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1. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Author

Liu, M, Jiang, Y, Wedow, R, Li, Y, Brazel, DM, Chen, F, Datta, G, Davila-Velderrain, J, McGuire, D, Tian, C, Zhan, X, Team, 23Andme Research, Psychiatry, Hunt All-In, Choquet, H, Docherty, AR, Faul, JD, Foerster, JR, Fritsche, LG, Gabrielsen, ME, Gordon, SD, Haessler, J, Hottenga, J-J, Huang, H, Jang, S-K, Jansen, PR, Ling, Y, Mägi, R, Matoba, N, McMahon, G, Mulas, A, Orrù, V, Palviainen, T, Pandit, A, Reginsson, GW, Skogholt, AH, Smith, JA, Taylor, AE, Turman, C, Willemsen, G, Young, H, Young, KA, Zajac, GJM, Zhao, W, Zhou, W, Bjornsdottir, G, Boardman, JD, Boehnke, M, Boomsma, DI, Chen, C, Cucca, F, Davies, GE, Eaton, CB, Ehringer, MA, Esko, T, Fiorillo, E, Gillespie, NA, Gudbjartsson, DF, Haller, T, Harris, KM, Heath, AC, Hewitt, JK, Hickie, IB, Hokanson, JE, Hopfer, CJ, Hunter, DJ, Iacono, WG, Johnson, EO, Kamatani, Y, Kardia, SLR, Keller, MC, Kellis, M, Kooperberg, C, Kraft, P, Krauter, KS, Laakso, M, Lind, PA, Loukola, A, Lutz, SM, Madden, PAF, Martin, NG, McGue, M, McQueen, MB, Medland, SE, Metspalu, A, Mohlke, KL, Nielsen, JB, Okada, Y, Peters, U, Polderman, TJC, Posthuma, D, Reiner, AP, Rice, JP, Rimm, E, Rose, RJ, Runarsdottir, V, Stallings, MC, Stančáková, A, Stefansson, H, Thai, KK, Tindle, HA, Tyrfingsson, T, Wall, TL, Weir, DR, Weisner, C, Whitfield, JB, Winsvold, BS, Yin, J, Zuccolo, L, Bierut, LJ, Hveem, K, Lee, JJ, Munafò, MR, Saccone, NL, Willer, CJ, Cornelis, MC, David, SP, Hinds, DA, Jorgenson, E, Kaprio, J, Stitzel, JA, Stefansson, K, Thorgeirsson, TE, Abecasis, G, Liu, DJ, Vrieze, S, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, APH - Methodology, Human genetics, Amsterdam Reproduction & Development (AR&D), APH - Aging & Later Life, and Human Genetics

Subjects
Male, Netherlands Twin Register (NTR), Smoking/genetics, ved/biology.organism_classification_rank.species, Alcohol, Genome-wide association study, Brain and Behaviour, chemistry.chemical_compound, 0302 clinical medicine, Tobacco Use Disorder/genetics, Tobacco/adverse effects, Genetics, 0303 health sciences, Smoking, Tobacco and Alcohol, public health, Tobacco Use Disorder, Middle Aged, 3. Good health, Phenotype, psychiatric disorders, Genetic Variation/genetics, Meta-analysis, Genome-Wide Association Study/methods, Female, Physical and Mental Health, Risk, Alcohol Drinking, psychology, Biology, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Tobacco, Humans, Model organism, Gene, 030304 developmental biology, Genetic association, ved/biology, Genetic Variation, Alcohol Drinking/genetics, Heritability, chemistry, genome-wide association studies, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6,7,8,9,10,11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures. © 2019. This is the authors’ accepted and refereed manuscript to the article.

Published
2019
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2. Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration

Author

Waksmunski, AR, Grunin, M, Kinzy, TG, Igo, RP, Haines, JL, Bailey, JNC, Fritsche, LG, Igl, W, Grassmann, F, Sengupta, S, Bragg-Gresham, JL, Burdon, KP, Hebbring, SJ, Wen, C, Gorski, M, Kim, IK, Cho, D, Zack, D, Souied, E, Scholl, HPN, Bala, E, Lee, KE, Hunter, DJ, Sardell, RJ, Mitchell, P, Merriam, JE, Cipriani, V, Hoffman, JD, Schick, T, Lechanteur, YTE, Guymer, RH, Johnson, MP, Jiang, Y, Stanton, CM, Buitendijk, GHS, Zhan, X, Kwong, AM, Boleda, A, Brooks, M, Gieser, L, Ratnapriya, R, Branham, KE, Foerster, JR, Heckenlively, JR, Othman, M, Vote, BJ, Liang, HH, Souzeau, E, McAllister, IL, Isaacs, T, Hall, J, Lake, S, Mackey, DA, Constable, IJ, Craig, JE, Kitchner, TE, Yang, Z, Su, Z, Luo, H, Chen, D, Ouyang, H, Flagg, K, Lin, D, Mao, G, Ferreyra, H, Stark, K, von Strachwitz, CN, Wolf, A, Brandl, C, Rudolph, G, Olden, M, Morrison, MA, Morgan, DJ, Schu, M, Ahn, J, Silvestri, G, Tsironi, EE, Park, KH, Farrer, LA, Orlin, A, Brucker, A, Li, M, Curcio, CA, Mohand-Said, S, Sahel, J-A, Audo, I, Benchaboune, M, Cree, AJ, Rennie, CA, Goverdhan, S, Hagbi-Levi, S, Campochiaro, P, Katsanis, N, Holz, FG, Blond, F, Blanche, H, Deleuze, J-F, Truitt, B, Peachey, NS, Meuer, SM, Myers, CE, Moore, EL, Klein, R, Hauser, MA, Postel, EA, Courtenay, MD, Schwartz, SG, Kovach, JL, Scott, WK, Liew, G, Tan, AG, Gopinath, B, Merriam, JC, Smith, RT, Khan, JC, Shahid, H, Moore, AT, McGrath, JA, Laux, R, Brantley, MA, Agarwal, A, Ersoy, L, Caramoy, A, Langmann, T, Saksens, NTM, de Jong, EK, Hoyng, CB, Cain, MS, Richardson, AJ, Martin, TM, Blangero, J, Weeks, DE, Dhillon, B, van Duijn, CM, Doheny, KF, Romm, J, Klaver, CCW, Hayward, C, Gorin, MB, Klein, ML, Baird, PN, den Hollander, A, Fauser, S, Yates, JRW, Allikmets, R, Wang, JJ, Schaumberg, DA, Klein, BEK, Hagstrom, SA, Chowers, I, Lotery, AJ, Leveillard, T, Zhang, K, Brilliant, MH, Hewitt, AW, Swaroop, A, Chew, EY, Pericak-Vance, MA, DeAngelis, M, Stambolian, D, Iyengar, SK, Weber, BHF, Abecasis, GR, Heid, IM, Waksmunski, AR, Grunin, M, Kinzy, TG, Igo, RP, Haines, JL, Bailey, JNC, Fritsche, LG, Igl, W, Grassmann, F, Sengupta, S, Bragg-Gresham, JL, Burdon, KP, Hebbring, SJ, Wen, C, Gorski, M, Kim, IK, Cho, D, Zack, D, Souied, E, Scholl, HPN, Bala, E, Lee, KE, Hunter, DJ, Sardell, RJ, Mitchell, P, Merriam, JE, Cipriani, V, Hoffman, JD, Schick, T, Lechanteur, YTE, Guymer, RH, Johnson, MP, Jiang, Y, Stanton, CM, Buitendijk, GHS, Zhan, X, Kwong, AM, Boleda, A, Brooks, M, Gieser, L, Ratnapriya, R, Branham, KE, Foerster, JR, Heckenlively, JR, Othman, M, Vote, BJ, Liang, HH, Souzeau, E, McAllister, IL, Isaacs, T, Hall, J, Lake, S, Mackey, DA, Constable, IJ, Craig, JE, Kitchner, TE, Yang, Z, Su, Z, Luo, H, Chen, D, Ouyang, H, Flagg, K, Lin, D, Mao, G, Ferreyra, H, Stark, K, von Strachwitz, CN, Wolf, A, Brandl, C, Rudolph, G, Olden, M, Morrison, MA, Morgan, DJ, Schu, M, Ahn, J, Silvestri, G, Tsironi, EE, Park, KH, Farrer, LA, Orlin, A, Brucker, A, Li, M, Curcio, CA, Mohand-Said, S, Sahel, J-A, Audo, I, Benchaboune, M, Cree, AJ, Rennie, CA, Goverdhan, S, Hagbi-Levi, S, Campochiaro, P, Katsanis, N, Holz, FG, Blond, F, Blanche, H, Deleuze, J-F, Truitt, B, Peachey, NS, Meuer, SM, Myers, CE, Moore, EL, Klein, R, Hauser, MA, Postel, EA, Courtenay, MD, Schwartz, SG, Kovach, JL, Scott, WK, Liew, G, Tan, AG, Gopinath, B, Merriam, JC, Smith, RT, Khan, JC, Shahid, H, Moore, AT, McGrath, JA, Laux, R, Brantley, MA, Agarwal, A, Ersoy, L, Caramoy, A, Langmann, T, Saksens, NTM, de Jong, EK, Hoyng, CB, Cain, MS, Richardson, AJ, Martin, TM, Blangero, J, Weeks, DE, Dhillon, B, van Duijn, CM, Doheny, KF, Romm, J, Klaver, CCW, Hayward, C, Gorin, MB, Klein, ML, Baird, PN, den Hollander, A, Fauser, S, Yates, JRW, Allikmets, R, Wang, JJ, Schaumberg, DA, Klein, BEK, Hagstrom, SA, Chowers, I, Lotery, AJ, Leveillard, T, Zhang, K, Brilliant, MH, Hewitt, AW, Swaroop, A, Chew, EY, Pericak-Vance, MA, DeAngelis, M, Stambolian, D, Iyengar, SK, Weber, BHF, Abecasis, GR, and Heid, IM

Abstract

PURPOSE: Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability. METHODS: We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis. RESULTS: We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive" the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P < 0.0001) across KEGG, Reactome, GO, and NetPath pathways. CONCLUSIONS: We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

Published
2019

3. Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry

Author

Sanchez-Roige, S, Fontanillas, P, Elson, SL, Pandit, A, Schmidt, EM, Foerster, JR, Abecasis, GR, Gray, JC, De Wit, H, Davis, LK, MacKillop, J, and Palmer, AA

Abstract

© 2017 The Author(s). Delay discounting (DD), the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated single-nucleotide polymorphism was rs6528024 (P = 2.40 × 10-8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition and body weight.

Published
2018
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4. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

Author

Fritsche, LG, Igl, W, Bailey, JNC, Grassmann, F, Sengupta, S, Bragg-Gresham, JL, Burdon, KP, Hebbring, SJ, Wen, C, Gorski, M, Kim, IK, Cho, D, Zack, D, Souied, E, Scholl, HPN, Bala, E, Lee, KE, Hunter, DJ, Sardell, RJ, Mitchell, P, Merriam, JE, Cipriani, V, Hoffman, JD, Schick, T, Lechanteur, YTE, Guymer, RH, Johnson, MP, Jiang, Y, Stanton, CM, Buitendijk, GHS, Zhan, X, Kwong, AM, Boleda, A, Brooks, M, Gieser, L, Ratnapriya, R, Branham, KE, Foerster, JR, Heckenlively, JR, Othman, MI, Vote, BJ, Liang, HH, Souzeau, E, McAllister, IL, Isaacs, T, Hall, J, Lake, S, Mackey, DA, Constable, IJ, Craig, JE, Kitchner, TE, Yang, Z, Su, Z, Luo, H, Chen, D, Hong, O, Flagg, K, Lin, D, Mao, G, Ferreyra, H, Starke, K, von Strachwitz, CN, Wolf, A, Brandl, C, Rudolph, G, Olden, M, Morrison, MA, Morgan, DJ, Schu, M, Ahn, J, Silvestri, G, Tsironi, EE, Park, KH, Farrer, LA, Orlin, A, Brucker, A, Li, M, Curcio, CA, Mohand-Said, S, Sahel, J-M, Audo, I, Benchaboune, M, Cree, AJ, Rennie, CA, Goverdhan, SV, Grunin, M, Hagbi-Levi, S, Campochiaro, P, Katsanis, N, Holz, FG, Blond, F, Blanche, H, Deleuze, J-F, Igo, RP, Truitt, B, Peachey, NS, Meuer, SM, Myers, CE, Moore, EL, Klein, R, Hauser, MA, Postel, EA, Courtenay, MD, Schwartz, SG, Kovach, JL, Scott, WK, Liew, G, Tan, AG, Gopinath, B, Merriam, JC, Smith, RT, Khan, JC, Shahid, H, Moore, AT, McGrath, JA, Laux, R, Brantley, MA, Agarwal, A, Ersoy, L, Caramoy, A, Langmann, T, Saksens, NTM, de Jong, EK, Hoyng, CB, Cain, MS, Richardson, AJ, Martin, TM, Blangero, J, Weeks, DE, Dhillon, B, van Duijn, CM, Doheny, KF, Romm, J, Klaver, CCW, Hayward, C, Gorin, MB, Klein, ML, Baird, PN, den Hollander, AI, Fauser, S, Yates, JRW, Allikmets, R, Wang, JJ, Schaumberg, DA, Klein, BEK, Hagstrom, SA, Chowers, I, Lotery, AJ, Leveillard, T, Zhang, K, Brilliant, MH, Hewitt, AW, Swaroop, A, Chew, EY, Pericak-Vance, MA, DeAngelis, M, Stambolian, D, Haines, JL, Iyengar, SK, Weber, BHF, Abecasis, GR, Heid, IM, Fritsche, LG, Igl, W, Bailey, JNC, Grassmann, F, Sengupta, S, Bragg-Gresham, JL, Burdon, KP, Hebbring, SJ, Wen, C, Gorski, M, Kim, IK, Cho, D, Zack, D, Souied, E, Scholl, HPN, Bala, E, Lee, KE, Hunter, DJ, Sardell, RJ, Mitchell, P, Merriam, JE, Cipriani, V, Hoffman, JD, Schick, T, Lechanteur, YTE, Guymer, RH, Johnson, MP, Jiang, Y, Stanton, CM, Buitendijk, GHS, Zhan, X, Kwong, AM, Boleda, A, Brooks, M, Gieser, L, Ratnapriya, R, Branham, KE, Foerster, JR, Heckenlively, JR, Othman, MI, Vote, BJ, Liang, HH, Souzeau, E, McAllister, IL, Isaacs, T, Hall, J, Lake, S, Mackey, DA, Constable, IJ, Craig, JE, Kitchner, TE, Yang, Z, Su, Z, Luo, H, Chen, D, Hong, O, Flagg, K, Lin, D, Mao, G, Ferreyra, H, Starke, K, von Strachwitz, CN, Wolf, A, Brandl, C, Rudolph, G, Olden, M, Morrison, MA, Morgan, DJ, Schu, M, Ahn, J, Silvestri, G, Tsironi, EE, Park, KH, Farrer, LA, Orlin, A, Brucker, A, Li, M, Curcio, CA, Mohand-Said, S, Sahel, J-M, Audo, I, Benchaboune, M, Cree, AJ, Rennie, CA, Goverdhan, SV, Grunin, M, Hagbi-Levi, S, Campochiaro, P, Katsanis, N, Holz, FG, Blond, F, Blanche, H, Deleuze, J-F, Igo, RP, Truitt, B, Peachey, NS, Meuer, SM, Myers, CE, Moore, EL, Klein, R, Hauser, MA, Postel, EA, Courtenay, MD, Schwartz, SG, Kovach, JL, Scott, WK, Liew, G, Tan, AG, Gopinath, B, Merriam, JC, Smith, RT, Khan, JC, Shahid, H, Moore, AT, McGrath, JA, Laux, R, Brantley, MA, Agarwal, A, Ersoy, L, Caramoy, A, Langmann, T, Saksens, NTM, de Jong, EK, Hoyng, CB, Cain, MS, Richardson, AJ, Martin, TM, Blangero, J, Weeks, DE, Dhillon, B, van Duijn, CM, Doheny, KF, Romm, J, Klaver, CCW, Hayward, C, Gorin, MB, Klein, ML, Baird, PN, den Hollander, AI, Fauser, S, Yates, JRW, Allikmets, R, Wang, JJ, Schaumberg, DA, Klein, BEK, Hagstrom, SA, Chowers, I, Lotery, AJ, Leveillard, T, Zhang, K, Brilliant, MH, Hewitt, AW, Swaroop, A, Chew, EY, Pericak-Vance, MA, DeAngelis, M, Stambolian, D, Haines, JL, Iyengar, SK, Weber, BHF, Abecasis, GR, and Heid, IM

Abstract

Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

Published
2016

6. Publisher Correction: Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry.

Author

Sanchez-Roige S, Fontanillas P, Elson SL, Pandit A, Schmidt EM, Foerster JR, Abecasis GR, Gray JC, de Wit H, Davis LK, MacKillop J, and Palmer AA

Abstract

The author list was in the wrong order in the HTML version of the original article and in the HTML version of the original correction notice. This has been corrected to show the 23andMe Research Team as the fourth author and Abraham A. Palmer as the last author in both places.

Published
2019
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7. Publisher Correction: Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry.

Author

Sanchez-Roige S, Fontanillas P, Elson SL, Pandit A, Schmidt EM, Foerster JR, Abecasis GR, Gray JC, de Wit H, Davis LK, MacKillop J, and Palmer AA

Abstract

In the version of this article initially published, the consortium authorship was not presented correctly. The 23andMe Research Team was listed as the last author, rather than the fourth, and a line directing readers to the Supplementary Note for a list of members did appear but was not directly associated with the consortium name. Also, the Supplementary Note description stated that both member names and affiliations were included; in fact, only names are given. Finally, the URL for S-PrediXcan was given in the Methods as https://github.com/hakyimlab/S-PrediXcan; the correct URL is https://github.com/hakyimlab/MetaXcan. The errors have been corrected in the HTML and PDF versions of the article.

Published
2018
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8. Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry.

Author

Sanchez-Roige S, Fontanillas P, Elson SL, Pandit A, Schmidt EM, Foerster JR, Abecasis GR, Gray JC, de Wit H, Davis LK, MacKillop J, and Palmer AA

Subjects
Adult, Cohort Studies, Female, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Male, Mental Disorders diagnosis, Personality Inventory, Surveys and Questionnaires, Young Adult, Delay Discounting, Mental Disorders genetics, Polymorphism, Single Nucleotide genetics, White People genetics
Abstract

Delay discounting (DD), the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated single-nucleotide polymorphism was rs6528024 (P = 2.40 × 10 -8 ), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition and body weight.

Published
2018
Full Text
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9. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

Author

Fritsche LG, Igl W, Bailey JN, Grassmann F, Sengupta S, Bragg-Gresham JL, Burdon KP, Hebbring SJ, Wen C, Gorski M, Kim IK, Cho D, Zack D, Souied E, Scholl HP, Bala E, Lee KE, Hunter DJ, Sardell RJ, Mitchell P, Merriam JE, Cipriani V, Hoffman JD, Schick T, Lechanteur YT, Guymer RH, Johnson MP, Jiang Y, Stanton CM, Buitendijk GH, Zhan X, Kwong AM, Boleda A, Brooks M, Gieser L, Ratnapriya R, Branham KE, Foerster JR, Heckenlively JR, Othman MI, Vote BJ, Liang HH, Souzeau E, McAllister IL, Isaacs T, Hall J, Lake S, Mackey DA, Constable IJ, Craig JE, Kitchner TE, Yang Z, Su Z, Luo H, Chen D, Ouyang H, Flagg K, Lin D, Mao G, Ferreyra H, Stark K, von Strachwitz CN, Wolf A, Brandl C, Rudolph G, Olden M, Morrison MA, Morgan DJ, Schu M, Ahn J, Silvestri G, Tsironi EE, Park KH, Farrer LA, Orlin A, Brucker A, Li M, Curcio CA, Mohand-Saïd S, Sahel JA, Audo I, Benchaboune M, Cree AJ, Rennie CA, Goverdhan SV, Grunin M, Hagbi-Levi S, Campochiaro P, Katsanis N, Holz FG, Blond F, Blanché H, Deleuze JF, Igo RP Jr, Truitt B, Peachey NS, Meuer SM, Myers CE, Moore EL, Klein R, Hauser MA, Postel EA, Courtenay MD, Schwartz SG, Kovach JL, Scott WK, Liew G, Tan AG, Gopinath B, Merriam JC, Smith RT, Khan JC, Shahid H, Moore AT, McGrath JA, Laux R, Brantley MA Jr, Agarwal A, Ersoy L, Caramoy A, Langmann T, Saksens NT, de Jong EK, Hoyng CB, Cain MS, Richardson AJ, Martin TM, Blangero J, Weeks DE, Dhillon B, van Duijn CM, Doheny KF, Romm J, Klaver CC, Hayward C, Gorin MB, Klein ML, Baird PN, den Hollander AI, Fauser S, Yates JR, Allikmets R, Wang JJ, Schaumberg DA, Klein BE, Hagstrom SA, Chowers I, Lotery AJ, Léveillard T, Zhang K, Brilliant MH, Hewitt AW, Swaroop A, Chew EY, Pericak-Vance MA, DeAngelis M, Stambolian D, Haines JL, Iyengar SK, Weber BH, Abecasis GR, and Heid IM

Subjects
Genetic Predisposition to Disease, Humans, Mutation, Genome-Wide Association Study, Macular Degeneration genetics
Abstract

Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

Published
2016
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10. Extended pancreas donor program - the EXPAND study rationale and study protocol.

Author

Proneth A, Schnitzbauer AA, Zeman F, Foerster JR, Holub I, Arbogast H, Bechstein WO, Becker T, Dietz C, Guba M, Heise M, Jonas S, Kersting S, Klempnauer J, Manekeller S, Müller V, Nadalin S, Nashan B, Pascher A, Rauchfuss F, Ströhlein MA, Schemmer P, Schenker P, Thorban S, Vogel T, Rahmel AO, Viebahn R, Banas B, Geissler EK, Schlitt HJ, and Farkas SA

Abstract

Background: Simultaneous pancreas kidney transplantation (SPK), pancreas transplantation alone (PTA) or pancreas transplantation after kidney (PAK) are the only curative treatment options for patients with type 1 (juvenile) diabetes mellitus with or without impaired renal function. Unfortunately, transplant waiting lists for this indication are increasing because the current organ acceptability criteria are restrictive; morbidity and mortality significantly increase with time on the waitlist. Currently, only pancreas organs from donors younger than 50 years of age and with a body mass index (BMI) less than 30 are allocated for transplantation in the Eurotransplant (ET) area. To address this issue we designed a study to increase the available donor pool for these patients., Methods/design: This study is a prospective, multicenter (20 German centers), single blinded, non-randomized, two armed trial comparing outcome after SPK, PTA or PAK between organs with the currently allowed donor criteria versus selected organs from donors with extended criteria. Extended donor criteria are defined as organs procured from donors with a BMI of 30 to 34 or a donor age between 50 and 60 years. Immunosuppression is generally standardized using induction therapy with Myfortic, tacrolimus and low dose steroids. In principle, all patients on the waitlist for primary SPK, PTA or PAK are eligible for the clinical trial when they consent to possibly receiving an extended donor criteria organ. Patients receiving an organ meeting the current standard criteria for pancreas allocation (control arm) are compared to those receiving extended criteria organ (study arm); patients are blinded for a follow-up period of one year. The combined primary endpoint is survival of the pancreas allograft and pancreas allograft function after three months, as an early relevant outcome parameter for pancreas transplantation., Discussion: The EXPAND Study has been initiated to investigate the hypothesis that locally allocated extended criteria organs can be transplanted with similar results compared to the currently allowed standard ET organ allocation. If our study shows a favorable comparison to standard organ allocation criteria, the morbidity and mortality for patients waiting for transplantation could be reduced in the future., Trial Registration: Trial registered at: NCT01384006.

Published
2013
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