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1. Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Author

Andreassen, OA, Harbo, HF, Wang, Y, Thompson, WK, Schork, AJ, Mattingsdal, M, Zuber, V, Bettella, F, Ripke, S, Kelsoe, JR, Kendler, KS, O'Donovan, MC, Sklar, P, McEvoy, LK, Desikan, RS, Lie, BA, Djurovic, S, and Dale, AM

Subjects
Clinical Research, Neurosciences, Multiple Sclerosis, Prevention, Autoimmune Disease, Genetics, Schizophrenia, Bipolar Disorder, Brain Disorders, Human Genome, Mental Health, Serious Mental Illness, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Female, Follow-Up Studies, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, HLA Antigens, Humans, Male, Polymorphism, Single Nucleotide, false discovery rate, HLA region, multiple sclerosis, polygenic pleiotropy, schizophrenia, Psychiatric Genomics Consortium (PGC) Bipolar Disorder and Schizophrenia Work Groups, International Multiple Sclerosis Genetics Consortium, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21,856) and multiple sclerosis (MS) (n=43,879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16,731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.

Published
2015

2. Identification of common genetic risk variants for autism spectrum disorder

Author

Grove, J., Ripke, S., Als, T.D., Mattheisen, M., Walters, R.K., Won, H., Pallesen, J., Agerbo, E., Andreassen, O.A., Anney, R., Awashti, S., Belliveau, R., Bettella, F., Buxbaum, J.D., Bybjerg-Grauholm, J., Baekvad-Hansen, M., Cerrato, F., Chambert, K., Christensen, J.H., Churchhouse, C., Dellenvall, K., Demontis, D., Rubeis, S. de, Devlin, B., Djurovic, S., Dumont, A.L., Goldstein, J.I., Hansen, C.S., Hauberg, M.E., Hollegaard, M.V., Hope, S., Howrigan, D.P., Huang, H., Hultman, C.M., Klei, L., Maller, J., Martin, J., Martin, A.R., Moran, J.L., Nyegaard, M., Naeland, T., Palmer, D.S., Palotie, A., Pedersen, C.B., Pedersen, M.G., dPoterba, T., Poulsen, J.B., St Pourcain, B., Qvist, P., Rehnstrom, K., Reichenberg, A., Reichert, J., Robinson, E.B., Roeder, K., Roussos, P., Saemundsen, E., Sandin, S., Satterstrom, F.K., Smith, G.D., Stefansson, H., Steinberg, S., Stevens, C.R., Sullivan, P.F., Turley, P., Walters, G.B., Xu, X.Y., Stefansson, K., Geschwind, D.H., Nordentoft, M., Hougaard, D.M., Werge, T., Mors, O., Mortensen, P.B., Neale, B.M., Daly, M.J., Borglum, A.D., Wray, N.R., Trzaskowski, M., Byrne, E.M., Abdellaoui, A., Adams, M.J., Air, T.M., Andlauer, T.F.M., Bacanu, S.A., Beekman, A.T.F., Bigdeli, T.B., Binder, E.B., Blackwood, D.H.R., Bryois, J., Buttenschon, H.N., Cai, N., Castelao, E., Clarke, T.K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G.E., Davies, G., Deary, I.J., Degenhardt, F., Derks, E.M., Direk, N., Dolan, C.V., Dunn, E.C., Eley, T.C., Escott-Price, V., Kiadeh, F.F.H., Finucane, H.K., Forstner, A.J., Frank, J., Gaspar, H.A., Gill, M., Goes, F.S., Gordon, S.D., Hall, L.S., Hansen, T.F., Herms, S., Hickie, I.B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J.J., Ising, M., Jansen, R., Jorgenson, E., Knowles, J.A., Kohane, I.S., Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z., Li, Y., Lind, P.A., MacIntyre, D.J., MacKinnon, D.F., Maier, R.M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S.E., Mehta, D., Middeldorp, C.M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F.M., Montgomery, G.W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R., O'Reilly, P.F., Oskarsson, H., Owen, M.J., Painter, J.N., Peterson, R.E., Pettersson, E., Peyrot, W.J., Pistis, G., Posthuma, D., Quiroz, J.A., Rice, J.P., Riley, B.P., Rivera, M., Mirza, S.S., Schoevers, R., Schulte, E.C., Shen, L., Shi, J.X., Shyn, S.I., Sigurdsson, E., Sinnamon, G.C.B., Smit, J.H., Smith, D.J., Streit, F., Strohmaier, J., Tansey, K.E., Teismann, H., Teumer, A., Thompson, W., Thomson, P.A., Thorgeirsson, T.E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A.G., Umbricht, D., Auwera, S. van der, Hemert, A.M. van, Viktorin, A., Visscher, P.M., Wang, Y.P., Webb, B.T., Weinsheimer, S.M., Wellmann, J., Willemsen, G., Witt, S.H., Wu, Y., Xi, H.S., Yang, J., Zhang, F.T., Arolt, V., Baune, B.T., Berger, K., Boomsma, D.I., Cichon, S., Dannlowski, U., Geus, E.J.C. de, DePaulo, J.R., Domenici, E., Domschke, K., Esko, T., Grabe, H.J., Hamilton, S.P., Hayward, C., Heath, A.C., Kendler, K.S., Kloiber, S., Lewis, G., Li, Q.S., Lucae, S., Madden, P.A.F., Magnusson, P.K., Martin, N.G., McIntosh, A.M., Metspalu, A., Muller-Myhsok, B., Nothen, M.M., O'Donovan, M.C., Paciga, S.A., Pedersen, N.L., Penninx, B.W.J.H., Perlis, R.H., Porteous, D.J., Potash, J.B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T.G., Smoller, J.W., Tiemeier, H., Uher, R., Volzke, H., Weissman, M.M., Lewis, C.M., Levinson, D.F., Breen, G., Agee, M., Alipanahi, B., Auton, A., Bell, R.K., Bryc, K., Elson, S.L., Fontanillas, P., Furlotte, N.A., Hromatka, B.S., Huber, K.E., Kleinman, A., Litterman, N.K., McIntyre, M.H., Mountain, J.L., Noblin, E.S., Northover, C.A.M., Pitts, S.J., Sathirapongsasuti, J.F., Sazonova, O.V., Shelton, J.F., Shringarpure, S., Tung, J.Y., Vacic, V., Wilson, C.H., Psychiat Genomics Consortium, BUPGEN, 23andMe Re, Biological Psychology, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Adult Psychiatry, Psychiatry, Human genetics, Amsterdam Reproduction & Development (AR&D), VU University medical center, APH - Digital Health, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium, BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Me Research Team, Epidemiology, and Child and Adolescent Psychiatry / Psychology

Subjects
Male, Netherlands Twin Register (NTR), Multifactorial Inheritance, Autism Spectrum Disorder, Denmark, LD SCORE REGRESSION, LOCI, Genome-wide association study, DE-NOVO, 0302 clinical medicine, Polymorphism (computer science), Risk Factors, SYNAPTIC PLASTICITY, CELL-SURFACE, Child, Genetics, 0303 health sciences, HERITABILITY, Genetic Predisposition to Disease/genetics, 1184 Genetics, developmental biology, physiology, Polymorphism, Single Nucleotide/genetics, Phenotype, 3. Good health, Schizophrenia, Autism spectrum disorder, Child, Preschool, Genome-Wide Association Study/methods, Female, SIMONS SIMPLEX COLLECTION, Adolescent, Biology, NEURITE OUTGROWTH, Polymorphism, Single Nucleotide, behavioral disciplines and activities, Article, 03 medical and health sciences, mental disorders, medicine, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, SDG 2 - Zero Hunger, Multifactorial Inheritance/genetics, METAANALYSIS, 030304 developmental biology, Case-control study, Heritability, medicine.disease, Autism Spectrum Disorder/genetics, Case-Control Studies, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Published in final edited form as: Nat Genet. 2019 March ; 51(3): 431–444. doi:10.1038/s41588-019-0344-8., Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture, we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD., The iPSYCH project is funded by the Lundbeck Foundation (grant numbers R102-A9118 and R155-2014-1724) and the universities and university hospitals of Aarhus and Copenhagen. Genotyping of iPSYCH and PGC samples was supported by grants from the Lundbeck Foundation, the Stanley Foundation, the Simons Foundation (SFARI 311789 to MJD), and NIMH (5U01MH094432–02 to MJD). The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis on the GenomeDK HPC facility was supported by NIMH (1U01MH109514–01 to M O’Donovan and ADB). High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK HPC facility was provided by the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). Drs. S De Rubeis and JD Buxbaum were supported by NIH grants MH097849 (to JDB) and MH111661 (to JDB), and by the Seaver Foundation (to SDR and JDB). Dr J Martin was supported by the Wellcome Trust (grant no: 106047). O. Andreassen received funding from Research Council of Norway (#213694, #223273, #248980, #248778), Stiftelsen KG Jebsen and South-East Norway Health Authority. We thank the research participants and employees of 23andMe for making this work possible.

Published
2019
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3. Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer

Author

Zuber, V., Bettella, F., Witoelar, A.W., Andreassen, O.A., Mills, I.G., Urbanucci, A., Eeles, R.A., Easton, D.F., Kote-Jarai, Z., Al Olama, A.A., Benlloch, S., Muir, K., Giles, G.G., Wiklund, F., Grönberg, H., Haiman, C.A., Schleutker, J., Weischer, M., Travis, R.C., Neal, D., Pharoah, P., Khaw, K.T., Stanford, J.L., Blot, W.J., Thibodeau, S.N., Maier, C., Kibel, A.S., Cybulski, C., Cannon-Albright, L., Brenner, H., Park, J., Kaneva, R., Batra, J., Teixeira, M.R., Pandha, H., Chenevix-Trench, G., Humphreys, M.K., Hung, R.J., Han, Y., Brennan, P., Bickeböller, H., Rosenberger, A., Houlston, R.S., Caporaso, N., Landi, M.T., Heinrich, J., Risch, A., Wu, X., Ye, Y., Christiani, D.C., Amos, C.I., Michailidou, K., Bolla, M.K., Wang, Q., Berchuck, A., Antoniou, A.C., McGuffog, L., Couch, F.J., Offit, K., Dennis, J., Dunning, A.M., Lee, A., Dicks, E., Luccarini, C., Benítez, J., González-Neira, A., Simard, J., Tessier, D.C., Bacot, F., Vincent, D., Laboissiere, S., and Wrightson, R

Subjects
Male, Quantitative Trait Loci, Breast Neoplasms, Cell Cycle Proteins, Brd4, Breast Cancer Risk, Chromatin, Functional Annotation, Genome-wide Association Studies, Prostate Cancer Risk, Risk Loci, Schizophrenia, Snps, Super-enhancer, Genome-wide association studies, Polymorphism, Single Nucleotide, Epigenesis, Genetic, Histones, breast cancer risk, SDG 3 - Good Health and Well-being, super-enhancer, Genetics, Journal Article, Humans, Genetic Predisposition to Disease, Risk loci, Binding Sites, Chromosome Mapping, Computational Biology, Nuclear Proteins, Prostatic Neoplasms, Functional annotation, Prostate cancer risk, schizophrenia, Gene Expression Regulation, Neoplastic, Enhancer Elements, Genetic, Organ Specificity, Receptors, Androgen, BRD4, Female, Research Article, SNPs, Genome-Wide Association Study, Protein Binding, Transcription Factors, Biotechnology
Abstract

Background Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs. Results Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia. Conclusions This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3620-y) contains supplementary material, which is available to authorized users.

Published
2018
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4. Genome-wide Pleiotropy Between Parkinson Disease and Autoimmune Diseases

Author

Witoelar, A.W., Jansen, I.E., Wang, Y., Desikan, R.S., Gibbs, J.R., Blauwendraat, C., Thompson, W.K., Hernandez, D.G., Djurovic, S., Schork, A.J., Bettella, F., Ellinghaus, D., Franke, A., Lie, B.A., McEvoy, L.K., Karlsen, T.H., Lesage, S., Morris, H.R., Brice, A., Wood, N.W., Heutink, P., Hardy, J., Singleton, A.B., Dale, A.M., Gasser, T., Andreassen, O.A., Sharma, M., Nalls, M.A., Plagnol, V., Sheerin, U.M., Saad, M., Simon-Sanchez, J., Schulte, C., Sveinbjörnsdóttir, S., Arepalli, S., Barker, R.A., Ben-Shlomo, Y., Berendse, H.W., Berg, D., Bhatia, K.P., de Bie, R.M.A., Biffi, A., Bloem, B., Bochdanovits, Z., Bonin, M., Bras, J.M., Brockmann, K., Brooks, J.M., Burn, D.J., Majounie, E., Illig, T., Lichtner, P., Weale, M.E., Neurology, Amsterdam Neuroscience - Neurodegeneration, Human genetics, Hu, M, ANS - Neurodegeneration, ANS - Amsterdam Neuroscience, Intensive Care Medicine, AII - Inflammatory diseases, ANS - Neuroinfection & -inflammation, Graduate School, ACS - Amsterdam Cardiovascular Sciences, and APH - Aging & Later Life

Subjects
0301 basic medicine, Aging, genetics [Autoimmune Diseases], genetics [Colitis, Ulcerative], Ulcerative, Genome-wide association study, Disease, Neurodegenerative, North American Brain Expression Consortium, Bioinformatics, Arthritis, Rheumatoid, International Parkinson’s Disease Genomics Consortium (IPDGC), 0302 clinical medicine, Crohn Disease, genetics [Parkinson Disease], Risk Factors, Pleiotropy, Rheumatoid, Pleiotropism, 2.1 Biological and endogenous factors, Medicine, genetics [Celiac Disease], Aetiology, Original Investigation, Parkinson's Disease, Genetic Pleiotropy, Parkinson Disease, Colitis, LRRK2, International Parkinson’s Disease Genomics Consortium, Neurological, Cognitive Sciences, Type 1, Biotechnology, genetics [Crohn Disease], Multiple Sclerosis, genetics [Arthritis, Rheumatoid], Clinical Sciences, Human leukocyte antigen, genetics [Psoriasis], Autoimmune Disease, Autoimmune Diseases, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Diabetes Mellitus, Genetics, Humans, Psoriasis, Genetic Predisposition to Disease, ddc:610, Genetic association, Neurology & Neurosurgery, North American Brain Expression Consortium (NABEC), business.industry, Arthritis, Prevention, Inflammatory and immune system, Human Genome, Inflammatory Bowel Disease, genetics [Multiple Sclerosis], Neurosciences, genetics [Diabetes Mellitus, Type 1], Brain Disorders, Celiac Disease, Diabetes Mellitus, Type 1, 030104 developmental biology, Genetic Loci, and United Kingdom Brain Expression Consortium (UKBEC) Investigators, Colitis, Ulcerative, Neurology (clinical), Digestive Diseases, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Importance Recent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS era provides an opportunity for cross-phenotype analyses between different complex phenotypes. Objectives To test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach. Design, Setting, and Participants Using the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017. Main Outcomes and Measures The primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases. Results Genome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK , HLA-DRB5 , LRRK2 , and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA , LRRK2 , MAPT , TRIM10 , and SE TD1A in PD. Among the novel genes discovered, WNT3 , KANSL1 , CRHR1 , BOLA2 , and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes. Conclusions and Relevance The study findings provide novel mechanistic insights into PD and autoimmune diseases and identify a common genetic pathway between these phenotypes. The results may have implications for future therapeutic trials involving anti-inflammatory agents.

Published
2017
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5. Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Author

Ripke, S, O'Dushlaine, C, Chambert, K, Moran, Jl, Kähler, Ak, Akterin, S, Bergen, Se, Collins, Al, Crowley, Jj, Fromer, M, Kim, Y, Lee, Sh, Magnusson, Pk, Sanchez, N, Stahl, Ea, Williams, S, Wray, Nr, Xia, K, Bettella, F, Borglum, Ad, Bulik Sullivan, Bk, Cormican, P, Craddock, N, Leeuw, De, C, Durmishi, N, Gill, M, Golimbet, V, Hamshere, Ml, Holmans, P, Hougaard, Dm, Kendler, Ks, Lin, K, Morris, Dw, Mors, O, Mortensen, Pb, Neale, Bm, O'Neill, Fa, Owen, Mj, Milovancevic, Mp, Posthuma, D, Powell, J, Richards, Al, Riley, Bp, Ruderfer, D, Rujescu, D, Sigurdsson, E, Silagadze, T, Smit, Ab, Stefansson, H, Steinberg, S, Suvisaari, J, Tosato, Sarah, Verhage, M, Walters, Jt, Multicenter Genetic Studies of Schizophrenia Consortium, Levinson, Df, Gejman, Pv, Laurent, C, Mowry, Bj, O'Donovan, Mc, Pulver, Ae, Schwab, Sg, Wildenauer, Db, Dudbridge, F, Shi, J, Albus, M, Alexander, M, Campion, D, Cohen, D, Dikeos, D, Duan, J, Eichhammer, P, Godard, S, Hansen, M, Lerer, Fb, Liang, Ky, Maier, W, Mallet, J, Nertney, Da, Nestadt, G, Norton, N, Papadimitriou, Gn, Ribble, R, Sanders, Ar, Silverman, Jm, Walsh, D, Williams, Nm, Wormley, B, Psychosis Endophenotypes International Consortium, Arranz, Mj, Bakker, S, Bender, S, Bramon, E, Collier, D, Crespo Facorro, B, Hall, J, Iyegbe, C, Jablensky, A, Kahn, Rs, Kalaydjieva, L, Lawrie, S, Lewis, Cm, Linszen, Dh, Mata, I, Mcintosh, A, Murray, Rm, Ophoff, Ra, Van, Os, J, Walshe, M, Weisbrod, M, Wiersma, D, Wellcome Trust Case Control Consortium 2, Donnelly, P, Barroso, I, Blackwell, Jm, Brown, Ma, Casas, Jp, Corvin, Ap, Deloukas, P, Duncanson, A, Jankowski, J, Markus, Hs, Mathew, Cg, Palmer, Cn, Plomin, R, Rautanen, A, Sawcer, Sj, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cc, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, Rd, Strange, A, Su, Z, Vukcevic, D, Langford, C, Hunt, Se, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Tashakkori Ghanbaria, A, Waller, Mj, Weston, P, Widaa, S, Whittaker, P, Mccarthy, Mi, Stefansson, K, Scolnick, E, Purcell, S, Mccarroll, Sa, Sklar, P, Hultman, Cm, Sullivan, P. F., Functional Genomics, Molecular and Cellular Neurobiology, AIMMS, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease, Adult Psychiatry, Ripke, Stephan, O'Dushlaine, Colm, Chambert, Kimberly, Moran, Jennifer L, Lee, Sang Hong, Sullivan, Patrick F, Multicenter Genetic Studies of Schizophrenia Consortium, Psychosis Endophenotypes International Consortium, Wellcome Trust Case Control Consortium 2, Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA 02114 USA Broad Inst MIT & Harvard, Stanley Ctr Psychiat Res, Cambridge, MA USA Univ N Carolina, Dept Genet, Chapel Hill, NC 27515 USA Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden Oslo Univ Hosp, Div Mental Hlth & Addict, Oslo, Norway Icahn Sch Med Mt Sinai, Dept Psychiat, Div Psychiat Genom, New York, NY USA Univ Queensland, Queensland Brain Inst, Brisbane, Qld, Australia Univ N Carolina, Dept Psychiat, Chapel Hill, NC USA deCODE Genet, Reykjavik, Iceland Aarhus Univ Hosp, Risskov, Denmark Aarhus Univ, Ctr Integrat Sequencing iSEQ, Aarhus, Denmark Lundbeck Fdn Initiat Integrat Psychiat Res iPSYCH, Aarhus, Denmark Lundbeck Fdn Initiat Integrat Psychiat Res iPSYCH, Copenhagen, Denmark Univ Dublin Trinity Coll, Dept Psychiat, Dublin 2, Ireland Cardiff Univ, Sch Med, Ctr Psychiat Genet & Genom, MRC, Cardiff CF10 3AX, S Glam, Wales Vrije Univ Amsterdam, Ctr Neurogen & Cognit Res, Dept Funct Genom, Amsterdam, Netherlands Vrije Univ Amsterdam Med Ctr, Amsterdam, Netherlands Radboud Univ Nijmegen, Inst Comp & Informat Sci, NL-6525 ED Nijmegen, Netherlands Univ Clin Psychiat, Dept Child & Adolescent Psychiat, Skopje, Macedonia Univ Dublin Trinity Coll, Neuropsychiat Genet Res Grp, Dublin 2, Ireland Russian Acad Med Sci, Mental Hlth Res Ctr, Moscow 109801, Russia Statens Serum Inst, DK-2300 Copenhagen, Denmark Virginia Commonwealth Univ, Dept Psychiat, Richmond, VA USA Virginia Commonwealth Univ, Virginia Inst Psychiat & Behav Genet, Richmond, VA USA Kings Coll London, Inst Psychiat, London, England Aarhus Univ Hosp, Ctr Psychiat Res, Risskov, Denmark Aarhus Univ, Natl Ctr Register Based Res, Aarhus, DenmarkQueens Univ Belfast, Ctr Publ Hlth, Belfast, Antrim, North Ireland Univ Belgrade, Fac Med, Belgrade, Serbia Erasmus Univ, Med Ctr, Dept Child & Adolescent Psychiat, Rotterdam, Netherlands Kings Coll London, Dept Neurosci, London, England Virginia Commonwealth Univ, Dept Human & Mol Genet, Richmond, VA USA Univ Halle, Dept Psychiat, Halle, Germany Univ Munich, Dept Psychiat, D-80539 Munich, Germany Univ Iceland, Dept Psychiat, Reykjavik, Iceland Landspitali University Hospital Reykjavik, Iceland Tbilisi State Univ, Dept Psychiat, GE-380086 Tbilisi, Rep of Georgia Vrije Univ Amsterdam, Ctr Neurogen & Cognit Res, Amsterdam, Netherlands Vrije Univ Amsterdam, Dept Mol & Cellular Neurosci, Amsterdam, Netherlands Natl Inst Hlth & Welf, Mental Hlth & Subst Abuse Serv, Helsinki, Finland Univ Verona, Sect Psychiat, I-37100 Verona, Italy UCL, Inst Cognit Neurosci, London, England UCL, Mental Hlth Sci Unit, London, England Massachusetts Gen Hosp, Psychiat & Neurodev Genet Unit, Boston, MA 02114 USA Harvard Univ, Sch Med, Dept Genet, Boston, MA USA, Child and Adolescent Psychiatry / Psychology, Psychiatrie & Neuropsychologie, RS: MHeNs School for Mental Health and Neuroscience, Human genetics, NCA - Brain mechanisms in health and disease, and NCA - Neurobiology of mental health

Subjects
Male, Candidate gene, SNP, Single-nucleotide polymorphism, Genome-wide association study, Disease, Biology, heritability, neuronal calcium signaling, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Genetics, medicine, Humans, GWAS, Genetic Predisposition to Disease, Bipolar disorder, 030304 developmental biology, Genetic association, Sweden, Genetics & Heredity, 0303 health sciences, medicine.disease, 3. Good health, genome sequencing, schizophrenia, Schizophrenia, Meta-analysis, Case-Control Studies, genetic variation, Female, genome-wide scan, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field. Schizophrenia is an idiopathic mental disorder with a heritable component and a 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 and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder. NIMH R01 MH077139 R01 MH095034 Stanley Center for Psychiatric Research Sylvan Herman Foundation Friedman Brain Institute at the Mount Sinai School of Medicine Karolinska Institutet, Karolinska University Hospital Swedish Research Council Swedish County Council Soderstrom Konigska Foundation Netherlands Scientific Organization NWO 645-000-003 info:eu-repo/grantAgreement/EC/FP7/223423 Danish Strategic Research Council H. Lundbeck A/S Faculty of Health Sciences at Aarhus University Lundbeck Foundation Stanley Research Foundation Wellcome Trust 085475/B/08/Z 085475/Z/08/Z

Published
2013
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6. Replication and meta-analysis of common variants identifies a genome-wide significant locus in migraine.

Author

Esserlind, A.‐L., Christensen, A. F., Le, H., Kirchmann, M., Hauge, A. W., Toyserkani, N. M., Hansen, T., Grarup, N., Werge, T., Steinberg, S., Bettella, F., Stefansson, H., and Olesen, J.

Subjects
MIGRAINE, ETIOLOGY of diseases, MIGRAINE aura, META-analysis, REPLICATION (Experimental design), GENETICS
Abstract

Background and purpose Genetic factors contribute to the aetiology of the prevalent form of migraine without aura ( MO) and migraine with typical aura ( MTA). Due to the complex inheritance of MO and MTA, the genetic background is still not fully established. In a population-based genome-wide association study by Chasman et al. ( Nat Genet 2011: 43: 695-698), three common variants were found to confer risk of migraine at a genome-wide significant level ( P < 5 × 10−8). We aimed to evaluate the top association single nucleotide polymorphisms ( SNPs) from the discovery set by Chasman et al. in a primarily clinic-based Danish and Icelandic cohort. Methods The top association SNPs were assessed in 2523 cases and 38 170 controls, and a meta-analysis was performed, combining the discovery set with all the follow-up studies. Finally the confirmed SNPs were assessed in a genotype-phenotype analysis. Results Two out of three SNPs that showed genome-wide significant associations in the previous study: rs10166942 (near TRPM8) and rs11172113 (in LRP1) were significantly associated with migraine in the present study. The meta-analysis confirmed the previous three genome-wide significant associated SNPs (rs2651899, rs10166942 and rs11172113) to confer risk of migraine. In addition, the C-allele of rs2078371 (near TSPAN-2) also reached genome-wide significance for association with migraine [ OR = 1.14; CI = (1.09-1.20); P = 2.55 × 10−8]. Conclusion TSPAN-2 encodes an integral membrane protein involved in oligodendrogenesis. This new finding supports the plausible implication of neuroglia in the pathophysiology of MO and MTA. [ABSTRACT FROM AUTHOR]

Published
2013
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7. MicroRNAs enrichment in GWAS of complex human phenotypes

Author

Goulart, LF, Bettella, F, Sønderby, IE, Schork, AJ, Thompson, WK, Mattingsdal, M, Steen, VM, Zuber, V, Wang, Y, Dale, AM, Andreassen, OA, and Djurovic, S

Subjects
Genome-wide association study, Binding Sites, Genotype, Genome, Human, Genomic enrichment, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Lipoproteins, LDL, MicroRNAs, Phenotype, Crohn Disease, Databases, Genetic, Schizophrenia, Genetics, Humans, Polygenic, Conditional false discovery rate, Research Article, miRNA, Biotechnology
Abstract

Background The genotype information carried by Genome-wide association studies (GWAS) seems to have the potential to explain more of the ‘missing heritability’ of complex human phenotypes, given improved statistical approaches. Several lines of evidence support the involvement of microRNA (miRNA) and other non-coding RNA in complex human traits and diseases. We employed a novel, genetic annotation-informed enrichment method for GWAS that captures more polygenic effects than standard GWAS analysis, to investigate if miRNA-tagging Single Nucleotide Polymorphisms (SNPs) are enriched of associations with 15 complex human phenotypes. We then leveraged the enrichment using a conditional False Discovery Rate (condFDR) approach to assess any improvement in the detection of individual miRNA SNPs associated with the disorders. Results We found SNPs tagging miRNA transcription regions to be significantly enriched of associations with 10 of 15 phenotypes. The enrichment remained significant after controlling for affiliation to other genomic categories, and was confirmed by replication. Albeit only nominally significant, enrichment was found also in miRNA binding sites for 10 phenotypes out of 15. Leveraging the enrichment in the condFDR framework, we observed a 2-4-fold increase in discovery of SNPs tagging miRNA regions. Conclusions Our results suggest that miRNAs play an important role in the polygenic architecture of complex human disorders and traits, and therefore that miRNAs are a genomic category that can and should be used to improve gene discovery. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1513-5) contains supplementary material, which is available to authorized users.

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8. Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment

Author

Le Hellard S, Wang Y, Witoelar A, Verena Zuber, Bettella F, Hugdahl K, Espeseth T, Vm, Steen, Melle I, Desikan R, Aj, Schork, Wk, Thompson, Am, Dale, Djurovic S, Oa, Andreassen, and Schizophrenia Working Group of the Psychiatric Genomics Consortium

Subjects
Adult, Male, Multifactorial Inheritance, Aptitude, Basic Behavioral and Social Science, Medical and Health Sciences, pleiotropy, Behavioral and Social Science, Genetics, Humans, GWAS, 2.1 Biological and endogenous factors, Aetiology, Polymorphism, Psychiatry, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Human Genome, Psychology and Cognitive Sciences, Single Nucleotide, Serious Mental Illness, Brain Disorders, conditional FDR, Mental Health, Genetic Loci, Schizophrenia, Educational Status, Female, Genome-Wide Association Study, Biotechnology
Abstract

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold

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9. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group

Author

Sophia I. Thomopoulos, Julian A Pineda-Zapata, Ronny Redlich, Bartholomeus C M Haarman, Mathew A. Harris, Orwa Dandash, Ulrik Fredrik Malt, Lauren E. Salminen, Michael Stäblein, Theo G.M. van Erp, Gloria Roberts, Michael Berk, Jochen Bauer, Edith Pomarol-Clotet, Carlos López-Jaramillo, Dominik Grotegerd, Tomas Hajek, Paul M. Thompson, Philipp G. Sämann, Francesco Benedetti, Tilo Kircher, Brian Hallahan, Jonathan Repple, Lena Waltemate, Maria M. Rive, Heather C. Whalley, Caterina del Mar Bonnín, Oliver Gruber, Igor Nenadic, Udo Dannlowski, Henricus G. Ruhé, Raymond Salvador, Bronwyn Overs, Torbjørn Elvsåshagen, Márcio Gerhardt Soeiro-de-Souza, Ana M. Díaz-Zuluaga, Katharina Förster, Jose Manuel Goikolea, Emma L. Hawkins, Vera Lonning, Silvia Alonso-Lana, Dan J. Stein, Theophilus N. Akudjedu, Elisa M T Melloni, Dag Alnæs, Nils Opel, Martin Alda, Rayus Kuplicki, Erlend Bøen, Salvador Sarró, Unn K. Haukvik, Philip B. Mitchell, Kang Sim, Lisa Rauer, Ole A. Andreassen, Colm McDonald, Eduard Vieta, Erick J. Canales-Rodríguez, Axel Krug, Viola Oertel, Frederike Stein, Xavier Caseras, Christopher R.K. Ching, Lucio Oldani, Dara M. Cannon, Andrew M. McIntosh, Kjetil Nordbø Jørgensen, Ingrid Melle, Rhoshel K. Lenroot, Lars T. Westlye, Giuseppe Delvecchio, Dick J. Veltman, Mar Fatjó-Vilas, Trine Vik Lagerberg, Leila Nabulsi, Henk Temmingh, Carina Hülsmann, Francesco Bettella, Paolo Brambilla, Dennis van der Meer, Sonya Foley, Tiril P. Gurholt, Fleur M. Howells, Joaquim Radua, Thomas M. Lancaster, Christian K. Tamnes, Maria Cg Otaduy, Jonathan Savitz, Stener Nerland, Genevieve McPhilemy, Janice M. Fullerton, Aart H. Schene, Neda Jahanshad, Ingrid Agartz, Bernhard T. Baune, Beathe Haatveit, Bernd Krämer, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Haukvik, U. K., Gurholt, T. P., Nerland, S., Elvsashagen, T., Akudjedu, T. N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B. T., Benedetti, F., Berk, M., Bettella, F., Boen, E., Bonnin, C. M., Brambilla, P., Canales-Rodriguez, E. J., Cannon, D. M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., van Erp, T. G. M., Fatjo-Vilas, M., Foley, S. F., Forster, K., Fullerton, J. M., Goikolea, J. M., Grotegerd, D., Gruber, O., Haarman, B. C. M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E. L., Howells, F. M., Hulsmann, C., Jahanshad, N., Jorgensen, K. N., Kircher, T., Kramer, B., Krug, A., Kuplicki, R., Lagerberg, T. V., Lancaster, T. M., Lenroot, R. K., Lonning, V., Lopez-Jaramillo, C., Malt, U. F., Mcdonald, C., Mcintosh, A. M., Mcphilemy, G., van der Meer, D., Melle, I., Melloni, E. M. T., Mitchell, P. B., Nabulsi, L., Nenadic, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M. C. G., Overs, B. J., Pineda-Zapata, J. A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salminen, L. E., Salvador, R., Sarro, S., Savitz, J., Schene, A. H., Sim, K., Soeiro-de-Souza, M. G., Stablein, M., Stein, D. J., Stein, F., Tamnes, C. K., Temmingh, H. S., Thomopoulos, S. I., Veltman, D. J., Vieta, E., Waltemate, L., Westlye, L. T., Whalley, H. C., Samann, P. G., Thompson, P. M., Ching, C. R. K., Andreassen, O. A., Agartz, I., Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Adult Psychiatry

Subjects
structural brain MRI, Bipolar Disorder, HALOPERIDOL, hippocampus, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], SEGMENTATION, Hippocampus, Hippocampal formation, 0302 clinical medicine, SCHIZOPHRENIA, Manic-depressive illness, psychosis, BRAIN, Research Articles, Trastorn bipolar, Radiological and Ultrasound Technology, 05 social sciences, Subiculum, ATLAS, Magnetic Resonance Imaging, Liti, 3. Good health, medicine.anatomical_structure, Neurology, Schizophrenia, lithium, Anatomy, Hippocampus (Brain), Research Article, MRI, INTERNEURONS, Psychosis, Hipocamp (Cervell), Neuroimaging, Amygdala, 050105 experimental psychology, CELL-PROLIFERATION, 03 medical and health sciences, Genetics, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, large‐scale, LITHIUM-TREATED PATIENTS, business.industry, Dentate gyrus, medicine.disease, nervous system, DENTATE GYRUS, large-scale, bipolar disorder subtype, Neurology (clinical), business, Neuroscience, 030217 neurology & neurosurgery
Abstract

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder.In the largest study of hippocampal subfields in bipolar disorder to date, from 23 sites worldwide, we report widespread reductions in nine of 12 subfields.The lack of differences between lithium users and healthy controls supports a possible protective role of lithium in bipolar disorder.

Published
2022
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