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1. Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci

Author: Mignogna, G, Carey, C, Wedow, R, Baya, N, Cordioli, M, Pirastu, N, Bellocco, R, Malerbi, K, Nivard, M, Neale, B, Walters, R, Ganna, A, Mignogna G., Carey C. E., Wedow R., Baya N., Cordioli M., Pirastu N., Bellocco R., Malerbi K. F., Nivard M. G., Neale B. M., Walters R. K., Ganna A., Mignogna, G, Carey, C, Wedow, R, Baya, N, Cordioli, M, Pirastu, N, Bellocco, R, Malerbi, K, Nivard, M, Neale, B, Walters, R, Ganna, A, Mignogna G., Carey C. E., Wedow R., Baya N., Cordioli M., Pirastu N., Bellocco R., Malerbi K. F., Nivard M. G., Neale B. M., Walters R. K., and Ganna A.
Abstract: Response to survey questionnaires is vital for social and behavioural research, and most analyses assume full and accurate response by participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behaviour across 109 questionnaire items in the UK Biobank (N = 360,628). Phenotypic factor scores for two participant-selected nonresponse answers, ‘Prefer not to answer’ (PNA) and ‘I don’t know’ (IDK), each predicted participant nonresponse in follow-up surveys (incremental pseudo-R 2 = 0.056), even when controlling for education and self-reported health (incremental pseudo-R 2 = 0.046). After performing genome-wide association studies of our factors, PNA and IDK were highly genetically correlated with one another (r g = 0.73 (s.e. = 0.03)) and with education (r g,PNA = −0.51 (s.e. = 0.03); r g,IDK = −0.38 (s.e. = 0.02)), health (r g,PNA = 0.51 (s.e. = 0.03); r g,IDK = 0.49 (s.e. = 0.02)) and income (r g,PNA = –0.57 (s.e. = 0.04); r g,IDK = −0.46 (s.e. = 0.02)), with additional unique genetic associations observed for both PNA and IDK (P < 5 × 10−8). We discuss how these associations may bias studies of traits correlated with item nonresponse and demonstrate how this bias may substantially affect genome-wide association studies. While the UK Biobank data are deidentified, we further protected participant privacy by avoiding exploring non-response behaviour to single questions, assuring that no information can be used to associate results with any particular respondents.
Published: 2023

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

Author: Munn-Chernoff, M.A. Johnson, E.C. Chou, Y.-L. Coleman, J.R.I. Thornton, L.M. Walters, R.K. Yilmaz, Z. Baker, J.H. Hübel, C. Gordon, S. Medland, S.E. Watson, H.J. Gaspar, H.A. Bryois, J. Hinney, A. Leppä, V.M. Mattheisen, M. Ripke, S. Yao, S. Giusti-Rodríguez, P. Hanscombe, K.B. Adan, R.A.H. Alfredsson, L. Ando, T. Andreassen, O.A. Berrettini, W.H. Boehm, I. Boni, C. Boraska Perica, V. Buehren, K. Burghardt, R. Cassina, M. Cichon, S. Clementi, M. Cone, R.D. Courtet, P. Crow, S. Crowley, J.J. Danner, U.N. Davis, O.S.P. de Zwaan, M. Dedoussis, G. Degortes, D. DeSocio, J.E. Dick, D.M. Dikeos, D. Dina, C. Dmitrzak-Weglarz, M. Docampo, E. Duncan, L.E. Egberts, K. Ehrlich, S. Escaramís, G. Esko, T. Estivill, X. Farmer, A. Favaro, A. Fernández-Aranda, F. Fichter, M.M. Fischer, K. Föcker, M. Foretova, L. Forstner, A.J. Forzan, M. Franklin, C.S. Gallinger, S. Giegling, I. Giuranna, J. Gonidakis, F. Gorwood, P. Gratacos Mayora, M. Guillaume, S. Guo, Y. Hakonarson, H. Hatzikotoulas, K. Hauser, J. Hebebrand, J. Helder, S.G. Herms, S. Herpertz-Dahlmann, B. Herzog, W. Huckins, L.M. Hudson, J.I. Imgart, H. Inoko, H. Janout, V. Jiménez-Murcia, S. Julià, A. Kalsi, G. Kaminská, D. Karhunen, L. Karwautz, A. Kas, M.J.H. Kennedy, J.L. Keski-Rahkonen, A. Kiezebrink, K. Kim, Y.-R. Klump, K.L. Knudsen, G.P.S. La Via, M.C. Le Hellard, S. Levitan, R.D. Li, D. Lilenfeld, L. Lin, B.D. Lissowska, J. Luykx, J. Magistretti, P.J. Maj, M. Mannik, K. Marsal, S. Marshall, C.R. Mattingsdal, M. McDevitt, S. McGuffin, P. Metspalu, A. Meulenbelt, I. Micali, N. Mitchell, K. Monteleone, A.M. Monteleone, P. Nacmias, B. Navratilova, M. Ntalla, I. O'Toole, J.K. Ophoff, R.A. Padyukov, L. Palotie, A. Pantel, J. Papezova, H. Pinto, D. Rabionet, R. Raevuori, A. Ramoz, N. Reichborn-Kjennerud, T. Ricca, V. Ripatti, S. Ritschel, F. Roberts, M. Rotondo, A. Rujescu, D. Rybakowski, F. Santonastaso, P. Scherag, A. Scherer, S.W. Schmidt, U. Schork, N.J. Schosser, A. Seitz, J. Slachtova, L. Slagboom, P.E. Slof-Op't Landt, M.C.T. Slopien, A. Sorbi, S. Świątkowska, B. Szatkiewicz, J.P. Tachmazidou, I. Tenconi, E. Tortorella, A. Tozzi, F. Treasure, J. Tsitsika, A. Tyszkiewicz-Nwafor, M. Tziouvas, K. van Elburg, A.A. van Furth, E.F. Wagner, G. Walton, E. Widen, E. Zeggini, E. Zerwas, S. Zipfel, S. Bergen, A.W. Boden, J.M. Brandt, H. Crawford, S. Halmi, K.A. Horwood, L.J. Johnson, C. Kaplan, A.S. Kaye, W.H. Mitchell, J. Olsen, C.M. Pearson, J.F. Pedersen, N.L. Strober, M. Werge, T. Whiteman, D.C. Woodside, D.B. Grove, J. Henders, A.K. Larsen, J.T. Parker, R. Petersen, L.V. Jordan, J. Kennedy, M.A. Birgegård, A. Lichtenstein, P. Norring, C. Landén, M. Mortensen, P.B. Polimanti, R. McClintick, J.N. Adkins, A.E. Aliev, F. Bacanu, S.-A. Batzler, A. Bertelsen, S. Biernacka, J.M. Bigdeli, T.B. Chen, L.-S. Clarke, T.-K. Degenhardt, F. Docherty, A.R. Edwards, A.C. Foo, J.C. Fox, L. Frank, J. Hack, L.M. Hartmann, A.M. Hartz, S.M. Heilmann-Heimbach, S. Hodgkinson, C. Hoffmann, P. Hottenga, J.-J. Konte, B. Lahti, J. Lahti-Pulkkinen, M. Lai, D. Ligthart, L. Loukola, A. Maher, B.S. Mbarek, H. McIntosh, A.M. McQueen, M.B. Meyers, J.L. Milaneschi, Y. Palviainen, T. Peterson, R.E. Ryu, E. Saccone, N.L. Salvatore, J.E. Sanchez-Roige, S. Schwandt, M. Sherva, R. Streit, F. Strohmaier, J. Thomas, N. Wang, J.-C. Webb, B.T. Wedow, R. Wetherill, L. Wills, A.G. Zhou, H. Boardman, J.D. Chen, D. Choi, D.-S. Copeland, W.E. Culverhouse, R.C. Dahmen, N. Degenhardt, L. Domingue, B.W. Frye, M.A. Gäebel, W. Hayward, C. Ising, M. Keyes, M. Kiefer, F. Koller, G. Kramer, J. Kuperman, S. Lucae, S. Lynskey, M.T. Maier, W. Mann, K. Männistö, S. Müller-Myhsok, B. Murray, A.D. Nurnberger, J.I. Preuss, U. Räikkönen, K. Reynolds, M.D. Ridinger, M. Scherbaum, N. Schuckit, M.A. Soyka, M. Treutlein, J. Witt, S.H. Wodarz, N. Zill, P. Adkins, D.E. Boomsma, D.I. Bierut, L.J. Brown, S.A. Bucholz, K.K. Costello, E.J. de Wit, H. Diazgranados, N. Eriksson, J.G. Farrer, L.A. Foroud, T.M. Gillespie, N.A. Goate, A.M. Goldman, D. Grucza, R.A. Hancock, D.B. Harris, K.M. Hesselbrock, V. Hewitt, J.K. Hopfer, C.J. Iacono, W.G. Johnson, E.O. Karpyak, V.M. Kendler, K.S. Kranzler, H.R. Krauter, K. Lind, P.A. McGue, M. MacKillop, J. Madden, P.A.F. Maes, H.H. Magnusson, P.K.E. Nelson, E.C. Nöthen, M.M. Palmer, A.A. Penninx, B.W.J.H. Porjesz, B. Rice, J.P. Rietschel, M. Riley, B.P. Rose, R.J. Shen, P.-H. Silberg, J. Stallings, M.C. Tarter, R.E. Vanyukov, M.M. Vrieze, S. Wall, T.L. Whitfield, J.B. Zhao, H. Neale, B.M. Wade, T.D. Heath, A.C. Montgomery, G.W. Martin, N.G. Sullivan, P.F. Kaprio, J. Breen, G. Gelernter, J. Edenberg, H.J. Bulik, C.M. Agrawal, A.
Subjects: mental disorders
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors. © 2020 Society for the Study of Addiction
Published: 2021

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

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

4. 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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5. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences

Author: Karlsson Linnér, R., Biroli, Pietro, Kong, E., Meddens, Fleur W., Wedow, R., Fontana, M.A., Hoen, P.A.C. 't, Galesloot, T.E., Leeuw, C.A. de, Kiemeney, B., Franke, B., Koellinger, P., Beauchamp, J.P., Karlsson Linnér, R., Biroli, Pietro, Kong, E., Meddens, Fleur W., Wedow, R., Fontana, M.A., Hoen, P.A.C. 't, Galesloot, T.E., Leeuw, C.A. de, Kiemeney, B., Franke, B., Koellinger, P., and Beauchamp, J.P.
Abstract: Contains fulltext : 201141.pdf (publisher's version ) (Closed access)
Published: 2019

6. Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences

Author: Linnér, R., Biroli, P., Kong, E., Meddens, S., Wedow, R., Fontana, M., Lebreton, M., Abdellaoui, A., Hammerschlag, A., Nivard, M., Okbay, A., Rietveld, C., Timshel, P., Tino, S., Trzaskowski, M., de Vlaming, R., Zünd, C., Bao, Y., Buzdugan, L., Caplin, A., Chen, C., Eibich, P., Fontanillas, P., Gonzalez, J., Joshi, P., Karhunen, V., Kleinman, A., Levin, R., Lill, C., Meddens, G., Muntané, G., Sanchez-Roige, S., van Rooij, F., Taskesen, E., Wu, Y., Zhang, F., Auton, A., Boardman, J., Clark, D., Conlin, A., Dolan, C., Fischbacher, U., Groenen, P., Harris, K., Hasler, G., Hofman, A., Ikram, M., Jain, S., Karlsson, R., Kessler, R., Kooyman, M., MacKillop, J., Männikkö, M., Morcillo-Suarez, C., McQueen, M., Schmidt, K., Smart, M., Sutter, M., Thurik, A., Uitterlinden, A., White, J., de Wit, H., Yang, J., Bertram, L., Boomsma, D., Esko, T., Fehr, E., Hinds, D., Johannesson, M., Kumari, M., Laibson, D., Magnusson, P., Meyer, M., Navarro, A., Palmer, A., Pers, T., Posthuma, D., Schunk, D., Stein, M., Svento, R., Tiemeier, H., Timmers, P., Turley, P., Ursano, R., Wagner, G., https://orcid.org/0000-0002-5985-4073, Wilson, J., Gratten, J., Lee, J., Cesarini, D., Benjamin, D., Koellinger, P., Beauchamp, J., 23andme Research Team, eQTLgen Consortium, International Cannabis Consortium, Psychiatric Genomics Consortium, and Social Science Genetic Association Consortium
Published: 2018

7. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Author: Lee, J.J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Galesloot, T.E., Kiemeney, L.A.L.M., Franke, B., Benjamin, D.J., Cesarini, D., Lee, J.J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Galesloot, T.E., Kiemeney, L.A.L.M., Franke, B., Benjamin, D.J., and Cesarini, D.
Abstract: Contains fulltext : 195595.pdf (publisher's version ) (Closed access), Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
Published: 2018

8. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Author: Lee, JJ, Wedow, R, Okbay, A, Kong, E, Maghzian, O, Zacher, M, Tuan Anh, N-V, Bowers, P, Sidorenko, J, Linner, RK, Fontana, MA, Kundu, T, Lee, C, Li, H, Li, R, Royer, R, Timshel, PN, Walters, RK, Willoughby, EA, Yengo, L, Alver, M, Bao, Y, Clark, DW, Day, FR, Furlotte, NA, Joshi, PK, Kemper, KE, Kleinman, A, Langenberg, C, Magi, R, Trampush, JW, Verma, SS, Wu, Y, Lam, Mei, Zhao, JH, Zheng, Z, Boardman, JD, Campbell, H, Freese, J, Harris, KM, Hayward, C, Herd, P, Kumari, M, Lencz, T, Luan, JA, Malhotra, AK, Metspalu, A, Milani, L, Ong, KK, Perry, JRB, Porteous, DJ, Ritchie, MD, Smart, MC, Smith, BH, Tung, JY, Wareham, NJ, Wilson, JF, Beauchamp, JP, Conley, DC, Esko, T, Lehrer, SF, Magnusson, PKE, Oskarsson, S, Pers, TH, Robinson, MR, Thom, K, Watson, C, Chabris, CF, Meyer, MN, Laibson, DI, Yang, Jiaqi, Johannesson, M, Koellinger, PD, Turley, P, Visscher, PM, Benjamin, DJ, Cesarini, D, Lee, JJ, Wedow, R, Okbay, A, Kong, E, Maghzian, O, Zacher, M, Tuan Anh, N-V, Bowers, P, Sidorenko, J, Linner, RK, Fontana, MA, Kundu, T, Lee, C, Li, H, Li, R, Royer, R, Timshel, PN, Walters, RK, Willoughby, EA, Yengo, L, Alver, M, Bao, Y, Clark, DW, Day, FR, Furlotte, NA, Joshi, PK, Kemper, KE, Kleinman, A, Langenberg, C, Magi, R, Trampush, JW, Verma, SS, Wu, Y, Lam, Mei, Zhao, JH, Zheng, Z, Boardman, JD, Campbell, H, Freese, J, Harris, KM, Hayward, C, Herd, P, Kumari, M, Lencz, T, Luan, JA, Malhotra, AK, Metspalu, A, Milani, L, Ong, KK, Perry, JRB, Porteous, DJ, Ritchie, MD, Smart, MC, Smith, BH, Tung, JY, Wareham, NJ, Wilson, JF, Beauchamp, JP, Conley, DC, Esko, T, Lehrer, SF, Magnusson, PKE, Oskarsson, S, Pers, TH, Robinson, MR, Thom, K, Watson, C, Chabris, CF, Meyer, MN, Laibson, DI, Yang, Jiaqi, Johannesson, M, Koellinger, PD, Turley, P, Visscher, PM, Benjamin, DJ, and Cesarini, D
Published: 2018

9. Body size reference norms and subjective weight status: A gender and life course approach

Author: Wedow, Robbee, Masters, Ryan K., Mollborn, Stefanie, Schnabel, Landon, and Boardman, Jason D.
Published: 2018

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

Author: Polderman, T.J.C., Stefansson, K., Zuccolo, L., Wall, T.L., Stan��kov��, A., Zhan, X., Hunter, D.J., Davila-Velderrain, J., Palviainen, T., Brazel, D.M., 23andMe Research Team, Haller, T., Chen, F., Jiang, Y., Johnson, E.O., Rose, R.J., Martin, N.G., Wedow, R., Rice, J.P., Boehnke, M., Jorgenson, E., Posthuma, D., Haessler, J., Kellis, M., Young, K.A., Jansen, P.R., Bjornsdottir, G., Kardia, S.L.R., Metspalu, A., Chen, C., Eaton, C.B., Madden, P.A.F., Gillespie, N.A., McGue, M., Choquet, H., McMahon, G., Jang, S.-K., Faul, J.D., Nielsen, J.B., Fritsche, L.G., Yin, J., Cucca, F., Medland, S.E., Vrieze, S., Thorgeirsson, T.E., Loukola, A., Reginsson, G.W., Tian, C., Orr��, V., HUNT All-In Psychiatry, Iacono, W.G., Gordon, S.D., Kraft, P., Fiorillo, E., Reiner, A.P., Willer, C.J., Boomsma, D.I., Munaf��, M.R., Tyrfingsson, T., Kaprio, J., Laakso, M., Zajac, G.J.M., Willemsen, G., Hickie, I.B., Runarsdottir, V., Li, Y., Hottenga, J.-J., McQueen, M.B., Ehringer, M.A., Zhou, W., Smith, J.A., Taylor, A.E., Tindle, H.A., Kooperberg, C., Boardman, J.D., Lee, J.J., McGuire, D., Zhao, W., Mulas, A., Cornelis, M.C., Lind, P.A., Hveem, K., Weisner, C., Datta, G., Gudbjartsson, D.F., Lutz, S.M., M��gi, R., Hewitt, J.K., Turman, C., Thai, K.K., Stallings, M.C., Kamatani, Y., Hopfer, C.J., David, S.P., Young, H., Rimm, E., Bierut, L.J., Ling, Y., Foerster, J.R., Harris, K.M., Davies, G.E., Krauter, K.S., Matoba, N., Abecasis, G., Esko, T., Keller, M.C., Whitfield, J.B., Liu, D.J., Huang, H., Stitzel, J.A., Liu, M., Peters, U., Saccone, N.L., Docherty, A.R., Pandit, A., Stefansson, H., Hokanson, J.E., Heath, A.C., Okada, Y., Weir, D.R., and Mohlke, K.L.
Subjects: 3. Good health
Abstract: Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders. They are heritable and etiologically related behaviors that have been resistant to gene discovery efforts. 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.

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

Author: Samuel Kuperman, Leila Karhunen, Geòrgia Escaramís, Sébastien Guillaume, Kelly L. Klump, David C. Whiteman, Colin A. Hodgkinson, Stephanie H. Witt, Artemis Tsitsika, Hana Papezova, Renato Polimanti, P. Eline Slagboom, Peter Zill, Jakob Grove, Toni-Kim Clarke, Michael Soyka, Jennifer Jordan, Steven Gallinger, Philip Gorwood, Preben Bo Mortensen, Yuri Milaneschi, Ingrid Meulenbelt, Jen Chyong Wang, Markus M. Nöthen, Katrin Männik, Henry R. Kranzler, Michael M. Vanyukov, Anna Keski-Rahkonen, William G. Iacono, Raymond K. Walters, Stephanie Le Hellard, Bochao Danae Lin, Vesna Boraska Perica, Marion Roberts, Patrick F. Sullivan, Steven Crawford, Mark A. Frye, Melissa A. Munn-Chernoff, Hakon Hakonarson, Andreas Birgegård, Robert Culverhouse, Alexis C. Edwards, Jerome C. Foo, Alessandro Rotondo, Brenda W.J.H. Penninx, Laura M. Hack, Michael T. Lynskey, Mario Maj, Alessio Maria Monteleone, Ted Reichborn-Kjennerud, Julie K. O'Toole, Marta Tyszkiewicz-Nwafor, Matt McGue, Julien Bryois, Martina de Zwaan, Norbert Dahmen, Stefanie Heilmann-Heimbach, Deborah Kaminská, Benedetta Nacmias, Nicholas G. Martin, Anna R. Docherty, Christopher Hübel, Nancy L. Pedersen, Janet Treasure, William E. Copeland, Roger A.H. Adan, Jaakko Kaprio, Aarno Palotie, L. John Horwood, Maria La Via, Philippe Courtet, Virpi M. Leppä, Judy L. Silberg, Jason D. Boardman, Fazil Aliev, Wade H. Berrettini, Doo Sup Choi, Youl-Ri Kim, Konstantinos Hatzikotoulas, Harriet de Wit, Sandra A. Brown, Elisabeth Widen, Caroline Hayward, Nicholas J. Schork, Penelope A. Lind, Ralph E. Tarter, Jana Strohmaier, Allan S. Kaplan, Richard A. Grucza, Bradley T. Webb, Angela Favaro, Dalila Pinto, Helena Gaspar, Andrew W. Bergen, Beate Herpertz-Dahlmann, Robert Levitan, Wolfgang Gäbel, Xavier Estivill, Emma C. Johnson, Konstantinos Tziouvas, Lindsay A. Farrer, Lenka Foretova, Marc A. Schuckit, Joanna M. Biernacka, André Scherag, Robbee Wedow, Abraham A. Palmer, Amy E. Adkins, Franziska Degenhardt, Louisa Degenhardt, Jurjen J. Luykx, Marius Lahti-Pulkkinen, Brien P. Riley, Monika Ridinger, Matteo Cassina, Harry Brandt, Yiran Guo, Stephan Ripke, Palmiero Monteleone, Katri Räikkönen, Jonathan R. I. Coleman, Martin A. Kennedy, Stephen W. Scherer, Ioanna Tachmazidou, Catherine M. Olsen, Bernice Porjesz, Esther Walton, Yi-Ling Chou, Nicolas Ramoz, Tetsuya Ando, Andres Metspalu, Bertram Müller-Myhsok, Brion S. Maher, Sarah Bertelsen, Melanie L. Schwandt, Janiece E. DeSocio, Margaret Keyes, John F. Pearson, Dongbing Lai, Paul Lichtenstein, James MacKillop, George Dedoussis, Jari Lahti, Ulrike Schmidt, Stefan Ehrlich, Amanda G. Wills, Teemu Palviainen, David Goldman, Elena Tenconi, Dimitris Dikeos, Scott I. Vrieze, Sietske G. Helder, Katharina Buehren, Hongyu Zhao, Sara McDevitt, Jolanta Lissowska, Joseph M. Boden, Li-Shiun Chen, Susanne Lucae, Sara Marsal, Dan Rujescu, Claes Norring, Howard J. Edenberg, Victor M. Karpyak, Fragiskos Gonidakis, Per Hoffmann, Christopher S. Franklin, Karin Egberts, Johanna Giuranna, Stefan Herms, Leah Wetherill, Stephanie Zerwas, Anthony Batzler, Elliot C. Nelson, Jouke-Jan Hottenga, Marcella Rietschel, Ioanna Ntalla, Victor Hesselbrock, Sarah M. Hartz, Marie Navratilova, Falk Kiefer, Martien J H Kas, Richard J. Rose, Andrew C. Heath, Jin P. Szatkiewicz, Lenka Slachtova, Lisa Lilenfeld, Katherine A. Halmi, John P. Rice, Anjali K. Henders, Christian Dina, Norbert Wodarz, Satu Männistö, Hamdi Mbarek, Shuyang Yao, Vladimir Janout, Alison Goate, Bettina Konte, Alexandra Schosser, Danfeng Chen, Kirsty Kiezebrink, Euijung Ryu, Dana B. Hancock, James Mitchell, Sarah E. Medland, Ina Giegling, Valdo Ricca, Scott D. Gordon, Gabrielle Koller, Samuli Ripatti, Laura M. Thornton, Alison D. Murray, Morten Mattingsdal, Zeynep Yilmaz, Jens Treutlein, Kathleen K. Bucholz, Tim B. Bigdeli, Eric F. van Furth, Hermine H. Maes, Ken B. Hanscombe, Sandra Sanchez-Roige, Daniela Degortes, Monica Forzan, Manuel Mattheisen, Richard Sherva, Scott J. Crow, Mikael Landén, Wolfgang Herzog, Jeanette N. McClintick, Tõnu Esko, Louis Fox, Wolfgang Maier, Liselotte Petersen, Laura J. Bierut, Roseann E. Peterson, Gursharan Kalsi, Kathleen Mullan Harris, Margarita C T Slof-Op 't Landt, Tamara L. Wall, Patrik K. E. Magnusson, Unna N. Danner, Stephan Zipfel, Ulrich W. Preuss, Elisa Docampo, D. Blake Woodside, Alfonso Tortorella, Benjamin W. Domingue, Franziska Ritschel, Johan G. Eriksson, Anu Raevuori, Benjamin M. Neale, Marcus Ising, Annemarie A. van Elburg, Filip Rybakowski, Maureen Reynolds, Tracey D. Wade, Manfred M. Fichter, Monica Gratacos Mayora, Claudette Boni, Andreas J. Forstner, John Whitfield, Silviu Alin Bacanu, Matthew B. McQueen, Andrew M. McIntosh, Norbert Scherbaum, Tatiana Foroud, Gun Peggy Knudsen, Sven Cichon, Christian J. Hopfer, Josef Frank, Eleftheria Zeggini, Federica Tozzi, Nadia Micali, Danielle M. Dick, Pamela A. F. Madden, Christian R. Marshall, Johannes Hebebrand, Fernando Fernández-Aranda, Roel A. Ophoff, Roland Burghardt, Nathaniel Thomas, Leonid Padyukov, Nancy L. Saccone, Anu Loukola, Fabian Streit, James L. Kennedy, Jessica H. Baker, Peter McGuffin, Walter H. Kaye, Pei Hong Shen, Anne Farmer, Roger D. Cone, Ilka Boehm, Jacquelyn L. Meyers, Paolo Santonastaso, Maurizio Clementi, Susana Jiménez-Murcia, Gudrun Wagner, Anke Hinney, Richard Parker, James I. Hudson, Nathan A. Gillespie, Michael Strober, John I. Nurnberger, Sandro Sorbi, Dorret I. Boomsma, Beata Świątkowska, Janne Tidselbak Larsen, Kenneth S. Kendler, Hidetoshi Inoko, Jessica E. Salvatore, Hunna J. Watson, Jochen Seitz, Jacques Pantel, Karl Mann, Hang Zhou, Antonio Julià, Oliver S. P. Davis, Nancy Diazgranados, Krista Fischer, John K. Hewitt, Karen S. Mitchell, Joanna Hauser, Eric O. Johnson, Craig Johnson, E. Jane Costello, Agnieszka Słopień, Dong Li, Laramie E. Duncan, Arpana Agrawal, Grant W. Montgomery, Manuel Föcker, Thomas Werge, Lannie Ligthart, Andreas Karwautz, Raquel Rabionet, Kenneth Krauter, Joel Gelernter, James J. Crowley, Cynthia M. Bulik, Paola Giusti-Rodríguez, Laura M. Huckins, Gerome Breen, Michael C. Stallings, Daniel E. Adkins, Pierre J. Magistretti, John Kramer, Lars Alfredsson, Hartmut Imgart, Annette M. Hartmann, Ole A. Andreassen, Monika Dmitrzak-Weglarz, Psychiatry, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Department Psychiatry [Chapel Hill], University of North Carolina System (UNC)-University of North Carolina System (UNC), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Harvard Medical School [Boston] (HMS), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], QIMR Berghofer Medical Research Institute, Karolinska Institutet [Stockholm], University Children's Hospital of Essen [Essen, Germany], University of Duisburg-Essen, Aarhus University [Aarhus], Stockholm County Council, University of Würzburg, Guy's Hospital [London], University Medical Center [Utrecht], University of Gothenburg (GU), Altrecht Center for Eating Disorders Rintveld [Zeist, The Netherlands] (Mental Health Institute), National Institute of Mental Health [Tokyo, Japan] (NIMH), National Center of Neurology and Psychiatry [Tokyo, Japan], University of Oslo (UiO), Norwegian Centre for Mental Disorders Research [Oslo] (NORMENT), University of Oslo (UiO)-Haukeland University Hospital, University of Bergen (UiB)-University of Bergen (UiB)-Oslo University Hospital [Oslo], Department of Psychiatry [Philadelphia], University of Pennsylvania [Philadelphia], Perelman School of Medicine, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Institut de psychiatrie et neurosciences (U894 / UMS 1266), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Split, The Wellcome Trust Sanger Institute [Cambridge], RWTH Aachen University, Universitätsklinikum Frankfurt, Universita degli Studi di Padova, University Hospital Basel [Basel], Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Minnesota System, University of Bristol [Bristol], Hannover Medical School [Hannover] (MHH), Harokopio University of Athens, Seattle University [Seattle], Virginia Commonwealth University (VCU), University of Athens Medical School [Athens], unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Poznan University of Medical Sciences [Poland] (PUMS), Institute of Environmental Science and Technology [Barcelona] (ICTA), Universitat Autònoma de Barcelona (UAB), Massachusetts General Hospital [Boston], Stanford University, MetaGenoPolis (MGP (US 1367)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Estonian Genome and Medicine, University of Tartu, Universitat Pompeu Fabra [Barcelona] (UPF), MRC Social, Genetic and Developmental Psychiatry Centre (SGDP), The Institute of Psychiatry-King‘s College London, Department of Psychiatry (IDIBELL), CIBERobn Fisiopatología de la Obesidad y Nutrición-University Hospital of Bellvitge, Ludwig-Maximilians-Universität München (LMU), Infectious diseases division, Department of internal medicine, University of Münster, Masaryk Memorial Cancer Institute, Masaryk Memorial Cancer Institute (RECAMO), Universitätsklinikum Bonn (UKB), Familial Gastrointestinal Cancer Registry, Mount Sinai Hospital [Toronto, Canada] (MSH), Medstar Research Institute, Universität Duisburg-Essen [Essen], National and Kapodistrian University of Athens (NKUA), Children’s Hospital of Philadelphia (CHOP ), The Center for Applied Genomics, Psychiatric Genetic Unit, Poznan University of Medical Sciences, Department of Child and Adolescent Psychiatry and Psychotherapy, LVR-Klinikum Essen, Centre for Epidemiology and Biostatistics, Faculty of Medicine and Health Leeds, University of Leeds, Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), Heidelberg University Hospital [Heidelberg], Icahn School of Medicine at Mount Sinai [New York] (MSSM), School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia., Parkland-Klinik [Bad Wildungen-Reinhardshausen, Germany], Tokai University, Department of Epidemiology and Public Health [university of Ostrava], Lékařská fakulta / Faculty of Medicine [University of Ostrava], Ostravská univerzita / University of Ostrava-Ostravská univerzita / University of Ostrava, Vall d'Hebron University Hospital [Barcelona], Charles University [Prague] (CU), University of Eastern Finland, Medizinische Universität Wien = Medical University of Vienna, Centre de toxicomanie et de santé mentale [Toronto, ON, Canada], University of Helsinki, University of Aberdeen, Faculty of Science, J.E. Purkinje University, J. E. Purkinje University, Michigan State University System, Norwegian Institute of Public Health [Oslo] (NIPH), Haukeland University Hospital, University of Bergen (UiB), Ingénierie Moléculaire et Physiopathologie Articulaire (IMoPA), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), The Chicago School of Professional Psychology [Washington, District of Columbia, USA] (Washington DC Campus), Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Brain and Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Department of Psychiatry, University of Napoli, Center for Integrative Genomics - Institute of Bioinformatics, Génopode (CIG), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne (UNIL)-Université de Lausanne (UNIL), Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, KG Jebsen Centre for Psychosis Research, University of Oslo (UiO)-Institute of Clinical Medicine-Oslo University Hospital [Oslo], University College Cork (UCC), Section Molecular Epidemiology, Leiden University Medical Center (LUMC), Institute of Psychiatry, King's College, VA Boston Healthcare System, Università degli studi della Campania 'Luigi Vanvitelli', Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Kartini Clinic [Portland, Oregon, USA], University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Head of Medical Sequencing, Vanderbilt University School of Medicine [Nashville], The Hospital for sick children [Toronto] (SickKids), Center for Genomic Regulation (CRG-UPF), CIBER de Epidemiología y Salud Pública (CIBERESP), Department of Medical Epidemiology and Biostatistics (MEB), University of Pisa - Università di Pisa, Division of Psychiatric Genomics, Institute of Medical Informatics, Biometry and Epidemiology, Department of Molecular and Experimental Medicine, The Scripps Research Institute, The Scripps Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University-Medical Research Council, Leiden University Medical Center (LUMC), Center for Eating Disorders Ursula [Leiden, The Netherlands] (Rivierduinen), Medical University of Łódź (MUL), The Jackson Laboratory [Bar Harbor] (JAX), Neurosciences Centre of Excellence in Drug Discovery, GlaxoSmithKline Research and Development, Utrecht University [Utrecht], SURFACES, Institut de recherches sur la catalyse et l'environnement de Lyon (IRCELYON), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Centre épigénétique et destin cellulaire (EDC (UMR_7216)), Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Human Genetics, Internal Medicine [Tuebingen, Germany], Tuebingen University [Germany], Oregon Research Institute (ORI), University of Otago [Dunedin, Nouvelle-Zélande], The Center for Eating Disorders at Sheppard Pratt [Baltimore, MD, USA], Weill Medical College of Cornell University [New York], Eating Recovery Center [Denver, CO, USA], Centre for Addiction and Mental Health [Toronto, ON, Canada], University of California [San Diego] (UC San Diego), University of California, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, Center for Genomic Medicine, Copenhagen University Hospital-Rigshospitalet [Copenhagen], Copenhagen University Hospital, Institute of Medical Science [Toronto], University of Toronto, Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Sahlgrenska Academy at University of Gothenburg [Göteborg], Department of Genomics, Yale University School of Medicine, Indiana University School of Medicine, Indiana University System, Mayo Clinic [Rochester], Mayo Clinic, SUNY Downstate Medical Center, State University of New York (SUNY), University of Edinburgh, Department of Genomics, Life and Brain Center, University of Bonn, University of Utah School of Medicine [Salt Lake City], University of Heidelberg, Medical Faculty, Department of Psychiatry and Behavioral Sciences, Howard University College of Medicine, Department of Genomics [Bonn, Germany] (Institute of Human Genetics), University of Bonn-Institute of Human Genetics [Bonn, Germany], National Institutes of Health [Bethesda] (NIH), National Institute on Alcohol Abuse and Alcoholism [Bethesda, MD, USA] (NIAAA), Martin-Luther-University Halle-Wittenberg, Helsinki Institute of Life Science (HiLIFE), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Vrije Universiteit Amsterdam [Amsterdam] (VU), Mathematical Sciences Institute (MSI), Australian National University (ANU), University of Colorado [Boulder], VU University Medical Center [Amsterdam], Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Universität Heidelberg [Heidelberg], Department of Genetic Epidemiology in Psychiatry [Mannhein], Universität Heidelberg [Heidelberg]-Central Institute of Mental Health Mannheim, Harvard University [Cambridge], University of Colorado Anschutz [Aurora], University of Vermont [Burlington], University of New South Wales [Sydney] (UNSW), University of Dusseldorf, Genetics and Pathology, Center for Human Genetic Research, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Heidelberg University, University of Iowa [Iowa City], Vienna University of Technology (TU Wien), Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, Chronic Disease Epidemiology and Prevention Unit, National Institute for Health and Welfare [Helsinki], Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Indiana University System-Indiana University System, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), University of Regensburg, Rush University Medical Center [Chicago], University of Utah, Duke University Medical Center, University of Illinois [Chicago] (UIC), University of Illinois System, Department of Medical and Molecular Genetics, Dpt of Neuroscience [New York], Laboratory of Neurogenetics, National Institutes of Health [Bethesda] (NIH)-National Institute on Alcohol Abuse and Alcoholism, Department of Health and Human Services, University of Connecticut (UCONN), University of Colorado [Denver], Research Triangle Institute International (RTI International), McMaster University [Hamilton, Ontario], CLinical Psychology, Department of Electrical and Computer Engineering [Montréal], McGill University = Université McGill [Montréal, Canada], Yale School of Public Health (YSPH), Analytic and Translational Genetics Unit, Flinders University [Adelaide, Australia], Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Department of Public Health, Indiana University - Purdue University Indianapolis (IUPUI), National Institute of Mental Health (NIMH), University of Pennsylvania, Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), Università degli Studi di Padova = University of Padua (Unipd), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Unité de recherche de l'institut du thorax (ITX-lab), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), King‘s College London-The Institute of Psychiatry, Westfälische Wilhelms-Universität Münster = University of Münster (WWU), Masaryk Memorial Cancer Institute (MMCI), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Université de Lausanne = University of Lausanne (UNIL)-Université de Lausanne = University of Lausanne (UNIL), Università degli studi della Campania 'Luigi Vanvitelli' = University of the Study of Campania Luigi Vanvitelli, Università degli Studi di Firenze = University of Florence (UniFI), Department of Molecular Medicine [Scripps Research Institute], The Scripps Research Institute [La Jolla, San Diego], Medical Research Council-Cardiff University, Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of California (UC), University of California (UC)-University of California (UC), Yale School of Medicine [New Haven, Connecticut] (YSM), Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], Martinez Rico, Clara, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, APH - Digital Health, Kas lab, Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Munn-Chernoff, M. A., Johnson, E. C., Chou, Y. -L., Coleman, J. R. I., Thornton, L. M., Walters, R. K., Yilmaz, Z., Baker, J. H., Hubel, C., Gordon, S., Medland, S. E., Watson, H. J., Gaspar, H. A., Bryois, J., Hinney, A., Leppa, V. M., Mattheisen, M., Ripke, S., Yao, S., Giusti-Rodriguez, P., Hanscombe, K. B., Adan, R. A. H., Alfredsson, L., Ando, T., Andreassen, O. A., Berrettini, W. H., Boehm, I., Boni, C., Boraska Perica, V., Buehren, K., Burghardt, R., Cassina, M., Cichon, S., Clementi, M., Cone, R. D., Courtet, P., Crow, S., Crowley, J. J., Danner, U. N., Davis, O. S. P., de Zwaan, M., Dedoussis, G., Degortes, D., Desocio, J. E., Dick, D. M., Dikeos, D., Dina, C., Dmitrzak-Weglarz, M., Docampo, E., Duncan, L. E., Egberts, K., Ehrlich, S., Escaramis, G., Esko, T., Estivill, X., Farmer, A., Favaro, A., Fernandez-Aranda, F., Fichter, M. M., Fischer, K., Focker, M., Foretova, L., Forstner, A. J., Forzan, M., Franklin, C. S., Gallinger, S., Giegling, I., Giuranna, J., Gonidakis, F., Gorwood, P., Gratacos Mayora, M., Guillaume, S., Guo, Y., Hakonarson, H., Hatzikotoulas, K., Hauser, J., Hebebrand, J., Helder, S. G., Herms, S., Herpertz-Dahlmann, B., Herzog, W., Huckins, L. M., Hudson, J. I., Imgart, H., Inoko, H., Janout, V., Jimenez-Murcia, S., Julia, A., Kalsi, G., Kaminska, D., Karhunen, L., Karwautz, A., Kas, M. J. H., Kennedy, J. L., Keski-Rahkonen, A., Kiezebrink, K., Kim, Y. -R., Klump, K. L., Knudsen, G. P. S., La Via, M. C., Le Hellard, S., Levitan, R. D., Li, D., Lilenfeld, L., Lin, B. D., Lissowska, J., Luykx, J., Magistretti, P. J., Maj, M., Mannik, K., Marsal, S., Marshall, C. R., Mattingsdal, M., Mcdevitt, S., Mcguffin, P., Metspalu, A., Meulenbelt, I., Micali, N., Mitchell, K., Monteleone, A. M., Monteleone, P., Nacmias, B., Navratilova, M., Ntalla, I., O'Toole, J. K., Ophoff, R. A., Padyukov, L., Palotie, A., Pantel, J., Papezova, H., Pinto, D., Rabionet, R., Raevuori, A., Ramoz, N., Reichborn-Kjennerud, T., Ricca, V., Ripatti, S., Ritschel, F., Roberts, M., Rotondo, A., Rujescu, D., Rybakowski, F., Santonastaso, P., Scherag, A., Scherer, S. W., Schmidt, U., Schork, N. J., Schosser, A., Seitz, J., Slachtova, L., Slagboom, P. E., Slof-Op't Landt, M. C. T., Slopien, A., Sorbi, S., Swiatkowska, B., Szatkiewicz, J. P., Tachmazidou, I., Tenconi, E., Tortorella, A., Tozzi, F., Treasure, J., Tsitsika, A., Tyszkiewicz-Nwafor, M., Tziouvas, K., van Elburg, A. A., van Furth, E. F., Wagner, G., Walton, E., Widen, E., Zeggini, E., Zerwas, S., Zipfel, S., Bergen, A. W., Boden, J. M., Brandt, H., Crawford, S., Halmi, K. A., Horwood, L. J., Johnson, C., Kaplan, A. S., Kaye, W. H., Mitchell, J., Olsen, C. M., Pearson, J. F., Pedersen, N. L., Strober, M., Werge, T., Whiteman, D. C., Woodside, D. B., Grove, J., Henders, A. K., Larsen, J. T., Parker, R., Petersen, L. V., Jordan, J., Kennedy, M. A., Birgegard, A., Lichtenstein, P., Norring, C., Landen, M., Mortensen, P. B., Polimanti, R., Mcclintick, J. N., Adkins, A. E., Aliev, F., Bacanu, S. -A., Batzler, A., Bertelsen, S., Biernacka, J. M., Bigdeli, T. B., Chen, L. -S., Clarke, T. -K., Degenhardt, F., Docherty, A. R., Edwards, A. C., Foo, J. C., Fox, L., Frank, J., Hack, L. M., Hartmann, A. M., Hartz, S. M., Heilmann-Heimbach, S., Hodgkinson, C., Hoffmann, P., Hottenga, J. -J., Konte, B., Lahti, J., Lahti-Pulkkinen, M., Lai, D., Ligthart, L., Loukola, A., Maher, B. S., Mbarek, H., Mcintosh, A. M., Mcqueen, M. B., Meyers, J. L., Milaneschi, Y., Palviainen, T., Peterson, R. E., Ryu, E., Saccone, N. L., Salvatore, J. E., Sanchez-Roige, S., Schwandt, M., Sherva, R., Streit, F., Strohmaier, J., Thomas, N., Wang, J. -C., Webb, B. T., Wedow, R., Wetherill, L., Wills, A. G., Zhou, H., Boardman, J. D., Chen, D., Choi, D. -S., Copeland, W. E., Culverhouse, R. C., Dahmen, N., Degenhardt, L., Domingue, B. W., Frye, M. A., Gaebel, W., Hayward, C., Ising, M., Keyes, M., Kiefer, F., Koller, G., Kramer, J., Kuperman, S., Lucae, S., Lynskey, M. T., Maier, W., Mann, K., Mannisto, S., Muller-Myhsok, B., Murray, A. D., Nurnberger, J. I., Preuss, U., Raikkonen, K., Reynolds, M. D., Ridinger, M., Scherbaum, N., Schuckit, M. A., Soyka, M., Treutlein, J., Witt, S. H., Wodarz, N., Zill, P., Adkins, D. E., Boomsma, D. I., Bierut, L. J., Brown, S. A., Bucholz, K. K., Costello, E. J., de Wit, H., Diazgranados, N., Eriksson, J. G., Farrer, L. A., Foroud, T. M., Gillespie, N. A., Goate, A. M., Goldman, D., Grucza, R. A., Hancock, D. B., Harris, K. M., Hesselbrock, V., Hewitt, J. K., Hopfer, C. J., Iacono, W. G., Johnson, E. O., Karpyak, V. M., Kendler, K. S., Kranzler, H. R., Krauter, K., Lind, P. A., Mcgue, M., Mackillop, J., Madden, P. A. F., Maes, H. H., Magnusson, P. K. E., Nelson, E. C., Nothen, M. M., Palmer, A. A., Penninx, B. W. J. H., Porjesz, B., Rice, J. P., Rietschel, M., Riley, B. P., Rose, R. J., Shen, P. -H., Silberg, J., Stallings, M. C., Tarter, R. E., Vanyukov, M. M., Vrieze, S., Wall, T. L., Whitfield, J. B., Zhao, H., Neale, B. M., Wade, T. D., Heath, A. C., Montgomery, G. W., Martin, N. G., Sullivan, P. F., Kaprio, J., Breen, G., Gelernter, J., Edenberg, H. J., Bulik, C. M., and Agrawal, A.
Subjects: Netherlands Twin Register (NTR), Alcoholism/genetics, Schizophrenia/genetics, [SDV]Life Sciences [q-bio], [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Medizin, Medicine (miscellaneous), Genome-wide association study, Alcohol use disorder, Anorexia nervosa, Linkage Disequilibrium, ddc:616.89, [SCCO]Cognitive science, 0302 clinical medicine, Risk Factors, Tobacco Use Disorder/genetics, Substance-Related Disorders/genetics, 0303 health sciences, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Factors de risc en les malalties, Bulimia nervosa, Feeding and Eating Disorders/genetics, eating disorders, genetic correlation, substance use, Tobacco Use Disorder, 3. Good health, Fenotip, [SDV] Life Sciences [q-bio], Psychiatry and Mental health, Alcoholism, Eating disorders, Phenotype, Schizophrenia, Drinking of alcoholic beverages, eating disorder, Consum d'alcohol, Major depressive disorder, medicine.symptom, Depressive Disorder, Major/genetics, eating disorders, genetic correlation, substance use, Clinical psychology, Substance abuse, Risk factors in diseases, Substance-Related Disorders, Polymorphism, Single Nucleotide, Article, Feeding and Eating Disorders, 03 medical and health sciences, SDG 3 - Good Health and Well-being, mental disorders, Genetics, medicine, Humans, Trastorns de la conducta alimentària, 030304 developmental biology, Genetic association, Pharmacology, Depressive Disorder, Major, Binge eating, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, [SCCO] Cognitive science, medicine.disease, Comorbidity, Twin study, 030227 psychiatry, Abús de substàncies, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, business, Genètica, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genome-Wide Association Study
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; qwith binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to −0.23; qs
Published: 2021
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12. Polygenic and Socioeconomic Contributions to Nicotine Use and Cardiometabolic Health in Early Mid-Life.

Author: Lippert AM, Corsi DJ, Kim R, Wedow R, Kim J, Taddess B, and Subramanian SV
Subjects: Humans, Male, Female, Adult, Longitudinal Studies, Adolescent, Body Mass Index, Socioeconomic Factors, United States epidemiology, Waist Circumference, Young Adult, Glycated Hemoglobin metabolism, White People genetics, White People statistics & numerical data, Life Style, Middle Aged, Tobacco Use epidemiology, Tobacco Use genetics, Vaping epidemiology, Cardiovascular Diseases genetics, Cardiovascular Diseases epidemiology, Nicotine, Black or African American genetics, Black or African American statistics & numerical data, White, Multifactorial Inheritance genetics
Abstract: Introduction: Early mid-life is marked by accumulating risks for cardiometabolic illness linked to health-risk behaviors like nicotine use. Identifying polygenic indices (PGI) has enriched scientific understanding of the cumulative genetic contributions to behavioral and cardiometabolic health, though few studies have assessed these associations alongside socioeconomic (SES) and lifestyle factors., Aims and Methods: Drawing on data from 2337 individuals from the United States participating in the National Longitudinal Study of Adolescent to Adult Health, the current study assesses the fraction of variance in five related outcomes-use of conventional and electronic cigarettes, body mass index (BMI), waist circumference, and glycosylated hemoglobin (A1c)-explained by PGI, SES, and lifestyle., Results: Regression models on African ancestry (AA) and European ancestry (EA) subsamples reveal that the fraction of variance explained by PGI ranges across outcomes. While adjusting for sex and age, PGI explained 3.5%, 2.2%, and 0% in the AA subsample of variability in BMI, waist circumference, and A1c, respectively (in the EA subsample these figures were 7.7%, 9.4%, and 1.3%). The proportion of variance explained by PGI in nicotine-use outcomes is also variable. Results further indicate that PGI and SES are generally complementary, accounting for more variance in the outcomes when modeled together versus separately., Conclusions: PGI are gaining attention in population health surveillance, but polygenic variability might not align clearly with health differences in populations or surpass SES as a fundamental cause of health disparities. We discuss future steps in integrating PGI and SES to refine population health prediction rules., Implications: Study findings point to the complementary relationship of PGI and socioeconomic indicators in explaining population variance in nicotine outcomes and cardiometabolic wellness. Population health surveillance and prediction rules would benefit from the combination of information from both polygenic and socioeconomic risks. Additionally, the risk for electronic cigarette use among users of conventional cigarettes may have a genetic component tied to the cumulative genetic propensity for heavy smoking. Further research on PGI for vaping is needed., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
Published: 2024
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13. The methodological and ethical concerns of genetic studies of same-sex sexual behavior.

Author: Ventresca C, Martschenko DO, Wedow R, Civelek M, Tabery J, Carlson J, Parker SCJ, and Ramos PS
Subjects: Humans, Male, Female, Homosexuality, Genome-Wide Association Study, Sexual Behavior
Abstract: Same-sex sexual behavior has long interested genetics researchers in part because, while there is evidence of heritability, the trait as typically defined is associated with fewer offspring. Investigations of this phenomenon began in the 1990s with linkage studies and continue today with the advent of genome-wide association studies. As this body of research grows, so does critical scientific and ethical review of it. Here, we provide a targeted overview of existing genetics studies on same-sex sexual behavior, highlight the ethical and scientific considerations of this nascent field, and provide recommendations developed by the authors to enhance social and ethical responsibility., Competing Interests: Declaration of interests R.W. is a research fellow at AnalytiXIN, which is a consortium of health-data organizations, industry partners and university partners in Indiana primarily funded through the Lilly Endowment, IU Health, and Eli Lilly and Company., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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14. Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation.

Author: Carey CE, Shafee R, Wedow R, Elliott A, Palmer DS, Compitello J, Kanai M, Abbott L, Schultz P, Karczewski KJ, Bryant SC, Cusick CM, Churchhouse C, Howrigan DP, King D, Davey Smith G, Neale BM, Walters RK, and Robinson EB
Subjects: Humans, United Kingdom, Male, Female, Social Class, Middle Aged, UK Biobank, Biological Specimen Banks, Phenotype
Abstract: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and health outcomes. In building a deeper understanding of ways in which constructs such as socioeconomic status, trauma, or physical activity are structured in the dataset, we emphasize the importance of considering the interwoven nature of the human phenome when evaluating public health patterns., (© 2024. The Author(s).)
Published: 2024
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15. Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci.

Author: Mignogna G, Carey CE, Wedow R, Baya N, Cordioli M, Pirastu N, Bellocco R, Malerbi KF, Nivard MG, Neale BM, Walters RK, and Ganna A
Subjects: Humans, Surveys and Questionnaires, Self Report, Genome-Wide Association Study, Genetic Loci
Abstract: Response to survey questionnaires is vital for social and behavioural research, and most analyses assume full and accurate response by participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behaviour across 109 questionnaire items in the UK Biobank (N = 360,628). Phenotypic factor scores for two participant-selected nonresponse answers, 'Prefer not to answer' (PNA) and 'I don't know' (IDK), each predicted participant nonresponse in follow-up surveys (incremental pseudo-R 2 = 0.056), even when controlling for education and self-reported health (incremental pseudo-R 2 = 0.046). After performing genome-wide association studies of our factors, PNA and IDK were highly genetically correlated with one another (r g = 0.73 (s.e. = 0.03)) and with education (r g,PNA = -0.51 (s.e. = 0.03); r g,IDK = -0.38 (s.e. = 0.02)), health (r g,PNA = 0.51 (s.e. = 0.03); r g,IDK = 0.49 (s.e. = 0.02)) and income (r g,PNA = -0.57 (s.e. = 0.04); r g,IDK = -0.46 (s.e. = 0.02)), with additional unique genetic associations observed for both PNA and IDK (P < 5 × 10 -8 ). We discuss how these associations may bias studies of traits correlated with item nonresponse and demonstrate how this bias may substantially affect genome-wide association studies. While the UK Biobank data are deidentified, we further protected participant privacy by avoiding exploring non-response behaviour to single questions, assuring that no information can be used to associate results with any particular respondents., (© 2023. The Author(s).)
Published: 2023
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16. Response to Comment on "Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior".

Author: Ganna A, Verweij KJH, Nivard MG, Maier R, Wedow R, Busch AS, Abdellaoui A, Guo S, Sathirapongsasuti JF, Lichtenstein P, Lundström S, Långström N, Auton A, Harris KM, Beecham GW, Martin ER, Sanders AR, Perry JRB, Neale BM, and Zietsch BP
Subjects: Humans, Genome-Wide Association Study, Sexual Behavior
Abstract: Hamer et al argue that the variable "ever versus never had a same-sex partner" does not capture the complexity of human sexuality. We agree and said so in our paper. But Hamer et al neglect to mention that we also reported follow-up analyses showing substantial overlap of the genetic influences on our main variable and on more nuanced measures of sexual behavior, attraction, and identity., (Copyright © 2021, American Association for the Advancement of Science.)
Published: 2021
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17. Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

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

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

Author: Kim R, Lippert AM, Wedow R, Jimenez MP, and Subramanian SV
Subjects: Adolescent, Black or African American genetics, Female, Genome-Wide Association Study, Humans, Longitudinal Studies, Male, Obesity epidemiology, Obesity etiology, United States epidemiology, White People genetics, Young Adult, Black or African American statistics & numerical data, Body Mass Index, Genetic Variation, Socioeconomic Factors, White People statistics & numerical data
Abstract: In light of recent findings on the small proportion of variance in body mass index (BMI) explained by shared environment, and growing interests in the role of genetic susceptibility, we assessed the relative contribution of socioeconomic status (SES) and genome-wide polygenic score for BMI to explaining variation in BMI. Our final analytic sample included 4,918 White and 1,546 Black individuals from the US National Longitudinal Study of Adolescent to Adult Health Wave IV (2007-2008) who had complete measures on BMI, demographics, SES, genetic data, and health behaviors. We used ordinary least-squares regression to assess variation in log(BMI) as a function of the aforementioned predictors, independently and mutually adjusted. All analyses were stratified by race/ethnicity in the main analysis, and further by sex. The age-adjusted variation in log(BMI) was 0.055 among Whites and 0.066 among Blacks. The contribution of SES and polygenic score ranged from less than1% to 6% and from 2% to 8%, respectively, and majority of the variation (87%-96%) in log(BMI) remained unexplained. Differential distribution of socioeconomic resources, stressors, and buffers may interact to produce systematically larger variation in vulnerable populations. More understanding of the contribution of biological, genetic, and environmental factors, as well as stochastic elements, in diverse phenotypic variance is needed in population health sciences., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Published: 2020
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20. Genome studies must account for history-Response.

Author: Ganna A, Verweij KJH, Nivard MG, Maier R, Wedow R, Busch AS, Abdellaoui A, Guo S, Sathirapongsasuti JF, Lichtenstein P, Lundström S, Långström N, Auton A, Harris KM, Beecham GW, Martin ER, Sanders AR, Perry JRB, Neale BM, and Zietsch BP
Subjects: Sequence Analysis, DNA, Genome, Informed Consent
Published: 2019
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21. Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior.

Author: Ganna A, Verweij KJH, Nivard MG, Maier R, Wedow R, Busch AS, Abdellaoui A, Guo S, Sathirapongsasuti JF, Lichtenstein P, Lundström S, Långström N, Auton A, Harris KM, Beecham GW, Martin ER, Sanders AR, Perry JRB, Neale BM, and Zietsch BP
Subjects: Datasets as Topic, Female, Genome-Wide Association Study, Humans, Male, Phenotype, Polymorphism, Single Nucleotide, United Kingdom, Homosexuality, Female genetics, Homosexuality, Male genetics, Quantitative Trait Loci
Abstract: Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for specific genes involved have been underpowered. We performed a genome-wide association study (GWAS) on 477,522 individuals, revealing five loci significantly associated with same-sex sexual behavior. In aggregate, all tested genetic variants accounted for 8 to 25% of variation in same-sex sexual behavior, only partially overlapped between males and females, and do not allow meaningful prediction of an individual's sexual behavior. Comparing these GWAS results with those for the proportion of same-sex to total number of sexual partners among nonheterosexuals suggests that there is no single continuum from opposite-sex to same-sex sexual behavior. Overall, our findings provide insights into the genetics underlying same-sex sexual behavior and underscore the complexity of sexuality., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
Published: 2019
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22. Author Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

Author: Turley P, Walters RK, Maghzian O, Okbay A, Lee JJ, Fontana MA, Nguyen-Viet TA, Wedow R, Zacher M, Furlotte NA, Magnusson P, Oskarsson S, Johannesson M, Visscher PM, Laibson D, Cesarini D, Neale BM, and Benjamin DJ
Abstract: In the version of the paper initially published, no competing interests were declared. The 'Competing interests' statement should have stated that B.M.N. is on the Scientific Advisory Board of Deep Genomics. The error has been corrected in the HTML and PDF versions of the article.
Published: 2019
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23. Publisher Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

Author: Turley P, Walters RK, Maghzian O, Okbay A, Lee JJ, Fontana MA, Nguyen-Viet TA, Wedow R, Zacher M, Furlotte NA, Magnusson P, Oskarsson S, Johannesson M, Visscher PM, Laibson D, Cesarini D, Neale BM, and Benjamin DJ
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019
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24. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

Author: Karlsson Linnér R, Biroli P, Kong E, Meddens SFW, Wedow R, Fontana MA, Lebreton M, Tino SP, Abdellaoui A, Hammerschlag AR, Nivard MG, Okbay A, Rietveld CA, Timshel PN, Trzaskowski M, Vlaming R, Zünd CL, Bao Y, Buzdugan L, Caplin AH, Chen CY, Eibich P, Fontanillas P, Gonzalez JR, Joshi PK, Karhunen V, Kleinman A, Levin RZ, Lill CM, Meddens GA, Muntané G, Sanchez-Roige S, Rooij FJV, Taskesen E, Wu Y, Zhang F, Auton A, Boardman JD, Clark DW, Conlin A, Dolan CC, Fischbacher U, Groenen PJF, Harris KM, Hasler G, Hofman A, Ikram MA, Jain S, Karlsson R, Kessler RC, Kooyman M, MacKillop J, Männikkö M, Morcillo-Suarez C, McQueen MB, Schmidt KM, Smart MC, Sutter M, Thurik AR, Uitterlinden AG, White J, Wit H, Yang J, Bertram L, Boomsma DI, Esko T, Fehr E, Hinds DA, Johannesson M, Kumari M, Laibson D, Magnusson PKE, Meyer MN, Navarro A, Palmer AA, Pers TH, Posthuma D, Schunk D, Stein MB, Svento R, Tiemeier H, Timmers PRHJ, Turley P, Ursano RJ, Wagner GG, Wilson JF, Gratten J, Lee JJ, Cesarini D, Benjamin DJ, Koellinger PD, and Beauchamp JP
Subjects: Case-Control Studies, Female, Genetics, Behavioral methods, Genome-Wide Association Study methods, Genotype, Humans, Male, Polymorphism, Single Nucleotide genetics, Behavior physiology, Genetic Loci genetics, Genetic Predisposition to Disease genetics
Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
Published: 2019
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25. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders.

Author: Walters RK, Polimanti R, Johnson EC, McClintick JN, Adams MJ, Adkins AE, Aliev F, Bacanu SA, Batzler A, Bertelsen S, Biernacka JM, Bigdeli TB, Chen LS, Clarke TK, Chou YL, Degenhardt F, Docherty AR, Edwards AC, Fontanillas P, Foo JC, Fox L, Frank J, Giegling I, Gordon S, Hack LM, Hartmann AM, Hartz SM, Heilmann-Heimbach S, Herms S, Hodgkinson C, Hoffmann P, Jan Hottenga J, Kennedy MA, Alanne-Kinnunen M, Konte B, Lahti J, Lahti-Pulkkinen M, Lai D, Ligthart L, Loukola A, Maher BS, Mbarek H, McIntosh AM, McQueen MB, Meyers JL, Milaneschi Y, Palviainen T, Pearson JF, Peterson RE, Ripatti S, Ryu E, Saccone NL, Salvatore JE, Sanchez-Roige S, Schwandt M, Sherva R, Streit F, Strohmaier J, Thomas N, Wang JC, Webb BT, Wedow R, Wetherill L, Wills AG, Boardman JD, Chen D, Choi DS, Copeland WE, Culverhouse RC, Dahmen N, Degenhardt L, Domingue BW, Elson SL, Frye MA, Gäbel W, Hayward C, Ising M, Keyes M, Kiefer F, Kramer J, Kuperman S, Lucae S, Lynskey MT, Maier W, Mann K, Männistö S, Müller-Myhsok B, Murray AD, Nurnberger JI, Palotie A, Preuss U, Räikkönen K, Reynolds MD, Ridinger M, Scherbaum N, Schuckit MA, Soyka M, Treutlein J, Witt S, Wodarz N, Zill P, Adkins DE, Boden JM, Boomsma DI, Bierut LJ, Brown SA, Bucholz KK, Cichon S, Costello EJ, de Wit H, Diazgranados N, Dick DM, Eriksson JG, Farrer LA, Foroud TM, Gillespie NA, Goate AM, Goldman D, Grucza RA, Hancock DB, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono W, Johnson EO, Kaprio JA, Karpyak VM, Kendler KS, Kranzler HR, Krauter K, Lichtenstein P, Lind PA, McGue M, MacKillop J, Madden PAF, Maes HH, Magnusson P, Martin NG, Medland SE, Montgomery GW, Nelson EC, Nöthen MM, Palmer AA, Pedersen NL, Penninx BWJH, Porjesz B, Rice JP, Rietschel M, Riley BP, Rose R, Rujescu D, Shen PH, Silberg J, Stallings MC, Tarter RE, Vanyukov MM, Vrieze S, Wall TL, Whitfield JB, Zhao H, Neale BM, Gelernter J, Edenberg HJ, and Agrawal A
Subjects: Alleles, Genome-Wide Association Study, Genotype, Humans, Phenotype, Alcoholism genetics, Genetic Predisposition to Disease, Mental Disorders genetics, Polymorphism, Single Nucleotide
Abstract: Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10 -13 ) and African ancestries (rs2066702; P = 2.2 × 10 -9 ). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Published: 2018
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26. Education, Smoking, and Cohort Change: Forwarding a Multidimensional Theory of the Environmental Moderation of Genetic Effects.

Author: Wedow R, Zacher M, Huibregtse BM, Harris KM, Domingue BW, and Boardman JD
Abstract: We introduce a genetic correlation by environment interaction model [(rG)xE] which allows for social environmental moderation of the genetic relationship between two traits. To empirically demonstrate the significance of the (rG)xE perspective, we use genome wide information from respondents of the Health and Retirement Study (HRS; n = 8,181; birth years 1920-1959) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,347; birth years 1974-1983) to examine whether the genetic correlation (rG) between education and smoking has increased over historical time. Genetic correlation estimates (rG HRS = -0.357; rG Add Health = -0.729) support this hypothesis. Using polygenic scores for educational attainment, we show that this is not due to latent indicators of intellectual capacity, and we highlight the importance of education itself as an explanation of the increasing genetic correlation. Analyses based on contextual variation the milieus of the Add Health respondents corroborate key elements of the birth cohort analyses. We argue that the increasing overlap with respect to genes associated with educational attainment and smoking is a fundamentally social process involving complex process of selection based on observable behaviors that may be linked to genotype.
Published: 2018
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27. Genetic analysis of social-class mobility in five longitudinal studies.

Author: Belsky DW, Domingue BW, Wedow R, Arseneault L, Boardman JD, Caspi A, Conley D, Fletcher JM, Freese J, Herd P, Moffitt TE, Poulton R, Sicinski K, Wertz J, and Harris KM
Subjects: Educational Status, Genetic Testing, Humans, Longitudinal Studies, Occupations, Siblings, Genome-Wide Association Study, Social Class, Social Mobility
Abstract: A summary genetic measure, called a "polygenic score," derived from a genome-wide association study (GWAS) of education can modestly predict a person's educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents' position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother's polygenic score predicted her child's attainment over and above the child's own polygenic score, suggesting parents' genetics can also affect their children's attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals' family-of-origin environments and their social mobility., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)
Published: 2018
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28. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.

Author: Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, Nguyen-Viet TA, Bowers P, Sidorenko J, Karlsson Linnér R, Fontana MA, Kundu T, Lee C, Li H, Li R, Royer R, Timshel PN, Walters RK, Willoughby EA, Yengo L, Alver M, Bao Y, Clark DW, Day FR, Furlotte NA, Joshi PK, Kemper KE, Kleinman A, Langenberg C, Mägi R, Trampush JW, Verma SS, Wu Y, Lam M, Zhao JH, Zheng Z, Boardman JD, Campbell H, Freese J, Harris KM, Hayward C, Herd P, Kumari M, Lencz T, Luan J, Malhotra AK, Metspalu A, Milani L, Ong KK, Perry JRB, Porteous DJ, Ritchie MD, Smart MC, Smith BH, Tung JY, Wareham NJ, Wilson JF, Beauchamp JP, Conley DC, Esko T, Lehrer SF, Magnusson PKE, Oskarsson S, Pers TH, Robinson MR, Thom K, Watson C, Chabris CF, Meyer MN, Laibson DI, Yang J, Johannesson M, Koellinger PD, Turley P, Visscher PM, Benjamin DJ, and Cesarini D
Subjects: Adult, Aged, Aged, 80 and over, Cohort Studies, Educational Status, Female, Genome-Wide Association Study methods, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Multifactorial Inheritance
Abstract: Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
Published: 2018
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29. Multi-trait analysis of genome-wide association summary statistics using MTAG.

Author: Turley P, Walters RK, Maghzian O, Okbay A, Lee JJ, Fontana MA, Nguyen-Viet TA, Wedow R, Zacher M, Furlotte NA, Magnusson P, Oskarsson S, Johannesson M, Visscher PM, Laibson D, Cesarini D, Neale BM, and Benjamin DJ
Subjects: Algorithms, Datasets as Topic statistics & numerical data, Depression epidemiology, Depression genetics, Diagnostic Self Evaluation, Genetic Association Studies methods, Genetic Association Studies statistics & numerical data, Health statistics & numerical data, Humans, Meta-Analysis as Topic, Neuroticism, Phenotype, Polymorphism, Single Nucleotide, Data Interpretation, Statistical, Genome-Wide Association Study methods, Genome-Wide Association Study statistics & numerical data, Multifactorial Inheritance, Quantitative Trait Loci genetics
Abstract: We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
Published: 2018
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30. Gender and genetic contributions to weight identity among adolescents and young adults in the U.S.

Author: Wedow R, Briley DA, Short SE, and Boardman JD
Subjects: Adolescent, Body Mass Index, Female, Gene-Environment Interaction, Humans, Male, Twin Studies as Topic, Twins, Dizygotic psychology, Twins, Monozygotic psychology, United States, Young Adult, Adolescent Behavior psychology, Body Weight, Gender Identity, Perception
Abstract: In this paper, we investigate the possibility that genetic variation contributes to self-perceived weight status among adolescents and young adults in the U.S. Using samples of identical and fraternal twins across four waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health) study, we calculate heritability estimates for objective body mass index (BMI) that are in line with previous estimates. We also show that perceived weight status is heritable (h(2) ∼ 0.47) and most importantly that this trait continues to be heritable above and beyond objective BMI (h(2) ∼ 0.25). We then demonstrate significant sex differences in the heritability of weight identity across the four waves of the study, where h(2)women = 0.39, 0.35, 0.40, and 0.50 for each wave, respectively, and h(2)men = 0.10, 0.10, 0.23, and 0.03. These results call for a deeper consideration of both identity and gender in genetics research., (Copyright © 2016 Elsevier Ltd. All rights reserved.)
Published: 2016
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31. Genome-Wide Estimates of Heritability for Social Demographic Outcomes.

Author: Domingue BW, Wedow R, Conley D, McQueen M, Hoffmann TJ, and Boardman JD
Subjects: Datasets as Topic, Genetic Variation, Humans, Models, Genetic, Genome-Wide Association Study methods, Quantitative Trait, Heritable
Abstract: An increasing number of studies that are widely used in the demographic research community have collected genome-wide data from their respondents. It is therefore important that demographers have a proper understanding of some of the methodological tools needed to analyze such data. This article details the underlying methodology behind one of the most common techniques for analyzing genome-wide data, genome-wide complex trait analysis (GCTA). GCTA models provide heritability estimates for health, health behaviors, or indicators of attainment using data from unrelated persons. Our goal was to describe this model, highlight the utility of the model for biodemographic research, and demonstrate the performance of this approach under modifications to the underlying assumptions. The first set of modifications involved changing the nature of the genetic data used to compute genetic similarities between individuals (the genetic relationship matrix). We then explored the sensitivity of the model to heteroscedastic errors. In general, GCTA estimates are found to be robust to the modifications proposed here, but we also highlight potential limitations of GCTA estimates.
Published: 2016
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31 results on '"Wedow, R"'

1. Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci

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

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

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

5. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences

6. Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences

7. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

8. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

9. Body size reference norms and subjective weight status: A gender and life course approach

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

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

12. Polygenic and Socioeconomic Contributions to Nicotine Use and Cardiometabolic Health in Early Mid-Life.

13. The methodological and ethical concerns of genetic studies of same-sex sexual behavior.

14. Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation.

15. Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci.

16. Response to Comment on "Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior".

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

18. A large-scale genome-wide association study meta-analysis of cannabis use disorder.

19. The Relative Contributions of Socioeconomic and Genetic Factors to Variations in Body Mass Index Among Young Adults.

20. Genome studies must account for history-Response.

21. Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior.

22. Author Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

23. Publisher Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

24. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

25. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders.

26. Education, Smoking, and Cohort Change: Forwarding a Multidimensional Theory of the Environmental Moderation of Genetic Effects.

27. Genetic analysis of social-class mobility in five longitudinal studies.

28. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.

29. Multi-trait analysis of genome-wide association summary statistics using MTAG.

30. Gender and genetic contributions to weight identity among adolescents and young adults in the U.S.

31. Genome-Wide Estimates of Heritability for Social Demographic Outcomes.

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31 results on '"Wedow, R"'

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