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

Author

Harold, Denise, Connolly, Siobhan, Riley, Brien P, Kendler, Kenneth S, McCarthy, Shane E, McCombie, William R, Richards, Alex, Owen, Michael J, O'Donovan, Michael C, Walters, James, Donnelly, Peter, Bates, Lesley, Barroso, Ines, Blackwell, Jenefer M, Bramon, Elvira, Brown, Matthew A, Casas, Juan P, Corvin, Aiden, Deloukas, Panos, Duncanson, Audrey, Jankowski, Janusz, Markus, Hugh S, Mathew, Christopher G, Palmer, Colin NA, Plomin, Robert, Rautanen, Anna, Sawcer, Stephen J, Trembath, Richard C, Viswanathan, Ananth C, Wood, Nicholas W, Spencer, Chris CA, Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Giannoulatou, Eleni, Hopkins, Lucinda, Pirinen, Matti, Pearson, Richard, Strange, Amy, Su, Zhan, Vukcevic, Damjan, Langford, Cordelia, Hunt, Sarah E, Edkins, Sarah, Gwilliam, Rhian, Blackburn, Hannah, Bumpstead, Suzannah J, Dronov, Serge, Gillman, Matthew, Gray, Emma, Hammond, Naomi, Jayakumar, Alagurevathi, McCann, Owen T, Liddle, Jennifer, Potter, Simon C, Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Ripke, Stephan, Neale, Benjamin M, Walters, James TR, Farh, Kai‐How, Holmans, Peter A, Lee, Phil, Bulik‐Sullivan, Brendan, Collier, David A, Huang, Hailiang, Pers, Tune H, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A, Begemann, Martin, Belliveau, Richard A, Bene, Judit, Bergen, Sarah E, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberley D, Chan, Raymond CK, and Chan, Ronald YL

Subjects
Biological Sciences, Genetics, Clinical Research, Schizophrenia, Brain Disorders, Human Genome, Prevention, Serious Mental Illness, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Adult, Case-Control Studies, Chromosome Mapping, DNA Copy Number Variations, Databases, Genetic, Exome, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Male, Middle Aged, Risk Factors, Sequence Analysis, DNA, Exome Sequencing, GWAS, IBD mapping, rare variants, Wellcome Trust Case Control Consortium 2, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Clinical Sciences, Neurosciences, Clinical sciences
Abstract

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

Published
2019

2. Analysis of shared heritability in common disorders of the brain

Author

Consortium, The Brainstorm, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Schott, Jonathan M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, and Cuenca-Leon, Ester

Subjects
Biological Sciences, Genetics, Biological Psychology, Health Sciences, Psychology, Clinical Research, Mental Health, Human Genome, Brain Disorders, Neurosciences, Mental Illness, 2.1 Biological and endogenous factors, Neurological, Mental health, Brain Diseases, Genetic Variation, Genome-Wide Association Study, Humans, Mental Disorders, Phenotype, Quantitative Trait, Heritable, Risk Factors, Brainstorm Consortium, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

3. Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Author

Consortium, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics, Ruderfer, Douglas M, Ripke, Stephan, McQuillin, Andrew, Boocock, James, Stahl, Eli A, Pavlides, Jennifer M Whitehead, Mullins, Niamh, Charney, Alexander W, Ori, Anil PS, Loohuis, Loes M Olde, Domenici, Enrico, Di Florio, Arianna, Papiol, Sergi, Kalman, Janos L, Trubetskoy, Vassily, Adolfsson, Rolf, Agartz, Ingrid, Agerbo, Esben, Akil, Huda, Albani, Diego, Albus, Margot, Alda, Martin, Alexander, Madeline, Alliey-Rodriguez, Ney, Als, Thomas D, Amin, Farooq, Anjorin, Adebayo, Arranz, Maria J, Awasthi, Swapnil, Bacanu, Silviu A, Badner, Judith A, Baekvad-Hansen, Marie, Bakker, Steven, Band, Gavin, Barchas, Jack D, Barroso, Ines, Bass, Nicholas, Bauer, Michael, Baune, Bernhard T, Begemann, Martin, Bellenguez, Celine, Belliveau, Richard A, Bellivier, Frank, Bender, Stephan, Bene, Judit, Bergen, Sarah E, Berrettini, Wade H, Bevilacqua, Elizabeth, Biernacka, Joanna M, Bigdeli, Tim B, Black, Donald W, Blackburn, Hannah, Blackwell, Jenefer M, Blackwood, Douglas HR, Pedersen, Carsten Bocker, Boehnke, Michael, Boks, Marco, Borglum, Anders D, Bramon, Elvira, Breen, Gerome, Brown, Matthew A, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Budde, Monika, Bulik-Sullivan, Brendan, Bumpstead, Suzannah J, Bunney, William, Burmeister, Margit, Buxbaum, Joseph D, Bybjerg-Grauholm, Jonas, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Cairns, Murray J, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Casas, Juan P, Casas, Miquel, Catts, Stanley V, Cervantes, Pablo, Chambert, Kimberley D, Chan, Raymond CK, Chen, Eric YH, Chen, Ronald YL, Cheng, Wei, Cheung, Eric FC, Chong, Siow Ann, Clarke, Toni-Kim, Cloninger, C Robert, Cohen, David, Cohen, Nadine, Coleman, Jonathan RI, Collier, David A, Cormican, Paul, Coryell, William, and Craddock, Nicholas

Subjects
Human Genome, Neurosciences, Serious Mental Illness, Bipolar Disorder, Biotechnology, Schizophrenia, Brain Disorders, Genetics, Mental Health, Mental health, Good Health and Well Being, Case-Control Studies, Genetic Loci, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Odds Ratio, Phenotype, Risk, White People, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Electronic address: douglas.ruderfer@vanderbilt.edu, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, bipolar disorder, polygenic risk, psychosis, schizophrenia, subphenotypes, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.

Published
2018

4. Analysis of shared heritability in common disorders of the brain.

Author

Brainstorm Consortium, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, Cuenca-Leon, Ester, and Furlotte, Nicholas

Subjects
Brainstorm Consortium, Humans, Brain Diseases, Risk Factors, Mental Disorders, Quantitative Trait, Heritable, Phenotype, Genetic Variation, Genome-Wide Association Study, Clinical Research, Neurosciences, Rare Diseases, Human Genome, Brain Disorders, Genetics, Mental Health, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

5. Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa

Author

Duncan, Laramie, Yilmaz, Zeynep, Gaspar, Helena, Walters, Raymond, Goldstein, Jackie, Anttila, Verneri, Bulik-Sullivan, Brendan, Ripke, Stephan, Thornton, Laura, Hinney, Anke, Daly, Mark, Sullivan, Patrick F, Zeggini, Eleftheria, Breen, Gerome, Bulik, Cynthia M, Gaspar, Héléna, Adan, Roger, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole, Aschauer, Harald, Baker, Jessica, Barrett, Jeffrey, Bencko, Vladimir, Bergen, Andrew, Berrettini, Wade, Birgegård, Andreas, Boni, Claudette, Perica, Vesna Boraska, Brandt, Harry, Burghardt, Roland, Carlberg, Laura, Cassina, Matteo, Cesta, Carolyn, Cichon, Sven, Clementi, Maurizio, Cohen-Woods, Sarah, Coleman, Joni, Cone, Roger, Courtet, Philippe, Crawford, Steven, Crow, Scott, Crowley, Jim, Danner, Unna, Davis, Oliver, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece, Dick, Danielle, Dikeos, Dimitris, Dina, Christian, Ding, Bo, Dmitrzak-Weglarz, Monika, Docampo, Elisa, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Espeseth, Thomas, Estivill, Xavier, Favaro, Angela, Fernández-Aranda, Fernando, Fichter, Manfred, Finan, Chris, Fischer, Krista, Floyd, James, Föcker, Manuel, Foretova, Lenka, Forzan, Monica, Fox, Caroline, Franklin, Christopher, Gaborieau, Valerie, Gallinger, Steven, Gambaro, Giovanni, Giegling, Ina, Gonidakis, Fragiskos, Gorwood, Philip, Gratacos, Monica, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine, Harrison, Rebecca, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske, Hendriks, Judith, Herms, Stefan, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, and Hilliard, Christopher

Subjects
Serious Mental Illness, Mental Health, Anorexia, Eating Disorders, Brain Disorders, Nutrition, Human Genome, Genetics, Prevention, Pediatric, Mental health, Anorexia Nervosa, Case-Control Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Eating Disorders Working Group of the Psychiatric Genomics Consortium, Diabetes, GWAS, Metabolism, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

ObjectiveThe authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes.MethodFollowing uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h2SNP]), partitioned heritability, and genetic correlations (rg) between anorexia nervosa and 159 other phenotypes.ResultsResults were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h2SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes.ConclusionsAnorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

Published
2017

6. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Author

Marshall, Christian R, Howrigan, Daniel P, Merico, Daniele, Thiruvahindrapuram, Bhooma, Wu, Wenting, Greer, Douglas S, Antaki, Danny, Shetty, Aniket, Holmans, Peter A, Pinto, Dalila, Gujral, Madhusudan, Brandler, William M, Malhotra, Dheeraj, Wang, Zhouzhi, Fajarado, Karin V Fuentes, Maile, Michelle S, Ripke, Stephan, Agartz, Ingrid, Albus, Margot, Alexander, Madeline, Amin, Farooq, Atkins, Joshua, Bacanu, Silviu A, Belliveau, Richard A, Bergen, Sarah E, Bertalan, Marcelo, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Bulik-Sullivan, Brendan, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Cairns, Murray J, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberley D, Cheng, Wei, Cloninger, C Robert, Cohen, David, Cormican, Paul, Craddock, Nick, Crespo-Facorro, Benedicto, Crowley, James J, Curtis, David, Davidson, Michael, Davis, Kenneth L, Degenhardt, Franziska, Del Favero, Jurgen, DeLisi, Lynn E, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H, Farh, Kai-How, Farrell, Martilias S, Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B, Friedman, Joseph I, Forstner, Andreas J, Fromer, Menachem, Genovese, Giulio, Georgieva, Lyudmila, Gershon, Elliot S, Giegling, Ina, Giusti-Rodríguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I, Gratten, Jacob, de Haan, Lieuwe, Hamshere, Marian L, Hansen, Mark, Hansen, Thomas, Haroutunian, Vahram, Hartmann, Annette M, Henskens, Frans A, Herms, Stefan, Hirschhorn, Joel N, Hoffmann, Per, Hofman, Andrea, Huang, Hailiang, Ikeda, Masashi, Joa, Inge, and Kähler, Anna K

Subjects
Serious Mental Illness, Human Genome, Schizophrenia, Genetics, Biotechnology, Prevention, Mental Health, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Mental health, Case-Control Studies, DNA Copy Number Variations, Female, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Risk Factors, Psychosis Endophenotypes International Consortium, CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

Published
2017

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

Author

Day, Felix R, Ruth, Katherine S, Thompson, Deborah J, Lunetta, Kathryn L, Pervjakova, Natalia, Chasman, Daniel I, Stolk, Lisette, Finucane, Hilary K, Sulem, Patrick, Bulik-Sullivan, Brendan, Esko, Tõnu, Johnson, Andrew D, Elks, Cathy E, Franceschini, Nora, He, Chunyan, Altmaier, Elisabeth, Brody, Jennifer A, Franke, Lude L, Huffman, Jennifer E, Keller, Margaux F, McArdle, Patrick F, Nutile, Teresa, Porcu, Eleonora, Robino, Antonietta, Rose, Lynda M, Schick, Ursula M, Smith, Jennifer A, Teumer, Alexander, Traglia, Michela, Vuckovic, Dragana, Yao, Jie, Zhao, Wei, Albrecht, Eva, Amin, Najaf, Corre, Tanguy, Hottenga, Jouke-Jan, Mangino, Massimo, Smith, Albert V, Tanaka, Toshiko, Abecasis, Gonçalo R, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Arndt, Volker, Arnold, Alice M, Barbieri, Caterina, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bernstein, Leslie, Bielinski, Suzette J, Blomqvist, Carl, Boerwinkle, Eric, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Borresen-Dale, Anne-Lise, Boutin, Thibaud S, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Burwinkel, Barbara, Campbell, Archie, Campbell, Harry, Chanock, Stephen J, Chapman, J Ross, Chen, Yii-Der Ida, Chenevix-Trench, Georgia, Couch, Fergus J, Coviello, Andrea D, Cox, Angela, Czene, Kamila, Darabi, Hatef, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Devilee, Peter, Dörk, Thilo, dos-Santos-Silva, Isabel, Dunning, Alison M, Eicher, John D, Fasching, Peter A, Faul, Jessica D, Figueroa, Jonine, Flesch-Janys, Dieter, Gandin, Ilaria, Garcia, Melissa E, García-Closas, Montserrat, Giles, Graham G, Girotto, Giorgia G, Goldberg, Mark S, González-Neira, Anna, Goodarzi, Mark O, Grove, Megan L, Gudbjartsson, Daniel F, Guénel, Pascal, Guo, Xiuqing, Haiman, Christopher A, Hall, Per, and Hamann, Ute

Subjects
Genetics, Biotechnology, Aging, Breast Cancer, Cancer, Human Genome, Contraception/Reproduction, 2.1 Biological and endogenous factors, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, Good Health and Well Being, Adult, Age Factors, BRCA1 Protein, Breast Neoplasms, DNA Repair, Female, Gene Regulatory Networks, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genomics, Genotype, Humans, Hypothalamus, Menopause, Middle Aged, Models, Genetic, Phenotype, Reproduction, Signal Transduction, PRACTICAL consortium, kConFab Investigators, AOCS Investigators, Generation Scotland, EPIC-InterAct Consortium, LifeLines Cohort Study, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Published
2015

8. Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Author

Vilhjálmsson, Bjarni J, Yang, Jian, Finucane, Hilary K, Gusev, Alexander, Lindström, Sara, Ripke, Stephan, Genovese, Giulio, Loh, Po-Ru, Bhatia, Gaurav, Do, Ron, Hayeck, Tristan, Won, Hong-Hee, Consortium, Schizophrenia Working Group of the Psychiatric Genomics, Neale, Benjamin M, Corvin, Aiden, Walters, James TR, Farh, Kai-How, Holmans, Peter A, Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A, Huang, Hailiang, Pers, Tune H, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A, Begemann, Martin, Belliveau, Richard A, Bene, Judit, Bergen, Sarah E, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberly D, Chan, Raymond CK, Chen, Ronald YL, Chen, Eric YH, Cheng, Wei, Cheung, Eric FC, Chong, Siow Ann, Cloninger, C Robert, Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J, Curtis, David, Davidson, Michael, Davis, Kenneth L, Degenhardt, Franziska, Del Favero, Jurgen, DeLisi, Lynn E, Demontis, Ditte, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Durmishi, Naser, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H, Farrell, Martilias S, Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B, Friedl, Marion, Friedman, Joseph I, Fromer, Menachem, Georgieva, Lyudmila, Gershon, Elliot S, Giegling, Ina, Giusti-Rodrguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I, Golimbet, Vera, Gopal, Srihari, Gratten, Jacob, and Grove, Jakob

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Schizophrenia, Mental Health, Brain Disorders, Serious Mental Illness, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Models, Theoretical, Multifactorial Inheritance, Multiple Sclerosis, Phenotype, Polymorphism, Single Nucleotide, Prognosis, Quantitative Trait Loci, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Published
2015

9. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Author

Bulik-Sullivan, Brendan K, Loh, Po-Ru, Finucane, Hilary K, Ripke, Stephan, Yang, Jian, Patterson, Nick, Daly, Mark J, Price, Alkes L, and Neale, Benjamin M

Subjects
Human Genome, Genetics, Computer Simulation, Genome, Human, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Regression Analysis, Sample Size, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Published
2015

10. Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases

Author

Gusev, Alexander, Lee, S Hong, Trynka, Gosia, Finucane, Hilary, Vilhjálmsson, Bjarni J, Xu, Han, Zang, Chongzhi, Ripke, Stephan, Bulik-Sullivan, Brendan, Stahl, Eli, Kähler, Anna K, Hultman, Christina M, Purcell, Shaun M, McCarroll, Steven A, Daly, Mark J, Pasaniuc, Bogdan, Sullivan, Patrick F, Neale, Benjamin M, Wray, Naomi R, Raychaudhuri, Soumya, Price, Alkes, Corvin, Aiden, Walters, James TR, Farh, Kai-How, Holmans, Peter A, Lee, Phil, Collier, David A, Huang, Hailiang, Pers, Tune H, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A, Begemann, Martin, Belliveau, Richard A, Bene, Judit, Bergen, Sarah E, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Børglum, Anders D, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberly D, Chan, Raymond CK, Chen, Ronald YL, Chen, Eric YH, Cheng, Wei, Cheung, Eric FC, Chong, Siow Ann, Cloninger, C Robert, Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J, Curtis, David, Davidson, Michael, Davis, Kenneth L, Degenhardt, Franziska, Del Favero, Jurgen, DeLisi, Lynn E, Demontis, Ditte, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Durmishi, Naser, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H, Farrell, Martilias S, Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B, Friedl, Marion, Friedman, Joseph I, Fromer, Menachem, Genovese, Giulio, and Georgieva, Lyudmila

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Prevention, Computer Simulation, Genetic Diseases, Inborn, Genetic Variation, Genome-Wide Association Study, Humans, Inheritance Patterns, Models, Genetic, Open Reading Frames, Regulatory Elements, Transcriptional, Schizophrenia Working Group of the Psychiatric Genomics Consortium, SWE-SCZ Consortium, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) from genotyped SNPs (1.6× enrichment, p = 1.0 × 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained

Published
2014

11. Biological insights from 108 schizophrenia-associated genetic loci

Author

Ripke, Stephan, Neale, Benjamin M, Corvin, Aiden, Walters, James TR, Farh, Kai-How, Holmans, Peter A, Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A, Huang, Hailiang, Pers, Tune H, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A, Begemann, Martin, Belliveau, Richard A Jr, Bene, Judit, Bergen, Sarah E, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberly D, Chan, Raymond CK, Chen, Ronald YL, Chen, Eric YH, Cheng, Wei, Cheung, Eric FC, Chong, Siow Ann, Cloninger, C Robert, Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J, Curtis, David, Davidson, Michael, Davis, Kenneth L, Degenhardt, Franziska, Del Favero, Jurgen, Demontis, Ditte, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Durmishi, Naser, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H, Farrell, Martilias S, Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B, Friedl, Marion, Friedman, Joseph I, Fromer, Menachem, Genovese, Giulio, Georgieva, Lyudmila, Giegling, Ina, Giusti-Rodriguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I, Golimbet, Vera, Gopal, Srihari, Gratten, Jacob, de Haan, Lieuwe, Hammer, Christian, Hamshere, Marian L, Hansen, Mark, Hansen, Thomas, Haroutunian, Vahram, Hartmann, Annette M, Henskens, Frans A, Herms, Stefan, Hirschhorn, Joel N, Hoffmann, Per, Hofman, Andrea, Hollegaard, Mads V, Hougaard, David M, Ikeda, Masashi, and Joa, Inge

Subjects
Human Genome, Brain Disorders, Serious Mental Illness, Prevention, Schizophrenia, Genetics, Neurosciences, Mental Health, 2.1 Biological and endogenous factors, Aetiology, Mental health, Alleles, Brain, Enhancer Elements, Genetic, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Glutamic Acid, Humans, Immunity, Multifactorial Inheritance, Mutation, Odds Ratio, Polymorphism, Single Nucleotide, Synaptic Transmission, Schizophrenia Working Group of the Psychiatric Genomics Consortium, General Science & Technology
Abstract

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

Published
2014

12. Genome-wide Association Analysis Identifies 14 New Risk Loci for Schizophrenia

Author

Ripke, Stephan, O'Dushlaine, Colm, Chambert, Kimberly, Moran, Jennifer L, Kähler, Anna K, Akterin, Susanne, Bergen, Sarah, Collins, Ann L, Crowley, James J, Fromer, Menachem, Kim, Yunjung, Lee, Sang Hong, Magnusson, Patrik KE, Sanchez, Nick, Stahl, Eli A, Williams, Stephanie, Wray, Naomi R, Xia, Kai, Bettella, Francesco, Børglum, Anders D, Bulik-Sullivan, Brendan K, Cormican, Paul, Craddock, Nick, de Leeuw, Christiaan, Durmishi, Naser, Gill, Michael, Golimbet, Vera, Hamshere, Marian L, Holmans, Peter, Hougaard, David M, Kendler, Kenneth S, Lin, Kuang, Morris, Derek W, Mors, Ole, Mortensen, Preben B, Neale, Benjamin M, O'Neill, Francis A, Owen, Michael J, Milovancevic, MilicaPejovic, Posthuma, Danielle, Powell, John, Richards, Alexander L, Riley, Brien P, Ruderfer, Douglas, Rujescu, Dan, Sigurdsson, Engilbert, Silagadze, Teimuraz, Smit, August B, Stefansson, Hreinn, Steinberg, Stacy, Suvisaari, Jaana, Tosato, Sarah, Verhage, Matthijs, Walters, James T, Bramon, Elvira, Corvin, Aiden P, O'Donovan, Michael C, Stefansson, Kari, Scolnick, Edward, Purcell, Shaun, McCarroll, Steve, Sklar, Pamela, Hultman, Christina M, and Sullivan, Patrick F

Subjects
schizophrenia, genetics, genome-wide association, meta-analysis
Abstract

Schizophrenia is a heritable disorder with substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases, 6,243 controls) followed by meta-analysis with prior schizophrenia GWAS (8,832 cases, 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls, and 581 trios). In total, 22 regions met genome-wide significance (14 novel and one previously implicated in bipolar disorder). The results strongly implicate calcium signaling in the etiology of schizophrenia, and include genome-wide significant results for CACNA1C and CACNB2 whose protein products interact. We estimate that ∼8,300 independent and predominantly common SNPs contribute to risk for schizophrenia and that these collectively account for most of its heritability. Common genetic variation plays an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this devastating disorder.

Published
2013
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