E.C., Shen, L. (Li), Shi, J. (Julia), Shyn, S.I. (Stanley I), Sigurdsson, E. (Engilbert), Sinnamon, G.C.B., Smit, J.H.M., Smith, D.J. (Derek James), Stefansson, H. (Hreinn), Steinberg, S. (Stacy), Streit, F., Strohmaier, J., Tansey, KE, Teismann, H., Teumer, A. (Alexander), Thompson, W., Thorgeirsson, T.E. (Thorgeir), Traylor, M. (Matthew), Treutlein, J. (Jens), Trubetskoy, V., Uitterlinden, A.G. (André), Umbricht, D., Van der Auwera, S., van Hemert, A.M., Viktorin, A, Visscher, P.M. (Peter), Wang, Y. (Yijing), Webb, BT, Weinsheimer, S.M., Wellmann, J. (Jürgen), Willemsen, G.A.H.M. (Gonneke), Witt, S.H. (Stephanie H), Wu, Y., Xi, HS, Yang, J., Zhang, F. (Feng), Arolt, V, Baune, BT, Berger, K. (Klaus), Boomsma, D.I. (Dorret), Cichon, S. (Sven), Dannlowski, U., de Geus, EJCN, DePaulo, J.R., Domenici, E, Domschke, K., Esko, T. (Tõnu), Grabe, H.J. (Hans Jörgen), Hamilton, S.P. (Steven P), Heath, A.C. (Andrew), Kendler, K. (K.), Kloiber, S, Lewis, G, Li, Q.S., Lucae, S. (Susanne), Madden, P.A. (Pamela), Magnusson, P.K. (Patrik), Martin, N.G. (Nicholas), Metspalu, A. (Andres), Mors, O., Mortensen, P.B., Müller-Myhsok, B., Nordentoft, M, Nöthen, M.M. (Markus), O'Donovan, M. (Michael), Paciga, S.A., Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Perlis, R.H. (Roy H), Porteous, D.J. (David J.), Potash, J.B. (James B), Preisig, M. (Martin), Rietschel, M., Schaefer, C. (Catherine), Schulze, T.G. (Thomas), Smoller, J.W., Zwart, J-A. (John-Anker), Tiemeier, H.W. (Henning), Uher, R, Völzke, H. (Henry), Weissman, M.M. (Myrna M), Werge, T.M. (Thomas), Lewis, C.M. (Cathryn), Levinson, D.F. (Douglas), Breen, G. (Gerome), Børglum, A.D., Sullivan, P.F. (Patrick), Arnau-Soler, A., Adams, M. J., Hayward, C. (Caroline), Thomson, PA, Porteous, D, Campbell, A. (Archie), Smith, B.H. (Blair), Black, C., Padmanabhan, S. (Sandosh), Mcintosh, A.M. (Andrew), Wray, N.R. (Naomi), Ripke, S. (Stephan), Mattheisen, M. (Manuel), Trzaskowski, M., Byrne, E.M. (Enda), Abdellaoui, A. (Abdel), Agerbo, E, Air, T.M., Andlauer, T.F.M., Bacanu, SA, Bækvad-Hansen, M., Beekman, A.T.F. (Aartjan), Bigdeli, TB, Binder, E.B. (Elisabeth), Blackwood, D.H.R. (Douglas), Bryois, J., Buttenschøn, H.N., Bybjerg-Grauholm, J., Cai, N., Castelao, E, Christensen, J.H., Clarke, T.-K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N.J. (Nick), Crawford, G.E., Davies, G. (Gail), Deary, I.J. (Ian), Degenhardt, F., Derks, E.M. (Eske), Direk, N., Dolan, C.V. (Conor), Dunn, EC, Eley, T.C. (T.), Escott-Price, V, Kiadeh, F.F.H., Finucane, HK, Forstner, A.J. (Andreas), Frank, J. (Josef), Gaspar, H.A., Gill, M. (Michael), Goes, F.S., Gordon, S.D., Grove, J. (Jakob), Hall, L.S., Hansen, C.S., Hansen, T.F. (Thomas F), Herms, S. (Stefan), Hickie, I.B. (Ian), Hoffmann, P. (Per), Homuth, G. (Georg), Horn, C., Hottenga, JJ, Hougaard, D.M. (David), Ising, M. (Marcus), Jansen, R, Jorgenson, E, Knowles, J.A. (James A), Kohane, IS, Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z. (Zoltán), Li, Y. (Yuwen), Lind, P.A. (Penelope), Macintyre, D.J. (Donald J), MacKinnon, D.F., Maier, R.M., Maier, W. (Wolfgang), Marchini, J. (Jonathan), Mbarek, H, McGrath, P., Mcguffin, P. (Peter), Medland, S.E., Mehta, D, Middeldorp, CM, Mihailov, E. (Evelin), Milaneschi, Y. (Yuri), Milani, L. (Lili), Mondimore, F.M., Montgomery, G.W. (Grant), Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R. (Dale), O'Reilly, P.F. (Paul), Oskarsson, H. (Hogni), Owen, M.J., Painter, JN, Pedersen, CB, Pedersen, M.G., Peterson, R.E., Pettersson, E, Peyrot, W.J. (Wouter ), Pistis, G. (Giorgio), Posthuma, D., Quiroz, J.A., Qvist, P., Rice, J.P. (John), Riley, B.P. (Brien), Rivera, M., Mirza, S.S., Schoevers, R. (Robert), Schulte, E.C., Shen, L. (Li), Shi, J. (Julia), Shyn, S.I. (Stanley I), Sigurdsson, E. (Engilbert), Sinnamon, G.C.B., Smit, J.H.M., Smith, D.J. (Derek James), Stefansson, H. (Hreinn), Steinberg, S. (Stacy), Streit, F., Strohmaier, J., Tansey, KE, Teismann, H., Teumer, A. (Alexander), Thompson, W., Thorgeirsson, T.E. (Thorgeir), Traylor, M. (Matthew), Treutlein, J. (Jens), Trubetskoy, V., Uitterlinden, A.G. (André), Umbricht, D., Van der Auwera, S., van Hemert, A.M., Viktorin, A, Visscher, P.M. (Peter), Wang, Y. (Yijing), Webb, BT, Weinsheimer, S.M., Wellmann, J. (Jürgen), Willemsen, G.A.H.M. (Gonneke), Witt, S.H. (Stephanie H), Wu, Y., Xi, HS, Yang, J., Zhang, F. (Feng), Arolt, V, Baune, BT, Berger, K. (Klaus), Boomsma, D.I. (Dorret), Cichon, S. (Sven), Dannlowski, U., de Geus, EJCN, DePaulo, J.R., Domenici, E, Domschke, K., Esko, T. (Tõnu), Grabe, H.J. (Hans Jörgen), Hamilton, S.P. (Steven P), Heath, A.C. (Andrew), Kendler, K. (K.), Kloiber, S, Lewis, G, Li, Q.S., Lucae, S. (Susanne), Madden, P.A. (Pamela), Magnusson, P.K. (Patrik), Martin, N.G. (Nicholas), Metspalu, A. (Andres), Mors, O., Mortensen, P.B., Müller-Myhsok, B., Nordentoft, M, Nöthen, M.M. (Markus), O'Donovan, M. (Michael), Paciga, S.A., Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Perlis, R.H. (Roy H), Porteous, D.J. (David J.), Potash, J.B. (James B), Preisig, M. (Martin), Rietschel, M., Schaefer, C. (Catherine), Schulze, T.G. (Thomas), Smoller, J.W., Zwart, J-A. (John-Anker), Tiemeier, H.W. (Henning), Uher, R, Völzke, H. (Henry), Weissman, M.M. (Myrna M), Werge, T.M. (Thomas), Lewis, C.M. (Cathryn), Levinson, D.F. (Douglas), Breen, G. (Gerome), Børglum, A.D., and Sullivan, P.F. (Patrick)
Abstract: Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of d
Published: 2018
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10. Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Author: de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, Shi, J, de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, and Shi, J
Abstract: Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
Published: 2018

11. Age at first birth in women is genetically associated with increased risk of schizophrenia

Author: Ni, G, Gratten, J, Wray, NR, Lee, SH, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, KH, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodríguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Haan, L de, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Juliá, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kähler, AK, Laurent, C, Keong, JLC, Legge, SE, Lerer, B, Li, M, Li, T, Liang, KY, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Müller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, SY, Olincy, A, Olsen, L, van Os, JV, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietiläinen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, HC, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Söderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, Xuebin, Zimprich, F, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Børglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jönsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Nöthen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, Daniëlle, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Clair, DS, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, O'Donovan, MC, Ni, G, Gratten, J, Wray, NR, Lee, SH, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, KH, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodríguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Haan, L de, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Juliá, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kähler, AK, Laurent, C, Keong, JLC, Legge, SE, Lerer, B, Li, M, Li, T, Liang, KY, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Müller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, SY, Olincy, A, Olsen, L, van Os, JV, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietiläinen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, HC, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Söderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, Xuebin, Zimprich, F, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Børglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jönsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Nöthen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, Daniëlle, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Clair, DS, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, and O'Donovan, MC
Published: 2018

12. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases

Author: Gusev, A, Lee, Sh, SWE SCZ, Consortium, O'Dushlaine, Cgusev, Trynka, G, Finucane, H, Vilhjálmsson, Bj, Xu, H, Zang, C, Ripke, S, Bulik Sullivan, B, Stahl, E, Schizophrenia, Working, Neale, Bm, Corvin, A, Walters, Jt, Farh, Kh, Holmans, Pa, Lee, P, Collier, Da, Huang, H, Pers, Th, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, Sa, Begemann, M, Belliveau, Ra, Bene, J, Bergen, Se, Bevilacqua, E, Bigdeli, Tb, Black, Dw, Børglum, Ad, Bruggeman, R, Buccola, Ng, Buckner, Rl, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, Rm, Carr, Vj, Carrera, N, Catts, Sv, Chambert, Kd, Chan, Rc, Chen, Ry, Chen, Ey, Cheng, W, Cheung, Ef, Chong, Sa, Cloninger, Cr, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, Jj, Curtis, D, Davidson, M, Davis, Kl, Degenhardt, F, Del, Favero, Delisi, Le, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott Price, V, Essioux, L, Fanous, Ah, Farrell, Ms, Frank, J, Franke, L, Freedman, R, Freimer, Nb, Friedl, M, Friedman, Ji, Fromer, M, Genovese, G, Georgieva, L, Gershon, Es, Giegling, I, Giusti Rodrguez, P, Godard, S, Goldstein, Ji, Golimbet, V, Gopal, S, Gratten, J, Grove, J, Haan, De, Hammer, C, Hamshere, Ml, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, Am, Henskens, Fa, Herms, S, Hirschhorn, Jn, Hoffmann, P, Hofman, A, Hollegaard, Mv, Hougaard, Dm, Ikeda, M, Joa, I, Julià, A, Kahn, Rs, Kalaydjieva, L, Karachanak Yankova, S, Karjalainen, J, Kavanagh, D, Keller, Mc, Kelly, Bj, Kennedy, Jl, Khrunin, A, Kim, Y, Klovins, J, Knowles, Ja, Konte, B, Kucinskas, V, Kucinskiene, Za, Kuzelova Ptackova, H, Kähler, Ak, Laurent, C, Keong, Jl, Legge, Se, Lerer, B, Li, M, Li, T, Liang, Ky, Lieberman, J, Limborska, S, Loughland, Cm, Lubinski, J, Lnnqvist, J, Macek, M, Magnusson, Pk, Maher, Bs, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, Mccarley, Rw, Mcdonald, C, Mcintosh, Am, Meier, S, Meijer, Cj, Melegh, B, Melle, I, Mesholam Gately, Ri, Metspalu, A, Michie, Pt, Milani, L, Milanova, V, Mokrab, Y, Morris, Dw, Mors, O, Mortensen, Pb, Murphy, Kc, Murray, Rm, Myin Germeys, I, Mller Myhsok, B, Nelis, M, Nenadic, I, Nertney, Da, Nestadt, G, Nicodemus, Kk, Nikitina Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, Fa, Sy, Oh, Olincy, A, Olsen, L, Van, Os, Pantelis, C, Papadimitriou, Gn, Papiol, S, Parkhomenko, E, Pato, Mt, Paunio, T, Pejovic Milovancevic, M, Perkins, Do, Pietilinen, O, Pimm, J, Pocklington, Aj, Powell, J, Price, A, Pulver, Ae, Purcell, Sm, Quested, D, Rasmussen, Hb, Reichenberg, A, Reimers, Ma, Richards, Al, Roffman, Jl, Roussos, P, Ruderfer, Dm, Salomaa, V, Sanders, Ar, Schall, U, Schubert, Cr, Schulze, Tg, Schwab, Sg, Scolnick, Em, Scott, Rj, Seidman, Lj, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, Jm, Sim, K, Slominsky, P, Smoller, Jw, Hc, So, Spencer, Cc, Stahl, Ea, Stefansson, H, Steinberg, S, Stogmann, E, Straub, Re, Strengman, E, Strohmaier, J, Stroup, Ts, Subramaniam, M, Suvisaari, J, Svrakic, Dm, Szatkiewicz, Jp, Sderman, E, Thirumalai, S, Toncheva, D, Tooney, Pa, Tosato, Sarah, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, Bt, Weiser, M, Wildenauer, Db, Williams, Nm, Williams, S, Witt, Sh, Wolen, Ar, Wong, Eh, Wormley, Bk, Jq, Wu, Hs, Xi, Zai, Cc, Zheng, X, Zimprich, F, Wray, Nr, Stefansson, K, Visscher, Pm, Adolfsson, R, Andreassen, Oa, Blackwood, Dh, Bramon, E, Buxbaum, Jd, Brglum, Ad, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, Pv, Gill, M, Gurling, H, Hultman, Cm, Iwata, N, Jablensky, Av, Jönsson, Eg, Kendler, Ks, Kirov, G, Knight, J, Lencz, T, Levinson, Df, Qs, Li, Liu, J, Malhotra, Ak, Mccarroll, Sa, Mcquillin, A, Moran, Jl, Mowry, Bj, Nthen, Mm, Ophoff, Ra, Owen, Mj, Palotie, A, Pato, Cn, Petryshen, Tl, Posthuma, D, Rietschel, M, Riley, Bp, Rujescu, D, Sham, Pc, Sklar, P, Clair, St, Weinberger, Dr, Wendland, Jr, Werge, T, Daly, Mj, Sullivan, Pf, O'Donovan, Mc, Chambert, K, Akterin, S, Bergen, S, Ruderfer, D, Scolnick, E, Purcell, S, Mccarroll, S, Daly, M, Pasaniuc, B, Raychaudhuri, S, Price, Al, Gusev, Alexander, Lee, S Hong, Trynka, Gosia, Finucane, Hilary K, Price, Alkes L, Schizophrenia Working Group of the Psychiatric Genomics Consortium, SWE-SCZ Consortium, ANS - Amsterdam Neuroscience, Adult Psychiatry, Other departments, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Complex Trait Genetics, Functional Genomics, and Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease
Subjects: Linkage disequilibrium, GWAS, schizophrenia, SNP, trait heritability, disease architecture, Inheritance Patterns, Single-nucleotide polymorphism, Genome-wide association study, Biology, Article, Open Reading Frames, SDG 3 - Good Health and Well-being, Genetic, Models, Genotype, Genetics, Humans, Genetics(clinical), Computer Simulation, Regulatory Elements, Transcriptional, Exome, Genetics (clinical), genotype imputation, Genetic association, Genetics & Heredity, genome-wide association study, Models, Genetic, Genetic Diseases, Inborn, Genetic Variation, Heritability, exome chips, Regulatory Elements, Inborn, Genetic Diseases, Transcriptional, coding variants, Genome-Wide Association Study
Abstract: Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (h(g)(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of h(g)(2) from imputed SNPs (5.1 x enrichment; p = 3.7 x 10(-17)) and 38% (SE = 4%) of h(g)(2) from genotyped SNPs (1.6 x enrichment, p = 1.0 x 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained
Published: 2014
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13. Biological insights from 108 schizophrenia-associated genetic loci

Author: Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Keong, JLC, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Mueller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Borglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Noethen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, O'Donovan, MC, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Keong, JLC, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Mueller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Borglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Noethen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, and O'Donovan, MC
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
Published: 2014

14. Quantitative linkage genome scan for atopy in a large collection of Caucasian families.

Author: Webb, BT, van den Oord, E, Akkari, A, Wilton, S, Ly, T, Duff, R, Barnes, KC, Carlsen, K, Gerritsen, J, Lenney, W, Silverman, M, Sly, P, Sundy, J, Tsanakas, J, von Berg, A, Whyte, M, Blumenthal, M, Vestbo, Jørgen, Middleton, L, Helms, PJ, Anderson, WH, Pillai, SG, Webb, BT, van den Oord, E, Akkari, A, Wilton, S, Ly, T, Duff, R, Barnes, KC, Carlsen, K, Gerritsen, J, Lenney, W, Silverman, M, Sly, P, Sundy, J, Tsanakas, J, von Berg, A, Whyte, M, Blumenthal, M, Vestbo, Jørgen, Middleton, L, Helms, PJ, Anderson, WH, and Pillai, SG
Abstract: Quantitative phenotypes correlated with a complex disorder offer increased power to detect linkage in comparison to affected-unaffected classifications. Asthma is a complex disorder characterized by periods of bronchial obstruction and increased bronchial hyper reactivity. In childhood and early adulthood, asthma is frequently associated also with quantitative measures of atopy. Genome wide quantitative multipoint linkage analysis was conducted for serum IgE levels and percentage of positive skin prick test (SPT(per)) using three large groups of families originally ascertained for asthma. In this report, 438 and 429 asthma families were informative for linkage using IgE and SPT(per) which represents 690 independent families. Suggestive linkage (LOD >/= 2) was found on chromosomes 1, 3, and 8q with maximum LODs of 2.34 (IgE), 2.03 (SPT(per)), and 2.25 (IgE) near markers D1S1653, D3S2322-D3S1764, and D8S2324, respectively. The results from chromosomes 1 and 3 replicate previous reports of linkage. We also replicate linkage to 5q with peak LODs of 1.96 (SPT(per)) and 1.77 (IgE) at or near marker D5S1480. Our results provide further evidence implicating chromosomes 1, 3, and 5q. The current report represents one of the biggest genome scans so far reported for asthma related phenotypes. This study also demonstrates the utility of increased sample sizes and quantitative phenotypes in linkage analysis of complex disorders., Quantitative phenotypes correlated with a complex disorder offer increased power to detect linkage in comparison to affected-unaffected classifications. Asthma is a complex disorder characterized by periods of bronchial obstruction and increased bronchial hyper reactivity. In childhood and early adulthood, asthma is frequently associated also with quantitative measures of atopy. Genome wide quantitative multipoint linkage analysis was conducted for serum IgE levels and percentage of positive skin prick test (SPT(per)) using three large groups of families originally ascertained for asthma. In this report, 438 and 429 asthma families were informative for linkage using IgE and SPT(per) which represents 690 independent families. Suggestive linkage (LOD >/= 2) was found on chromosomes 1, 3, and 8q with maximum LODs of 2.34 (IgE), 2.03 (SPT(per)), and 2.25 (IgE) near markers D1S1653, D3S2322-D3S1764, and D8S2324, respectively. The results from chromosomes 1 and 3 replicate previous reports of linkage. We also replicate linkage to 5q with peak LODs of 1.96 (SPT(per)) and 1.77 (IgE) at or near marker D5S1480. Our results provide further evidence implicating chromosomes 1, 3, and 5q. The current report represents one of the biggest genome scans so far reported for asthma related phenotypes. This study also demonstrates the utility of increased sample sizes and quantitative phenotypes in linkage analysis of complex disorders.
Published: 2007

15. Haplotype analysis of the USH1D locus and genotype–phenotype correlations

Author: Liu, X‐Z, primary, Blanton, SH, additional, Bitner‐Glindzicz, M, additional, Pandya, A, additional, Landa, B, additional, MacArdle, B, additional, Rajput, K, additional, Bellman, S, additional, Webb, BT, additional, Ping, X, additional, Smith, RJH, additional, and Nance, WE, additional
Published: 2001
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16. Gene expression differences associated with alcohol use disorder in human brain.

Author: Willis C, White JD, Minto MS, Quach BC, Han S, Tao R, Shin JH, Deep-Soboslay A, Hyde TM, Mayfield RD, Webb BT, Johnson EO, Kleinman JE, Bierut LJ, and Hancock DB
Abstract: Excessive alcohol consumption is a leading cause of preventable death worldwide. To improve understanding of neurobiological mechanisms associated with alcohol use disorder (AUD) in humans, we compared gene expression data from deceased individuals with and without AUD across two addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Bulk RNA-seq data from NAc and DLPFC (N ≥50 with AUD, ≥46 non-AUD) were analyzed for differential gene expression using modified negative binomial regression adjusting for technical and biological covariates. The region-level results were meta-analyzed with those from an independent dataset (N NAc = 28 AUD, 29 non-AUD; N PFC = 66 AUD, 77 non-AUD). We further tested for heritability enrichment of AUD-related phenotypes, gene co-expression networks, gene ontology enrichment, and drug repurposing. We identified 176 differentially expressed genes (DEGs; 12 in both regions, 78 in NAc only, 86 in DLPFC only) for AUD in our new dataset. After meta-analyzing with published data, we identified 476 AUD DEGs (25 in both regions, 29 in NAc only, 422 in PFC only). Of these DEGs, 17 were significant when looked up in GWAS of problematic alcohol use or drinks per week. Gene co-expression analysis showed both concordant and unique gene networks across brain regions. We also identified 29 and 436 drug compounds that target DEGs from our meta-analysis in NAc and PFC, respectively. This study identified robust AUD-associated DEGs, contributing novel neurobiological insights into AUD and highlighting genes targeted by known drug compounds, generating opportunity for drug repurposing to treat AUD., (© 2024. The Author(s).)
Published: 2024
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17. Associations between polygenic liability to psychopathology and non-suicidal versus suicidal self-injury.

Author: Edwards AC, Singh M, Peterson RE, Webb BT, and Gentry AE
Subjects: Humans, Female, Male, Middle Aged, Psychopathology, Adult, Suicidal Ideation, Aged, Anorexia Nervosa genetics, Anorexia Nervosa psychology, Phenotype, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study, United Kingdom, Risk Factors, Multifactorial Inheritance genetics, Self-Injurious Behavior genetics, Self-Injurious Behavior psychology, Suicide, Attempted psychology, Genetic Predisposition to Disease
Abstract: Little is known about how non-suicidal and suicidal self-injury are differentially genetically related to psychopathology and related measures. This research was conducted using the UK Biobank Resource, in participants of European ancestry (N = 2320 non-suicidal self-injury [NSSI] only; N = 2648 suicide attempt; 69.18% female). We compared polygenic scores (PGS) for psychopathology and other relevant measures within self-injuring individuals. Logistic regressions and likelihood ratio tests (LRT) were used to identify PGS that were differentially associated with these outcomes. In a multivariable model, PGS for anorexia nervosa (odds ratio [OR] = 1.07; 95% confidence intervals [CI] 1.01; 1.15) and suicidal behavior (OR = 1.06; 95% CI 1.00; 1.12) both differentiated between NSSI and suicide attempt, while the PGS for other phenotypes did not. The LRT between the multivariable and base models was significant (Chi square = 11.38, df = 2, p = 0.003), and the multivariable model explained a larger proportion of variance (Nagelkerke's pseudo-R 2 = 0.028 vs. 0.025). While NSSI and suicidal behavior are similarly genetically related to a range of mental health and related outcomes, genetic liability to anorexia nervosa and suicidal behavior is higher among those reporting a suicide attempt than those reporting NSSI-only. Further elucidation of these distinctions is necessary, which will require a nuanced assessment of suicidal versus non-suicidal self-injury in large samples., (© 2024 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)
Published: 2024
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18. Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex.

Author: White JD, Minto MS, Willis C, Quach BC, Han S, Tao R, Deep-Soboslay A, Zillich L, Witt SH, Spanagel R, Hansson AC, Clark SL, van den Oord EJCG, Hyde TM, Mayfield RD, Webb BT, Johnson EO, Kleinman JE, Bierut LJ, and Hancock DB
Abstract: Background: Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex., Methods: Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region-shared and brain region-specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain., Results: At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies., Conclusions: Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD., (© 2024 The Authors.)
Published: 2024
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19. Comparative evaluation of assay performance for SARS-CoV-2 detection in animal oral samples, lung homogenates, and phosphate-buffered saline using the TaqPath COVID-19 Combo kit.

Author: Miller MR, Tkachenko A, Guag J, Alexander S, Webb BT, and Stenger BLS
Subjects: Animals, Cats, Dogs, Humans, SARS-CoV-2, Pandemics, COVID-19 Testing veterinary, Clinical Laboratory Techniques methods, Clinical Laboratory Techniques veterinary, RNA, Viral analysis, Lung, Phosphates, Sensitivity and Specificity, COVID-19 diagnosis, COVID-19 veterinary, Cat Diseases, Dog Diseases
Abstract: A One Health approach has been key to monitoring the COVID-19 pandemic, as human and veterinary medical professionals jointly met the demands for an extraordinary testing effort for SARS-CoV-2. Veterinary diagnostic laboratories continue to monitor SARS-CoV-2 infection in animals, furthering the understanding of zoonotic transmission dynamics between humans and animals. A RT-PCR assay is a primary animal screening tool established within validation and verification guidelines provided by the American Association of Veterinary Laboratory Diagnosticians (AAVLD), World Organisation for Animal Health (WOAH), and the U.S. Food and Drug Administration (FDA). However, differences in sample matrices, RNA extraction methods, instrument platforms, gene targets, and cutoff values may affect test outcomes. Therefore, targeted validation for a new sample matrix used in any PCR assay is critical. We evaluated a COVID-19 assay for the detection of SARS-CoV-2 in feline and canine lung homogenates and oral swab samples. We used the commercial Applied Biosystems MagMAX Viral/Pathogen II (MVP II) nucleic acid isolation kit and TaqPath COVID-19 Combo kit, which are validated for a variety of human samples, including nasopharyngeal and oropharyngeal swab samples. Our masked test showed a high detection rate and no false-positive or false-negative results, supporting sample extension to include feline oral swab samples. Our study is a prime example of One Health, illustrating how a COVID-19 assay designed for human testing can be adapted and used to detect SARS-CoV-2 in oral swab samples from cats and likely dogs, but not lung homogenates., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Published: 2024
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20. Breakthrough infections by SARS-CoV-2 variants boost cross-reactive hybrid immune responses in mRNA-vaccinated Golden Syrian hamsters.

Author: Diego JG, Singh G, Jangra S, Handrejk K, Laporte M, Chang LA, El Zahed SS, Pache L, Chang MW, Warang P, Aslam S, Mena I, Webb BT, Benner C, García-Sastre A, and Schotsaert M
Subjects: Animals, Cricetinae, Humans, BNT162 Vaccine, Breakthrough Infections, Mesocricetus, Antibodies, Neutralizing, Postoperative Complications, RNA, Messenger genetics, Immunity, Antibodies, Viral, Vaccination, SARS-CoV-2, COVID-19 prevention & control
Abstract: Hybrid immunity (vaccination + natural infection) to SARS-CoV-2 provides superior protection to re-infection. We performed immune profiling studies during breakthrough infections in mRNA-vaccinated hamsters to evaluate hybrid immunity induction. The mRNA vaccine, BNT162b2, was dosed to induce binding antibody titers against ancestral spike, but inefficient serum virus neutralization of ancestral SARS-CoV-2 or variants of concern (VoCs). Vaccination reduced morbidity and controlled lung virus titers for ancestral virus and Alpha but allowed breakthrough infections in Beta, Delta and Mu-challenged hamsters. Vaccination primed for T cell responses that were boosted by infection. Infection back-boosted neutralizing antibody responses against ancestral virus and VoCs. Hybrid immunity resulted in more cross-reactive sera, reflected by smaller antigenic cartography distances. Transcriptomics post-infection reflects both vaccination status and disease course and suggests a role for interstitial macrophages in vaccine-mediated protection. Therefore, protection by vaccination, even in the absence of high titers of neutralizing antibodies in the serum, correlates with recall of broadly reactive B- and T-cell responses., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: the M.S. laboratory has received unrelated research funding in sponsored research agreements from ArgenX BV, Moderna, 7Hills Pharma and Phio Pharmaceuticals which has no competing interest with this work. The A.G.-S. laboratory has received research support from GSK, Pfizer, Senhwa Biosciences, Kenall Manufacturing, Blade Therapeutics, Avimex, Johnson & Johnson, Dynavax, 7Hills Pharma, Pharmamar, ImmunityBio, Accurius, Nanocomposix, Hexamer, N-fold LLC, Model Medicines, Atea Pharma, Applied Biological Laboratories and Merck, outside of the reported work. A.G.-S. has consulting agreements for the following companies involving cash and/or stock: Castlevax, Amovir, Vivaldi Biosciences, Contrafect, 7Hills Pharma, Avimex, Pagoda, Accurius, Esperovax, Farmak, Applied Biological Laboratories, Pharmamar, CureLab Oncology, CureLab Veterinary, Synairgen, Paratus and Pfizer, outside of the reported work. A.G.-S. has been an invited speaker in meeting events organized by Seqirus, Janssen, Abbott and Astrazeneca. A.G.-S. is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections and cancer, owned by the Icahn School of Medicine at Mount Sinai, New York, outside of the reported work., (Copyright: © 2024 Diego et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2024
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21. Angular limb deformity associated with TSPAN18, NRG3 and NOVA2 in Rambouillet rams.

Author: Becker GM, Shira KA, Woods JL, Khilji SF, Schauer CS, Webb BT, Stewart WC, and Murdoch BM
Subjects: Animals, Male, Sheep genetics, Introns genetics, RNA-Binding Proteins genetics, Exons, Genome-Wide Association Study, Nerve Tissue Proteins
Abstract: Angular limb deformity (ALD) affects many species of livestock and companion animals. The mechanisms of ALD development are not well understood, but previous research suggests the involvement of genetic risk factors. A case-control genome-wide association study (GWAS) was conducted with 40 ALD-affected and 302 unaffected Rambouillet rams and 40,945 single nucleotide polymorphisms (SNPs). Forelimbs of 6 ALD-affected rams were examined and diagnosed with osteochondrosis. Genome-wide or chromosome-wide significant SNPs were positioned exonic, intronic or within the 3'UTR of genes TSPAN18, NRG3 and NOVA2, respectively. These genes have previously described roles related to angiogenesis and osteoblast, osteoclast and chondrocyte proliferation and differentiation, which suggests the possibility for their involvement in the pathogenesis of osteochondrosis. Functional consequences of SNPs were evaluated through transcription factor binding site analysis, which predicted binding sites for transcription factors of known importance to bone growth, including SOX6, SOX9 and RUNX2. The identification of genetic risk factors for ALD may help to improve animal welfare and production in Rambouillet, a breed known to be at risk for ALD development. This study proposes genes TSPAN18, NRG3 and NOVA2 as targets for further research towards understanding the etiology of ALD in Rambouillet sheep., (© 2023. Springer Nature Limited.)
Published: 2023
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22. Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information.

Author: Ahangari M, Gentry AE, Hassan MF, Nguyen TH, Kendler KS, Bacanu SA, Peterson RE, Riley BP, and Webb BT
Abstract: Alcohol use disorder (AUD) is moderately heritable with significant social and economic impact. Genome-wide association studies (GWAS) have identified common variants associated with AUD, however, rare variant investigations have yet to achieve well-powered sample sizes. In this study, we conducted an interval-based exome-wide analysis of the Alcohol Use Disorder Identification Test Problems subscale (AUDIT-P) using both machine learning (ML) predicted risk and empirical functional weights. This research has been conducted using the UK Biobank Resource (application number 30782.) Filtering the 200k exome release to unrelated individuals of European ancestry resulted in a sample of 147,386 individuals with 51,357 observed and 96,029 unmeasured but predicted AUDIT-P for exome analysis. Sequence Kernel Association Test (SKAT/SKAT-O) was used for rare variant (Minor Allele Frequency (MAF) < 0.01) interval analyses using default and empirical weights. Empirical weights were constructed using annotations found significant by stratified LD Score Regression analysis of predicted AUDIT-P GWAS, providing prior functional weights specific to AUDIT-P. Using only samples with observed AUDIT-P yielded no significantly associated intervals. In contrast, ADH1C and THRA gene intervals were significant (False discovery rate (FDR) <0.05) using default and empirical weights in the predicted AUDIT-P sample, with the most significant association found using predicted AUDIT-P and empirical weights in the ADH1C gene (SKAT-O P Default = 1.06 x 10 -9 and P Empirical weight = 6.25 x 10 -11 ). These findings provide evidence for rare variant association of the ADH1C gene with the AUDIT-P and highlight the successful leveraging of ML to increase effective sample size and prior empirical functional weights based on common variant GWAS data to refine and increase the statistical significance in underpowered phenotypes.
Published: 2023
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23. Differences in genetic correlations between posttraumatic stress disorder and alcohol-related problems phenotypes compared to alcohol consumption-related phenotypes.

Author: Bountress KE, Bustamante D, Subbie-Saenz de Viteri S, Chatzinakos C, Sheerin C, Daskalakis NP, Edenberg HJ, Peterson RE, Webb BT, Meyers J, and Amstadter A
Subjects: Humans, Genome-Wide Association Study, Alcohol Drinking epidemiology, Alcohol Drinking genetics, Phenotype, Alcoholism epidemiology, Alcoholism genetics, Stress Disorders, Post-Traumatic epidemiology, Stress Disorders, Post-Traumatic genetics, Alcohol-Related Disorders epidemiology, Alcohol-Related Disorders genetics
Abstract: Background: Posttraumatic Stress Disorder (PTSD) tends to co-occur with greater alcohol consumption as well as alcohol use disorder (AUD). However, it is unknown whether the same etiologic factors that underlie PTSD-alcohol-related problems comorbidity also contribute to PTSD- alcohol consumption., Methods: We used summary statistics from large-scale genome-wide association studies (GWAS) of European-ancestry (EA) and African-ancestry (AA) participants to estimate genetic correlations between PTSD and a range of alcohol consumption-related and alcohol-related problems phenotypes., Results: In EAs, there were positive genetic correlations between PTSD phenotypes and alcohol-related problems phenotypes (e.g. Alcohol Use Disorders Identification Test (AUDIT) problem score) (rGs: 0.132-0.533, all FDR adjusted p < 0.05). However, the genetic correlations between PTSD phenotypes and alcohol consumption -related phenotypes (e.g. drinks per week) were negatively associated or non-significant (rGs: -0.417 to -0.042, FDR adjusted p : <0.05-NS). For AAs, the direction of correlations was sometimes consistent and sometimes inconsistent with that in EAs, and the ranges were larger (rGs for alcohol-related problems: -0.275 to 0.266, FDR adjusted p : NS, alcohol consumption-related: 0.145-0.699, FDR adjusted p : NS)., Conclusions: These findings illustrate that the genetic associations between consumption and problem alcohol phenotypes and PTSD differ in both strength and direction. Thus, the genetic factors that may lead someone to develop PTSD and high levels of alcohol consumption are not the same as those that lead someone to develop PTSD and alcohol-related problems. Discussion around needing improved methods to better estimate heritabilities and genetic correlations in diverse and admixed ancestry samples is provided.
Published: 2023
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24. Missingness adapted group informed clustered (MAGIC)-LASSO: a novel paradigm for phenotype prediction to improve power for genetic loci discovery.

Author: Gentry AE, Kirkpatrick RM, Peterson RE, and Webb BT
Abstract: Introduction: The availability of large-scale biobanks linking genetic data, rich phenotypes, and biological measures is a powerful opportunity for scientific discovery. However, real-world collections frequently have extensive missingness. While missing data prediction is possible, performance is significantly impaired by block-wise missingness inherent to many biobanks. Methods: To address this, we developed Missingness Adapted Group-wise Informed Clustered (MAGIC)-LASSO which performs hierarchical clustering of variables based on missingness followed by sequential Group LASSO within clusters. Variables are pre-filtered for missingness and balance between training and target sets with final models built using stepwise inclusion of features ranked by completeness. This research has been conducted using the UK Biobank ( n > 500 k) to predict unmeasured Alcohol Use Disorders Identification Test (AUDIT) scores. Results: The phenotypic correlation between measured and predicted total score was 0.67 while genetic correlations between independent subjects was high >0.86. Discussion: Phenotypic and genetic correlations in real data application, as well as simulations, demonstrate the method has significant accuracy and utility for increasing power for genetic loci discovery., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gentry, Kirkpatrick, Peterson and Webb.)
Published: 2023
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25. Multifaceted risk for non-suicidal self-injury only versus suicide attempt in a population-based cohort of adults.

Author: Edwards AC, Gentry AE, Peterson RE, Webb BT, and Mościcki EK
Subjects: Humans, Adult, Cohort Studies, United Kingdom epidemiology, Economic Status statistics & numerical data, Educational Status, Risk Assessment, Self Report, Logistic Models, Male, Female, Odds Ratio, Databases, Factual, Middle Aged, Aged, Self-Injurious Behavior epidemiology, Self-Injurious Behavior etiology, Self-Injurious Behavior psychology, Suicide, Attempted psychology, Suicide, Attempted statistics & numerical data, Sociodemographic Factors
Abstract: Background: Non-suicidal self-injury and suicide attempt represent significant public health concerns. While these outcomes are related, there is prior evidence that their etiology does not entirely overlap. Efforts to directly differentiate risk across outcomes are uncommon, particularly among older, population-based cohorts., Methods: This research has been conducted using the UK Biobank. Data on individuals' self-reported history of non-suicidal self-injury only versus suicide attempt (maximum N = 6643) were analyzed. Applying LASSO and standard logistic regression, participants reporting one of these outcomes were assessed for differences across a range of sociodemographic, behavioral, and environmental features., Results: Sociodemographic features most strongly differentiated between the outcomes of non-suicidal self-injury only versus suicide attempt. Specifically, Black individuals were more likely to report a suicide attempt, as were those of mixed race, those endorsing higher levels of depressive symptoms or trauma history, and those who had experienced financial problems (odds ratios 1.02-3.92). Those more likely to engage in non-suicidal self-injury only were younger, female, had higher levels of education, those who resided with a partner, and those who had a recently injured relative., Limitations: Differences in timing across correlates and outcomes preclude the ability to establish causal pathways., Conclusions: The factors identified in the current study as differentially associated with non-suicidal self-injury only versus suicide attempt provide further evidence of at least partially distinct correlates, and warrant follow-up in independent samples to investigate causality., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2023 Elsevier B.V. All rights reserved.)
Published: 2023
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26. Relationship between polygenic risk scores and symptom dimensions of schizophrenia and schizotypy in multiplex families with schizophrenia.

Author: Ahangari M, Bustamante D, Kirkpatrick R, Nguyen TH, Verrelli BC, Fanous A, Kendler KS, Webb BT, Bacanu SA, and Riley BP
Subjects: Humans, Risk Factors, Schizophrenia diagnosis, Schizophrenia genetics, Schizotypal Personality Disorder diagnosis, Schizotypal Personality Disorder genetics, Schizotypal Personality Disorder psychology, Depressive Disorder, Major diagnosis, Depressive Disorder, Major genetics, Psychotic Disorders genetics, Psychotic Disorders psychology
Abstract: Background: Psychotic disorders and schizotypal traits aggregate in the relatives of probands with schizophrenia. It is currently unclear how variability in symptom dimensions in schizophrenia probands and their relatives is associated with polygenic liability to psychiatric disorders., Aims: To investigate whether polygenic risk scores (PRSs) can predict symptom dimensions in members of multiplex families with schizophrenia., Method: The largest genome-wide data-sets for schizophrenia, bipolar disorder and major depressive disorder were used to construct PRSs in 861 participants from the Irish Study of High-Density Multiplex Schizophrenia Families. Symptom dimensions were derived using the Operational Criteria Checklist for Psychotic Disorders in participants with a history of a psychotic episode, and the Structured Interview for Schizotypy in participants without a history of a psychotic episode. Mixed-effects linear regression models were used to assess the relationship between PRS and symptom dimensions across the psychosis spectrum., Results: Schizophrenia PRS is significantly associated with the negative/disorganised symptom dimension in participants with a history of a psychotic episode ( P = 2.31 × 10 -4 ) and negative dimension in participants without a history of a psychotic episode ( P = 1.42 × 10 -3 ). Bipolar disorder PRS is significantly associated with the manic symptom dimension in participants with a history of a psychotic episode ( P = 3.70 × 10 -4 ). No association with major depressive disorder PRS was observed., Conclusions: Polygenic liability to schizophrenia is associated with higher negative/disorganised symptoms in participants with a history of a psychotic episode and negative symptoms in participants without a history of a psychotic episode in multiplex families with schizophrenia. These results provide genetic evidence in support of the spectrum model of schizophrenia, and support the view that negative and disorganised symptoms may have greater genetic basis than positive symptoms, making them better indices of familial liability to schizophrenia.
Published: 2023
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27. Breakthrough infections by SARS-CoV-2 variants boost cross-reactive hybrid immune responses in mRNA-vaccinated Golden Syrian Hamsters.

Author: García-Bernalt Diego J, Singh G, Jangra S, Handrejk K, Laporte M, Chang LA, El Zahed SS, Pache L, Chang MW, Warang P, Aslam S, Mena I, Webb BT, Benner C, García-Sastre A, and Schotsaert M
Abstract: Hybrid immunity to SARS-CoV-2 provides superior protection to re-infection. We performed immune profiling studies during breakthrough infections in mRNA-vaccinated hamsters to evaluate hybrid immunity induction. mRNA vaccine, BNT162b2, was dosed to induce binding antibody titers against ancestral spike, but inefficient serum virus neutralization of ancestral SARS-CoV-2 or variants of concern (VoCs). Vaccination reduced morbidity and controlled lung virus titers for ancestral virus and Alpha but allowed breakthrough infections in Beta, Delta and Mu-challenged hamsters. Vaccination primed T cell responses that were boosted by infection. Infection back-boosted neutralizing antibody responses against ancestral virus and VoCs. Hybrid immunity resulted in more cross-reactive sera. Transcriptomics post-infection reflects both vaccination status and disease course and suggests a role for interstitial macrophages in vaccine-mediated protection. Therefore, protection by vaccination, even in the absence of high titers of neutralizing antibodies in the serum, correlates with recall of broadly reactive B- and T-cell responses., Competing Interests: CONFLICTS OF INTEREST The M.S. laboratory has received unrelated research funding in sponsored research agreements from ArgenX BV, Moderna, 7Hills Pharma and Phio Pharmaceuticals which has no competing interest with this work. The A.G.-S. laboratory has received research support from GSK, Pfizer, Senhwa Biosciences, Kenall Manufacturing, Blade Therapeutics, Avimex, Johnson & Johnson, Dynavax, 7Hills Pharma, Pharmamar, ImmunityBio, Accurius, Nanocomposix, Hexamer, N-fold LLC, Model Medicines, Atea Pharma, Applied Biological Laboratories and Merck, outside of the reported work. A.G.-S. has consulting agreements for the following companies involving cash and/or stock: Castlevax, Amovir, Vivaldi Biosciences, Contrafect, 7Hills Pharma, Avimex, Pagoda, Accurius, Esperovax, Farmak, Applied Biological Laboratories, Pharmamar, CureLab Oncology, CureLab Veterinary, Synairgen, Paratus and Pfizer, outside of the reported work. A.G.-S. has been an invited speaker in meeting events organized by Seqirus, Janssen, Abbott and Astrazeneca. A.G.-S. is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections and cancer, owned by the Icahn School of Medicine at Mount Sinai, New York, outside of the reported work.
Published: 2023
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28. Case-only exome variation analysis of severe alcohol dependence using a multivariate hierarchical gene clustering approach.

Author: Gentry AE, Alexander JC, Ahangari M, Peterson RE, Miles MF, Bettinger JC, Davies AG, Groteweil M, Bacanu SA, Kendler KS, Riley BP, and Webb BT
Subjects: Humans, Mice, Animals, Exome genetics, Alleles, Ethanol, Silent Mutation, Genetic Variation, Alcoholism genetics, Alcoholism diagnosis
Abstract: Background: Variation in genes involved in ethanol metabolism has been shown to influence risk for alcohol dependence (AD) including protective loss of function alleles in ethanol metabolizing genes. We therefore hypothesized that people with severe AD would exhibit different patterns of rare functional variation in genes with strong prior evidence for influencing ethanol metabolism and response when compared to genes not meeting these criteria., Objective: Leverage a novel case only design and Whole Exome Sequencing (WES) of severe AD cases from the island of Ireland to quantify differences in functional variation between genes associated with ethanol metabolism and/or response and their matched control genes., Methods: First, three sets of ethanol related genes were identified including those a) involved in alcohol metabolism in humans b) showing altered expression in mouse brain after alcohol exposure, and altering ethanol behavioral responses in invertebrate models. These genes of interest (GOI) sets were matched to control gene sets using multivariate hierarchical clustering of gene-level summary features from gnomAD. Using WES data from 190 individuals with severe AD, GOI were compared to matched control genes using logistic regression to detect aggregate differences in abundance of loss of function, missense, and synonymous variants, respectively., Results: Three non-independent sets of 10, 117, and 359 genes were queried against control gene sets of 139, 1522, and 3360 matched genes, respectively. Significant differences were not detected in the number of functional variants in the primary set of ethanol-metabolizing genes. In both the mouse expression and invertebrate sets, we observed an increased number of synonymous variants in GOI over matched control genes. Post-hoc simulations showed the estimated effects sizes observed are unlikely to be under-estimated., Conclusion: The proposed method demonstrates a computationally viable and statistically appropriate approach for genetic analysis of case-only data for hypothesized gene sets supported by empirical evidence., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Gentry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2023
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29. Comparative Genomics of Listeria monocytogenes Isolates from Ruminant Listeriosis Cases in the Midwest United States.

Author: Cardenas-Alvarez MX, Zeng H, Webb BT, Mani R, Muñoz M, and Bergholz TM
Subjects: Cattle, Sheep, Humans, Animals, United States epidemiology, Ruminants, Genomics, Virulence, Food Microbiology, Listeria monocytogenes, Listeriosis epidemiology, Listeriosis veterinary
Abstract: Ruminants are a well-known reservoir for Listeria monocytogenes. In addition to asymptomatic carriage of the pathogen, ruminants can also acquire listeriosis and develop clinical manifestations in the form of neurologic or fetal infections, similar to those occurring in humans. Genomic characterization of ruminant listeriosis cases in Europe have identified lineage 1 and 2 strains associated with infection, as well as clonal complexes (CCs) that are commonly isolated from human cases of listeriosis; however, there is little information on the diversity of L. monocytogenes from ruminant listeriosis in the United States. In this study, we characterized and compared 73 L. monocytogenes isolates from ruminant listeriosis cases from the Midwest and the Upper Great Plains collected from 2015 to 2020. Using whole-genome sequence data, we classified the isolates and identified key virulence factors, stress-associated genes, and mobile genetic elements within our data set. Our isolates belonged to three different lineages: 31% to lineage 1, 53% to lineage 2, and 15% to lineage 3. Lineage 1 and 3 isolates were associated with neurologic infections, while lineage 2 showed a greater frequency of fetal infections. Additionally, the presence of mobile elements, virulence-associated genes, and stress and antimicrobial resistance genes was evaluated. These genetic elements are responsible for most of the subgroup-specific features and may play a key role in the spread of hypervirulent clones, including the spread of hypervirulent CC1 clone commonly associated with disease in humans, and may explain the increased frequency of certain clones in the area. IMPORTANCE Listeria monocytogenes affects humans and animals, causing encephalitis, septicemia, and abortions, among other clinical outcomes. Ruminants such as cattle, goats, and sheep are the main carriers contributing to the maintenance and dispersal of this pathogen in the farm environment. Contamination of food products from farms is of concern not only because many L. monocytogenes genotypes found there are associated with human listeriosis but also as a cause of significant economic losses when livestock and food products are affected. Ruminant listeriosis has been characterized extensively in Europe; however, there is limited information about the genetic diversity of these cases in the United States. Identification of subgroups with a greater ability to spread may facilitate surveillance and management of listeriosis and contribute to a better understanding of the genome diversity of this pathogen, providing insights into the molecular epidemiology of ruminant listeriosis in the region.
Published: 2022
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30. Examining the source of increased bipolar disorder and major depressive disorder common risk variation burden in multiplex schizophrenia families.

Author: Ahangari M, Kirkpatrick R, Nguyen TH, Gillespie N, Kendler KS, Bacanu SA, Webb BT, Verrelli BC, and Riley BP
Abstract: Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia, and genetic studies show substantial genetic correlation among schizophrenia, bipolar disorder, and major depressive disorder. In this study, we examined the polygenic risk burden of bipolar disorder and major depressive disorder in 257 multiplex schizophrenia families (N = 1005) from the Irish Study of High-Density Multiplex Schizophrenia Families versus 2205 ancestry-matched controls. Our results indicate that members of multiplex schizophrenia families have an increased polygenic risk for bipolar disorder and major depressive disorder compared to population controls. However, this observation is largely attributable to the part of the genetic risk that bipolar disorder or major depressive disorder share with schizophrenia due to genetic correlation, rather than the affective portion of the genetic risk unique to them. These findings suggest that a complete interpretation of cross-disorder polygenic risks in multiplex families requires an assessment of the relative contribution of shared versus unique genetic factors to account for genetic correlations across psychiatric disorders., (© 2022. The Author(s).)
Published: 2022
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31. Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.

Author: Gaddis N, Mathur R, Marks J, Zhou L, Quach B, Waldrop A, Levran O, Agrawal A, Randesi M, Adelson M, Jeffries PW, Martin NG, Degenhardt L, Montgomery GW, Wetherill L, Lai D, Bucholz K, Foroud T, Porjesz B, Runarsdottir V, Tyrfingsson T, Einarsson G, Gudbjartsson DF, Webb BT, Crist RC, Kranzler HR, Sherva R, Zhou H, Hulse G, Wildenauer D, Kelty E, Attia J, Holliday EG, McEvoy M, Scott RJ, Schwab SG, Maher BS, Gruza R, Kreek MJ, Nelson EC, Thorgeirsson T, Stefansson K, Berrettini WH, Gelernter J, Edenberg HJ, Bierut L, Hancock DB, and Johnson EO
Subjects: Furin genetics, Genetic Predisposition to Disease, Humans, Phenotype, Polymorphism, Single Nucleotide, Receptors, Opioid, mu genetics, Genome-Wide Association Study, Opioid-Related Disorders genetics
Abstract: Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (r g > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10 -9 ). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits., (© 2022. The Author(s).)
Published: 2022
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32. Gross and histologic description of trematodosis in fetal and neonatal beef calves in North Dakota and Minnesota.

Author: Pecoraro HL, Stenger BLS, Rice LE, and Webb BT
Subjects: Animals, Cattle, Female, Male, Minnesota epidemiology, North Dakota epidemiology, Pregnancy, Cattle Diseases epidemiology, Cattle Diseases parasitology, Fasciola hepatica, Fasciolidae, Trematode Infections epidemiology, Trematode Infections parasitology, Trematode Infections veterinary
Abstract: Hepatic trematodes, such as Fasciola hepatica and Fascioloides magna , have variable distribution throughout the United States. F. magna is endemic in the upper midwestern United States, and F. magna infections are diagnosed frequently in weaned calves and adult beef cattle at the North Dakota State University Veterinary Diagnostic Laboratory (NDSU-VDL). Rarely, liver fluke infestation has also been observed in much younger calves, including aborted fetuses. We describe here, in 2 fetal and 7 neonatal beef calves submitted to the NDSU-VDL between 2011 and 2020, parasitic migration tracts in livers, consisting of regionally extensive, random, linear tracts of fibrosis admixed with black porphyrin pigment, along with foci of necrosis and hemorrhage, and mixed inflammatory cells, which were caused presumptively by F. magna infection. Samples were not available from our 9 cases for PCR assay and sequencing, but we did confirm F. magna within liver samples collected from regional cattle in 2020 and 2021. Fetal and neonatal trematodosis was often concurrent with other common causes of fetal abortion and neonatal calf loss in our cases; however, based on the prepatent period of F. magna , fetal and neonatal beef calf trematode infestations occurred in utero.
Published: 2022
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33. Determining the stability of genome-wide factors in BMI between ages 40 to 69 years.

Author: Gillespie NA, Gentry AE, Kirkpatrick RM, Reynolds CA, Mathur R, Kendler KS, Maes HH, Webb BT, and Peterson RE
Subjects: Adult, Aged, Body Mass Index, Female, Genome, Genomics, Humans, Male, Middle Aged, Genome-Wide Association Study, Polymorphism, Single Nucleotide genetics
Abstract: Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike., Competing Interests: The authors have declared that no competing interests exist.
Published: 2022
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34. Genome-wide analysis of schizophrenia and multiple sclerosis identifies shared genomic loci with mixed direction of effects.

Author: Ahangari M, Everest E, Nguyen TH, Verrelli BC, Webb BT, Bacanu SA, Tahir Turanli E, and Riley BP
Abstract: Common genetic variants identified in genome-wide association studies (GWAS) show varying degrees of genetic pleiotropy across complex human disorders. Clinical studies of schizophrenia (SCZ) suggest that in addition to neuropsychiatric symptoms, patients with SCZ also show variable immune dysregulation. Epidemiological studies of multiple sclerosis (MS), an autoimmune, neurodegenerative disorder of the central nervous system, suggest that in addition to the manifestation of neuroinflammatory complications, patients with MS may also show co-occurring neuropsychiatric symptoms with disease progression. In this study, we analyzed the largest available GWAS datasets for SCZ (N = 161,405) and MS (N = 41,505) using Gaussian causal mixture modeling (MiXeR) and conditional/conjunctional false discovery rate (condFDR) frameworks to explore and quantify the shared genetic architecture of these two complex disorders at common variant level. Despite detecting only a negligible genetic correlation (r G = 0.057), we observe polygenic overlap between SCZ and MS, and a substantial genetic enrichment in SCZ conditional on associations with MS, and vice versa. By leveraging this cross-disorder enrichment, we identified 36 loci jointly associated with SCZ and MS at conjunctional FDR < 0.05 with mixed direction of effects. Follow-up functional analysis of the shared loci implicates candidate genes and biological processes involved in immune response and B-cell receptor signaling pathways. In conclusion, this study demonstrates the presence of polygenic overlap between SCZ and MS in the absence of a genetic correlation and provides new insights into the shared genetic architecture of these two disorders at the common variant level., (Copyright © 2022 Elsevier Inc. All rights reserved.)
Published: 2022
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35. Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families.

Author: Ahangari M, Gentry AE, Nguyen TH, Kirkpatrick R, Verrelli BC, Bacanu SA, Kendler KS, Webb BT, and Riley BP
Subjects: Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Risk Factors, Psychotic Disorders genetics, Schizophrenia epidemiology, Schizophrenia genetics
Abstract: Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH- cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction., (© 2022. The Author(s).)
Published: 2022
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36. Mapping genomic loci implicates genes and synaptic biology in schizophrenia.

Author: Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, Bryois J, Chen CY, Dennison CA, Hall LS, Lam M, Watanabe K, Frei O, Ge T, Harwood JC, Koopmans F, Magnusson S, Richards AL, Sidorenko J, Wu Y, Zeng J, Grove J, Kim M, Li Z, Voloudakis G, Zhang W, Adams M, Agartz I, Atkinson EG, Agerbo E, Al Eissa M, Albus M, Alexander M, Alizadeh BZ, Alptekin K, Als TD, Amin F, Arolt V, Arrojo M, Athanasiu L, Azevedo MH, Bacanu SA, Bass NJ, Begemann M, Belliveau RA, Bene J, Benyamin B, Bergen SE, Blasi G, Bobes J, Bonassi S, Braun A, Bressan RA, Bromet EJ, Bruggeman R, Buckley PF, Buckner RL, Bybjerg-Grauholm J, Cahn W, Cairns MJ, Calkins ME, Carr VJ, Castle D, Catts SV, Chambert KD, Chan RCK, Chaumette B, Cheng W, Cheung EFC, Chong SA, Cohen D, Consoli A, Cordeiro Q, Costas J, Curtis C, Davidson M, Davis KL, de Haan L, Degenhardt F, DeLisi LE, Demontis D, Dickerson F, Dikeos D, Dinan T, Djurovic S, Duan J, Ducci G, Dudbridge F, Eriksson JG, Fañanás L, Faraone SV, Fiorentino A, Forstner A, Frank J, Freimer NB, Fromer M, Frustaci A, Gadelha A, Genovese G, Gershon ES, Giannitelli M, Giegling I, Giusti-Rodríguez P, Godard S, Goldstein JI, González Peñas J, González-Pinto A, Gopal S, Gratten J, Green MF, Greenwood TA, Guillin O, Gülöksüz S, Gur RE, Gur RC, Gutiérrez B, Hahn E, Hakonarson H, Haroutunian V, Hartmann AM, Harvey C, Hayward C, Henskens FA, Herms S, Hoffmann P, Howrigan DP, Ikeda M, Iyegbe C, Joa I, Julià A, Kähler AK, Kam-Thong T, Kamatani Y, Karachanak-Yankova S, Kebir O, Keller MC, Kelly BJ, Khrunin A, Kim SW, Klovins J, Kondratiev N, Konte B, Kraft J, Kubo M, Kučinskas V, Kučinskiene ZA, Kusumawardhani A, Kuzelova-Ptackova H, Landi S, Lazzeroni LC, Lee PH, Legge SE, Lehrer DS, Lencer R, Lerer B, Li M, Lieberman J, Light GA, Limborska S, Liu CM, Lönnqvist J, Loughland CM, Lubinski J, Luykx JJ, Lynham A, Macek M Jr, Mackinnon A, Magnusson PKE, Maher BS, Maier W, Malaspina D, Mallet J, Marder SR, Marsal S, Martin AR, Martorell L, Mattheisen M, McCarley RW, McDonald C, McGrath JJ, Medeiros H, Meier S, Melegh B, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mitjans M, Molden E, Molina E, Molto MD, Mondelli V, Moreno C, Morley CP, Muntané G, Murphy KC, Myin-Germeys I, Nenadić I, Nestadt G, Nikitina-Zake L, Noto C, Nuechterlein KH, O'Brien NL, O'Neill FA, Oh SY, Olincy A, Ota VK, Pantelis C, Papadimitriou GN, Parellada M, Paunio T, Pellegrino R, Periyasamy S, Perkins DO, Pfuhlmann B, Pietiläinen O, Pimm J, Porteous D, Powell J, Quattrone D, Quested D, Radant AD, Rampino A, Rapaport MH, Rautanen A, Reichenberg A, Roe C, Roffman JL, Roth J, Rothermundt M, Rutten BPF, Saker-Delye S, Salomaa V, Sanjuan J, Santoro ML, Savitz A, Schall U, Scott RJ, Seidman LJ, Sharp SI, Shi J, Siever LJ, Sigurdsson E, Sim K, Skarabis N, Slominsky P, So HC, Sobell JL, Söderman E, Stain HJ, Steen NE, Steixner-Kumar AA, Stögmann E, Stone WS, Straub RE, Streit F, Strengman E, Stroup TS, Subramaniam M, Sugar CA, Suvisaari J, Svrakic DM, Swerdlow NR, Szatkiewicz JP, Ta TMT, Takahashi A, Terao C, Thibaut F, Toncheva D, Tooney PA, Torretta S, Tosato S, Tura GB, Turetsky BI, Üçok A, Vaaler A, van Amelsvoort T, van Winkel R, Veijola J, Waddington J, Walter H, Waterreus A, Webb BT, Weiser M, Williams NM, Witt SH, Wormley BK, Wu JQ, Xu Z, Yolken R, Zai CC, Zhou W, Zhu F, Zimprich F, Atbaşoğlu EC, Ayub M, Benner C, Bertolino A, Black DW, Bray NJ, Breen G, Buccola NG, Byerley WF, Chen WJ, Cloninger CR, Crespo-Facorro B, Donohoe G, Freedman R, Galletly C, Gandal MJ, Gennarelli M, Hougaard DM, Hwu HG, Jablensky AV, McCarroll SA, Moran JL, Mors O, Mortensen PB, Müller-Myhsok B, Neil AL, Nordentoft M, Pato MT, Petryshen TL, Pirinen M, Pulver AE, Schulze TG, Silverman JM, Smoller JW, Stahl EA, Tsuang DW, Vilella E, Wang SH, Xu S, Adolfsson R, Arango C, Baune BT, Belangero SI, Børglum AD, Braff D, Bramon E, Buxbaum JD, Campion D, Cervilla JA, Cichon S, Collier DA, Corvin A, Curtis D, Forti MD, Domenici E, Ehrenreich H, Escott-Price V, Esko T, Fanous AH, Gareeva A, Gawlik M, Gejman PV, Gill M, Glatt SJ, Golimbet V, Hong KS, Hultman CM, Hyman SE, Iwata N, Jönsson EG, Kahn RS, Kennedy JL, Khusnutdinova E, Kirov G, Knowles JA, Krebs MO, Laurent-Levinson C, Lee J, Lencz T, Levinson DF, Li QS, Liu J, Malhotra AK, Malhotra D, McIntosh A, McQuillin A, Menezes PR, Morgan VA, Morris DW, Mowry BJ, Murray RM, Nimgaonkar V, Nöthen MM, Ophoff RA, Paciga SA, Palotie A, Pato CN, Qin S, Rietschel M, Riley BP, Rivera M, Rujescu D, Saka MC, Sanders AR, Schwab SG, Serretti A, Sham PC, Shi Y, St Clair D, Stefánsson H, Stefansson K, Tsuang MT, van Os J, Vawter MP, Weinberger DR, Werge T, Wildenauer DB, Yu X, Yue W, Holmans PA, Pocklington AJ, Roussos P, Vassos E, Verhage M, Visscher PM, Yang J, Posthuma D, Andreassen OA, Kendler KS, Owen MJ, Wray NR, Daly MJ, Huang H, Neale BM, Sullivan PF, Ripke S, Walters JTR, and O'Donovan MC
Subjects: Alleles, Genetic Predisposition to Disease genetics, Genomics, Humans, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study, Schizophrenia genetics
Abstract: Schizophrenia has a heritability of 60-80% 1 , much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2022
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37. Study protocol to quantify the genetic architecture of sonographic cervical length and its relationship to spontaneous preterm birth.

Author: Wolf HM, Romero R, Strauss JF, Hassan SS, Latendresse SJ, Webb BT, Tarca AL, Gomez-Lopez N, Hsu CD, and York TP
Subjects: Cervix Uteri diagnostic imaging, Female, Gestational Age, Humans, Infant, Newborn, Pregnancy, Pregnancy Trimester, Second, Ultrasonography, Premature Birth genetics
Abstract: Introduction: A short cervix (cervical length <25 mm) in the midtrimester (18-24 weeks) of pregnancy is a powerful predictor of spontaneous preterm delivery. Although the biological mechanisms of cervical change during pregnancy have been the subject of extensive investigation, little is known about whether genes influence the length of the cervix, or the extent to which genetic factors contribute to premature cervical shortening. Defining the genetic architecture of cervical length is foundational to understanding the aetiology of a short cervix and its contribution to an increased risk of spontaneous preterm delivery., Methods/analysis: The proposed study is designed to characterise the genetic architecture of cervical length and its genetic relationship to gestational age at delivery in a large cohort of Black/African American women, who are at an increased risk of developing a short cervix and delivering preterm. Repeated measurements of cervical length will be modelled as a longitudinal growth curve, with parameters estimating the initial length of the cervix at the beginning of pregnancy, and its rate of change over time. Genome-wide complex trait analysis methods will be used to estimate the heritability of cervical length growth parameters and their bivariate genetic correlation with gestational age at delivery. Polygenic risk profiling will assess maternal genetic risk for developing a short cervix and subsequently delivering preterm and evaluate the role of cervical length in mediating the relationship between maternal genetic variation and gestational age at delivery., Ethics/dissemination: The proposed analyses will be conducted using deidentified data from participants in an IRB-approved study of longitudinal cervical length who provided blood samples and written informed consent for their use in future genetic research. These analyses are preregistered with the Center for Open Science using the AsPredicted format and the results and genomic summary statistics will be published in a peer-reviewed journal., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2022
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38. DECO: a framework for jointly analyzing de novo and rare case/control variants, and biological pathways.

Author: Nguyen TH, He X, Brown RC, Webb BT, Kendler KS, Vladimirov VI, Riley BP, and Bacanu SA
Subjects: Case-Control Studies, Computer Simulation, DNA Mutational Analysis methods, Humans, Models, Statistical, Protein Interaction Mapping methods, Protein Interaction Maps genetics, Genetic Predisposition to Disease genetics, Mutation, Neurodevelopmental Disorders genetics, Schizophrenia genetics, Systems Biology methods
Abstract: Motivation: Rare variant-based analyses are beginning to identify risk genes for neuropsychiatric disorders and other diseases. However, the identified genes only account for a fraction of predicted causal genes. Recent studies have shown that rare damaging variants are significantly enriched in specific gene-sets. Methods which are able to jointly model rare variants and gene-sets to identify enriched gene-sets and use these enriched gene-sets to prioritize additional risk genes could improve understanding of the genetic architecture of diseases., Results: We propose DECO (Integrated analysis of de novo mutations, rare case/control variants and omics information via gene-sets), an integrated method for rare-variant and gene-set analysis. The method can (i) test the enrichment of gene-sets directly within the statistical model, and (ii) use enriched gene-sets to rank existing genes and prioritize additional risk genes for tested disorders. In simulations, DECO performs better than a homologous method that uses only variant data. To demonstrate the application of the proposed protocol, we have applied this approach to rare-variant datasets of schizophrenia. Compared with a method which only uses variant information, DECO is able to prioritize additional risk genes., Availability: DECO can be used to analyze rare-variants and biological pathways or cell types for any disease. The package is available on Github https://github.com/hoangtn/DECO., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
Published: 2021
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39. Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Author: Munn-Chernoff MA, Johnson EC, Chou YL, Coleman JRI, Thornton LM, Walters RK, Yilmaz Z, Baker JH, Hübel C, Gordon S, Medland SE, Watson HJ, Gaspar HA, Bryois J, Hinney A, Leppä VM, Mattheisen M, Ripke S, Yao S, Giusti-Rodríguez P, Hanscombe KB, Adan RAH, Alfredsson L, Ando T, Andreassen OA, Berrettini WH, Boehm I, Boni C, Boraska Perica V, Buehren K, Burghardt R, Cassina M, Cichon S, Clementi M, Cone RD, Courtet P, Crow S, Crowley JJ, Danner UN, Davis OSP, de Zwaan M, Dedoussis G, Degortes D, DeSocio JE, Dick DM, Dikeos D, Dina C, Dmitrzak-Weglarz M, Docampo E, Duncan LE, Egberts K, Ehrlich S, Escaramís G, Esko T, Estivill X, Farmer A, Favaro A, Fernández-Aranda F, Fichter MM, Fischer K, Föcker M, Foretova L, Forstner AJ, Forzan M, Franklin CS, Gallinger S, Giegling I, Giuranna J, Gonidakis F, Gorwood P, Gratacos Mayora M, Guillaume S, Guo Y, Hakonarson H, Hatzikotoulas K, Hauser J, Hebebrand J, Helder SG, Herms S, Herpertz-Dahlmann B, Herzog W, Huckins LM, Hudson JI, Imgart H, Inoko H, Janout V, Jiménez-Murcia S, Julià A, Kalsi G, Kaminská D, Karhunen L, Karwautz A, Kas MJH, Kennedy JL, Keski-Rahkonen A, Kiezebrink K, Kim YR, Klump KL, Knudsen GPS, La Via MC, Le Hellard S, Levitan RD, Li D, Lilenfeld L, Lin BD, Lissowska J, Luykx J, Magistretti PJ, Maj M, Mannik K, Marsal S, Marshall CR, Mattingsdal M, McDevitt S, McGuffin P, Metspalu A, Meulenbelt I, Micali N, Mitchell K, Monteleone AM, Monteleone P, Nacmias B, Navratilova M, Ntalla I, O'Toole JK, Ophoff RA, Padyukov L, Palotie A, Pantel J, Papezova H, Pinto D, Rabionet R, Raevuori A, Ramoz N, Reichborn-Kjennerud T, Ricca V, Ripatti S, Ritschel F, Roberts M, Rotondo A, Rujescu D, Rybakowski F, Santonastaso P, Scherag A, Scherer SW, Schmidt U, Schork NJ, Schosser A, Seitz J, Slachtova L, Slagboom PE, Slof-Op't Landt MCT, Slopien A, Sorbi S, Świątkowska B, Szatkiewicz JP, Tachmazidou I, Tenconi E, Tortorella A, Tozzi F, Treasure J, Tsitsika A, Tyszkiewicz-Nwafor M, Tziouvas K, van Elburg AA, van Furth EF, Wagner G, Walton E, Widen E, Zeggini E, Zerwas S, Zipfel S, Bergen AW, Boden JM, Brandt H, Crawford S, Halmi KA, Horwood LJ, Johnson C, Kaplan AS, Kaye WH, Mitchell J, Olsen CM, Pearson JF, Pedersen NL, Strober M, Werge T, Whiteman DC, Woodside DB, Grove J, Henders AK, Larsen JT, Parker R, Petersen LV, Jordan J, Kennedy MA, Birgegård A, Lichtenstein P, Norring C, Landén M, Mortensen PB, Polimanti R, McClintick JN, Adkins AE, Aliev F, Bacanu SA, Batzler A, Bertelsen S, Biernacka JM, Bigdeli TB, Chen LS, Clarke TK, Degenhardt F, Docherty AR, Edwards AC, Foo JC, Fox L, Frank J, Hack LM, Hartmann AM, Hartz SM, Heilmann-Heimbach S, Hodgkinson C, Hoffmann P, Hottenga JJ, Konte B, Lahti J, Lahti-Pulkkinen M, Lai D, Ligthart L, Loukola A, Maher BS, Mbarek H, McIntosh AM, McQueen MB, Meyers JL, Milaneschi Y, Palviainen T, Peterson RE, Ryu E, Saccone NL, Salvatore JE, Sanchez-Roige S, Schwandt M, Sherva R, Streit F, Strohmaier J, Thomas N, Wang JC, Webb BT, Wedow R, Wetherill L, Wills AG, Zhou H, Boardman JD, Chen D, Choi DS, Copeland WE, Culverhouse RC, Dahmen N, Degenhardt L, Domingue BW, Frye MA, Gäebel W, Hayward C, Ising M, Keyes M, Kiefer F, Koller G, Kramer J, Kuperman S, Lucae S, Lynskey MT, Maier W, Mann K, Männistö S, Müller-Myhsok B, Murray AD, Nurnberger JI, Preuss U, Räikkönen K, Reynolds MD, Ridinger M, Scherbaum N, Schuckit MA, Soyka M, Treutlein J, Witt SH, Wodarz N, Zill P, Adkins DE, Boomsma DI, Bierut LJ, Brown SA, Bucholz KK, Costello EJ, de Wit H, Diazgranados N, Eriksson JG, Farrer LA, Foroud TM, Gillespie NA, Goate AM, Goldman D, Grucza RA, Hancock DB, Harris KM, Hesselbrock V, Hewitt JK, Hopfer CJ, Iacono WG, Johnson EO, Karpyak VM, Kendler KS, Kranzler HR, Krauter K, Lind PA, McGue M, MacKillop J, Madden PAF, Maes HH, Magnusson PKE, Nelson EC, Nöthen MM, Palmer AA, Penninx BWJH, Porjesz B, Rice JP, Rietschel M, Riley BP, Rose RJ, Shen PH, Silberg J, Stallings MC, Tarter RE, Vanyukov MM, Vrieze S, Wall TL, Whitfield JB, Zhao H, Neale BM, Wade TD, Heath AC, Montgomery GW, Martin NG, Sullivan PF, Kaprio J, Breen G, Gelernter J, Edenberg HJ, Bulik CM, and Agrawal A
Subjects: Alcoholism genetics, Depressive Disorder, Major genetics, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia genetics, Tobacco Use Disorder genetics, Feeding and Eating Disorders genetics, Substance-Related Disorders genetics
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r g ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r gs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors., (© 2020 Society for the Study of Addiction.)
Published: 2021
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40. Increasing the resolution and precision of psychiatric genome-wide association studies by re-imputing summary statistics using a large, diverse reference panel.

Author: Chatzinakos C, Lee D, Cai N, Vladimirov VI, Webb BT, Riley BP, Flint J, Kendler KS, Ressler KJ, Daskalakis NP, and Bacanu SA
Subjects: Cohort Studies, Gene Frequency, Humans, Linkage Disequilibrium, Phenotype, Reference Standards, Software, Genome-Wide Association Study standards, Mental Disorders diagnosis, Mental Disorders genetics, Polymorphism, Single Nucleotide
Abstract: Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large-scale genome-wide association studies (GWAS). Methods for direct imputation of GWAS summary-statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage-disequilibrium (LD) and that most of the methods using a small reference panel for example, ~2,500-subject coming from the 1000 Genome-Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: (a) uses a much larger and more diverse reference panel compared to traditional reference panels, and (b) can estimate weights of ethnic-mixture based solely on Z-scores, when allele frequencies are not available. We applied DISTMIX2 to GWAS summary-statistics from the psychiatric genetic consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post-traumatic stress disorder GWAS found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most psychiatric GWAS-studies., (© 2021 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)
Published: 2021
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41. TWAS pathway method greatly enhances the number of leads for uncovering the molecular underpinnings of psychiatric disorders.

Author: Chatzinakos C, Georgiadis F, Lee D, Cai N, Vladimirov VI, Docherty A, Webb BT, Riley BP, Flint J, Kendler KS, Daskalakis NP, and Bacanu SA
Subjects: Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Phenotype, Prognosis, Psychotic Disorders genetics, Risk Factors, Signal Transduction, Software, Computational Biology methods, Genetic Markers, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Psychotic Disorders pathology, Quantitative Trait Loci, Transcriptome
Abstract: Genetic signal detection in genome-wide association studies (GWAS) is enhanced by pooling small signals from multiple Single Nucleotide Polymorphism (SNP), for example, across genes and pathways. Because genes are believed to influence traits via gene expression, it is of interest to combine information from expression Quantitative Trait Loci (eQTLs) in a gene or genes in the same pathway. Such methods, widely referred to as transcriptomic wide association studies (TWAS), already exist for gene analysis. Due to the possibility of eliminating most of the confounding effects of linkage disequilibrium (LD) from TWAS gene statistics, pathway TWAS methods would be very useful in uncovering the true molecular basis of psychiatric disorders. However, such methods are not yet available for arbitrarily large pathways/gene sets. This is possibly due to the quadratic (as a function of the number of SNPs) computational burden for computing LD across large chromosomal regions. To overcome this obstacle, we propose JEPEGMIX2-P, a novel TWAS pathway method that (a) has a linear computational burden, (b) uses a large and diverse reference panel (33 K subjects), (c) is competitive (adjusts for background enrichment in gene TWAS statistics), and (d) is applicable as-is to ethnically mixed-cohorts. To underline its potential for increasing the power to uncover genetic signals over the commonly used nontranscriptomics methods, for example, MAGMA, we applied JEPEGMIX2-P to summary statistics of most large meta-analyses from Psychiatric Genetics Consortium (PGC). While our work is just the very first step toward clinical translation of psychiatric disorders, PGC anorexia results suggest a possible avenue for treatment., (© 2020 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)
Published: 2020
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42. A large-scale genome-wide association study meta-analysis of cannabis use disorder.

Author: Johnson EC, Demontis D, Thorgeirsson TE, Walters RK, Polimanti R, Hatoum AS, Sanchez-Roige S, Paul SE, Wendt FR, Clarke TK, Lai D, Reginsson GW, Zhou H, He J, Baranger DAA, Gudbjartsson DF, Wedow R, Adkins DE, Adkins AE, Alexander J, Bacanu SA, Bigdeli TB, Boden J, Brown SA, Bucholz KK, Bybjerg-Grauholm J, Corley RP, Degenhardt L, Dick DM, Domingue BW, Fox L, Goate AM, Gordon SD, Hack LM, Hancock DB, Hartz SM, Hickie IB, Hougaard DM, Krauter K, Lind PA, McClintick JN, McQueen MB, Meyers JL, Montgomery GW, Mors O, Mortensen PB, Nordentoft M, Pearson JF, Peterson RE, Reynolds MD, Rice JP, Runarsdottir V, Saccone NL, Sherva R, Silberg JL, Tarter RE, Tyrfingsson T, Wall TL, Webb BT, Werge T, Wetherill L, Wright MJ, Zellers S, Adams MJ, Bierut LJ, Boardman JD, Copeland WE, Farrer LA, Foroud TM, Gillespie NA, Grucza RA, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono WG, Johnson EO, Kendler KS, Kennedy MA, Kranzler HR, Madden PAF, Maes HH, Maher BS, Martin NG, McGue M, McIntosh AM, Medland SE, Nelson EC, Porjesz B, Riley BP, Stallings MC, Vanyukov MM, Vrieze S, Davis LK, Bogdan R, Gelernter J, Edenberg HJ, Stefansson K, Børglum AD, and Agrawal A
Subjects: Humans, Polymorphism, Single Nucleotide, Risk, Genome-Wide Association Study, Marijuana Abuse genetics
Abstract: Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder., Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations., Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10 -9 ) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10 -9 ). Cannabis use disorder and cannabis use were genetically correlated (r g 0·50, p=1·50 × 10 -21 ), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia., Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder., Funding: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2020
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43. Equine dental and skeletal fluorosis induced by well water consumption.

Author: Kelly LH, Uzal FA, Poppenga RH, Kinde H, Hill AE, Wilson WD, and Webb BT
Subjects: Animals, Bone and Bones chemistry, Fluorides analysis, Fluorosis, Dental etiology, Horses, Bone and Bones drug effects, Drinking Water chemistry, Fluorides toxicity, Fluorosis, Dental veterinary, Horse Diseases chemically induced
Abstract: Two horses that consumed well water with high fluoride content exhibited clinical signs of chronic dental and skeletal fluoride toxicosis and were later euthanized and autopsied. Both horses had degenerative disease of multiple joints and multiple dental defects. Elevated fluoride concentrations were found in bone and tooth samples of both horses, well water, and feed. Microscopically, abnormalities were noted in bone and tooth samples, and consisted mostly of foci of cement necrosis and hypercementosis. Horses exhibiting bilateral, highly symmetrical dental and/or skeletal lesions, with chronic lameness, should be evaluated for the possible presence of fluoride toxicosis.
Published: 2020
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44. An epigenome-wide association study of early-onset major depression in monozygotic twins.

Author: Roberson-Nay R, Lapato DM, Wolen AR, Lancaster EE, Webb BT, Verhulst B, Hettema JM, and York TP
Subjects: Adolescent, Adult, DNA Methylation, Depression, Epigenesis, Genetic, Epigenome, Female, Humans, Male, Young Adult, Depressive Disorder, Major genetics, Twins, Monozygotic genetics
Abstract: Major depression (MD) is a debilitating mental health condition with peak prevalence occurring early in life. Genome-wide examination of DNA methylation (DNAm) offers an attractive complement to studies of allelic risk given it can reflect the combined influence of genes and environment. The current study used monozygotic twins to identify differentially and variably methylated regions of the genome that distinguish twins with and without a lifetime history of early-onset MD. The sample included 150 Caucasian monozygotic twins between the ages of 15 and 20 (73% female; Mage = 17.52 SD = 1.28) who were assessed during a developmental stage characterized by relatively distinct neurophysiological changes. All twins were generally healthy and currently free of medications with psychotropic effects. DNAm was measured in peripheral blood cells using the Infinium Human BeadChip 450 K Array. MD associations with early-onset MD were detected at 760 differentially and variably methylated probes/regions that mapped to 428 genes. Genes and genomic regions involved neural circuitry formation, projection, functioning, and plasticity. Gene enrichment analyses implicated genes related to neuron structures and neurodevelopmental processes including cell-cell adhesion genes (e.g., PCDHA genes). Genes previously implicated in mood and psychiatric disorders as well as chronic stress (e.g., NRG3) also were identified. DNAm regions associated with early-onset MD were found to overlap genetic loci identified in the latest Psychiatric Genomics Consortium meta-analysis of depression. Understanding the time course of epigenetic influences during emerging adulthood may clarify developmental phases where changes in the DNA methylome may modulate individual differences in MD risk.
Published: 2020
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45. Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium.

Author: Polimanti R, Walters RK, Johnson EC, McClintick JN, Adkins AE, Adkins DE, Bacanu SA, Bierut LJ, Bigdeli TB, Brown S, Bucholz KK, Copeland WE, Costello EJ, Degenhardt L, Farrer LA, Foroud TM, Fox L, Goate AM, Grucza R, Hack LM, Hancock DB, Hartz SM, Heath AC, Hewitt JK, Hopfer CJ, Johnson EO, Kendler KS, Kranzler HR, Krauter K, Lai D, Madden PAF, Martin NG, Maes HH, Nelson EC, Peterson RE, Porjesz B, Riley BP, Saccone N, Stallings M, Wall TL, Webb BT, Wetherill L, Edenberg HJ, Agrawal A, and Gelernter J
Subjects: Analgesics, Opioid pharmacology, Female, Genome, Human genetics, Humans, Male, Multifactorial Inheritance genetics, Analgesics, Opioid administration & dosage, Behavior, Addictive genetics, Genetic Predisposition to Disease genetics, Genetic Variation genetics, Genome-Wide Association Study, Genomics, Opioid-Related Disorders genetics
Abstract: To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10 -8 ). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10 -8 ). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10 -6 ), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10 -8 ) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10 -7 ). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10 -5 ; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10 -5 ). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10 -5 ; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.
Published: 2020
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46. Components of Endocannabinoid Signaling System Are Expressed in the Perinatal Mouse Cerebellum and Required for Its Normal Development.

Author: Martinez LR, Black KC, Webb BT, Bell A, Baygani SK, Mier TJ, Dominguez L, Mackie K, and Kalinovsky A
Subjects: Animals, Cerebellum metabolism, Mice, Mice, Knockout, Receptor, Cannabinoid, CB1 genetics, Receptors, Cannabinoid metabolism, Endocannabinoids, Signal Transduction
Abstract: Endocannabinoid (eCB) signaling system (ECS), encompassing cannabinoid receptors and enzymes involved in the synthesis and degradation of the endogenous cannabinoid signaling lipids, is highly expressed in the cerebellar cortex of adult humans and rodents. In addition to their well-established role in neuromodulation, eCBs have been shown to play key roles in aspects of neurodevelopment in the fore- and mid-brain, including neurogenesis, cell migration, and synapse specification. However, little is known about the role of ECS in cerebellar development. In this study, we conducted immunohistochemical characterization of ECS components through key stages of cerebellar development in mice using antibodies for 2-arachidonoylglycerol (2-AG) synthetizing and degrading enzymes and the major brain cannabinoid receptor, cannabinoid receptor 1 (CB1), in combination with cerebellar cell markers. Our results reveal a temporally, spatially, and cytologically dynamic pattern of expression. Production, receptor binding, and degradation of eCBs are tightly controlled, thus localization of eCB receptors and the complementary cannabinoid signaling machinery determines the direction, duration, and ultimately the outcome of eCB signaling. To gain insights into the role of eCB signaling in cerebellar development, we characterized gross anatomy of cerebellar midvermis in CB1 knock-out (CB1 KO) mice, as well as their performance in cerebellar-influenced motor tasks. Our results show persistent and selective anatomic and behavioral alterations in CB1 KOs. Consequently, the insights gained from this study lay down the foundation for investigating specific cellular and molecular mechanisms regulated by eCB signaling during cerebellar development., (Copyright © 2020 Martinez et al.)
Published: 2020
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47. Retraction Note: 11,670 whole-genome sequences representative of the Han Chinese population from the CONVERGE project.

Author: Cai N, Bigdeli TB, Kretzschmar WW, Li Y, Liang J, Hu J, Peterson RE, Bacanu S, Webb BT, Riley B, Li Q, Marchini J, Mott R, Kendler KS, and Flint J
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020
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48. Long-Chain ω-3 Levels Are Associated With Increased Alcohol Sensitivity in a Population-Based Sample of Adolescents.

Author: Edwards AC, Heron J, Hibbeln J, Schuckit MA, Webb BT, Hickman M, Davies AG, and Bettinger JC
Subjects: Adolescent, Age Factors, Databases, Factual statistics & numerical data, Female, Humans, Male, Multifactorial Inheritance, Self Report, Alcohol Drinking blood, Alcohol-Related Disorders blood, Docosahexaenoic Acids blood, Eicosapentaenoic Acid blood, Fatty Acids, Omega-3 blood, Underage Drinking
Abstract: Background: The levels of the ω-3 long-chain polyunsaturated fatty acids (ω-3 LC-PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have been associated with alcohol sensitivity in vertebrate and invertebrate model systems, but prior studies have not examined this association in human samples despite evidence of associations between ω-3 LC-PUFA levels and alcohol-related phenotypes. Both alcohol sensitivity and ω-3 LC-PUFA levels are impacted by genetic factors, and these influences may contribute to observed associations between phenotypes. Given the potential for using EPA and DHA supplementation in adjuvant care for alcohol misuse and other outcomes, it is important to clarify how ω-3 LC-PUFA levels relate to alcohol sensitivity., Methods: Analyses were conducted using data from the Avon Longitudinal Study of Parents and Children. Plasma ω-3 LC-PUFA levels were measured at ages 15.5 and 17.5. Participants reported on their initial alcohol sensitivity using the early drinking Self-Rating of the Effects of Alcohol (SRE-5) scale, for which more drinks needed for effects indicates lower levels of response per drink, at ages 15.5, 16.5, and 17.5. Polygenic liability for alcohol consumption, alcohol problems, EPA levels, and DHA levels was derived using summary statistics from large, publicly available datasets. Linear regressions were used to examine the cross-sectional and longitudinal associations between ω-3 LC-PUFA levels and SRE scores., Results: Age 15.5 ω-3 LC-PUFA levels were negatively associated with contemporaneous SRE scores and with age 17.5 SRE scores. One modest association (p = 0.02) between polygenic liability and SRE scores was observed, between alcohol problems-based polygenic risk scores (PRS) and age 16.5 SRE scores. Tests of moderation by genetic liability were not warranted., Conclusions: Plasma ω-3 LC-PUFA levels may be related to initial sensitivity to alcohol during adolescence. These data indicate that diet-related factors have the potential to impact humans' earliest responses to alcohol exposure., (© 2019 by the Research Society on Alcoholism.)
Published: 2019
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49. DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression.

Author: Lapato DM, Roberson-Nay R, Kirkpatrick RM, Webb BT, York TP, and Kinser PA
Subjects: Adult, Black or African American genetics, Black or African American statistics & numerical data, Depression, Postpartum ethnology, Epigenesis, Genetic, Female, Genome-Wide Association Study, Humans, Linear Models, Maternal Age, Perinatal Care, Pregnancy, Smoking epidemiology, Smoking genetics, DNA Methylation, Depression, Postpartum genetics, Genetic Association Studies methods
Abstract: Background: Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology., Results: Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression., Conclusions: Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.
Published: 2019
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50. Expanding the phenotype for the recurrent p.Ala391Glu variant in FGFR3: Beyond crouzon syndrome and acanthosis nigricans.

Author: Rymer K, Shiang R, Hsiung A, Pandya A, Bigdeli T, Webb BT, and Rhodes J
Subjects: Adult, Child, Craniosynostoses genetics, Female, Humans, Infant, Male, Phenotype, Point Mutation, Polymorphism, Single Nucleotide, Receptor, Fibroblast Growth Factor, Type 3 metabolism, Acanthosis Nigricans genetics, Craniofacial Dysostosis genetics, Receptor, Fibroblast Growth Factor, Type 3 genetics
Abstract: Background: Craniosynostosis, or premature fusion of the skull sutures, is a group of disorders that can present in isolation (nonsyndromic) or be associated with other anomalies (syndromic). Delineation of syndromic craniosynostosis is confounded due to phenotypic overlap, variable expression as well as molecular heterogeneity. We report on an infant who presented at birth with multisuture synostosis, turribrachycephaly, midface hypoplasia, beaked nose, low set ears, a high palate and short squat appearing thumbs, and great toes without deviation. The additional MRI findings of choanal stenosis and a Chiari I malformation suggested a diagnosis of Pfeiffer syndrome. First tier molecular testing did not reveal a pathogenic variant., Methods: Whole exome sequencing on DNA samples from the proband and her unaffected parents was utilized to delineate the variant causative for the Pfeiffer syndrome diagnosis., Results: On whole exome sequencing, a de novo NM_000142.4:c.1428C>A missense variant causing a p.Ala391Glu amino acid change in FGFR3 has been identified. The p.Ala391Glu change has been predominantly identified in patients with Crouzon syndrome with acanthosis nigricans., Conclusions: This finding illustrates the first reported case of a child with an overlap with Pfeiffer syndrome to have the p.Ala391Glu variant., (© 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)
Published: 2019
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