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Polygenic prediction of the phenome, across ancestry, in emerging adulthood

Published online by Cambridge University Press:  27 November 2017

Anna R. Docherty*
Affiliation:
Departments of Psychiatry & Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA Consortium for Families and Health Research, University of Utah, Salt Lake City, UT, USA
Arden Moscati
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
Danielle Dick
Affiliation:
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA Department of Human & Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
Jeanne E. Savage
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA Department of Health Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
Jessica E. Salvatore
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
Megan Cooke
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Fazil Aliev
Affiliation:
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA Department of Business, Karabuk University, Turkey
Ashlee A. Moore
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Alexis C. Edwards
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Brien P. Riley
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Daniel E. Adkins
Affiliation:
Departments of Psychiatry & Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA Consortium for Families and Health Research, University of Utah, Salt Lake City, UT, USA
Roseann Peterson
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Bradley T. Webb
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Silviu A. Bacanu
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Kenneth S. Kendler
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
*
Author for correspondence: Anna R. Docherty, E-mail: anna.docherty@utah.edu

Abstract

Background

Identifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.

Methods

This study examined a sample of emerging adults 18–22 years of age (N = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.

Results

Polygenic risk for schizophrenia (SZ) in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.

Conclusions

These results demonstrate the extensive impact of genetic risk for SZ, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

*

Both authors contributed equally to the manuscript

References

Akaike, H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716723.Google Scholar
Benjamini, Y and Hochberg, Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289300.Google Scholar
Bulik-Sullivan, B, Finucane, HK, Anttila, V, Gusev, A, Day, FR, Loh, PR, Duncan, L, Perry, JR, Patterson, N, Robinson, EB, Daly, MJ, Price, AL and Neale, BM (2015) An atlas of genetic correlations across human diseases and traits. Nature Genetics 47, 12361241.Google Scholar
Buysse, DJ, Reynolds, CF, Monk, TH, Berman, SR and Kupfer, DJ (1989) The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Research 28, 193213.Google Scholar
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013) Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 13711379.Google Scholar
Cuijpers, P, Smit, F, Penninx, BW, de Graaf, R, ten Have, M and Beekman, AT (2010) Economic costs of neuroticism: a population-based study. Archives of General Psychiatry 67, 10861093.Google Scholar
Derogatis, LR and Cleary, PA (1977) Confirmation of the dimensional structure of the SCL-90: a study in construct validation. Journal of Clinical Psychology 33, 981989.Google Scholar
Dick, DM, Nasim, A, Edwards, AC, Salvatore, JE, Cho, SB, Adkins, A, Meyers, J, Yan, J, Cooke, M, Clifford, J, Goyal, N, Halberstadt, L, Ailstock, K, Neale, Z, Opalesky, J, Hancock, L, Donovan, KK, Sun, C, Riley, B and Kendler, KS (2014) Spit for science: launching a longitudinal study of genetic and environmental influences on substance use and emotional health at a large US university. Fronteirs in Genetics 5, 47.Google Scholar
Docherty, AR, Moscati, A, Peterson, R, Edwards, AC, Bigdeli, TB, Adkins, DE, Bacanu, SA, Bigdeli, TB, Webb, BT, Flint, J and Kendler, KS (2016 a). SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE. Translational Psychiatry 6, e926.Google Scholar
Docherty, AR, Moscati, AA and Fanous, AH (2016 b). Cross-disorder psychiatric genomics: a review. Current Behavioral Neuroscience Reports 3, 256263.Google Scholar
Docherty, AR and Sponheim, SR (2008) Anhedonia as a phenotype for the Val158Met COMT polymorphism in relatives of patients with schizophrenia. Journal of Abnormal Psychology 117, 788798.Google Scholar
Docherty, AR and Sponheim, SR (2014) Anhedonia as an indicator of genetic liability to schizophrenia. In Ritsner, M (ed). Anhedonia: A Comprehensive Handbook. Dordecht: Springer, pp. 105120.Google Scholar
Docherty, AR, Sponheim, SR and Kerns, JG (2015) Self-reported affective traits and current affective experiences of biological relatives of people with schizophrenia. Schizophria Research 161, 340344.Google Scholar
Fanous, A, Gardner, C, Walsh, D and Kendler, KS (2001) Relationship between positive and negative symptoms of schizophrenia and schizotypal symptoms in nonpsychotic relatives. Archives of General Psychiatry 58, 669673.Google Scholar
Fisher, RA (1919) On the correlation between relatives on the supposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh: Earth and Environmental Science 52, 399433.Google Scholar
Gale, CR, Hagenaars, SP, Davies, G, Hill, WD, Liewald, DC, Cullen, B, Penninx, BW, Boomsma, DI, Pell, J, McIntosh, AM, Smith, DJ, Deary, IJ and Harris, SE (2016) Pleiotropy between neuroticism and physical and mental health: findings from 108038 men and women in UK biobank. Translational Psychiatry 6, e791.Google Scholar
Genetics of Personality Consortium, de Moor, MH, van den Berg, SM, Verweij, KJ, Krueger, RF, Luciano, M and Boomsma, DI (2015) Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry 72, 642650.Google Scholar
Gray, MJ, Litz, BT, Hsu, JL and Lombardo, TW (2004) Psychometric properties of the life events checklist. Assessment 11, 330341.Google Scholar
Hagenaars, SP, Harris, SE, Davies, G, Hill, WD, Liewald, DC, Ritchie, SJ, Marioni, RE, Fawns-Ritchie, C, Cullen, B, Malik, R, Worrall, BB, Sudlow, CL, Wardlaw, JM, Gallacher, J, Pell, J, McIntosh, AM, Smith, DJ, Gale, CR and Deary, IJ (2016) Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N = 112 151) and 24 GWAS consortia. Molecular Psychiatry 21, 16241632.Google Scholar
Jones, HJ, Stergiakouli, E, Tansey, KE, Hubbard, L, Heron, J, Cannon, M, Holmans, P, Lewis, G, Linden, DE, Jones, PB, Davey Smith, G, O'Donovan, MC, Owen, MJ, Walters, JT and Zammit, S (2016) Phenotypic manifestation of genetic risk for schizophrenia during adolescence in the general population. JAMA Psychiatry 73, 221228.Google Scholar
Kendler, KS (2016) The schizophrenia polygenic risk score: to what does it predispose in adolescence? JAMA Psychiatry 73, 193194.Google Scholar
Kendler, KS, Karkowski-Shuman, L and Walsh, D (1996) The risk for psychiatric illness in siblings of schizophrenics: the impact of psychotic and non-psychotic affective illness and alcoholism in parents. Acta Psychiatrica Scandinavica 94, 4955.Google Scholar
Kendler, KS and Myers, J (2010) The genetic and environmental relationship between major depression and the five-factor model of personality. Psychological Medicine 40, 801806.Google Scholar
Kessler, RC, Angermeyer, M, Anthony, JC, DEG, R, Demyttenaere, K, Gasquet, I, DEG, G, Gluzman, S, Gureje, O, Haro, JM, Kawakami, N, Karam, A, Levinson, D, Medina Mora, ME, Oakley Browne, MA, Posada-Villa, J, Stein, DJ, Adley Tsang, CH, Aguilar-Gaxiola, S, Alonso, J, Lee, S, Heeringa, S, Pennell, BE, Berglund, P, Gruber, MJ, Petukhova, M, Chatterji, S and Ustun, TB (2007): Lifetime prevalence and age-of-onset distributions of mental disorders in the world health organization's world mental health survey initiative. World Psychiatry 6, 168176.Google Scholar
Kessler, RC, Berglund, P, Demler, O, Jin, R, Merikangas, KR and Walters, EE (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Archives of General Psychiatry 62, 593602.Google Scholar
Kokkinos, PF and Fernhall, B (1999) Physical activity and high density lipoprotein cholesterol levels: what is the relationship? Sports Medicine 28, 307314.Google Scholar
Krapohl, E, Euesden, J, Zabaneh, D, Pingault, JB, Rimfeld, K, von Stumm, S, Dale, PS, Breen, G, O'Reilly, PF and Plomin, R (2015) Phenome-wide analysis of genome-wide polygenic scores. Molecular Psychiatry 21, 11881193.Google Scholar
Rader, DJ (2006) Molecular regulation of HDL metabolism and function: implications for novel therapies. The Journal of Clinical Investigation 116, 30903100.Google Scholar
Teslovich, TM, Musunuru, K, Smith, AV, Edmondson, AC, Stylianou, IM, Koseki, M, Pirruccello, JP, Ripatti, S, Chasman, DI, Willer, CJ, Johansen, CT, Fouchier, SW, Isaacs, A, Peloso, GM, Barbalic, M, Ricketts, SL, Bis, JC, Aulchenko, YS, Thorleifsson, G, Feitosa, MF, Chambers, J, Orho-Melander, M, Melander, O, Johnson, T, Li, X, Guo, X, Li, M, Shin Cho, Y, Jin Go, M, Jin Kim, Y, Lee, JY, Park, T, Kim, K, Sim, X, Twee-Hee Ong, R, Croteau-Chonka, DC, Lange, LA, Smith, JD, Song, K, Hua Zhao, J, Yuan, X, Luan, J, Lamina, C, Ziegler, A, Zhang, W, Zee, RY, Wright, AF, Witteman, JC, Wilson, JF, Willemsen, G, Wichmann, HE, Whitfield, JB, Waterworth, DM, Wareham, NJ, Waeber, G, Vollenweider, P, Voight, BF, Vitart, V, Uitterlinden, AG, Uda, M, Tuomilehto, J, Thompson, JR, Tanaka, T, Surakka, I, Stringham, HM, Spector, TD, Soranzo, N, Smit, JH, Sinisalo, J, Silander, K, Sijbrands, EJ, Scuteri, A, Scott, J, Schlessinger, D, Sanna, S, Salomaa, V, Saharinen, J, Sabatti, C, Ruokonen, A, Rudan, I, Rose, LM, Roberts, R, Rieder, M, Psaty, BM, Pramstaller, PP, Pichler, I, Perola, M, Penninx, BW, Pedersen, NL, Pattaro, C, Parker, AN, Pare, G, Oostra, BA, O'Donnell, CJ, Nieminen, MS, Nickerson, DA, Montgomery, GW, Meitinger, T, McPherson, R, McCarthy, MI, McArdle, W, Masson, D, Martin, NG, Marroni, F, Mangino, M, Magnusson, PK, Lucas, G, Luben, R, Loos, RJ, Lokki, ML, Lettre, G, Langenberg, C, Launer, LJ, Lakatta, EG, Laaksonen, R, Kyvik, KO, Kronenberg, F, Konig, IR, Khaw, KT, Kaprio, J, Kaplan, LM, Johansson, A, Jarvelin, MR, Janssens, AC, Ingelsson, E, Igl, W, Kees Hovingh, G, Hottenga, JJ, Hofman, A, Hicks, AA, Hengstenberg, C, Heid, IM, Hayward, C, Havulinna, AS, Hastie, ND, Harris, TB, Haritunians, T, Hall, AS, Gyllensten, U, Guiducci, C, Groop, LC, Gonzalez, E, Gieger, C, Freimer, NB, Ferrucci, L, Erdmann, J, Elliott, P, Ejebe, KG, Doring, A, Dominiczak, AF, Demissie, S, Deloukas, P, de Geus, EJ, de Faire, U, Crawford, G, Collins, FS, Chen, YD, Caulfield, MJ, Campbell, H, Burtt, NP, Bonnycastle, LL, Boomsma, DI, Boekholdt, SM, Bergman, RN, Barroso, I, Bandinelli, S, Ballantyne, CM, Assimes, TL, Quertermous, T, Altshuler, D, Seielstad, M, Wong, TY, Tai, ES, Feranil, AB, Kuzawa, CW, Adair, LS, Taylor, HA Jr., Borecki, IB, Gabriel, SB, Wilson, JG, Holm, H, Thorsteinsdottir, U, Gudnason, V, Krauss, RM, Mohlke, KL, Ordovas, JM, Munroe, PB, Kooner, JS, Tall, AR, Hegele, RA, Kastelein, JJ, Schadt, EE, Rotter, JI, Boerwinkle, E, Strachan, DP, Mooser, V, Stefansson, K, Reilly, MP, Samani, NJ, Schunkert, H, Cupples, LA, Sandhu, MS, Ridker, PM, Rader, DJ, van Duijn, CM, Peltonen, L, Abecasis, GR, Boehnke, M and Kathiresan, S (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707713.Google Scholar
van den Berg, SM, de Moor, MH, Verweij, KJ, Krueger, RF, Luciano, M, Arias Vasquez, A, Matteson, LK, Derringer, J, Esko, T, Amin, N, Gordon, SD, Hansell, NK, Hart, AB, Seppala, I, Huffman, JE, Konte, B, Lahti, J, Lee, M, Miller, M, Nutile, T, Tanaka, T, Teumer, A, Viktorin, A, Wedenoja, J, Abdellaoui, A, Abecasis, GR, Adkins, DE, Agrawal, A, Allik, J, Appel, K, Bigdeli, TB, Busonero, F, Campbell, H, Costa, PT, Smith, GD, Davies, G, de Wit, H, Ding, J, Engelhardt, BE, Eriksson, JG, Fedko, IO, Ferrucci, L, Franke, B, Giegling, I, Grucza, R, Hartmann, AM, Heath, AC, Heinonen, K, Henders, AK, Homuth, G, Hottenga, JJ, Iacono, WG, Janzing, J, Jokela, M, Karlsson, R, Kemp, JP, Kirkpatrick, MG, Latvala, A, Lehtimaki, T, Liewald, DC, Madden, PA, Magri, C, Magnusson, PK, Marten, J, Maschio, A, Mbarek, H, Medland, SE, Mihailov, E, Milaneschi, Y, Montgomery, GW, Nauck, M, Nivard, MG, Ouwens, KG, Palotie, A, Pettersson, E, Polasek, O, Qian, Y, Pulkki-Raback, L, Raitakari, OT, Realo, A, Rose, RJ, Ruggiero, D, Schmidt, CO, Slutske, WS, Sorice, R, Starr, JM, St Pourcain, B, Sutin, AR, Timpson, NJ, Trochet, H, Vermeulen, S, Vuoksimaa, E, Widen, E, Wouda, J, Wright, MJ, Zgaga, L, Porteous, D, Minelli, A, Palmer, AA, Rujescu, D, Ciullo, M, Hayward, C, Rudan, I, Metspalu, A, Kaprio, J, Deary, IJ, Raikkonen, K, Wilson, JF, Keltikangas-Jarvinen, L, Bierut, LJ, Hettema, JM, Grabe, HJ, Penninx, BW, van Duijn, CM, Evans, DM, Schlessinger, D, Pedersen, NL, Terracciano, A, McGue, M, Martin, NG and Boomsma, DI (2016) Meta-analysis of genome-wide association studies for extraversion: findings from the genetics of personality consortium. Behavior Genetics 46, 170182.Google Scholar
Vilhjalmsson, BJ, Yang, J, Finucane, HK, Gusev, A, Lindstrom, S, Ripke, S, Genovese, G, Loh, PR, Bhatia, G, Do, R, Hayeck, T, Won, HH, Kathiresan, S, Pato, M, Pato, C, Tamimi, R, Stahl, E, Zaitlen, N, Pasaniuc, B, Belbin, G, Kenny, EE, Schierup, MH, De Jager, P, Patsopoulos, NA, McCarroll, S, Daly, M, Purcell, S, Chasman, D, Neale, B, Goddard, M, Visscher, PM, Kraft, P, Patterson, N and Price, AL (2015) Modeling linkage disequilibrium increases accuracy of polygenic risk scores. American Journal of Human Genetics 97, 576592.Google Scholar
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