Author: "Price, Al" / Publication Year Range: Last 10 years - Searchworks@Jio Institute Digital Library Search Results

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161 results on '"Price, Al"'

1. Do Not Fear What You Are About to Suffer

Author: Price, Allen M.
Published: 2024
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2. Shared heritability and functional enrichment across six solid cancers

Author: Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S
Abstract: Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Published: 2019

3. Shared heritability and functional enrichment across six solid cancers (vol 10, 431, 2019)

Author: Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019

4. 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

5. A genome-wide association study suggests new evidence for an association of the NADPH Oxidase 4 (NOX4) gene with severe diabetic retinopathy in type 2 diabetes

Author: Meng, W, Shah, KP, Pollack, S, Toppila, I, Hebert, HL, McCarthy, MI, Groop, L, Ahlqvist, E, Lyssenko, V, Agardh, E, Daniell, M, Kaidonis, G, Craig, JE, Mitchell, P, Liew, G, Kifley, A, Wang, JJ, Christiansen, MW, Jensen, RA, Penman, A, Hancock, HA, Chen, CJ, Correa, A, Kuo, JZ, Li, X, Chen, Y-DI, Rotter, JI, Klein, R, Klein, B, Wong, TY, Morris, AD, Doney, ASF, Colhoun, HM, Price, AL, Burdon, KP, Groop, P-H, Sandholm, N, Grassi, MA, Sobrin, L, Palmer, CNA, Meng, W, Shah, KP, Pollack, S, Toppila, I, Hebert, HL, McCarthy, MI, Groop, L, Ahlqvist, E, Lyssenko, V, Agardh, E, Daniell, M, Kaidonis, G, Craig, JE, Mitchell, P, Liew, G, Kifley, A, Wang, JJ, Christiansen, MW, Jensen, RA, Penman, A, Hancock, HA, Chen, CJ, Correa, A, Kuo, JZ, Li, X, Chen, Y-DI, Rotter, JI, Klein, R, Klein, B, Wong, TY, Morris, AD, Doney, ASF, Colhoun, HM, Price, AL, Burdon, KP, Groop, P-H, Sandholm, N, Grassi, MA, Sobrin, L, and Palmer, CNA
Abstract: PURPOSE: Diabetic retinopathy is the most common eye complication in patients with diabetes. The purpose of this study is to identify genetic factors contributing to severe diabetic retinopathy. METHODS: A genome-wide association approach was applied. In the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) datasets, cases of severe diabetic retinopathy were defined as type 2 diabetic patients who were ever graded as having severe background retinopathy (Level R3) or proliferative retinopathy (Level R4) in at least one eye according to the Scottish Diabetic Retinopathy Grading Scheme or who were once treated by laser photocoagulation. Controls were diabetic individuals whose longitudinal retinopathy screening records were either normal (Level R0) or only with mild background retinopathy (Level R1) in both eyes. Significant Single Nucleotide Polymorphisms (SNPs) were taken forward for meta-analysis using multiple Caucasian cohorts. RESULTS: Five hundred and sixty cases of type 2 diabetes with severe diabetic retinopathy and 4,106 controls were identified in the GoDARTS cohort. We revealed that rs3913535 in the NADPH Oxidase 4 (NOX4) gene reached a p value of 4.05 × 10-9 . Two nearby SNPs, rs10765219 and rs11018670 also showed promising p values (p values = 7.41 × 10-8 and 1.23 × 10-8 , respectively). In the meta-analysis using multiple Caucasian cohorts (excluding GoDARTS), rs10765219 and rs11018670 showed associations for diabetic retinopathy (p = 0.003 and 0.007, respectively), while the p value of rs3913535 was not significant (p = 0.429). CONCLUSION: This genome-wide association study of severe diabetic retinopathy suggests new evidence for the involvement of the NOX4 gene.
Published: 2018

6. Biological interpretation of genome-wide association studies using predicted gene functions

Author: Pers TH, Karjalainen JM, Chan Y, Westra HJ, Wood AR, Yang J, Lui JC, Vedantam S, Gustafsson S, Esko T, Frayling T, Speliotes EK, Boehnke M, Raychaudhuri S, Fehrmann RS, Hirschhorn JN, Franke L, Chu AY, Estrada K, Luan J, Kutalik Z, Amin N, Buchkovich ML, Croteau Chonka DC, Day FR, Duan Y, Fall T, Fehrmann R, Ferreira T, Jackson AU, Karjalainen J, Lo KS, Locke AE, Mägi R, Mihailov E, Porcu E, Randall JC, Scherag A, Vinkhuyzen AA, Winkler TW, Workalemahu T, Zhao JH, Absher D, Albrecht E, Anderson D, Baron J, Beekman M, Demirkan A, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Fraser RM, Goel A, Gong J, Justice E, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Mateo Leach I, Medina Gomez C, Nalls MA, Nyholt DR, Palmer CD, Pasko D, Pechlivanis S, Prokopenko I, Ried JS, Ripke S, Shungin D, Stancáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Afzal U, Ärnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Bolton JL, Böttcher Y, Boyd HA, Bruinenberg M, Buckley BM, Buyske S, Caspersen IH, Chines PS, Clarke R, Claudi Boehm S, Cooper M, Daw EW, De Jong A, Deelen J, Delgado G, Denny JC, Dhonukshe Rutten R, Dimitriou M, Doney AS, Dörr M, Eklund N, Eury E, Folkersen L, Garcia ME, Geller F, Giedraitis V, Go AS, Grallert H, Grammer TB, Gräßler J, Grönberg H, de Groot LC, Groves CJ, Haessler J, Haller T, Hallmans G, Hannemann A, Hartman CA, Hassinen M, Hayward C, Heard Costa NL, Helmer Q, Hemani G, Henders AK, Hillege HL, Hlatky MA, Hoffmann W, Hoffmann P, Holmen O, Houwing Duistermaat JJ, Illig T, Isaacs A, James AL, Jeff J, Johansen B, Johansson Å, Jolley J, Juliusdottir T, Junttila J, Kho AN, Kinnunen L, Klopp N, Kocher T, Kratzer W, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Lu Y, Lyssenko V, Magnusson PK, Mahajan A, Maillard M, McArdle WL, McKenzie CA, McLachlan S, McLaren PJ, Menni C, Merger S, Milani L, 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Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Gansevoort RT, Gejman PV, Gieger C, Golay A, Gottesman O, Gudnason V, Gyllensten U, Haas DW, Hall AS, Harris TB, Hattersley AT, Heath AC, Hengstenberg C, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Jacobs KB, Jarvelin MR, Jousilahti P, Jula AM, Kaprio J, Kastelein JJ, Kayser M, Kee F, Keinanen Kiukaanniemi SM, Kiemeney LA, Kooner JS, Kooperberg C, Koskinen S, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lupoli S, Madden PA, Männistö S, Manunta P, Marette A, Matise TC, McKnight B, Meitinger T, Moll FL, Montgomery GW, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Ouwehand WH, Pasterkamp G, Peters A, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ritchie M, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Sebert S, Sever P, Shuldiner AR, Sinisalo J, 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Borecki IB, McCarthy MI, Metspalu A, Stefansson K, Uitterlinden AG, van Duijn CM, Willer CJ, Price AL, Lettre G, Loos RJ, Weedon MN, Ingelsson E, O'Connell JR, Abecasis GR, Chasman DI, Goddard ME, Visscher PM, Frayling T.M., Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Wood, AR., Esko, T., Yang, J., Vedantam, S., Pers, TH., Gustafsson, S., Chu, AY., Estrada, K., Luan£££Jian'an£££ J., Kutalik£££Zoltán£££ Z., Amin, N., Buchkovich, ML., Croteau-Chonka, DC., Day, FR., Duan, Y., Fall, T., Fehrmann, R., Ferreira, T., Jackson, AU., Karjalainen, J., Lo, KS., Locke, AE., Mägi, R., Mihailov, E., Porcu, E., Randall, JC., Scherag, A., Vinkhuyzen, AA., Westra, HJ., Winkler, TW., Workalemahu, T., Zhao, JH., Absher, D., Albrecht, E., Anderson, D., Baron, J., Beekman, M., Demirkan, A., Ehret, GB., Feenstra, B., Feitosa, MF., Fischer, K., Fraser, RM., Goel, A., Gong, J., Justice, E., Kanoni, S., Kleber, ME., Kristiansson, K., Lim, U., Lotay, V., Lui, JC., Mangino, M., Mateo Leach, I., Medina-Gomez, C., Nalls, MA., Nyholt, DR., Palmer, CD., Pasko, D., Pechlivanis, S., Prokopenko, I., Ried, JS., Ripke, S., Shungin, D., Stancáková, A., Strawbridge, RJ., Sung, YJ., Tanaka, T., Teumer, A., Trompet, S., van der Laan SW., van Setten, J., Van Vliet-Ostaptchouk JV., Wang, Z., Yengo£££Loïc£££ L., Zhang, W., Afzal, U., Ärnlöv, J., Arscott, GM., Bandinelli, S., Barrett, A., Bellis, C., Bennett, AJ., Berne, C., Blüher, M., Bolton, JL., Böttcher, Y., Boyd, HA., Bruinenberg, M., Buckley, BM., Buyske, S., Caspersen, IH., Chines, PS., Clarke, R., Claudi-Boehm, S., Cooper, M., Daw, EW., De Jong, A., Deelen, J., Delgado, G., Denny, JC., Dhonukshe-Rutten, R., Dimitriou, M., Doney, AS., Dörr, M., Eklund, N., Eury, E., Folkersen, L., Garcia, ME., Geller, F., Giedraitis, V., Go, AS., Grallert, H., Grammer, TB., Gräßler, J., Grönberg, H., de Groot LC., Groves, CJ., Haessler, J., Haller, T., Hallmans, G., Hannemann, A., Hartman, CA., Hassinen, M., Hayward, C., Heard-Costa, NL., Helmer, Q., Hemani, G., Henders, AK., Hillege, HL., Hlatky, MA., Hoffmann, W., Hoffmann, P., Holmen, O., Houwing-Duistermaat, JJ., Illig, T., Isaacs, A., James, AL., Jeff, J., Johansen, B., Johansson£££Åsa£££ Å., Jolley, J., Juliusdottir, T., Junttila, J., Kho, AN., Kinnunen, L., Klopp, N., Kocher, T., Kratzer, W., Lichtner, P., Lind, L., Lindström, J., Lobbens, S., Lorentzon, M., Lu, Y., Lyssenko, V., Magnusson, PK., Mahajan, A., Maillard, M., McArdle, WL., McKenzie, CA., McLachlan, S., McLaren, PJ., Menni, C., Merger, S., Milani, L., Moayyeri, A., Monda, KL., Morken, MA., Müller, G., Müller-Nurasyid, M., Musk, AW., Narisu, N., Nauck, M., Nolte, IM., Nöthen, MM., Oozageer, L., Pilz, S., Rayner, NW., Renstrom, F., Robertson, NR., Rose, LM., Roussel, R., Sanna, S., Scharnagl, H., Scholtens, S., Schumacher, FR., Schunkert, H., Scott, RA., Sehmi, J., Seufferlein, T., Shi, J., Silventoinen, K., Smit, JH., Smith, AV., Smolonska, J., Stanton, AV., Stirrups, K., Stott, DJ., Stringham, HM., Sundström, J., Swertz, MA., Syvänen, AC., Tayo, BO., Thorleifsson, G., Tyrer, JP., van Dijk, S., van Schoor NM., van der Velde, N., van Heemst, D., van Oort FV., Vermeulen, SH., Verweij, N., Vonk, JM., Waite, LL., Waldenberger, M., Wennauer, R., Wilkens, LR., Willenborg, C., Wilsgaard, T., Wojczynski, MK., Wong, A., Wright, AF., Zhang, Q., Arveiler, D., Bakker, SJ., Beilby, J., Bergman, RN., Bergmann, S., Biffar, R., Blangero, J., Boomsma, I., Bornstein, SR., Bovet, P., Brambilla, P., Brown, MJ., Campbell, H., Caulfield, MJ., Chakravarti, A., Collins, R., Collins, FS., Crawford, DC., Cupples, LA., Danesh, J., de Faire, U., den Ruijter HM., Erbel, R., Erdmann, J., Eriksson, JG., Farrall, M., Ferrannini, E., Ferrières, J., Ford, I., Forouhi, NG., Forrester, T., Gansevoort, RT., Gejman, PV., Gieger, C., Golay, A., Gottesman, O., Gudnason, V., Gyllensten, U., Haas, DW., Hall, AS., Harris, TB., Hattersley, AT., Heath, AC., Hengstenberg, C., Hicks, AA., Hindorff, LA., Hingorani, AD., Hofman, A., Hovingh, GK., Humphries, SE., Hunt, SC., Hypponen, E., Jacobs, KB., Jarvelin, MR., Jousilahti, P., Jula, AM., Kaprio, J., Kastelein, JJ., Kayser, M., Kee, F., Keinanen-Kiukaanniemi, SM., Kiemeney, LA., Kooner, JS., Kooperberg, C., Koskinen, S., Kovacs, P., Kraja, AT., Kumari, M., Kuusisto, J., Lakka, TA., Langenberg, C., Le Marchand, L., Lehtimäki, T., Lupoli, S., Madden, PA., Männistö, S., Manunta, P., Marette, A., Matise, TC., McKnight, B., Meitinger, T., Moll, FL., Montgomery, GW., Morris, AD., Morris, AP., Murray, JC., Nelis, M., Ohlsson, C., Oldehinkel, AJ., Ong, KK., Ouwehand, WH., Pasterkamp, G., Peters, A., Pramstaller, PP., Price, JF., Qi, L., Raitakari, OT., Rankinen, T., Rao, DC., Rice, TK., Ritchie, M., Rudan, I., Salomaa, V., Samani, NJ., Saramies, J., Sarzynski, MA., Schwarz, PE., Sebert, S., Sever, P., Shuldiner, AR., Sinisalo, J., Steinthorsdottir, V., Stolk, RP., Tardif, JC., Tönjes, A., Tremblay, A., Tremoli, E., Virtamo, J., Vohl, MC., Amouyel, P., Asselbergs, FW., Assimes, TL., Bochud, M., Boehm, BO., Boerwinkle, E., Bottinger, EP., Bouchard, C., Cauchi, S., Chambers, JC., Chanock, SJ., Cooper, RS., de Bakker PI., Dedoussis, G., Ferrucci, L., Franks, PW., Froguel, P., Groop, LC., Haiman, CA., Hamsten, A., Hayes, MG., Hui, J., Hunter, DJ., Hveem, K., Jukema, JW., Kaplan, RC., Kivimaki, M., Kuh, D., Laakso, M., Liu, Y., Martin, NG., März, W., Melbye, M., Moebus, S., Munroe, PB., Njølstad, I., Oostra, BA., Palmer, CN., Pedersen, NL., Perola, M., Pérusse, L., Peters, U., Powell, JE., Power, C., Quertermous, T., Rauramaa, R., Reinmaa, E., Ridker, PM., Rivadeneira, F., Rotter, JI., Saaristo, TE., Saleheen, D., Schlessinger, D., Slagboom, PE., Snieder, H., Spector, TD., Strauch, K., Stumvoll, M., Tuomilehto, J., Uusitupa, M., van der Harst, P., Völzke, H., Walker, M., Wareham, NJ., Watkins, H., Wichmann, HE., Wilson, JF., Zanen, P., Deloukas, P., Heid, IM., Lindgren, CM., Mohlke, KL., Speliotes, EK., Thorsteinsdottir, U., Barroso£££Inês£££ I., Fox, CS., North, KE., Strachan, DP., Beckmann, JS., Berndt, SI., Boehnke, M., Borecki, IB., McCarthy, MI., Metspalu, A., Stefansson, K., Uitterlinden, AG., van Duijn CM., Franke, L., Willer, CJ., Price, AL., Lettre, G., Loos, RJ., Weedon, MN., Ingelsson, E., O'Connell, JR., Abecasis, GR., Chasman, DI., Goddard, ME., Visscher, PM., Hirschhorn, JN., Frayling, TM., Clinicum, Jaakko Kaprio / Principal Investigator, Department of Public Health, Institute for Molecular Medicine Finland, Genetic Epidemiology, Pers, T, Karjalainen, J, Chan, Y, Westra, H, Wood, A, Yang, J, Lui, J, Vedantam, S, Gustafsson, S, Esko, T, Frayling, T, Speliotes, E, Boehnke, M, Raychaudhuri, S, Fehrmann, R, Hirschhorn, J, Franke, L, Chu, A, Estrada, K, Luan, J, Kutalik, Z, Amin, N, Buchkovich, M, Croteau Chonka, D, Day, F, Duan, Y, Fall, T, Ferreira, T, Jackson, A, Lo, K, Locke, A, Mägi, R, Mihailov, E, Porcu, E, Randall, J, Scherag, A, Vinkhuyzen, A, Winkler, T, Workalemahu, T, Zhao, J, Absher, D, Albrecht, E, Anderson, D, Baron, J, Beekman, M, Demirkan, A, Ehret, G, Feenstra, B, Feitosa, M, Fischer, K, Fraser, R, Goel, A, Gong, J, Justice, E, Kanoni, S, Kleber, M, Kristiansson, K, Lim, U, Lotay, V, Mangino, M, Mateo Leach, I, Medina Gomez, C, Nalls, M, Nyholt, D, Palmer, C, Pasko, D, Pechlivanis, S, Prokopenko, I, Ried, J, Ripke, S, Shungin, D, Stancáková, A, Strawbridge, R, Sung, Y, Tanaka, T, Teumer, A, Trompet, S, van der Laan, S, van Setten, J, Van Vliet Ostaptchouk, J, Wang, Z, Yengo, L, Zhang, W, Afzal, U, Ärnlöv, J, Arscott, G, Bandinelli, S, Barrett, A, Bellis, C, Bennett, A, Berne, C, Blüher, M, Bolton, J, Böttcher, Y, Boyd, H, Bruinenberg, M, Buckley, B, Buyske, S, Caspersen, I, Chines, P, Clarke, R, Claudi Boehm, S, Cooper, M, Daw, E, De Jong, A, Deelen, J, Delgado, G, Denny, J, Dhonukshe Rutten, R, Dimitriou, M, Doney, A, Dörr, M, Eklund, N, Eury, E, Folkersen, L, Garcia, M, Geller, F, Giedraitis, V, Go, A, Grallert, H, Grammer, T, Gräßler, J, Grönberg, H, de Groot, L, Groves, C, Haessler, J, Haller, T, Hallmans, G, Hannemann, A, Hartman, C, Hassinen, M, Hayward, C, Heard Costa, N, Helmer, Q, Hemani, G, Henders, A, Hillege, H, Hlatky, M, Hoffmann, W, Hoffmann, P, Holmen, O, Houwing Duistermaat, J, Illig, T, Isaacs, A, James, A, Jeff, J, Johansen, B, Johansson, Å, Jolley, J, Juliusdottir, T, Junttila, J, Kho, A, Kinnunen, L, Klopp, N, Kocher, T, Kratzer, W, Lichtner, P, Lind, L, Lindström, J, Lobbens, S, Lorentzon, M, Lu, Y, Lyssenko, V, Magnusson, P, Mahajan, A, Maillard, M, Mcardle, W, Mckenzie, C, Mclachlan, S, Mclaren, P, Menni, C, Merger, S, Milani, L, Moayyeri, A, Monda, K, Morken, M, Müller, G, Müller Nurasyid, M, Musk, A, Narisu, N, Nauck, M, Nolte, I, Nöthen, M, Oozageer, L, Pilz, S, Rayner, N, Renstrom, F, Robertson, N, Rose, L, Roussel, R, Sanna, S, Scharnagl, H, Scholtens, S, Schumacher, F, Schunkert, H, Scott, R, Sehmi, J, Seufferlein, T, Shi, J, Silventoinen, K, Smit, J, Smith, A, Smolonska, J, Stanton, A, Stirrups, K, Stott, D, Stringham, H, Sundström, J, Swertz, M, Syvänen, A, Tayo, B, Thorleifsson, G, Tyrer, J, van Dijk, S, van Schoor, N, van der Velde, N, van Heemst, D, van Oort, F, Vermeulen, S, Verweij, N, Vonk, J, Waite, L, Waldenberger, M, Wennauer, R, Wilkens, L, Willenborg, C, Wilsgaard, T, Wojczynski, M, Wong, A, Wright, A, Zhang, Q, Arveiler, D, Bakker, S, Beilby, J, Bergman, R, Bergmann, S, Biffar, R, Blangero, J, Boomsma, I, Bornstein, S, Bovet, P, Brambilla, P, Brown, M, Campbell, H, Caulfield, M, Chakravarti, A, Collins, R, Collins, F, Crawford, D, Cupples, L, Danesh, J, de Faire, U, den Ruijter, H, Erbel, R, Erdmann, J, Eriksson, J, Farrall, M, Ferrannini, E, Ferrières, J, Ford, I, Forouhi, N, Forrester, T, Gansevoort, R, Gejman, P, Gieger, C, Golay, A, Gottesman, O, Gudnason, V, Gyllensten, U, Haas, D, Hall, A, Harris, T, Hattersley, A, Heath, A, Hengstenberg, C, Hicks, A, Hindorff, L, Hingorani, A, Hofman, A, Hovingh, G, Humphries, S, Hunt, S, Hypponen, E, Jacobs, K, Jarvelin, M, Jousilahti, P, Jula, A, Kaprio, J, Kastelein, J, Kayser, M, Kee, F, Keinanen Kiukaanniemi, S, Kiemeney, L, Kooner, J, Kooperberg, C, Koskinen, S, Kovacs, P, Kraja, A, Kumari, M, Kuusisto, J, Lakka, T, Langenberg, C, Le Marchand, L, Lehtimäki, T, Lupoli, S, Madden, P, Männistö, S, Manunta, P, Marette, A, Matise, T, Mcknight, B, Meitinger, T, Moll, F, Montgomery, G, Morris, A, Murray, J, Nelis, M, Ohlsson, C, Oldehinkel, A, Ong, K, Ouwehand, W, Pasterkamp, G, Peters, A, Pramstaller, P, Price, J, Qi, L, Raitakari, O, Rankinen, T, Rao, D, Rice, T, Ritchie, M, Rudan, I, Salomaa, V, Samani, N, Saramies, J, Sarzynski, M, Schwarz, P, Sebert, S, Sever, P, Shuldiner, A, Sinisalo, J, Steinthorsdottir, V, Stolk, R, Tardif, J, Tönjes, A, Tremblay, A, Tremoli, E, Virtamo, J, Vohl, M, Amouyel, P, Asselbergs, F, Assimes, T, Bochud, M, Boehm, B, Boerwinkle, E, Bottinger, E, Bouchard, C, Cauchi, S, Chambers, J, Chanock, S, Cooper, R, de Bakker, P, Dedoussis, G, Ferrucci, L, Franks, P, Froguel, P, Groop, L, Haiman, C, Hamsten, A, Hayes, M, Hui, J, Hunter, D, Hveem, K, Jukema, J, Kaplan, R, Kivimaki, M, Kuh, D, Laakso, M, Liu, Y, Martin, N, März, W, Melbye, M, Moebus, S, Munroe, P, Njølstad, I, Oostra, B, Pedersen, N, Perola, M, Pérusse, L, Peters, U, Powell, J, Power, C, Quertermous, T, Rauramaa, R, Reinmaa, E, Ridker, P, Rivadeneira, F, Rotter, J, Saaristo, T, Saleheen, D, Schlessinger, D, Slagboom, P, Snieder, H, Spector, T, Strauch, K, Stumvoll, M, Tuomilehto, J, Uusitupa, M, van der Harst, P, Völzke, H, Walker, M, Wareham, N, Watkins, H, Wichmann, H, Wilson, J, Zanen, P, Deloukas, P, Heid, I, Lindgren, C, Mohlke, K, Thorsteinsdottir, U, Barroso, I, Fox, C, North, K, Strachan, D, Beckmann, J, Berndt, S, Borecki, I, Mccarthy, M, Metspalu, A, Stefansson, K, Uitterlinden, A, van Duijn, C, Willer, C, Price, A, Lettre, G, Loos, R, Weedon, M, Ingelsson, E, O'Connell, J, Abecasis, G, Chasman, D, Goddard, M, Visscher, P, APH - Amsterdam Public Health, AMS - Amsterdam Movement Sciences, Geriatrics, Other departments, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Pers, Th, Karjalainen, Jm, Westra, Hj, Wood, Ar, Lui, Jc, Speliotes, Ek, Hirschhorn, Jn, and Faculty of Health Sciences
Subjects: Cell type, Candidate gene, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, LOCI, General Physics and Astronomy, Genome-wide association study, Disease, Computational biology, Biology, Research Support, General Biochemistry, Genetics and Molecular Biology, Article, DISEASE, N.I.H, CANDIDATE GENES, Genome-Wide Association Study/methods, Software, HEIGHT, Research Support, N.I.H., Extramural, Genetics, Journal Article, NETWORK, Non-U.S. Gov't, Gene, COMMON, Intramural, ARCHITECTURE, Biochemistry, Genetics and Molecular Biology (all), Multidisciplinary, IDENTIFICATION, ta1184, Research Support, Non-U.S. Gov't, Gene sets, Extramural, General Chemistry, ta3121, Research Support, N.I.H., Intramural, Phenotype, 3142 Public health care science, environmental and occupational health, Biological sciences, DATA SETS, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Identification (biology), INTEGRATION, Genome-Wide Association Study
Abstract: Article, The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes., published version, http://purl.org/eprint/status/PeerReviewed
Published: 2015

7. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Author: Gusev, A, Shi, H, Kichaev, G, Pomerantz, M, Li, F, Long, HW, Ingles, SA, Kittles, RA, Strom, SS, Rybicki, BA, Nemesure, B, Isaacs, WB, Zheng, W, Pettaway, CA, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Chokkalingam, AP, John, EM, Murphy, AB, Signorello, LB, Carpten, J, Leske, MC, Wu, S-Y, Hennis, AJM, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Witte, JS, Casey, G, Kaggwa, S, Cook, MB, Stram, DO, Blot, WJ, Eeles, RA, Easton, D, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Muir, K, Giles, GG, Southey, MC, Fitzgerald, LM, Gronberg, H, Wiklund, F, Aly, M, Henderson, BE, Schleutker, J, Wahlfors, T, Tammela, TLJ, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Cannon-Albright, L, Teerlink, C, Brenner, H, Dieffenbach, AK, Arndt, V, Park, JY, Sellers, TA, Lin, H-Y, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Spurdle, A, Clements, JA, Teixeira, MR, Pandha, H, Michael, A, Paulo, P, Maia, S, Kierzek, A, Conti, DV, Albanes, D, Berg, C, Berndt, SI, Campa, D, Crawford, ED, Diver, WR, Gapstur, SM, Gaziano, JM, Giovannucci, E, Hoover, R, Hunter, DJ, Johansson, M, Kraft, P, Le Marchand, L, Lindstrom, S, Navarro, C, Overvad, K, Riboli, E, Siddiq, A, Stevens, VL, Trichopoulos, D, Vineis, P, Yeager, M, Trynka, G, Raychaudhuri, S, Schumacher, FR, Price, AL, Freedman, ML, Haiman, CA, Pasaniuc, B, Cook, M, Guy, M, Govindasami, K, Leongamornlert, D, Sawyer, EJ, Wilkinson, R, Saunders, EJ, Tymrakiewicz, M, Dadaev, T, Morgan, A, Fisher, C, Hazel, S, Livni, N, Lophatananon, A, Pedersen, J, Hopper, JL, Adolfson, J, Stattin, P, Johansson, J-E, Cavalli-Bjoerkman, C, Karlsson, A, Broms, M, Auvinen, A, Kujala, P, Maeaettaenen, L, Murtola, T, Taari, K, Weischer, M, Nielsen, SF, Klarskov, P, Roder, A, Iversen, P, Wallinder, H, Gustafsson, S, Cox, A, Brown, P, George, A, Marsden, G, Lane, A, Davis, M, Tillmans, L, Riska, S, Wang, L, Rinckleb, A, Lubiski, J, Stegmaier, C, Pow-Sang, J, Park, H, Radlein, S, Rincon, M, Haley, J, Zachariah, B, Kachakova, D, Popov, E, Mitkova, A, Vlahova, A, Dikov, T, Christova, S, Heathcote, P, Wood, G, Malone, G, Saunders, P, Eckert, A, Yeadon, T, Kerr, K, Collins, A, Turner, M, Srinivasan, S, Kedda, M-A, Alexander, K, Omara, T, Wu, H, Henrique, R, Pinto, P, Santos, J, Barros-Silva, J, and Consortium, PRACTICAL
Subjects: urologic and male genital diseases
Abstract: Although genome-wide association studies have identified over 100 risk loci that explain ~33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.
Published: 2016

8. Large-Scale Genomic Analyses Link Reproductive Aging to Hypothalamic Signaling, Breast Cancer Susceptibility, and BRCA1-Mediated DNA Repair EDITORIAL COMMENT

Author: Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, Lisette, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, Najaf, Corre, T, Hottenga, JJ (Jouke Jan), Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, AL, Boutin, TS, Brauch, H, Brenner, H, Bruning, T, Burwinkel, B, Campbell, A (Archie), Campbell, H, Chanock, SJ, Chapman, JR, Chen, YDI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, de Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Dork, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, XQ, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, Bert, Homuth, G, Hooning, Maartje, Hopper, JL, Hu, FB, Huang, JY, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, VM, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, JM, Li, X, Lindstrom, S, Liu, YM, Luan, JA, Lubinski, J, Magi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Muller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, Fernando, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK (Marjanka), Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, Caroline, Simard, J, Sorice, R, Southey, MC, Stockl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q (Qing), Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, Duijn, Cornelia, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, Jenny, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Systems Ecology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Internal Medicine, Epidemiology, Medical Oncology, and Clinical Genetics
Subjects: SDG 3 - Good Health and Well-being
Published: 2015

9. Drosophila Muller F elements maintain a distinct set of genomic properties over 40 million years of evolution

Author: Leung, W, Shaffer, CD, Reed, LK, Smith, ST, Barshop, W, Dirkes, W, Dothager, M, Lee, P, Wong, J, Xiong, D, Yuan, H, Bedard, JEJ, Machone, JF, Patterson, SD, Price, AL, Turner, BA, Robic, S, Luippold, EK, McCartha, SR, Walji, TA, Walker, CA, Saville, K, Abrams, MK, Armstrong, AR, Armstrong, W, Bailey, RJ, Barberi, CR, Beck, LR, Blaker, AL, Blunden, CE, Brand, JP, Brock, EJ, Brooks, DW, Brown, M, Butzler, SC, Clark, EM, Clark, NB, Collins, AA, Cotteleer, RJ, Cullimore, PR, Dawson, SG, Docking, CT, Dorsett, SL, Dougherty, GA, Downey, KA, Drake, AP, Earl, EK, Floyd, TG, Forsyth, JD, Foust, JD, Franchi, SL, Geary, JF, Hanson, CK, Harding, TS, Harris, CB, Heckman, JM, Holderness, HL, Howey, NA, Jacobs, DA, Jewell, ES, Kaisler, M, Karaska, EA, Kehoe, JL, Koaches, HC, Koehler, J, Koenig, D, Kujawski, AJ, Kus, JE, Lammers, JA, Leads, RR, Leatherman, EC, Lippert, RN, Messenger, GS, Morrow, AT, NewcombVictoria, HJ, Plasman, Potocny, SJ, Powers, MK, Reem, RM, Rennhack, JP, Reynolds, KR, Reynolds, LA, Rhee, DK, Rivard, AB, Ronk, AJ, Rooney, MB, Rubin, LS, Salbert, LR, Saluja, RK, Schauder, T, Schneiter, AR, Schulz, RW, Smith, KE, Spencer, S, Swanson, BR, Tache, MA, Tewilliager, AA, Tilot, AK, and VanEck, E
Abstract: © 2015 Leung et al. The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25-50%) than euchromatic reference regions (3-11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11-27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4-3.6 vs. 8.4-8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination.Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu.
Published: 2015

10. Deep targeted sequencing of 12 breast cancer susceptibility regions in 4611 women across four different ethnicities

Author: Lindstroem, S, Ablorh, A, Chapman, B, Gusev, A, Chen, G, Turman, C, Eliassen, AH, Price, AL, Henderson, BE, Le Marchand, L, Hofmann, O, Haiman, CA, Kraft, P, Lindstroem, S, Ablorh, A, Chapman, B, Gusev, A, Chen, G, Turman, C, Eliassen, AH, Price, AL, Henderson, BE, Le Marchand, L, Hofmann, O, Haiman, CA, and Kraft, P
Abstract: BACKGROUND: Although genome-wide association studies (GWASs) have identified thousands of disease susceptibility regions, the underlying causal mechanism in these regions is not fully known. It is likely that the GWAS signal originates from one or many as yet unidentified causal variants. METHODS: Using next-generation sequencing, we characterized 12 breast cancer susceptibility regions identified by GWASs in 2288 breast cancer cases and 2323 controls across four populations of African American, European, Japanese, and Hispanic ancestry. RESULTS: After genotype calling and quality control, we identified 137,530 single-nucleotide variants (SNVs); of those, 87.2 % had a minor allele frequency (MAF) <0.005. For SNVs with MAF >0.005, we calculated the smallest number of SNVs needed to obtain a posterior probability set (PPS) such that there is 90 % probability that the causal SNV is included. We found that the PPS for two regions, 2q35 and 11q13, contained less than 5 % of the original SNVs, dramatically decreasing the number of potentially causal SNVs. However, we did not find strong evidence supporting a causal role for any individual SNV. In addition, there were no significant gene-based rare SNV associations after correcting for multiple testing. CONCLUSIONS: This study illustrates some of the challenges faced in fine-mapping studies in the post-GWAS era, most importantly the large sample sizes needed to identify rare-variant associations or to distinguish the effects of strongly correlated common SNVs.
Published: 2016

11. The Unschooling of the Well-educated Negro

Author: Price, Allen
Published: 2021

12. Biological interpretation of genome-wide association studies using predicted gene functions

Author: Pers, T, Karjalainen, J, Chan, Y, Westra, H, Wood, A, Yang, J, Lui, J, Vedantam, S, Gustafsson, S, Esko, T, Frayling, T, Speliotes, E, Boehnke, M, Raychaudhuri, S, Fehrmann, R, Hirschhorn, J, Franke, L, Chu, A, Estrada, K, Luan, J, Kutalik, Z, Amin, N, Buchkovich, M, Croteau Chonka, D, Day, F, Duan, Y, Fall, T, Ferreira, T, Jackson, A, Lo, K, Locke, A, Mägi, R, Mihailov, E, Porcu, E, Randall, J, Scherag, A, Vinkhuyzen, A, Winkler, T, Workalemahu, T, Zhao, J, Absher, D, Albrecht, E, Anderson, D, Baron, J, Beekman, M, Demirkan, A, Ehret, G, Feenstra, B, Feitosa, M, Fischer, K, Fraser, R, Goel, A, Gong, J, Justice, E, Kanoni, S, Kleber, M, Kristiansson, K, Lim, U, Lotay, V, Mangino, M, Mateo Leach, I, Medina Gomez, C, Nalls, M, Nyholt, D, Palmer, C, Pasko, D, Pechlivanis, S, Prokopenko, I, Ried, J, Ripke, S, Shungin, D, Stancáková, A, Strawbridge, R, Sung, Y, Tanaka, T, Teumer, A, Trompet, S, van der Laan, S, van Setten, J, Van Vliet Ostaptchouk, J, Wang, Z, Yengo, L, Zhang, W, Afzal, U, Ärnlöv, J, Arscott, G, Bandinelli, S, Barrett, A, Bellis, C, Bennett, A, Berne, C, Blüher, M, Bolton, J, Böttcher, Y, Boyd, H, Bruinenberg, M, Buckley, B, Buyske, S, Caspersen, I, Chines, P, Clarke, R, Claudi Boehm, S, Cooper, M, Daw, E, De Jong, A, Deelen, J, Delgado, G, Denny, J, Dhonukshe Rutten, R, Dimitriou, M, Doney, A, Dörr, M, Eklund, N, Eury, E, Folkersen, L, Garcia, M, Geller, F, Giedraitis, V, Go, A, Grallert, H, Grammer, T, Gräßler, J, Grönberg, H, de Groot, L, Groves, C, Haessler, J, Haller, T, Hallmans, G, Hannemann, A, Hartman, C, Hassinen, M, Hayward, C, Heard Costa, N, Helmer, Q, Hemani, G, Henders, A, Hillege, H, Hlatky, M, Hoffmann, W, Hoffmann, P, Holmen, O, Houwing Duistermaat, J, Illig, T, Isaacs, A, James, A, Jeff, J, Johansen, B, Johansson, Å, Jolley, J, Juliusdottir, T, Junttila, J, Kho, A, Kinnunen, L, Klopp, N, Kocher, T, Kratzer, W, Lichtner, P, Lind, L, Lindström, J, Lobbens, S, Lorentzon, M, Lu, Y, Lyssenko, V, Magnusson, P, Mahajan, A, Maillard, M, Mcardle, W, Mckenzie, C, Mclachlan, S, Mclaren, P, Menni, C, Merger, S, Milani, L, Moayyeri, A, Monda, K, Morken, M, Müller, G, Müller Nurasyid, M, Musk, A, Narisu, N, Nauck, M, Nolte, I, Nöthen, M, Oozageer, L, Pilz, S, Rayner, N, Renstrom, F, Robertson, N, Rose, L, Roussel, R, Sanna, S, Scharnagl, H, Scholtens, S, Schumacher, F, Schunkert, H, Scott, R, Sehmi, J, Seufferlein, T, Shi, J, Silventoinen, K, Smit, J, Smith, A, Smolonska, J, Stanton, A, Stirrups, K, Stott, D, Stringham, H, Sundström, J, Swertz, M, Syvänen, A, Tayo, B, Thorleifsson, G, Tyrer, J, van Dijk, S, van Schoor, N, van der Velde, N, van Heemst, D, van Oort, F, Vermeulen, S, Verweij, N, Vonk, J, Waite, L, Waldenberger, M, Wennauer, R, Wilkens, L, Willenborg, C, Wilsgaard, T, Wojczynski, M, Wong, A, Wright, A, Zhang, Q, Arveiler, D, Bakker, S, Beilby, J, Bergman, R, Bergmann, S, Biffar, R, Blangero, J, Boomsma, I, Bornstein, S, Bovet, P, Brambilla, P, Brown, M, Campbell, H, Caulfield, M, Chakravarti, A, Collins, R, Collins, F, Crawford, D, Cupples, L, Danesh, J, de Faire, U, den Ruijter, H, Erbel, R, Erdmann, J, Eriksson, J, Farrall, M, Ferrannini, E, Ferrières, J, Ford, I, Forouhi, N, Forrester, T, Gansevoort, R, Gejman, P, Gieger, C, Golay, A, Gottesman, O, Gudnason, V, Gyllensten, U, Haas, D, Hall, A, Harris, T, Hattersley, A, Heath, A, Hengstenberg, C, Hicks, A, Hindorff, L, Hingorani, A, Hofman, A, Hovingh, G, Humphries, S, Hunt, S, Hypponen, E, Jacobs, K, Jarvelin, M, Jousilahti, P, Jula, A, Kaprio, J, Kastelein, J, Kayser, M, Kee, F, Keinanen Kiukaanniemi, S, Kiemeney, L, Kooner, J, Kooperberg, C, Koskinen, S, Kovacs, P, Kraja, A, Kumari, M, Kuusisto, J, Lakka, T, Langenberg, C, Le Marchand, L, Lehtimäki, T, Lupoli, S, Madden, P, Männistö, S, Manunta, P, Marette, A, Matise, T, Mcknight, B, Meitinger, T, Moll, F, Montgomery, G, Morris, A, Murray, J, Nelis, M, Ohlsson, C, Oldehinkel, A, Ong, K, Ouwehand, W, Pasterkamp, G, Peters, A, Pramstaller, P, Price, J, Qi, L, Raitakari, O, Rankinen, T, Rao, D, Rice, T, Ritchie, M, Rudan, I, Salomaa, V, Samani, N, Saramies, J, Sarzynski, M, Schwarz, P, Sebert, S, Sever, P, Shuldiner, A, Sinisalo, J, Steinthorsdottir, V, Stolk, R, Tardif, J, Tönjes, A, Tremblay, A, Tremoli, E, Virtamo, J, Vohl, M, Amouyel, P, Asselbergs, F, Assimes, T, Bochud, M, Boehm, B, Boerwinkle, E, Bottinger, E, Bouchard, C, Cauchi, S, Chambers, J, Chanock, S, Cooper, R, de Bakker, P, Dedoussis, G, Ferrucci, L, Franks, P, Froguel, P, Groop, L, Haiman, C, Hamsten, A, Hayes, M, Hui, J, Hunter, D, Hveem, K, Jukema, J, Kaplan, R, Kivimaki, M, Kuh, D, Laakso, M, Liu, Y, Martin, N, März, W, Melbye, M, Moebus, S, Munroe, P, Njølstad, I, Oostra, B, Pedersen, N, Perola, M, Pérusse, L, Peters, U, Powell, J, Power, C, Quertermous, T, Rauramaa, R, Reinmaa, E, Ridker, P, Rivadeneira, F, Rotter, J, Saaristo, T, Saleheen, D, Schlessinger, D, Slagboom, P, Snieder, H, Spector, T, Strauch, K, Stumvoll, M, Tuomilehto, J, Uusitupa, M, van der Harst, P, Völzke, H, Walker, M, Wareham, N, Watkins, H, Wichmann, H, Wilson, J, Zanen, P, Deloukas, P, Heid, I, Lindgren, C, Mohlke, K, Thorsteinsdottir, U, Barroso, I, Fox, C, North, K, Strachan, D, Beckmann, J, Berndt, S, Borecki, I, Mccarthy, M, Metspalu, A, Stefansson, K, Uitterlinden, A, van Duijn, C, Willer, C, Price, A, Lettre, G, Loos, R, Weedon, M, Ingelsson, E, O'Connell, J, Abecasis, G, Chasman, D, Goddard, M, Visscher, P, Pers TH, Karjalainen JM, Chan Y, Westra HJ, Wood AR, Yang J, Lui JC, Vedantam S, Gustafsson S, Esko T, Frayling T, Speliotes EK, Boehnke M, Raychaudhuri S, Fehrmann RS, Hirschhorn JN, Franke L, Chu AY, Estrada K, Luan J, Kutalik Z, Amin N, Buchkovich ML, Croteau Chonka DC, Day FR, Duan Y, Fall T, Fehrmann R, Ferreira T, Jackson AU, Karjalainen J, Lo KS, Locke AE, Mägi R, Mihailov E, Porcu E, Randall JC, Scherag A, Vinkhuyzen AA, Winkler TW, Workalemahu T, Zhao JH, Absher D, Albrecht E, Anderson D, Baron J, Beekman M, Demirkan A, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Fraser RM, Goel A, Gong J, Justice E, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Mateo Leach I, Medina Gomez C, Nalls MA, Nyholt DR, Palmer CD, Pasko D, Pechlivanis S, Prokopenko I, Ried JS, Ripke S, Shungin D, Stancáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Afzal U, Ärnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Bolton JL, Böttcher Y, Boyd HA, Bruinenberg M, Buckley BM, Buyske S, Caspersen IH, Chines PS, Clarke R, Claudi Boehm S, Cooper M, Daw EW, De Jong A, Deelen J, Delgado G, Denny JC, Dhonukshe Rutten R, Dimitriou M, Doney AS, Dörr M, Eklund N, Eury E, Folkersen L, Garcia ME, Geller F, Giedraitis V, Go AS, Grallert H, Grammer TB, Gräßler J, Grönberg H, de Groot LC, Groves CJ, Haessler J, Haller T, Hallmans G, Hannemann A, Hartman CA, Hassinen M, Hayward C, Heard Costa NL, Helmer Q, Hemani G, Henders AK, Hillege HL, Hlatky MA, Hoffmann W, Hoffmann P, Holmen O, Houwing Duistermaat JJ, Illig T, Isaacs A, James AL, Jeff J, Johansen B, Johansson Å, Jolley J, Juliusdottir T, Junttila J, Kho AN, Kinnunen L, Klopp N, Kocher T, Kratzer W, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Lu Y, Lyssenko V, Magnusson PK, Mahajan A, Maillard M, McArdle WL, McKenzie CA, McLachlan S, McLaren PJ, Menni C, Merger S, Milani L, Moayyeri A, Monda KL, Morken MA, Müller G, Müller Nurasyid M, Musk AW, Narisu N, Nauck M, Nolte IM, Nöthen MM, Oozageer L, Pilz S, Rayner NW, Renstrom F, Robertson NR, Rose LM, Roussel R, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Schunkert H, Scott RA, Sehmi J, Seufferlein T, Shi J, Silventoinen K, Smit JH, Smith AV, Smolonska J, Stanton AV, Stirrups K, Stott DJ, Stringham HM, Sundström J, Swertz MA, Syvänen AC, Tayo BO, Thorleifsson G, Tyrer JP, van Dijk S, van Schoor NM, van der Velde N, van Heemst D, van Oort FV, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Waldenberger M, Wennauer R, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, Arveiler D, Bakker SJ, Beilby J, Bergman RN, Bergmann S, Biffar R, Blangero J, Boomsma I, Bornstein SR, Bovet P, BRAMBILLA, PAOLO, Brown MJ, Campbell H, Caulfield MJ, Chakravarti A, Collins R, Collins FS, Crawford DC, Cupples LA, Danesh J, de Faire U, den Ruijter HM, Erbel R, Erdmann J, Eriksson JG, Farrall M, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Gansevoort RT, Gejman PV, Gieger C, Golay A, Gottesman O, Gudnason V, Gyllensten U, Haas DW, Hall AS, Harris TB, Hattersley AT, Heath AC, Hengstenberg C, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Jacobs KB, Jarvelin MR, Jousilahti P, Jula AM, Kaprio J, Kastelein JJ, Kayser M, Kee F, Keinanen Kiukaanniemi SM, Kiemeney LA, Kooner JS, Kooperberg C, Koskinen S, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lupoli S, Madden PA, Männistö S, Manunta P, Marette A, Matise TC, McKnight B, Meitinger T, Moll FL, Montgomery GW, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Ouwehand WH, Pasterkamp G, Peters A, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ritchie M, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Sebert S, Sever P, Shuldiner AR, Sinisalo J, Steinthorsdottir V, Stolk RP, Tardif JC, Tönjes A, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PI, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hayes MG, Hui J, Hunter DJ, Hveem K, Jukema JW, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CN, Pedersen NL, Perola M, Pérusse L, Peters U, Powell JE, Power C, Quertermous T, Rauramaa R, Reinmaa E, Ridker PM, Rivadeneira F, Rotter JI, Saaristo TE, Saleheen D, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Strauch K, Stumvoll M, Tuomilehto J, Uusitupa M, van der Harst P, Völzke H, Walker M, Wareham NJ, Watkins H, Wichmann HE, Wilson JF, Zanen P, Deloukas P, Heid IM, Lindgren CM, Mohlke KL, Thorsteinsdottir U, Barroso I, Fox CS, North KE, Strachan DP, Beckmann JS, Berndt SI, Borecki IB, McCarthy MI, Metspalu A, Stefansson K, Uitterlinden AG, van Duijn CM, Willer CJ, Price AL, Lettre G, Loos RJ, Weedon MN, Ingelsson E, O'Connell JR, Abecasis GR, Chasman DI, Goddard ME, Visscher PM, Frayling T.M., Pers, T, Karjalainen, J, Chan, Y, Westra, H, Wood, A, Yang, J, Lui, J, Vedantam, S, Gustafsson, S, Esko, T, Frayling, T, Speliotes, E, Boehnke, M, Raychaudhuri, S, Fehrmann, R, Hirschhorn, J, Franke, L, Chu, A, Estrada, K, Luan, J, Kutalik, Z, Amin, N, Buchkovich, M, Croteau Chonka, D, Day, F, Duan, Y, Fall, T, Ferreira, T, Jackson, A, Lo, K, Locke, A, Mägi, R, Mihailov, E, Porcu, E, Randall, J, Scherag, A, Vinkhuyzen, A, Winkler, T, Workalemahu, T, Zhao, J, Absher, D, Albrecht, E, Anderson, D, Baron, J, Beekman, M, Demirkan, A, Ehret, G, Feenstra, B, Feitosa, M, Fischer, K, Fraser, R, Goel, A, Gong, J, Justice, E, Kanoni, S, Kleber, M, Kristiansson, K, Lim, U, Lotay, V, Mangino, M, Mateo Leach, I, Medina Gomez, C, Nalls, M, Nyholt, D, Palmer, C, Pasko, D, Pechlivanis, S, Prokopenko, I, Ried, J, Ripke, S, Shungin, D, Stancáková, A, Strawbridge, R, Sung, Y, Tanaka, T, Teumer, A, Trompet, S, van der Laan, S, van Setten, J, Van Vliet Ostaptchouk, J, Wang, Z, Yengo, L, Zhang, W, Afzal, U, Ärnlöv, J, Arscott, G, Bandinelli, S, Barrett, A, Bellis, C, Bennett, A, Berne, C, Blüher, M, Bolton, J, Böttcher, Y, Boyd, H, Bruinenberg, M, Buckley, B, Buyske, S, Caspersen, I, Chines, P, Clarke, R, Claudi Boehm, S, Cooper, M, Daw, E, De Jong, A, Deelen, J, Delgado, G, Denny, J, Dhonukshe Rutten, R, Dimitriou, M, Doney, A, Dörr, M, Eklund, N, Eury, E, Folkersen, L, Garcia, M, Geller, F, Giedraitis, V, Go, A, Grallert, H, Grammer, T, Gräßler, J, Grönberg, H, de Groot, L, Groves, C, Haessler, J, Haller, T, Hallmans, G, Hannemann, A, Hartman, C, Hassinen, M, Hayward, C, Heard Costa, N, Helmer, Q, Hemani, G, Henders, A, Hillege, H, Hlatky, M, Hoffmann, W, Hoffmann, P, Holmen, O, Houwing Duistermaat, J, Illig, T, Isaacs, A, James, A, Jeff, J, Johansen, B, Johansson, Å, Jolley, J, Juliusdottir, T, Junttila, J, Kho, A, Kinnunen, L, Klopp, N, Kocher, T, Kratzer, W, Lichtner, P, Lind, L, Lindström, J, Lobbens, S, Lorentzon, M, Lu, Y, Lyssenko, V, Magnusson, P, Mahajan, A, Maillard, M, Mcardle, W, Mckenzie, C, Mclachlan, S, Mclaren, P, Menni, C, Merger, S, Milani, L, Moayyeri, A, Monda, K, Morken, M, Müller, G, Müller Nurasyid, M, Musk, A, Narisu, N, Nauck, M, Nolte, I, Nöthen, M, Oozageer, L, Pilz, S, Rayner, N, Renstrom, F, Robertson, N, Rose, L, Roussel, R, Sanna, S, Scharnagl, H, Scholtens, S, Schumacher, F, Schunkert, H, Scott, R, Sehmi, J, Seufferlein, T, Shi, J, Silventoinen, K, Smit, J, Smith, A, Smolonska, J, Stanton, A, Stirrups, K, Stott, D, Stringham, H, Sundström, J, Swertz, M, Syvänen, A, Tayo, B, Thorleifsson, G, Tyrer, J, van Dijk, S, van Schoor, N, van der Velde, N, van Heemst, D, van Oort, F, Vermeulen, S, Verweij, N, Vonk, J, Waite, L, Waldenberger, M, Wennauer, R, Wilkens, L, Willenborg, C, Wilsgaard, T, Wojczynski, M, Wong, A, Wright, A, Zhang, Q, Arveiler, D, Bakker, S, Beilby, J, Bergman, R, Bergmann, S, Biffar, R, Blangero, J, Boomsma, I, Bornstein, S, Bovet, P, Brambilla, P, Brown, M, Campbell, H, Caulfield, M, Chakravarti, A, Collins, R, Collins, F, Crawford, D, Cupples, L, Danesh, J, de Faire, U, den Ruijter, H, Erbel, R, Erdmann, J, Eriksson, J, Farrall, M, Ferrannini, E, Ferrières, J, Ford, I, Forouhi, N, Forrester, T, Gansevoort, R, Gejman, P, Gieger, C, Golay, A, Gottesman, O, Gudnason, V, Gyllensten, U, Haas, D, Hall, A, Harris, T, Hattersley, A, Heath, A, Hengstenberg, C, Hicks, A, Hindorff, L, Hingorani, A, Hofman, A, Hovingh, G, Humphries, S, Hunt, S, Hypponen, E, Jacobs, K, Jarvelin, M, Jousilahti, P, Jula, A, Kaprio, J, Kastelein, J, Kayser, M, Kee, F, Keinanen Kiukaanniemi, S, Kiemeney, L, Kooner, J, Kooperberg, C, Koskinen, S, Kovacs, P, Kraja, A, Kumari, M, Kuusisto, J, Lakka, T, Langenberg, C, Le Marchand, L, Lehtimäki, T, Lupoli, S, Madden, P, Männistö, S, Manunta, P, Marette, A, Matise, T, Mcknight, B, Meitinger, T, Moll, F, Montgomery, G, Morris, A, Murray, J, Nelis, M, Ohlsson, C, Oldehinkel, A, Ong, K, Ouwehand, W, Pasterkamp, G, Peters, A, Pramstaller, P, Price, J, Qi, L, Raitakari, O, Rankinen, T, Rao, D, Rice, T, Ritchie, M, Rudan, I, Salomaa, V, Samani, N, Saramies, J, Sarzynski, M, Schwarz, P, Sebert, S, Sever, P, Shuldiner, A, Sinisalo, J, Steinthorsdottir, V, Stolk, R, Tardif, J, Tönjes, A, Tremblay, A, Tremoli, E, Virtamo, J, Vohl, M, Amouyel, P, Asselbergs, F, Assimes, T, Bochud, M, Boehm, B, Boerwinkle, E, Bottinger, E, Bouchard, C, Cauchi, S, Chambers, J, Chanock, S, Cooper, R, de Bakker, P, Dedoussis, G, Ferrucci, L, Franks, P, Froguel, P, Groop, L, Haiman, C, Hamsten, A, Hayes, M, Hui, J, Hunter, D, Hveem, K, Jukema, J, Kaplan, R, Kivimaki, M, Kuh, D, Laakso, M, Liu, Y, Martin, N, März, W, Melbye, M, Moebus, S, Munroe, P, Njølstad, I, Oostra, B, Pedersen, N, Perola, M, Pérusse, L, Peters, U, Powell, J, Power, C, Quertermous, T, Rauramaa, R, Reinmaa, E, Ridker, P, Rivadeneira, F, Rotter, J, Saaristo, T, Saleheen, D, Schlessinger, D, Slagboom, P, Snieder, H, Spector, T, Strauch, K, Stumvoll, M, Tuomilehto, J, Uusitupa, M, van der Harst, P, Völzke, H, Walker, M, Wareham, N, Watkins, H, Wichmann, H, Wilson, J, Zanen, P, Deloukas, P, Heid, I, Lindgren, C, Mohlke, K, Thorsteinsdottir, U, Barroso, I, Fox, C, North, K, Strachan, D, Beckmann, J, Berndt, S, Borecki, I, Mccarthy, M, Metspalu, A, Stefansson, K, Uitterlinden, A, van Duijn, C, Willer, C, Price, A, Lettre, G, Loos, R, Weedon, M, Ingelsson, E, O'Connell, J, Abecasis, G, Chasman, D, Goddard, M, Visscher, P, Pers TH, Karjalainen JM, Chan Y, Westra HJ, Wood AR, Yang J, Lui JC, Vedantam S, Gustafsson S, Esko T, Frayling T, Speliotes EK, Boehnke M, Raychaudhuri S, Fehrmann RS, Hirschhorn JN, Franke L, Chu AY, Estrada K, Luan J, Kutalik Z, Amin N, Buchkovich ML, Croteau Chonka DC, Day FR, Duan Y, Fall T, Fehrmann R, Ferreira T, Jackson AU, Karjalainen J, Lo KS, Locke AE, Mägi R, Mihailov E, Porcu E, Randall JC, Scherag A, Vinkhuyzen AA, Winkler TW, Workalemahu T, Zhao JH, Absher D, Albrecht E, Anderson D, Baron J, Beekman M, Demirkan A, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Fraser RM, Goel A, Gong J, Justice E, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Mateo Leach I, Medina Gomez C, Nalls MA, Nyholt DR, Palmer CD, Pasko D, Pechlivanis S, Prokopenko I, Ried JS, Ripke S, Shungin D, Stancáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Afzal U, Ärnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Bolton JL, Böttcher Y, Boyd HA, Bruinenberg M, Buckley BM, Buyske S, Caspersen IH, Chines PS, Clarke R, Claudi Boehm S, Cooper M, Daw EW, De Jong A, Deelen J, Delgado G, Denny JC, Dhonukshe Rutten R, Dimitriou M, Doney AS, Dörr M, Eklund N, Eury E, Folkersen L, Garcia ME, Geller F, Giedraitis V, Go AS, Grallert H, Grammer TB, Gräßler J, Grönberg H, de Groot LC, Groves CJ, Haessler J, Haller T, Hallmans G, Hannemann A, Hartman CA, Hassinen M, Hayward C, Heard Costa NL, Helmer Q, Hemani G, Henders AK, Hillege HL, Hlatky MA, Hoffmann W, Hoffmann P, Holmen O, Houwing Duistermaat JJ, Illig T, Isaacs A, James AL, Jeff J, Johansen B, Johansson Å, Jolley J, Juliusdottir T, Junttila J, Kho AN, Kinnunen L, Klopp N, Kocher T, Kratzer W, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Lu Y, Lyssenko V, Magnusson PK, Mahajan A, Maillard M, McArdle WL, McKenzie CA, McLachlan S, McLaren PJ, Menni C, Merger S, Milani L, Moayyeri A, Monda KL, Morken MA, Müller G, Müller Nurasyid M, Musk AW, Narisu N, Nauck M, Nolte IM, Nöthen MM, Oozageer L, Pilz S, Rayner NW, Renstrom F, Robertson NR, Rose LM, Roussel R, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Schunkert H, Scott RA, Sehmi J, Seufferlein T, Shi J, Silventoinen K, Smit JH, Smith AV, Smolonska J, Stanton AV, Stirrups K, Stott DJ, Stringham HM, Sundström J, Swertz MA, Syvänen AC, Tayo BO, Thorleifsson G, Tyrer JP, van Dijk S, van Schoor NM, van der Velde N, van Heemst D, van Oort FV, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Waldenberger M, Wennauer R, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, Arveiler D, Bakker SJ, Beilby J, Bergman RN, Bergmann S, Biffar R, Blangero J, Boomsma I, Bornstein SR, Bovet P, BRAMBILLA, PAOLO, Brown MJ, Campbell H, Caulfield MJ, Chakravarti A, Collins R, Collins FS, Crawford DC, Cupples LA, Danesh J, de Faire U, den Ruijter HM, Erbel R, Erdmann J, Eriksson JG, Farrall M, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Gansevoort RT, Gejman PV, Gieger C, Golay A, Gottesman O, Gudnason V, Gyllensten U, Haas DW, Hall AS, Harris TB, Hattersley AT, Heath AC, Hengstenberg C, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Jacobs KB, Jarvelin MR, Jousilahti P, Jula AM, Kaprio J, Kastelein JJ, Kayser M, Kee F, Keinanen Kiukaanniemi SM, Kiemeney LA, Kooner JS, Kooperberg C, Koskinen S, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lupoli S, Madden PA, Männistö S, Manunta P, Marette A, Matise TC, McKnight B, Meitinger T, Moll FL, Montgomery GW, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Ouwehand WH, Pasterkamp G, Peters A, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ritchie M, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Sebert S, Sever P, Shuldiner AR, Sinisalo J, Steinthorsdottir V, Stolk RP, Tardif JC, Tönjes A, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PI, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hayes MG, Hui J, Hunter DJ, Hveem K, Jukema JW, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CN, Pedersen NL, Perola M, Pérusse L, Peters U, Powell JE, Power C, Quertermous T, Rauramaa R, Reinmaa E, Ridker PM, Rivadeneira F, Rotter JI, Saaristo TE, Saleheen D, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Strauch K, Stumvoll M, Tuomilehto J, Uusitupa M, van der Harst P, Völzke H, Walker M, Wareham NJ, Watkins H, Wichmann HE, Wilson JF, Zanen P, Deloukas P, Heid IM, Lindgren CM, Mohlke KL, Thorsteinsdottir U, Barroso I, Fox CS, North KE, Strachan DP, Beckmann JS, Berndt SI, Borecki IB, McCarthy MI, Metspalu A, Stefansson K, Uitterlinden AG, van Duijn CM, Willer CJ, Price AL, Lettre G, Loos RJ, Weedon MN, Ingelsson E, O'Connell JR, Abecasis GR, Chasman DI, Goddard ME, Visscher PM, and Frayling T.M.
Abstract: The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.
Published: 2015

13. Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis

Author: Loh, P-R, Bhatia, G, Gusev, A, Finucane, HK, Bulik-Sullivan, BK, Pollack, SJ, de Candia, TR, Lee, SH, Wray, NR, Kendler, KS, O'Donovan, MC, Neale, BM, Patterson, N, Price, AL, Loh, P-R, Bhatia, G, Gusev, A, Finucane, HK, Bulik-Sullivan, BK, Pollack, SJ, de Candia, TR, Lee, SH, Wray, NR, Kendler, KS, O'Donovan, MC, Neale, BM, Patterson, N, and Price, AL
Abstract: Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) for several pairs of GERA diseases; genetic correlations were on average 1.3 tunes stronger than the correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.
Published: 2015

14. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair

Author: Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, L, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, N, Corre, T, Hottenga, J-J, Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, A-L, Boutin, TS, Brauch, H, Brenner, H, Bruening, T, Burwinkel, B, Campbell, A, Campbell, H, Chanock, SJ, Chapman, JR, Chen, Y-DI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, De Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Doerk, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, X, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, A, Homuth, G, Hooning, MJ, Hopper, JL, Hu, FB, Huang, J, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, V-M, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, J, Li, X, Lindstroem, S, Liu, Y, Luan, J, Lubinski, J, Maegi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Mueller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, F, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK, Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, CM, Simard, J, Sorice, R, Southey, MC, Stoeckl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q, Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, van Duijn, CM, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, AG, Ulivi, S, Voelzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, JA, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, L, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, N, Corre, T, Hottenga, J-J, Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, A-L, Boutin, TS, Brauch, H, Brenner, H, Bruening, T, Burwinkel, B, Campbell, A, Campbell, H, Chanock, SJ, Chapman, JR, Chen, Y-DI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, De Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Doerk, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, X, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, A, Homuth, G, Hooning, MJ, Hopper, JL, Hu, FB, Huang, J, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, V-M, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, J, Li, X, Lindstroem, S, Liu, Y, Luan, J, Lubinski, J, Maegi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Mueller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, F, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK, Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, CM, Simard, J, Sorice, R, Southey, MC, Stoeckl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q, Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, van Duijn, CM, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, AG, Ulivi, S, Voelzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, JA, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, and Murray, A
Abstract: Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.
Published: 2015

15. Epidemiology of iliopsoas haematoma in patients with haemophilia

Author: Caviglia, HA, primary, Landro, ME, additional, Salgado, P, additional, Price, AL Douglas, additional, Daffunchio, C, additional, and Neme, D, additional
Published: 2015
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16. Planktonic ingress of fiddler crab megalopae to the Newport River Estuary, NC: evidence for semilunar periodicity in Uca pugnax and species-specific sampling bias by hog’s hair larval collectors

Author: Reinsel, KA, primary, Welch, JM, additional, Romero, AO, additional, Parks, EM, additional, McQueen, KM, additional, Smith, MJ, additional, Price, AL, additional, Clark, HR, additional, Zmina, SE, additional, Williams, CA, additional, and Forward, RB, additional
Published: 2015
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17. Retrospective Analysis of Population Demographic Characteristics, Medical Interventions, and Resource Use at a Medical Student-Run Clinic on the Texas-Mexico Border

Author: Mootz, Allison, Price, Alyssa, Elahi, Cyrus, Steffen, Kelcy, de Santiago, Andres Belmont, Gutierrez, Jesus, Krimbill, Jacob, Sidhu, Natalia, Swinney, Ira, and Francis, Maureen
Published: 2019
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18. Writing with WIT: The Gender Gap Seen through the Women-in-Translation Activism

Author: Carson, Margaret and Price, Alta L.
Published: 2019
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19. The Transformative Promise of Queer Politics

Author: Price, Alana Yu-lan
Published: 2016

20. Readers Respond

Author: Waldman, Mel, Artson, Bradley, Price, Alana Y., Campolo, Tony, Zylman, Jack, Vradenburg, George, Landy, Joanne, Lerner, Michael, Weinstein, David, O’Sullivan, Kathleen, Fisher, Adam D., Reuveny, Rafael, Garrett, Jan, Yura, Mark D., Sorgen, Phoebe Ann, Seebeck, Paul, and Moore, Zac
Published: 2016

21. Painting Past Borders

Author: Price, Alana Y.
Published: 2016

22. Emily Robison Strayer: Dixie Chick and Banjo Trailblazer.

Author: Price, Al
Abstract: The article discusses about the Emily Robison Strayer, a banjo player including her training from John Evans and Gerald Jones, her first album ``Wide Open Spaces'' with Dixie Chicks and her music band.
Published: 2016

23. Patterns of use of malnutrition risk screening in pediatric populations: A survey of current practice among pediatric hospitals in North America.

Author: Bellini SG, Becker PJ, Abdelhadi RA, Karls CA, Price AL, Puthoff TD, and Malone A
Abstract: Information on the use of validated malnutrition risk screening tools in pediatric facilities to guide malnutrition identification, diagnosis, and treatment is scarce. Therefore, a survey of pediatric healthcare facilities and practitioners to ascertain malnutrition risk screening practices in North America was conducted. A pediatric nutrition screening practices survey was developed and sent to members of the American Society for Parenteral and Enteral Nutrition, the Council for Pediatric Nutrition Professionals and the Academy of Nutrition and Dietetics Pediatric Nutrition Practice Group. Respondents represented 113 pediatric hospitals in the United States and six in Canada, of which 94 were inpatient and 59 were outpatient. Nutrition risk screening was completed in 90% inpatient settings, and 63% used a validated screening tool. Nurses performed most malnutrition risk screens in the inpatient setting. Nutrition risk screening was reported in 51% of outpatient settings, with a validated screening tool being used in 53%. Measured anthropometrics were used in 78% of inpatient settings, whereas 45% used verbally reported anthropometrics. Measured anthropometrics were used in 97% outpatient settings. Nutrition risk screening was completed in the electronic health record in 80% inpatient settings and 81% outpatient settings. Electronic health record positive screen generated an automatic referral in 80% of inpatient and 45% of outpatient settings. In this sample of pediatric healthcare organizations, the results demonstrate variation in pediatric malnutrition risk screening in North America. These inconsistencies justify the need to standardize pediatric malnutrition risk screening using validated pediatric tools and allocate resources to perform screening., (© 2024 American Society for Parenteral and Enteral Nutrition.)
Published: 2024
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24. Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation.

Author: Akbari A, Barton AR, Gazal S, Li Z, Kariminejad M, Perry A, Zeng Y, Mittnik A, Patterson N, Mah M, Zhou X, Price AL, Lander ES, Pinhasi R, Rohland N, Mallick S, and Reich D
Abstract: We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from ~0% to ~20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1 ; a rise from ~0% to ~8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from ~2% to ~9% from ~5500 to ~3000 years ago before dropping to ~3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.
Published: 2024
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25. JACC: Advances Expert Panel Perspective: Shared Decision-Making in Multidisciplinary Team-Based Cardiovascular Care.

Author: Perpetua EM, Palmer R, Le VT, Al-Khatib SM, Beavers CJ, Beckman JA, Bozkurt B, Coylewright M, Lloyd Doherty C, Guibone KA, Hawkey M, Keegan PA, Kirkpatrick JN, Laperle J, Lauck SB, Levine G, Lindman BR, Mack MJ, Price AL, Strong S, Wyman JF, Youmans QR, and Gulati M
Abstract: Shared decision-making (SDM) and multidisciplinary team-based care delivery are recommended across several cardiology clinical practice guidelines. However, evidence for benefit and guidance on implementation are limited. Informed consent, the use of patient decision aids, or the documentation of these elements for governmental or societal agencies may be conflated as SDM. SDM is a bidirectional exchange between experts: patients are the experts on their goals, values, and preferences, and clinicians provide their expertise on clinical factors. In this Expert Panel perspective, we review the current state of SDM in team-based cardiovascular care and propose best practice recommendations for multidisciplinary team implementation of SDM., Competing Interests: Dr Perpetua has been a consultant for Edwards Lifesciences and is a consultant for Abbott Vascular. Ms. Palmer is a consultant for Edwards Lifesciences. Dr Beckman is a consultant for Norvartis, Janssen, and JanOne. Dr Keegan is a consultant for Edwards Lifesciences and Abbott Vascular. Dr Guibone is a consultant for Medtronic and Abbott Vascular. Dr Lauck is a consultant for Edwards Lifesciences. Dr Le has received research grant funding from Janssen and is a consultant for 10.13039/100008272Novartis. Dr Lindman is supported by R01AG073633 from the 10.13039/100000002National Institutes of Health and has been a consultant for and received investigator-initiated research grants from 10.13039/100006520Edwards Lifesciences. Dr Wyman has been a consultant for Edwards Lifesciences and Boston Scientific. Dr Gulati has been a consultant for Esperion, Boehringer Ingelheim, and Medtronic. There was no funding support for this expert panel. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)
Published: 2024
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26. Fine-mapping causal tissues and genes at disease-associated loci.

Author: Strober BJ, Zhang MJ, Amariuta T, Rossen J, and Price AL
Abstract: Heritable diseases often manifest in a highly tissue-specific manner, with different disease loci mediated by genes in distinct tissues or cell types. We propose Tissue-Gene Fine-Mapping (TGFM), a fine-mapping method that infers the posterior probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing GWAS summary statistics (and in-sample LD) and leveraging eQTL data from diverse tissues to build cis-predicted expression models; TGFM also assigns PIPs to causal variants that are not mediated by gene expression in assayed genes and tissues. TGFM accounts for both co-regulation across genes and tissues and LD between SNPs (generalizing existing fine-mapping methods), and incorporates genome-wide estimates of each tissue's contribution to disease as tissue-level priors. TGFM was well-calibrated and moderately well-powered in simulations; unlike previous methods, TGFM was able to attain correct calibration by modeling uncertainty in cis-predicted expression models. We applied TGFM to 45 UK Biobank diseases/traits (average N = 316K) using eQTL data from 38 GTEx tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease/trait, of which 11% were gene-tissue pairs. Implicated gene-tissue pairs were concentrated in known disease-critical tissues, and causal genes were strongly enriched in disease-relevant gene sets. Causal gene-tissue pairs identified by TGFM recapitulated known biology (e.g., TPO -thyroid for Hypothyroidism), but also included biologically plausible novel findings (e.g., SLC20A2 -artery aorta for Diastolic blood pressure). Further application of TGFM to single-cell eQTL data from 9 cell types in peripheral blood mononuclear cells (PBMC), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs at PIP > 0.5-primarily for autoimmune disease and blood cell traits, including the biologically plausible example of CD52 in classical monocyte cells for Monocyte count. In conclusion, TGFM is a robust and powerful method for fine-mapping causal tissues and genes at disease-associated loci.
Published: 2024
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27. Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance.

Author: Dorans E, Jagadeesh K, Dey K, and Price AL
Abstract: Methods that analyze single-cell paired RNA-seq and ATAC-seq multiome data have shown great promise in linking regulatory elements to genes. However, existing methods differ in their modeling assumptions and approaches to account for biological and technical noise-leading to low concordance in their linking scores-and do not capture the effects of genomic distance. We propose pgBoost, an integrative modeling framework that trains a non-linear combination of existing linking strategies (including genomic distance) on fine-mapped eQTL data to assign a probabilistic score to each candidate SNP-gene link. We applied pgBoost to single-cell multiome data from 85k cells representing 6 major immune/blood cell types. pgBoost attained higher enrichment for fine-mapped eSNP-eGene pairs (e.g. 21x at distance >10kb) than existing methods (1.2-10x; p-value for difference = 5e-13 vs. distance-based method and < 4e-35 for each other method), with larger improvements at larger distances (e.g. 35x vs. 0.89-6.6x at distance >100kb; p-value for difference < 0.002 vs. each other method). pgBoost also outperformed existing methods in enrichment for CRISPR-validated links (e.g. 4.8x vs. 1.6-4.1x at distance >10kb; p-value for difference = 0.25 vs. distance-based method and < 2e-5 for each other method), with larger improvements at larger distances (e.g. 15x vs. 1.6-2.5x at distance >100kb; p-value for difference < 0.009 for each other method). Similar improvements in enrichment were observed for links derived from Activity-By-Contact (ABC) scores and GWAS data. We further determined that restricting pgBoost to features from a focal cell type improved the identification of SNP-gene links relevant to that cell type. We highlight several examples where pgBoost linked fine-mapped GWAS variants to experimentally validated or biologically plausible target genes that were not implicated by other methods. In conclusion, a non-linear combination of linking strategies, including genomic distance, improves power to identify target genes underlying GWAS associations.
Published: 2024
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28. Genome-wide association studies in a large Korean cohort identify novel quantitative trait loci for 36 traits and illuminates their genetic architectures.

Author: Jee YH, Wang Y, Jung KJ, Lee JY, Kimm H, Duan R, Price AL, Martin AR, and Kraft P
Abstract: Genome-wide association studies (GWAS) have been predominantly conducted in populations of European ancestry, limiting opportunities for biological discovery in diverse populations. We report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 616 novel genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 3,524 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotropic missense variant in ALDH2, which fine-mapping identified as a likely causal variant for a diverse set of traits. Our findings provide insights into the genetic architecture of complex traits in East Asian populations and highlight how broadening the population diversity of GWAS samples can aid discovery.
Published: 2024
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29. MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data.

Author: Rossen J, Shi H, Strober BJ, Zhang MJ, Kanai M, McCaw ZR, Liang L, Weissbrod O, and Price AL
Abstract: Leveraging data from multiple ancestries can greatly improve fine-mapping power due to differences in linkage disequilibrium and allele frequencies. We propose MultiSuSiE, an extension of the sum of single effects model (SuSiE) to multiple ancestries that allows causal effect sizes to vary across ancestries based on a multivariate normal prior informed by empirical data. We evaluated MultiSuSiE via simulations and analyses of 14 quantitative traits leveraging whole-genome sequencing data in 47k African-ancestry and 94k European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr47k+Eur47k was well-calibrated and attained higher power than SuSiE applied to Eur94k; interestingly, higher causal variant PIPs in Afr47k compared to Eur47k were entirely explained by differences in the extent of LD quantified by LD 4th moments. Compared to very recently proposed multi-ancestry fine-mapping methods, MultiSuSiE attained higher power and/or much lower computational costs, making the analysis of large-scale All of Us data feasible. In real trait analyses, MultiSuSiE applied to Afr47k+Eur94k identified 579 fine-mapped variants with PIP > 0.5, and MultiSuSiE applied to Afr47k+Eur47k identified 44% more fine-mapped variants with PIP > 0.5 than SuSiE applied to Eur94k. We validated MultiSuSiE results for real traits via functional enrichment of fine-mapped variants. We highlight several examples where MultiSuSiE implicates well-studied or biologically plausible fine-mapped variants that were not implicated by other methods.
Published: 2024
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30. Distinct explanations underlie gene-environment interactions in the UK Biobank.

Author: Durvasula A and Price AL
Abstract: The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized, but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for a given trait and E variable. First, we detect locus-specific GxE interaction by testing for genetic correlation r g < 1 across E bins. Second, we detect genome-wide effects of the E variable on genetic variance by leveraging polygenic risk scores (PRS) to test for significant PRSxE in a regression of phenotypes on PRS, E, and PRSxE, together with differences in SNP-heritability across E bins. Third, we detect genome-wide proportional amplification of genetic and environmental effects as a function of the E variable by testing for significant PRSxE with no differences in SNP-heritability across E bins. Simulations show that these approaches achieve high sensitivity and specificity in distinguishing these three GxE scenarios. We applied our framework to 33 UK Biobank traits (25 quantitative traits and 8 diseases; average N = 325 K ) and 10 E variables spanning lifestyle, diet, and other environmental exposures. First, we identified 19 trait-E pairs with r g significantly < 1 (FDR<5%) (average r g = 0.95 ); for example, white blood cell count had r g = 0.95 (s.e. 0.01) between smokers and non-smokers. Second, we identified 28 trait-E pairs with significant PRSxE and significant SNP-heritability differences across E bins; for example, BMI had a significant PRSxE for physical activity (P=4.6e-5) with 5% larger SNP-heritability in the largest versus smallest quintiles of physical activity (P=7e-4). Third, we identified 15 trait-E pairs with significant PRSxE with no SNP-heritability differences across E bins; for example, waist-hip ratio adjusted for BMI had a significant PRSxE effect for time spent watching television (P=5e-3) with no SNP-heritability differences. Across the three scenarios, 8 of the trait-E pairs involved disease traits, whose interpretation is complicated by scale effects. Analyses using biological sex as the E variable produced additional significant findings in each of the three scenarios. Overall, we infer a significant contribution of GxE and GxSex effects to complex trait and disease variance.
Published: 2024
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31. Lateral cell polarization drives organization of epithelia in sea anemone embryos and embryonic cell aggregates.

Author: Atajanova T, Kang EM, Postnikova A, Price AL, Doerr S, Du M, Ugenti A, and Ragkousi K
Abstract: One of the first organizing processes during animal development is the assembly of embryonic cells into epithelia. In certain animals, including Hydra and sea anemones, epithelia also emerge when cells from dissociated tissues are aggregated back together. Although cell adhesion is required to keep cells together, it is not clear whether cell polarization plays a role as epithelia emerge from disordered aggregates. Here, we demonstrate that lateral cell polarization is essential for epithelial organization in both embryos and aggregates of the sea anemone Nematostella vectensis . Specifically, knock down of the lateral polarity protein Lgl disrupts epithelia in developing embryos and impairs the capacity of dissociated cells to epithelialize from aggregates. Cells in lgl mutant epithelia lose their columnar shape and have mispositioned mitotic spindles and ciliary basal bodies. Together, our data suggest that in Nematostella , Lgl is required to establish lateral cell polarity and position cytoskeletal organelles in cells of embryos and aggregates during de novo epithelial organization.
Published: 2024
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32. Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.

Author: Sakaue S, Weinand K, Isaac S, Dey KK, Jagadeesh K, Kanai M, Watts GFM, Zhu Z, Brenner MB, McDavid A, Donlin LT, Wei K, Price AL, and Raychaudhuri S
Subjects: Humans, Alleles, Chromosome Mapping, Phenotype, Chromatin genetics, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Regulatory Sequences, Nucleic Acid
Abstract: Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2024
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33. Implementation of a Multidimensional Strategy to Reduce Post-PCI Bleeding Risk.

Author: Price AL, Amin AP, Rogers S, Messenger JC, Moussa ID, Miller JM, Jennings J, Masoudi FA, Abbott JD, Young R, Wojdyla DM, and Rao SV
Subjects: Humans, Hemorrhage etiology, Hemorrhage prevention & control, Registries, Risk Factors, Treatment Outcome, United States, Acute Coronary Syndrome diagnostic imaging, Acute Coronary Syndrome therapy, Percutaneous Coronary Intervention adverse effects, Percutaneous Coronary Intervention methods
Abstract: Background: The American College of Cardiology Reduce the Risk: PCI Bleed Campaign was a hospital-based quality improvement campaign designed to reduce post-percutaneous coronary intervention (PCI) bleeding events. The aim of the campaign was to provide actionable evidence-based tools for participants to review, adapt, and adopt, depending upon hospital resources and engagement., Methods: We used data from 8 757 737 procedures in the National Cardiovascular Data Registry between 2015 and 2021 to compare patient and hospital characteristics and bleeding outcomes among campaign participants (n=195 hospitals) and noncampaign participants (n=1384). Post-PCI bleeding risk was compared before and after campaign participation. Multivariable hierarchical logistic regression was used to determine the adjusted association between campaign participation and post-PCI bleeding events. Prespecified subgroups were examined., Results: Campaign hospitals were more often higher volume teaching facilities located in urban or suburban locations. After adjustment, campaign participation was associated with a significant reduction in the rate of bleeding (bleeding: adjusted odds ratio, 0.61 [95% CI, 0.53-0.71]). Campaign hospitals had a greater decrease in bleeding events than noncampaign hospitals. In a subgroup analysis, the reduction in bleeding was noted in non-ST-segment-elevation acute coronary syndrome and ST-segment-elevation myocardial infarction patients, but no significant reduction was seen in patients without acute coronary syndrome., Conclusions: Participation in the American College of Cardiology Reduce the Risk: PCI Bleed Campaign was associated with a significant reduction in post-PCI bleeding. Our results underscore that national quality improvement efforts can be associated with a significant impact on PCI outcomes., Competing Interests: Dr Amin has institutional grant support (modest) from GE Healthcare and Chiesi. Dr Abbott has the following relationships with industry: research: Boston Scientific and Microport; consulting: Abbott, Medtronic, Penumbra, Shockwave, and Philips. Dr Masoudi had a contract with the American College of Cardiology for his role as the Chief Scientific Advisor, National Cardiovascular Data Registry. The other authors report no conflicts.
Published: 2024
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34. Distinguishing different psychiatric disorders using DDx-PRS.

Author: Peyrot WJ, Panagiotaropoulou G, Olde Loohuis LM, Adams MJ, Awasthi S, Ge T, McIntosh AM, Mitchell BL, Mullins N, O'Connell KS, Penninx BWJH, Posthuma D, Ripke S, Ruderfer DM, Uffelmann E, Vilhjalmsson BJ, Zhu Z, Smoller JW, and Price AL
Abstract: Despite great progress on methods for case-control polygenic prediction (e.g. schizophrenia vs. control), there remains an unmet need for a method that genetically distinguishes clinically related disorders (e.g. schizophrenia (SCZ) vs. bipolar disorder (BIP) vs. depression (MDD) vs. control); such a method could have important clinical value, especially at disorder onset when differential diagnosis can be challenging. Here, we introduce a method, Differential Diagnosis-Polygenic Risk Score (DDx-PRS), that jointly estimates posterior probabilities of each possible diagnostic category (e.g. SCZ=50%, BIP=25%, MDD=15%, control=10%) by modeling variance/covariance structure across disorders, leveraging case-control polygenic risk scores (PRS) for each disorder (computed using existing methods) and prior clinical probabilities for each diagnostic category. DDx-PRS uses only summary-level training data and does not use tuning data, facilitating implementation in clinical settings. In simulations, DDx-PRS was well-calibrated (whereas a simpler approach that analyzes each disorder marginally was poorly calibrated), and effective in distinguishing each diagnostic category vs. the rest. We then applied DDx-PRS to Psychiatric Genomics Consortium SCZ/BIP/MDD/control data, including summary-level training data from 3 case-control GWAS ( N =41,917-173,140 cases; total N =1,048,683) and held-out test data from different cohorts with equal numbers of each diagnostic category (total N =11,460). DDx-PRS was well-calibrated and well-powered relative to these training sample sizes, attaining AUCs of 0.66 for SCZ vs. rest, 0.64 for BIP vs. rest, 0.59 for MDD vs. rest, and 0.68 for control vs. rest. DDx-PRS produced comparable results to methods that leverage tuning data, confirming that DDx-PRS is an effective method. True diagnosis probabilities in top deciles of predicted diagnosis probabilities were considerably larger than prior baseline probabilities, particularly in projections to larger training sample sizes, implying considerable potential for clinical utility under certain circumstances. In conclusion, DDx-PRS is an effective method for distinguishing clinically related disorders.
Published: 2024
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35. May We Be Spared to Meet on Earth : Letters of the Lost Franklin Arctic Expedition

Author: POTTER, RUSSELL A., KOELLNER, REGINA, CARNEY, PETER, WILLIAMSON, MARY, Alexander, Alison, Battersby, William, Betts, Matthew, Burrows, Rick, Campbell, A. J., Dore, Jonathan, Freebairn, Alison, Hill, Andrew, Holzhueter, D. J., Kimmins, Olga, Moore, Jonathan, Price, Alexa, Schuster, Frank Michael, Smith, Michael, Tracy, Michael, PALIN, MICHAEL, Foreword by, POTTER, RUSSELL A., KOELLNER, REGINA, CARNEY, PETER, WILLIAMSON, MARY, Alexander, Alison, Battersby, William, Betts, Matthew, Burrows, Rick, Campbell, A. J., Dore, Jonathan, Freebairn, Alison, Hill, Andrew, Holzhueter, D. J., Kimmins, Olga, Moore, Jonathan, Price, Alexa, Schuster, Frank Michael, Smith, Michael, Tracy, Michael, and PALIN, MICHAEL
Published: 2022
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36. Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.

Author: Kim SS, Truong B, Jagadeesh K, Dey KK, Shen AZ, Raychaudhuri S, Kellis M, and Price AL
Subjects: Humans, RNA-Seq, Genome-Wide Association Study, Chromatin genetics, Brain, Single-Cell Analysis, Chromatin Immunoprecipitation Sequencing, Depressive Disorder, Major
Abstract: Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Published: 2024
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37. Estimating Disorder Probability Based on Polygenic Prediction Using the BPC Approach.

Author: Uffelmann E, Price AL, Posthuma D, and Peyrot WJ
Abstract: Polygenic Scores (PGSs) summarize an individual's genetic propensity for a given trait in a single value, based on SNP effect sizes derived from Genome-Wide Association Study (GWAS) results. Methods have been developed that apply Bayesian approaches to improve the prediction accuracy of PGSs through optimization of estimated effect sizes. While these methods are generally well-calibrated for continuous traits (implying the predicted values are on average equal to the true trait values), they are not well-calibrated for binary disorder traits in ascertained samples. This is a problem because well-calibrated PGSs are needed to reliably compute the absolute disorder probability for an individual to facilitate future clinical implementation. Here we introduce the Bayesian polygenic score Probability Conversion (BPC) approach, which computes an individual's predicted disorder probability using GWAS summary statistics, an existing Bayesian PGS method (e.g. PRScs, SBayesR), the individual's genotype data, and a prior disorder probability. The BPC approach transforms the PGS to its underlying liability scale, computes the variances of the PGS in cases and controls, and applies Bayes' Theorem to compute the absolute disorder probability; it is practical in its application as it does not require a tuning dataset with both genotype and phenotype data. We applied the BPC approach to extensive simulated data and empirical data of nine disorders. The BPC approach yielded well-calibrated results that were consistently better than the results of another recently published approach., Competing Interests: Declaration of interests The authors declare no competing interests.
Published: 2024
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38. Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

Author: Zhang MJ, Durvasula A, Chiang C, Koch EM, Strober BJ, Shi H, Barton AR, Kim SS, Weissbrod O, Loh PR, Gazal S, Sunyaev S, and Price AL
Abstract: The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N =306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection., Competing Interests: Competing Interests Statement The authors declare no competing interests.
Published: 2023
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39. Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability.

Author: Gupta A, Weinand K, Nathan A, Sakaue S, Zhang MJ, Donlin L, Wei K, Price AL, Amariuta T, and Raychaudhuri S
Subjects: Humans, Regulatory Sequences, Nucleic Acid genetics, Chromosomes, Genome, Human, Chromatin genetics, Autoimmune Diseases genetics
Abstract: In autoimmune diseases such as rheumatoid arthritis, the immune system attacks the body's own cells. Developing a precise understanding of the cell states where noncoding autoimmune risk variants impart causal mechanisms is critical to developing curative therapies. Here, to identify noncoding regions with accessible chromatin that associate with cell-state-defining gene expression patterns, we leveraged multimodal single-nucleus RNA and assay for transposase-accessible chromatin (ATAC) sequencing data across 28,674 cells from the inflamed synovial tissue of 12 donors. Specifically, we used a multivariate Poisson model to predict peak accessibility from single-nucleus RNA sequencing principal components. For 14 autoimmune diseases, we discovered that cell-state-dependent ('dynamic') chromatin accessibility peaks in immune cell types were enriched for heritability, compared with cell-state-invariant ('cs-invariant') peaks. These dynamic peaks marked regulatory elements associated with T peripheral helper, regulatory T, dendritic and STAT1 + CXCL10 + myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2023
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40. An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Author: Gschwind AR, Mualim KS, Karbalayghareh A, Sheth MU, Dey KK, Jagoda E, Nurtdinov RN, Xi W, Tan AS, Jones H, Ma XR, Yao D, Nasser J, Avsec Ž, James BT, Shamim MS, Durand NC, Rao SSP, Mahajan R, Doughty BR, Andreeva K, Ulirsch JC, Fan K, Perez EM, Nguyen TC, Kelley DR, Finucane HK, Moore JE, Weng Z, Kellis M, Bassik MC, Price AL, Beer MA, Guigó R, Stamatoyannopoulos JA, Lieberman Aiden E, Greenleaf WJ, Leslie CS, Steinmetz LM, Kundaje A, and Engreitz JM
Abstract: Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease 1-6 . Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium 7 . We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics., Competing Interests: Conflict of Interest Statement Z.A. is employed by Google DeepMind. J.C.U. is an employee of Illumina, Inc. D.R.K. is employed by Calico Life Sciences LLC. Z.W. co-founded Rgenta Therapeutics, and she serves as a scientific advisor for the company and is a member of its board. W.J.G. is an inventor on IP licensed by 10x Genomics. A.Kundaje is on the scientific advisory board of PatchBio, SerImmune and OpenTargets, was a consultant with Illumina, and owns shares in DeepGenomics, ImmunAI and Freenome. J.M.E. is a consultant and equity holder in Martingale Labs, Inc. and has received materials from 10x Genomics unrelated to this study.
Published: 2023
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41. Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk.

Author: Jiang X, Zhang MJ, Zhang Y, Durvasula A, Inouye M, Holmes C, Price AL, and McVean G
Subjects: Humans, Biological Specimen Banks, Genome-Wide Association Study methods, Risk Factors, Comorbidity, Multifactorial Inheritance genetics, United Kingdom epidemiology, Genetic Predisposition to Disease, Population Health
Abstract: The analysis of longitudinal data from electronic health records (EHRs) has the potential to improve clinical diagnoses and enable personalized medicine, motivating efforts to identify disease subtypes from patient comorbidity information. Here we introduce an age-dependent topic modeling (ATM) method that provides a low-rank representation of longitudinal records of hundreds of distinct diseases in large EHR datasets. We applied ATM to 282,957 UK Biobank samples, identifying 52 diseases with heterogeneous comorbidity profiles; analyses of 211,908 All of Us samples produced concordant results. We defined subtypes of the 52 heterogeneous diseases based on their comorbidity profiles and compared genetic risk across disease subtypes using polygenic risk scores (PRSs), identifying 18 disease subtypes whose PRS differed significantly from other subtypes of the same disease. We further identified specific genetic variants with subtype-dependent effects on disease risk. In conclusion, ATM identifies disease subtypes with differential genome-wide and locus-specific genetic risk profiles., (© 2023. The Author(s).)
Published: 2023
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42. The Five-Factor Modified Frailty Index as a Predictor of Outcomes in Deep Brain Stimulation Surgery for Parkinson's Disease.

Author: Hancock JU, Price AL, Zaki PG, Graves JC, Locke KC, and Luck T
Abstract: Introduction Parkinson's disease (PD) is one of the most common neurodegenerative diseases worldwide. Though there are many pharmacological therapeutics approved today for PD, surgical interventions such as deep brain stimulation (DBS) have shown convincing symptom mitigation and minimal complication rates in aggregate. Recently, the concept of frailty - defined as reduced physiologic reserve and function affecting multiple systems throughout the patient - has gained traction as a predictor of short-term postoperative morbidity and mortality. As such, the Modified Frailty Index-5 (mFI-5) is a postoperative morbidity predictor based on five factors and has been used in neurosurgical subspecialties such as tumor, vascular, and spine. Yet, there is minimal literature assessing frailty in the field of functional neurosurgery. With the prevalence of DBS in PD, this study evaluated the mFI-5 as a predictor of postoperative complications in a selected patient population. Methods The American College of Surgeons National Surgical Quality Improvement Program 2010-2019 Database was queried for Current Procedural Terminology (CPT) codes, as well as the International Classification of Diseases (ICD)-9 and ICD-10 codes pertaining to DBS procedures in PD patients. Each patient was scored by the mFI-5 protocol and stratified into groups of No Frailty (mFI-5=0), Moderate Frailty (mFI-5=1), and Significant Frailty (mFI-5≥2). The No Frailty group was used as a reference in multivariate and univariate analyses of the groups. Results A total of 1,645 subjects were included in the study and were subcategorized into groups of No Frailty (N=877), Moderate Frailty (N=561), and Significant Frailty (N=207) based on their frailty scores. The subjects' mean age was 65.8±9.4 years. Overall, 1,161 (70.6%) were male, while 484 (29.4%) were female. With reference to the No Frailty group in multivariate analysis, patients with moderate frailty experienced greater unplanned readmission (OR 2.613, 95% CI 1.143-5.973, p=0.023), while those with significant frailty experienced greater unplanned readmission (OR 3.723, 95% CI 1.376-10.073, p=0.010), any readmission (OR 2.396, 95% CI 1.098-5.230, p=0.028), non-home discharge (OR 4.317, 95% CI 1.765-10.562, p<0.001), and complications in aggregate (OR 2.211, 95% CI 1.285-3.806, p=0.004). Conclusions Until now, the available clinical tools were limited in providing accurate predictions with minimal information for postoperative outcomes in DBS for PD patients. Our data give clinicians insight into the relationship between frailty and surgical outcomes and will assist physicians in preparing for postoperative care by predicting outcomes of significantly frail PD patients receiving DBS therapy., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Hancock et al.)
Published: 2023
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43. Modeling tissue co-regulation estimates tissue-specific contributions to disease.

Author: Amariuta T, Siewert-Rocks K, and Price AL
Subjects: Humans, Quantitative Trait Loci, Polymorphism, Single Nucleotide, Transcriptome genetics, Genetic Predisposition to Disease, Genome-Wide Association Study methods
Abstract: Integrative analyses of genome-wide association studies and gene expression data have implicated many disease-critical tissues. However, co-regulation of genetic effects on gene expression across tissues impedes distinguishing biologically causal tissues from tagging tissues. In the present study, we introduce tissue co-regulation score regression (TCSC), which disentangles causal tissues from tagging tissues by regressing gene-disease association statistics (from transcriptome-wide association studies) on tissue co-regulation scores, reflecting correlations of predicted gene expression across genes and tissues. We applied TCSC to 78 diseases/traits (average n = 302,000) and gene expression prediction models for 48 GTEx tissues. TCSC identified 21 causal tissue-trait pairs at a 5% false discovery rate (FDR), including well-established findings, biologically plausible new findings (for example, aorta artery and glaucoma) and increased specificity of known tissue-trait associations (for example, subcutaneous adipose, but not visceral adipose, and high-density lipoprotein). TCSC also identified 17 causal tissue-trait covariance pairs at 5% FDR. In conclusion, TCSC is a precise method for distinguishing causal tissues from tagging tissues., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2023
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44. Molecular Mechanisms Underlying TNFα-Induced Mitochondrial Biogenesis in Human Airway Smooth Muscle.

Author: Dasgupta D, Mahadev Bhat S, Price AL, Delmotte P, and Sieck GC
Subjects: Humans, Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha genetics, Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha metabolism, Mitochondria metabolism, DNA, Mitochondrial genetics, Muscle, Smooth metabolism, Mitochondrial Proteins genetics, Mitochondrial Proteins metabolism, Tumor Necrosis Factor-alpha pharmacology, Tumor Necrosis Factor-alpha metabolism, Organelle Biogenesis
Abstract: Proinflammatory cytokines such as TNFα mediate airway inflammation. Previously, we showed that TNFα increases mitochondrial biogenesis in human ASM (hASM) cells, which is associated with increased PGC1α expression. We hypothesized that TNFα induces CREB and ATF1 phosphorylation (pCREB S133 and pATF1 S63 ), which transcriptionally co-activate PGC1α expression. Primary hASM cells were dissociated from bronchiolar tissue obtained from patients undergoing lung resection, cultured (one-three passages), and then differentiated by serum deprivation (48 h). hASM cells from the same patient were divided into two groups: TNFα (20 ng/mL) treated for 6 h and untreated controls. Mitochondria were labeled using MitoTracker green and imaged using 3D confocal microscopy to determine mitochondrial volume density. Mitochondrial biogenesis was assessed based on relative mitochondrial DNA (mtDNA) copy number determined by quantitative real-time PCR (qPCR). Gene and/or protein expression of pCREB S133 , pATF1 S63 , PCG1α, and downstream signaling molecules (NRFs, TFAM) that regulate transcription and replication of the mitochondrial genome, were determined by qPCR and/or Western blot. TNFα increased mitochondrial volume density and mitochondrial biogenesis in hASM cells, which was associated with an increase in pCREB S133 , pATF1 S63 and PCG1α expression, with downstream transcriptional activation of NRF1, NRF2 , and TFAM. We conclude that TNFα increases mitochondrial volume density in hASM cells via a pCREB S133 /pATF1 S63 /PCG1α-mediated pathway.
Published: 2023
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45. Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq.

Author: Geiger-Schuller K, Eraslan B, Kuksenko O, Dey KK, Jagadeesh KA, Thakore PI, Karayel O, Yung AR, Rajagopalan A, Meireles AM, Yang KD, Amir-Zilberstein L, Delorey T, Phillips D, Raychowdhury R, Moussion C, Price AL, Hacohen N, Doench JG, Uhler C, Rozenblatt-Rosen O, and Regev A
Abstract: E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, comβVAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.
Published: 2023
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46. Canalized gene expression during development mediates caste differentiation in ants.

Author: Qiu B, Dai X, Li P, Larsen RS, Li R, Price AL, Ding G, Texada MJ, Zhang X, Zuo D, Gao Q, Jiang W, Wen T, Pontieri L, Guo C, Rewitz K, Li Q, Liu W, Boomsma JJ, and Zhang G
Subjects: Animals, Female, Gene Expression Profiling, Larva genetics, Phenotype, Transcriptome, Ants genetics
Abstract: Ant colonies are higher-level organisms consisting of specialized reproductive and non-reproductive individuals that differentiate early in development, similar to germ-soma segregation in bilateral Metazoa. Analogous to diverging cell lines, developmental differentiation of individual ants has often been considered in epigenetic terms but the sets of genes that determine caste phenotypes throughout larval and pupal development remain unknown. Here, we reconstruct the individual developmental trajectories of two ant species, Monomorium pharaonis and Acromyrmex echinatior, after obtaining >1,400 whole-genome transcriptomes. Using a new backward prediction algorithm, we show that caste phenotypes can be accurately predicted by genome-wide transcriptome profiling. We find that caste differentiation is increasingly canalized from early development onwards, particularly in germline individuals (gynes/queens) and that the juvenile hormone signalling pathway plays a key role in this process by regulating body mass divergence between castes. We quantified gene-specific canalization levels and found that canalized genes with gyne/queen-biased expression were enriched for ovary and wing functions while canalized genes with worker-biased expression were enriched in brain and behavioural functions. Suppression in gyne larvae of Freja, a highly canalized gyne-biased ovary gene, disturbed pupal development by inducing non-adaptive intermediate phenotypes between gynes and workers. Our results are consistent with natural selection actively maintaining canalized caste phenotypes while securing robustness in the life cycle ontogeny of ant colonies., (© 2022. The Author(s).)
Published: 2022
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47. Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics.

Author: Jagadeesh KA, Dey KK, Montoro DT, Mohan R, Gazal S, Engreitz JM, Xavier RJ, Price AL, and Regev A
Subjects: Genetic Predisposition to Disease, Human Genetics, Humans, Polymorphism, Single Nucleotide genetics, RNA, gamma-Aminobutyric Acid, Depressive Disorder, Major genetics, Genome-Wide Association Study
Abstract: Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease, but in many cases, the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is important for identifying pathogenic processes and developing therapeutics. In the present study, we introduce sc-linker, a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease. The inferred disease enrichments recapitulated known biology and highlighted notable cell-disease relationships, including γ-aminobutyric acid-ergic neurons in major depressive disorder, a disease-dependent M-cell program in ulcerative colitis and a disease-specific complement cascade process in multiple sclerosis. In autoimmune disease, both healthy and disease-dependent immune cell-type programs were associated, whereas only disease-dependent epithelial cell programs were prominent, suggesting a role in disease response rather than initiation. Our framework provides a powerful approach for identifying the cell types and cellular processes by which genetic variants influence disease., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2022
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48. Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data.

Author: Zhang MJ, Hou K, Dey KK, Sakaue S, Jagadeesh KA, Weinand K, Taychameekiatchai A, Rao P, Pisco AO, Zou J, Wang B, Gandal M, Raychaudhuri S, Pasaniuc B, and Price AL
Subjects: Gene Expression Profiling methods, Multifactorial Inheritance genetics, RNA-Seq, Triglycerides, Genome-Wide Association Study, Single-Cell Analysis methods
Abstract: Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). We applied scDRS to 74 diseases/traits and 1.3 million single-cell gene-expression profiles across 31 tissues/organs. Cell-type-level results broadly recapitulated known cell-type-disease associations. Individual-cell-level results identified subpopulations of disease-associated cells not captured by existing cell-type labels, including T cell subpopulations associated with inflammatory bowel disease, partially characterized by their effector-like states; neuron subpopulations associated with schizophrenia, partially characterized by their spatial locations; and hepatocyte subpopulations associated with triglyceride levels, partially characterized by their higher ploidy levels. Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2022
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49. Draft genome assemblies of four manakins.

Author: Li X, Gao R, Chen G, Price AL, Øksnebjerg DB, Hosner PA, Zhou Y, Zhang G, and Feng S
Subjects: Animals, Molecular Sequence Annotation, Repetitive Sequences, Nucleic Acid, Whole Genome Sequencing, Genome, Passeriformes genetics
Abstract: Manakins are a family of small suboscine passerine birds characterized by their elaborate courtship displays, non-monogamous mating system, and sexual dimorphism. This family has served as a good model for the study of sexual selection. Here we present genome assemblies of four manakin species, including Cryptopipo holochlora, Dixiphia pipra (also known as Pseudopipra pipra), Machaeropterus deliciosus and Masius chrysopterus, generated by Single-tube Long Fragment Read (stLFR) technology. The assembled genome sizes ranged from 1.10 Gb to 1.19 Gb, with average scaffold N50 of 29 Mb and contig N50 of 169 Kb. On average, 12,055 protein-coding genes were annotated in the genomes, and 9.79% of the genomes were annotated as repetitive elements. We further identified 75 Mb of Z-linked sequences in manakins, containing 585 to 751 genes and an ~600 Kb pseudoautosomal region (PAR). One notable finding from these Z-linked sequences is that a possible Z-to-autosome/PAR reversal could have occurred in M. chrysopterus. These de novo genomes will contribute to a deeper understanding of evolutionary history and sexual selection in manakins., (© 2022. The Author(s).)
Published: 2022
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50. Incorporating family history of disease improves polygenic risk scores in diverse populations.

Author: Hujoel MLA, Loh PR, Neale BM, and Price AL
Abstract: Polygenic risk scores (PRSs) derived from genotype data and family history (FH) of disease provide valuable information for predicting disease risk, but PRSs perform poorly when applied to diverse populations. Here, we explore methods for combining both types of information (PRS-FH) in UK Biobank data. PRSs were trained using all British individuals (n = 409,000), and target samples consisted of unrelated non-British Europeans (n = 42,000), South Asians (n = 7,000), or Africans (n = 7,000). We evaluated PRS, FH, and PRS-FH using liability-scale R 2 , primarily focusing on 3 well-powered diseases (type 2 diabetes, hypertension, and depression). PRS attained average prediction R 2 s of 5.8%, 4.0%, and 0.53% in non-British Europeans, South Asians, and Africans, confirming poor cross-population transferability. In contrast, PRS-FH attained average prediction R 2 s of 13%, 12%, and 10%, respectively, representing a large improvement in Europeans and an extremely large improvement in Africans. In conclusion, including family history improves the accuracy of polygenic risk scores, particularly in diverse populations., Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests.
Published: 2022
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