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Clay SM, Schoettler N, Goldstein AM, Carbonetto P, Dapas M, Altman MC, Rosasco MG, Gern JE, Jackson DJ, Im HK, Stephens M, Nicolae DL, Ober C. Fine-mapping studies distinguish genetic risks for childhood- and adult-onset asthma in the HLA region. Genome Med 2022; 14:55. [PMID: 35606880 PMCID: PMC9128203 DOI: 10.1186/s13073-022-01058-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 05/12/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Genome-wide association studies of asthma have revealed robust associations with variation across the human leukocyte antigen (HLA) complex with independent associations in the HLA class I and class II regions for both childhood-onset asthma (COA) and adult-onset asthma (AOA). However, the specific variants and genes contributing to risk are unknown. METHODS We used Bayesian approaches to perform genetic fine-mapping for COA and AOA (n=9432 and 21,556, respectively; n=318,167 shared controls) in White British individuals from the UK Biobank and to perform expression quantitative trait locus (eQTL) fine-mapping in immune (lymphoblastoid cell lines, n=398; peripheral blood mononuclear cells, n=132) and airway (nasal epithelial cells, n=188) cells from ethnically diverse individuals. We also examined putatively causal protein coding variation from protein crystal structures and conducted replication studies in independent multi-ethnic cohorts from the UK Biobank (COA n=1686; AOA n=3666; controls n=56,063). RESULTS Genetic fine-mapping revealed both shared and distinct causal variation between COA and AOA in the class I region but only distinct causal variation in the class II region. Both gene expression levels and amino acid variation contributed to risk. Our results from eQTL fine-mapping and amino acid visualization suggested that the HLA-DQA1*03:01 allele and variation associated with expression of the nonclassical HLA-DQA2 and HLA-DQB2 genes accounted entirely for the most significant association with AOA in GWAS. Our studies also suggested a potentially prominent role for HLA-C protein coding variation in the class I region in COA. We replicated putatively causal variant associations in a multi-ethnic cohort. CONCLUSIONS We highlight roles for both gene expression and protein coding variation in asthma risk and identified putatively causal variation and genes in the HLA region. A convergence of genomic, transcriptional, and protein coding evidence implicates the HLA-DQA2 and HLA-DQB2 genes and HLA-DQA1*03:01 allele in AOA.
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Affiliation(s)
- Selene M Clay
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.
| | - Nathan Schoettler
- Section of Pulmonary and Critical Care, Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
| | - Andrew M Goldstein
- Department of Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Peter Carbonetto
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Matthew Dapas
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Matthew C Altman
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, 98109, USA
- Systems Immunology Program, Benaroya Research Institute, Seattle, WA, 98101, USA
| | - Mario G Rosasco
- Systems Immunology Program, Benaroya Research Institute, Seattle, WA, 98101, USA
| | - James E Gern
- Department of Pediatrics, University of Wisconsin, School of Medicine and Public Health, Madison, WI, 53706, USA
| | - Daniel J Jackson
- Department of Pediatrics, University of Wisconsin, School of Medicine and Public Health, Madison, WI, 53706, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
| | - Matthew Stephens
- Department of Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Dan L Nicolae
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Department of Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.
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Zuber V, Grinberg NF, Gill D, Manipur I, Slob EAW, Patel A, Wallace C, Burgess S. Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches. Am J Hum Genet 2022; 109:767-782. [PMID: 35452592 PMCID: PMC7612737 DOI: 10.1016/j.ajhg.2022.04.001] [Citation(s) in RCA: 102] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Mendelian randomization and colocalization are two statistical approaches that can be applied to summarized data from genome-wide association studies (GWASs) to understand relationships between traits and diseases. However, despite similarities in scope, they are different in their objectives, implementation, and interpretation, in part because they were developed to serve different scientific communities. Mendelian randomization assesses whether genetic predictors of an exposure are associated with the outcome and interprets an association as evidence that the exposure has a causal effect on the outcome, whereas colocalization assesses whether two traits are affected by the same or distinct causal variants. When considering genetic variants in a single genetic region, both approaches can be performed. While a positive colocalization finding typically implies a non-zero Mendelian randomization estimate, the reverse is not generally true: there are several scenarios which would lead to a non-zero Mendelian randomization estimate but lack evidence for colocalization. These include the existence of distinct but correlated causal variants for the exposure and outcome, which would violate the Mendelian randomization assumptions, and a lack of strong associations with the outcome. As colocalization was developed in the GWAS tradition, typically evidence for colocalization is concluded only when there is strong evidence for associations with both traits. In contrast, a non-zero estimate from Mendelian randomization can be obtained despite only nominally significant genetic associations with the outcome at the locus. In this review, we discuss how the two approaches can provide complementary information on potential therapeutic targets.
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Affiliation(s)
- Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | | | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK; Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK; Genetics Department, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Ichcha Manipur
- Cambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Eric A W Slob
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Ashish Patel
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Chris Wallace
- Cambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
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Investigating the genetic architecture of eye colour in a Canadian cohort. iScience 2022; 25:104485. [PMID: 35712076 PMCID: PMC9194134 DOI: 10.1016/j.isci.2022.104485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 04/18/2022] [Accepted: 05/24/2022] [Indexed: 11/24/2022] Open
Abstract
Eye color is highly variable in populations with European ancestry, ranging from low to high quantities of melanin in the iris. Polymorphisms in the HERC2/OCA2 locus have the largest effect on eye color in these populations, although other genomic regions also influence eye color. We performed genome-wide association studies of eye color in a Canadian cohort of European ancestry (N = 5,641) and investigated candidate causal variants. We uncovered several candidate causal signals in the HERC2/OCA2 region, whereas other loci likely harbor a single causal signal. We observed colocalization of eye color signals with the expression or methylation profiles of cultured primary melanocytes. Genetic correlations of eye and hair color suggest high genome-wide pleiotropy, but locus-level differences in the genetic architecture of both traits. Overall, we provide a better picture of the polymorphisms underpinning eye color variation, which may be a consequence of specific molecular processes in the iris melanocytes. Genome-wide association studies of eye color in 5,641 participants Multiple independent candidate causal variants were identified across HERC2/OCA2 Single candidate causal variants observed on or near IRF4, SLC24A4, TYR, and TYRP1 Colocalization of eye color signals with expression and methylation profiles
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Škrabišová M, Dietz N, Zeng S, Chan YO, Wang J, Liu Y, Biová J, Joshi T, Bilyeu KD. A novel Synthetic phenotype association study approach reveals the landscape of association for genomic variants and phenotypes. J Adv Res 2022; 42:117-133. [PMID: 36513408 PMCID: PMC9788956 DOI: 10.1016/j.jare.2022.04.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 02/14/2022] [Accepted: 04/08/2022] [Indexed: 12/27/2022] Open
Abstract
INTRODUCTION Genome-Wide Association Studies (GWAS) identify tagging variants in the genome that are statistically associated with the phenotype because of their linkage disequilibrium (LD) relationship with the causative mutation (CM). When both low-density genotyped accession panels with phenotypes and resequenced data accession panels are available, tagging variants can assist with post-GWAS challenges in CM discovery. OBJECTIVES Our objective was to identify additional GWAS evaluation criteria to assess correspondence between genomic variants and phenotypes, as well as enable deeper analysis of the localized landscape of association. METHODS We used genomic variant positions as Synthetic phenotypes in GWAS that we named "Synthetic phenotype association study" (SPAS). The extreme case of SPAS is what we call an "Inverse GWAS" where we used CM positions of cloned soybean genes. We developed and validated the Accuracy concept as a measure of the correspondence between variant positions and phenotypes. RESULTS The SPAS approach demonstrated that the genotype status of an associated variant used as a Synthetic phenotype enabled us to explore the relationships between tagging variants and CMs, and further, that utilizing CMs as Synthetic phenotypes in Inverse GWAS illuminated the landscape of association. We implemented the Accuracy calculation for a curated accession panel to an online Accuracy calculation tool (AccuTool) as a resource for gene identification in soybean. We demonstrated our concepts on three examples of soybean cloned genes. As a result of our findings, we devised an enhanced "GWAS to Genes" analysis (Synthetic phenotype to CM strategy, SP2CM). Using SP2CM, we identified a CM for a novel gene. CONCLUSION The SP2CM strategy utilizing Synthetic phenotypes and the Accuracy calculation of correspondence provides crucial information to assist researchers in CM discovery. The impact of this work is a more effective evaluation of landscapes of GWAS associations.
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Affiliation(s)
- Mária Škrabišová
- Department of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc 78371, Czech Republic
| | - Nicholas Dietz
- Division of Plant Sciences, University of Missouri, Columbia, MO 65201, USA
| | - Shuai Zeng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA,Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA
| | - Yen On Chan
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA,MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA
| | - Juexin Wang
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA,Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA
| | - Yang Liu
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA,MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA
| | - Jana Biová
- Department of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc 78371, Czech Republic
| | - Trupti Joshi
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA,Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA,MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA,Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO 65212, USA,Corresponding authors at: Department of Health Management and Informatics, School of Medicine, 1201 E Rollins St, 271B Life Science Center, Columbia, MO 65201, USA (T. Joshi). Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, 110 Waters Hall, University of Missouri, Columbia, MO 65211, USA (K.D. Bilyeu).
| | - Kristin D. Bilyeu
- Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, MO 65211, USA,Corresponding authors at: Department of Health Management and Informatics, School of Medicine, 1201 E Rollins St, 271B Life Science Center, Columbia, MO 65201, USA (T. Joshi). Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, 110 Waters Hall, University of Missouri, Columbia, MO 65211, USA (K.D. Bilyeu).
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Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, Bryois J, Chen CY, Dennison CA, Hall LS, Lam M, Watanabe K, Frei O, Ge T, Harwood JC, Koopmans F, Magnusson S, Richards AL, Sidorenko J, Wu Y, Zeng J, Grove J, Kim M, Li Z, Voloudakis G, Zhang W, Adams M, Agartz I, Atkinson EG, Agerbo E, Al Eissa M, Albus M, Alexander M, Alizadeh BZ, Alptekin K, Als TD, Amin F, Arolt V, Arrojo M, Athanasiu L, Azevedo MH, Bacanu SA, Bass NJ, Begemann M, Belliveau RA, Bene J, Benyamin B, Bergen SE, Blasi G, Bobes J, Bonassi S, Braun A, Bressan RA, Bromet EJ, Bruggeman R, Buckley PF, Buckner RL, Bybjerg-Grauholm J, Cahn W, Cairns MJ, Calkins ME, Carr VJ, Castle D, Catts SV, Chambert KD, Chan RCK, Chaumette B, Cheng W, Cheung EFC, Chong SA, Cohen D, Consoli A, Cordeiro Q, Costas J, Curtis C, Davidson M, Davis KL, de Haan L, Degenhardt F, DeLisi LE, Demontis D, Dickerson F, Dikeos D, Dinan T, Djurovic S, Duan J, Ducci G, Dudbridge F, Eriksson JG, Fañanás L, Faraone SV, Fiorentino A, Forstner A, Frank J, Freimer NB, Fromer M, Frustaci A, Gadelha A, Genovese G, Gershon ES, Giannitelli M, Giegling I, Giusti-Rodríguez P, Godard S, Goldstein JI, González Peñas J, González-Pinto A, Gopal S, Gratten J, Green MF, Greenwood TA, Guillin O, Gülöksüz S, Gur RE, Gur RC, Gutiérrez B, Hahn E, Hakonarson H, Haroutunian V, Hartmann AM, Harvey C, Hayward C, Henskens FA, Herms S, Hoffmann P, Howrigan DP, Ikeda M, Iyegbe C, Joa I, Julià A, Kähler AK, Kam-Thong T, Kamatani Y, Karachanak-Yankova S, Kebir O, Keller MC, Kelly BJ, Khrunin A, Kim SW, Klovins J, Kondratiev N, Konte B, Kraft J, Kubo M, Kučinskas V, Kučinskiene ZA, Kusumawardhani A, Kuzelova-Ptackova H, Landi S, Lazzeroni LC, Lee PH, Legge SE, Lehrer DS, Lencer R, Lerer B, Li M, Lieberman J, Light GA, Limborska S, Liu CM, Lönnqvist J, Loughland CM, Lubinski J, Luykx JJ, Lynham A, Macek M, Mackinnon A, Magnusson PKE, Maher BS, Maier W, Malaspina D, Mallet J, Marder SR, Marsal S, Martin AR, Martorell L, Mattheisen M, McCarley RW, McDonald C, McGrath JJ, Medeiros H, Meier S, Melegh B, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mitjans M, Molden E, Molina E, Molto MD, Mondelli V, Moreno C, Morley CP, Muntané G, Murphy KC, Myin-Germeys I, Nenadić I, Nestadt G, Nikitina-Zake L, Noto C, Nuechterlein KH, O'Brien NL, O'Neill FA, Oh SY, Olincy A, Ota VK, Pantelis C, Papadimitriou GN, Parellada M, Paunio T, Pellegrino R, Periyasamy S, Perkins DO, Pfuhlmann B, Pietiläinen O, Pimm J, Porteous D, Powell J, Quattrone D, Quested D, Radant AD, Rampino A, Rapaport MH, Rautanen A, Reichenberg A, Roe C, Roffman JL, Roth J, Rothermundt M, Rutten BPF, Saker-Delye S, Salomaa V, Sanjuan J, Santoro ML, Savitz A, Schall U, Scott RJ, Seidman LJ, Sharp SI, Shi J, Siever LJ, Sigurdsson E, Sim K, Skarabis N, Slominsky P, So HC, Sobell JL, Söderman E, Stain HJ, Steen NE, Steixner-Kumar AA, Stögmann E, Stone WS, Straub RE, Streit F, Strengman E, Stroup TS, Subramaniam M, Sugar CA, Suvisaari J, Svrakic DM, Swerdlow NR, Szatkiewicz JP, Ta TMT, Takahashi A, Terao C, Thibaut F, Toncheva D, Tooney PA, Torretta S, Tosato S, Tura GB, Turetsky BI, Üçok A, Vaaler A, van Amelsvoort T, van Winkel R, Veijola J, Waddington J, Walter H, Waterreus A, Webb BT, Weiser M, Williams NM, Witt SH, Wormley BK, Wu JQ, Xu Z, Yolken R, Zai CC, Zhou W, Zhu F, Zimprich F, Atbaşoğlu EC, Ayub M, Benner C, Bertolino A, Black DW, Bray NJ, Breen G, Buccola NG, Byerley WF, Chen WJ, Cloninger CR, Crespo-Facorro B, Donohoe G, Freedman R, Galletly C, Gandal MJ, Gennarelli M, Hougaard DM, Hwu HG, Jablensky AV, McCarroll SA, Moran JL, Mors O, Mortensen PB, Müller-Myhsok B, Neil AL, Nordentoft M, Pato MT, Petryshen TL, Pirinen M, Pulver AE, Schulze TG, Silverman JM, Smoller JW, Stahl EA, Tsuang DW, Vilella E, Wang SH, Xu S, Adolfsson R, Arango C, Baune BT, Belangero SI, Børglum AD, Braff D, Bramon E, Buxbaum JD, Campion D, Cervilla JA, Cichon S, Collier DA, Corvin A, Curtis D, Forti MD, Domenici E, Ehrenreich H, Escott-Price V, Esko T, Fanous AH, Gareeva A, Gawlik M, Gejman PV, Gill M, Glatt SJ, Golimbet V, Hong KS, Hultman CM, Hyman SE, Iwata N, Jönsson EG, Kahn RS, Kennedy JL, Khusnutdinova E, Kirov G, Knowles JA, Krebs MO, Laurent-Levinson C, Lee J, Lencz T, Levinson DF, Li QS, Liu J, Malhotra AK, Malhotra D, McIntosh A, McQuillin A, Menezes PR, Morgan VA, Morris DW, Mowry BJ, Murray RM, Nimgaonkar V, Nöthen MM, Ophoff RA, Paciga SA, Palotie A, Pato CN, Qin S, Rietschel M, Riley BP, Rivera M, Rujescu D, Saka MC, Sanders AR, Schwab SG, Serretti A, Sham PC, Shi Y, St Clair D, Stefánsson H, Stefansson K, Tsuang MT, van Os J, Vawter MP, Weinberger DR, Werge T, Wildenauer DB, Yu X, Yue W, Holmans PA, Pocklington AJ, Roussos P, Vassos E, Verhage M, Visscher PM, Yang J, Posthuma D, Andreassen OA, Kendler KS, Owen MJ, Wray NR, Daly MJ, Huang H, Neale BM, Sullivan PF, Ripke S, Walters JTR, O'Donovan MC. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 2022; 604:502-508. [PMID: 35396580 PMCID: PMC9392466 DOI: 10.1038/s41586-022-04434-5] [Citation(s) in RCA: 893] [Impact Index Per Article: 446.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 01/10/2022] [Indexed: 01/16/2023]
Abstract
Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.
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Affiliation(s)
- Vassily Trubetskoy
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Ting Qi
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- School of Life Sciences, Westlake University, Hangzhou, China
| | | | - Swapnil Awasthi
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Tim B Bigdeli
- Department of Psychiatry and the Behavioral Sciences, SUNY Downstate Medical Center, New York, NY, USA
- Institute for Genomic Health, SUNY Downstate Medical Center, New York, NY, USA
- Department of Psychiatry, Veterans Affairs New York Harbor Healthcare System, New York, NY, USA
| | - Julien Bryois
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chia-Yen Chen
- Biogen, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Charlotte A Dennison
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Lynsey S Hall
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Max Lam
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Research Division, Institute of Mental Health, Singapore, Republic of Singapore
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Kyoko Watanabe
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Janet C Harwood
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Frank Koopmans
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Faculty of Science, Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, The Netherlands
| | | | - Alexander L Richards
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Julia Sidorenko
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Yang Wu
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Minsoo Kim
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Zhiqiang Li
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | - Georgios Voloudakis
- Department of Psychiatry, Pamela Sklar Division of Psychiatric Genomics, Friedman Brain Institute, Department of Genetics and Genomic Science and Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wen Zhang
- Department of Psychiatry, Pamela Sklar Division of Psychiatric Genomics, Friedman Brain Institute, Department of Genetics and Genomic Science and Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mark Adams
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ingrid Agartz
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Elizabeth G Atkinson
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Esben Agerbo
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Mariam Al Eissa
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | | | - Madeline Alexander
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Behrooz Z Alizadeh
- University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, University of Groningen, Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Köksal Alptekin
- Department of Psychiatry, Dokuz Eylül University School of Medicine, Izmir, Turkey
- Department of Neuroscience, Dokuz Eylül University Graduate School of Health Sciences, Izmir, Turkey
| | - Thomas D Als
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Farooq Amin
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Volker Arolt
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Manuel Arrojo
- Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Spain
| | - Lavinia Athanasiu
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Maria Helena Azevedo
- Institute of Medical Psychology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Silviu A Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Nicholas J Bass
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Martin Begemann
- Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany
| | - Richard A Belliveau
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Judit Bene
- Department of Medical Genetics, Medical School, University of Pécs, Pécs, Hungary
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, South Australia, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Sarah E Bergen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari 'Aldo Moro', Bari, Italy
| | - Julio Bobes
- Área de Psiquiatría-Universidad de Oviedo, Hospital Universitario Central de Asturias (HUCA), Asturias, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Asturias, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Oviedo, Asturias, Spain
| | - Stefano Bonassi
- Unit of Clinical and Molecular Epidemiology, IRCCS San Raffaele Roma and San Raffaele University, Rome, Italy
| | - Alice Braun
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Rodrigo Affonseca Bressan
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Evelyn J Bromet
- Department of Psychiatry and Behavioural Health, Stony Brook University, Stony Brook, NY, USA
| | - Richard Bruggeman
- University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, University of Groningen, Groningen, The Netherlands
- Department of Clinical and Developmental Neuropsychology, University of Groningen, Groningen, The Netherlands
| | - Peter F Buckley
- Health Science Center, University of Tennessee, Memphis, TN, USA
| | - Randy L Buckner
- Department of Psychology, Harvard University, Cambridge, MA, USA
| | - Jonas Bybjerg-Grauholm
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Wiepke Cahn
- University Medical Center Utrecht, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, Utrecht, The Netherlands
- Altrecht, General Menthal Health Care, Utrecht, The Netherlands
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle, New South Wales, Australia
| | - Monica E Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Vaughan J Carr
- School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
- Department of Psychiatry, Monash University, Melbourne, Victoria, Australia
- Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - David Castle
- Department of Psychiatry, University of Melbourne, Parkville, Victoria, Australia
- St Vincent's Hospital, Melbourne, Victoria, Australia
| | - Stanley V Catts
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
- School of Medicine, University of Queensland, Herston, Queensland, Australia
| | - Kimberley D Chambert
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Raymond C K Chan
- Institute of Psychology, Chinese Academy of Science, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Boris Chaumette
- INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Université de Paris, GHU Paris Psychiatrie & Neurosciences, Paris, France
- Department of Psychiatry, McGill University, Montreal, Québec, Canada
| | - Wei Cheng
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | | | - Siow Ann Chong
- Research Division, Institute of Mental Health, Singapore, Republic of Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore
| | - David Cohen
- Faculté de Médecine Sorbonne Université, Groupe de Recherche Clinique no. 15 - Troubles Psychiatriques et Développement (PSYDEV), Department of Child and Adolescent Psychiatry, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
- Centre de Référence des Maladies Rares à Expression Psychiatrique, Department of Child and Adolescent Psychiatry, AP-HP Sorbonne Université, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
- Institut des Systèmes Intelligents et de Robotique (ISIR), CNRS UMR7222, Faculté des Sciences et Ingénierie, Sorbonne Université, Paris, France
| | - Angèle Consoli
- Faculté de Médecine Sorbonne Université, Groupe de Recherche Clinique no. 15 - Troubles Psychiatriques et Développement (PSYDEV), Department of Child and Adolescent Psychiatry, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
- Centre de Référence des Maladies Rares à Expression Psychiatrique, Department of Child and Adolescent Psychiatry, AP-HP Sorbonne Université, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
| | - Quirino Cordeiro
- Department of Psychiatry, Irmandade da Santa Casa de Misericórdia de São Paulo, São Paulo, Brazil
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Spain
| | - Charles Curtis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | | | - Kenneth L Davis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lieuwe de Haan
- Department of Psychiatry, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
- Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | | | - Lynn E DeLisi
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Cambridge Health Alliance, Cambridge, MA, USA
| | - Ditte Demontis
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | | | - Dimitris Dikeos
- First Department of Psychiatry, Medical School, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece
| | - Timothy Dinan
- Department of Psychiatry and Neurobehavioural Sciences, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Srdjan Djurovic
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL, USA
| | | | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore
| | - Lourdes Fañanás
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
| | - Stephen V Faraone
- Departments of Psychiatry and Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Alessia Fiorentino
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Andreas Forstner
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nelson B Freimer
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Menachem Fromer
- Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alessandra Frustaci
- Barnet, Enfield and Haringey Mental Health NHS Trust, St Ann's Hospital, London, UK
| | - Ary Gadelha
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elliot S Gershon
- Departments of Psychiatry and Human Genetics, University of Chicago, Chicago, IL, USA
| | - Marianna Giannitelli
- Faculté de Médecine Sorbonne Université, Groupe de Recherche Clinique no. 15 - Troubles Psychiatriques et Développement (PSYDEV), Department of Child and Adolescent Psychiatry, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
- Centre de Référence des Maladies Rares à Expression Psychiatrique, Department of Child and Adolescent Psychiatry, AP-HP Sorbonne Université, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
| | - Ina Giegling
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | | | - Stephanie Godard
- Departments of Psychiatry and Human and Molecular Genetics, INSERM, Institut de Myologie, Hôpital de la Pitiè-Salpêtrière, Paris, France
| | - Jacqueline I Goldstein
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Javier González Peñas
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, Madrid, Spain
| | - Ana González-Pinto
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- BIOARABA Health Research Institute, OSI Araba, University Hospital, University of the Basque Country, Vitoria, Spain
| | - Srihari Gopal
- Neuroscience Therapeutic Area, Janssen Research and Development, Titusville, NJ, USA
| | - Jacob Gratten
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Olivier Guillin
- INSERM, Rouen, France
- Centre Hospitalier du Rouvray, Rouen, France
- UFR Santé, Université de Rouen Normandie, Rouen, France
| | - Sinan Gülöksüz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Blanca Gutiérrez
- Department of Psychiatry, Faculty of Medicine and Biomedical Research Centre (CIBM), University of Granada, Granada, Spain
| | - Eric Hahn
- Department of Psychiatry, Charité - Universitätsmedizin, Berlin, Germany
| | - Hakon Hakonarson
- Children's Hospital of Philadelphia, Leonard Madlyn Abramson Research Center, Philadelphia, PA, USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Clinical and Education Center (MIRECC), JJ Peters VA Medical Center, New York, NY, USA
| | - Annette M Hartmann
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Carol Harvey
- Department of Psychiatry, University of Melbourne, Parkville, Victoria, Australia
- NorthWestern Mental Health, Melbourne, Victoria, Australia
| | - Caroline Hayward
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Cancer, Western General Hospital, Edinburgh, UK
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
| | - Stefan Herms
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Per Hoffmann
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Daniel P Howrigan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masashi Ikeda
- Department of Psychiatry, Fujita Health University School of Medicine, Toyoake Aichi, Japan
| | - Conrad Iyegbe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Inge Joa
- Regional Centre for Clinical Research in Psychosis, Department of Psychiatry, Stavanger University Hospital, Stavanger, Norway
| | - Antonio Julià
- Rheumatology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Anna K Kähler
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tony Kam-Thong
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffman-La Roche, Basel, Switzerland
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sena Karachanak-Yankova
- Department of Medical Genetics, Medical University, Sofia, Bulgaria
- Department of Genetics, Faculty of Biology, Sofia University "St. Kliment Ohridski", Sofia, Bulgaria
| | - Oussama Kebir
- INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Université de Paris, GHU Paris Psychiatrie & Neurosciences, Paris, France
| | - Matthew C Keller
- Institute for Behavioural Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Brian J Kelly
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
| | - Andrey Khrunin
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, Russia
| | - Sung-Wan Kim
- Department of Psychiatry, Chonnam National University Medical School, Gwangju, Korea
| | - Janis Klovins
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | | | - Bettina Konte
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Julia Kraft
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | | | - Agung Kusumawardhani
- Psychiatry Department, University of Indonesia - Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia
| | - Hana Kuzelova-Ptackova
- Department of Psychiatry, 1st Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Stefano Landi
- Dipartimento di Biologia, Universita' di Pisa, Pisa, Italy
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Phil H Lee
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sophie E Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Douglas S Lehrer
- Department of Psychiatry, Wright State University, Dayton, OH, USA
| | - Rebecca Lencer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Bernard Lerer
- Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Miaoxin Li
- Zhongshan School of Medicine and Key Laboratory of Tropical Diseases Control (SYSU), Sun Yat-sen University, Guangzhou, China
| | | | - Gregory A Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VISN 22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, USA
| | - Svetlana Limborska
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, Russia
| | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
| | - Jouko Lönnqvist
- Mental Health Unit, Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry, University of Helsinki, Helsinki, Finland
| | - Carmel M Loughland
- Hunter New England Health and University of Newcastle, Newcastle, New South Wales, Australia
| | - Jan Lubinski
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Jurjen J Luykx
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Second Opinion Outpatient Clinic, GGNet Mental Health, Warnsveld, The Netherlands
| | - Amy Lynham
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Milan Macek
- Department of Biology and Medical Genetics, 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Andrew Mackinnon
- Black Dog Institute, University of New South Wales, Randwick, New South Wales, Australia
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brion S Maher
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Wolfgang Maier
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Dolores Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jacques Mallet
- Asfalia Biologics, iPEPS-ICM, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
| | - Stephen R Marder
- Semel Institute for Neurosciene, University of California Los Angeles, Los Angeles, CA, USA
| | - Sara Marsal
- Rheumatology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Lourdes Martorell
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, CIBERSAM, Reus, Spain
| | - Manuel Mattheisen
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | | | - Colm McDonald
- Centre for Neuroimaging, Cognition and Genomics (NICOG), National University of Ireland Galway, Galway, Ireland
| | - John J McGrath
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Brisbane, Queensland, Australia
| | - Helena Medeiros
- Department of Psychiatry and the Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- College of Medicine, SUNY Downstate Health Sciences University, New York, NY, USA
| | - Sandra Meier
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Bela Melegh
- Department of Medical Genetics, University of Pécs, School of Medicine, Pécs, Hungary
| | - Ingrid Melle
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Raquelle I Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Patricia T Michie
- School of Psychology, University of Newcastle, Newcastle, New South Wales, Australia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Vihra Milanova
- Psychiatric Clinic, Alexandrovska University Hospital, Sofia, Bulgaria
| | - Marina Mitjans
- Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany
| | - Espen Molden
- Department of Pharmacy, University of Oslo, Oslo, Norway
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Esther Molina
- Department of Nursing, Faculty of Health Sciences and Biomedical Research Centre (CIBM), University of Granada, Granada, Spain
| | - María Dolores Molto
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Department of Genetics, Faculty of Biological Sciences, Universidad de Valencia, Valencia, Spain
- Biomedical Research Institute INCLIVA, Valencia, Spain
| | - Valeria Mondelli
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Carmen Moreno
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, Madrid, Spain
| | - Christopher P Morley
- Departments of Public Health and Preventive Medicine, Family Medicine, and Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY, USA
| | - Gerard Muntané
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, CIBERSAM, Reus, Spain
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, PRBB, Barcelona, Spain
| | - Kieran C Murphy
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Inez Myin-Germeys
- Department for Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium
| | - Igor Nenadić
- Cognitive Neuropsychiatry Laboratory, Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Gerald Nestadt
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Cristiano Noto
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Niamh Louise O'Brien
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - F Anthony O'Neill
- Centre for Public Health, Institute of Clinical Sciences, Queen's University Belfast, Belfast, UK
| | - Sang-Yun Oh
- Department of Statistics and Applied Probability, University of California at Santa Barbara, Santa Barbara, CA, USA
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Denver, Aurora, CO, USA
| | - Vanessa Kiyomi Ota
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
- Department of Morphology and Genetics, Laboratorio de Genetica, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Christos Pantelis
- NorthWestern Mental Health, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Parkville, Victoria, Australia
| | - George N Papadimitriou
- First Department of Psychiatry, Medical School, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece
| | - Mara Parellada
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, Madrid, Spain
| | - Tiina Paunio
- Department of Public Health Solutions, Genomics and Biomarkers Unit, National Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Renata Pellegrino
- Children's Hospital of Philadelphia, Leonard Madlyn Abramson Research Center, Philadelphia, PA, USA
| | - Sathish Periyasamy
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Bruno Pfuhlmann
- Clinic of Psychiatry and Psychotherapy, Weißer Hirsch, Dresden, Germany
| | - Olli Pietiläinen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jonathan Pimm
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - John Powell
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Diego Quattrone
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- South London and Maudsley NHS Mental Health Foundation Trust, London, UK
| | - Digby Quested
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Allen D Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
- VA Puget Sound Health Care System, Seattle, WA, USA
| | - Antonio Rampino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari 'Aldo Moro', Bari, Italy
| | - Mark H Rapaport
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Anna Rautanen
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffman-La Roche, Basel, Switzerland
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Cheryl Roe
- SUNY Upstate Medical University, Syracuse, NY, USA
| | - Joshua L Roffman
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Julian Roth
- Department of Psychiatry, Psychosomatics and Psychotherapy, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | | | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | - Veikko Salomaa
- THL-Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Julio Sanjuan
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Biomedical Research Institute INCLIVA, Valencia, Spain
- Department of Psychiatry, School of Medicine, University of Valencia, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Marcos Leite Santoro
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
- Department of Morphology and Genetics, Laboratorio de Genetica, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Adam Savitz
- Neuroscience Therapeutic Area, Janssen Research and Development, Titusville, NJ, USA
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Priority Centre for Brain and Mental Health Research, University of Newcastle, Mater Hospital, McAuley Centre, Newcastle, New South Wales, Australia
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Division of Molecular Medicine, NSW Health Pathology North, Newcastle, New South Wales, Australia
| | - Larry J Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sally Isabel Sharp
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - Engilbert Sigurdsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Psychiatry, Landspitali University Hospital, Reykjavik, Iceland
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yoo Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Nora Skarabis
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Petr Slominsky
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, Russia
| | - Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
| | - Janet L Sobell
- Department of Psychiatry and the Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Erik Söderman
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Helen J Stain
- School of Social and Health Sciences, Leeds Trinity University, Leeds, UK
- TIPS - Network for Clinical Research in Psychosis, Stavanger University Hospital, Stavanger, Norway
| | - Nils Eiel Steen
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Agnes A Steixner-Kumar
- Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany
| | | | - William S Stone
- Harvard Medical School Department of Psychiatry at Beth Israel Deaconess Medical Center, Boston, MA, USA
- Massachusetts Mental Health Center, Boston, MA, USA
| | | | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Eric Strengman
- Department of Medical Genetics, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - T Scott Stroup
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Mythily Subramaniam
- Research Division, Institute of Mental Health, Singapore, Republic of Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore
| | - Catherine A Sugar
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Jaana Suvisaari
- THL-Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Dragan M Svrakic
- Department of Psychiatry, Washington University, St Louis, MO, USA
| | - Neal R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jin P Szatkiewicz
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Thi Minh Tam Ta
- Department of Psychiatry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Atsushi Takahashi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Florence Thibaut
- Université de Paris, Faculté de Médecine, Hôpital Cochin-Tarnier, Paris, France
- INSERM U1266, Institut de Psychiatrie et de Neurosciences, Paris, France
| | - Draga Toncheva
- Department of Medical Genetics, Medical University, Sofia, Bulgaria
- Bulgarian Academy of Science, Sofia, Bulgaria
| | - Paul A Tooney
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle, New South Wales, Australia
| | - Silvia Torretta
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari 'Aldo Moro', Bari, Italy
| | - Sarah Tosato
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Gian Battista Tura
- Psychiatry Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bruce I Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Alp Üçok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Arne Vaaler
- Division of Mental Health, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Therese van Amelsvoort
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Ruud van Winkel
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Neurosciences, Center for Clinical Psychiatry, KU Leuven, Leuven, Belgium
| | - Juha Veijola
- Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - John Waddington
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Anna Waterreus
- Neuropsychiatric Epidemiology Research Unit, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia
- Centre for Clinical Research in Neuropsychiatry, University of Western Australia, Perth, Western Australia, Australia
| | - Bradley T Webb
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Nigel M Williams
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Brandon K Wormley
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Jing Qin Wu
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Zhida Xu
- Department of Psychiatry, GGz Centraal, Utrecht, The Netherlands
| | - Robert Yolken
- Stanley Neurovirology Laboratory, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Clement C Zai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Wei Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | - Feng Zhu
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fritz Zimprich
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Eşref Cem Atbaşoğlu
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Muhammad Ayub
- Department of Psychiatry, Queens University Kingston, Kingston, Ontario, Canada
| | - Christian Benner
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari 'Aldo Moro', Bari, Italy
| | - Donald W Black
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Nicholas J Bray
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Nancy G Buccola
- School of Nursing, Louisiana State University Health Sciences Center, New Orleans, LA, USA
| | - William F Byerley
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Wei J Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Zhunan Town, Taiwan
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | | | - Benedicto Crespo-Facorro
- University of Sevilla, CIBERSAM IBiS, Seville, Spain
- Hospital Universitario Virgen del Rocio, Department of Psychiatry, Universidad del Sevilla, Seville, Spain
| | - Gary Donohoe
- Centre for Neuroimaging, Cognition and Genomics (NICOG), National University of Ireland Galway, Galway, Ireland
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Denver, Aurora, CO, USA
| | - Cherrie Galletly
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
- Ramsay Health Care (SA) Mental Health, Adelaide, South Australia, Australia
- Northern Adelaide Local Health Network, Adelaide, South Australia, Australia
| | - Michael J Gandal
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Hai-Gwo Hwu
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
- Department of Psychiatry, College of Medicine and National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan
| | - Assen V Jablensky
- Centre for Clinical Research in Neuropsychiatry, University of Western Australia, Perth, Western Australia, Australia
| | - Steven A McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jennifer L Moran
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Aarhus, Denmark
| | - Preben B Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Amanda L Neil
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Services in the Capital Region of Denmark, Mental Health Center Copenhagen, University of Copenhagen, Copenhagen, Denmark
| | - Michele T Pato
- Rutgers University, Robert Wood Johnson Medical School, New Brunswick, NJ, USA
- Rutgers University, New Jersey Medical School, Newark, NJ, USA
| | - Tracey L Petryshen
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Ann E Pulver
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University, Baltimore, MD, USA
| | - Jeremy M Silverman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - Jordan W Smoller
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eli A Stahl
- Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Regeneron Genetics Center, Orange, CA, USA
| | - Debby W Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
- VA Puget Sound Health Care System, Seattle, WA, USA
| | - Elisabet Vilella
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, CIBERSAM, Reus, Spain
| | - Shi-Heng Wang
- College of Public Health, China Medical University, Taichung, Taiwan
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Rolf Adolfsson
- Department of Clinical Sciences, Psychiatry, Umeå University, Umeå, Sweden
| | - Celso Arango
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, Madrid, Spain
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Parkville, Victoria, Australia
| | - Sintia Iole Belangero
- Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
- Department of Morphology and Genetics, Laboratorio de Genetica, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - David Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VISN 22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, USA
| | - Elvira Bramon
- Division of Psychiatry, Department of Mental Health Neuroscience, University College London, London, UK
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Jorge A Cervilla
- Department of Psychiatry, San Cecilio University Hospital, University of Granada, Granada, Spain
| | - Sven Cichon
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
- Department of Biomedicine, University of Basel, Basel, Switzerland
- Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany
| | | | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - David Curtis
- UCL Genetics Institute, University College London, London, UK
- Centre for Psychiatry, Queen Mary University London, London, UK
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- South London and Maudsley NHS Mental Health Foundation Trust, London, UK
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Hannelore Ehrenreich
- Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany
| | - Valentina Escott-Price
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ayman H Fanous
- Department of Psychiatry, Veterans Affairs New York Harbor Healthcare System, New York, NY, USA
- Department of Psychiatry, Phoenix VA Healthcare System, Phoenix, AZ, USA
- Banner-University Medical Center, Phoenix, AZ, USA
| | - Anna Gareeva
- Department of Human Molecular Genetics of the Institute of Biochemistry and Genetics of the Ufa Federal Research Center of the Russian Academy of Sciences (IBG UFRC RAS), Ufa, Russia
- Federal State Educational Institution of Highest Education Bashkir State Medical University of Public Health Ministry of Russian Federation (BSMU), Ufa, Russia
| | - Micha Gawlik
- Department of Psychiatry, Psychosomatics and Psychotherapy, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Pablo V Gejman
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL, USA
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Stephen J Glatt
- Psychiatric Genetic Epidemiology and Neurobiology Laboratory (PsychGENe lab), Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Vera Golimbet
- Mental Health Research Center, Moscow, Russian Federation
| | - Kyung Sue Hong
- Department of Psychiatry, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Christina M Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Steven E Hyman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Nakao Iwata
- Department of Psychiatry, Fujita Health University School of Medicine, Toyoake Aichi, Japan
| | - Erik G Jönsson
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - René S Kahn
- University Medical Center Utrecht, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - James L Kennedy
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Elza Khusnutdinova
- Department of Human Molecular Genetics of the Institute of Biochemistry and Genetics of the Ufa Federal Research Center of the Russian Academy of Sciences (IBG UFRC RAS), Ufa, Russia
- Federal State Educational Institution of Highest Education Bashkir State Medical University of Public Health Ministry of Russian Federation (BSMU), Ufa, Russia
| | - George Kirov
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James A Knowles
- Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine at University of Southern California, Los Angeles, CA, USA
- Department of Cell Biology, State University of New York, Downstate Health Sciences University, New York, NY, USA
| | - Marie-Odile Krebs
- INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Université de Paris, GHU Paris Psychiatrie & Neurosciences, Paris, France
| | - Claudine Laurent-Levinson
- Faculté de Médecine Sorbonne Université, Groupe de Recherche Clinique no. 15 - Troubles Psychiatriques et Développement (PSYDEV), Department of Child and Adolescent Psychiatry, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
- Centre de Référence des Maladies Rares à Expression Psychiatrique, Department of Child and Adolescent Psychiatry, AP-HP Sorbonne Université, Hôpital Universitaire de la Pitié-Salpêtrière, Paris, France
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Todd Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Douglas F Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research and Development, Titusville, NJ, USA
| | - Jianjun Liu
- Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Anil K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Dheeraj Malhotra
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffman-La Roche, Basel, Switzerland
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Paulo R Menezes
- Department of Preventative Medicine, Faculdade de Medicina FMUSP, University of São Paulo, São Paulo, Brazil
| | - Vera A Morgan
- Neuropsychiatric Epidemiology Research Unit, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia
- Centre for Clinical Research in Neuropsychiatry, University of Western Australia, Perth, Western Australia, Australia
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics (NICOG), National University of Ireland Galway, Galway, Ireland
| | - Bryan J Mowry
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia
| | - Robin M Murray
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | | | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Roel A Ophoff
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Sara A Paciga
- Early Clinical Development, Pfizer Worldwide Research and Development, Groton, CT, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Carlos N Pato
- Rutgers University, Robert Wood Johnson Medical School, New Brunswick, NJ, USA
- Rutgers University, New Jersey Medical School, Newark, NJ, USA
| | - Shengying Qin
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Brien P Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Margarita Rivera
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain
- Institute of Neurosciences, Biomedical Research Center (CIBM), University of Granada, Granada, Spain
| | - Dan Rujescu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Meram C Saka
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Alan R Sanders
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL, USA
| | - Sibylle G Schwab
- Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia
- Illawarra Health and Medical Research Institute, Wollongong, New South Wales, Australia
| | - Alessandro Serretti
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Pak C Sham
- Centre for PanorOmic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- State Key Laboratory of Brain and Cognitive Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Department of Psychiatry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Yongyong Shi
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | - David St Clair
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | | | | | - Ming T Tsuang
- Center for Behavioral Genomics, Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jim van Os
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- University Medical Center Utrecht, Department of Psychiatry, Utrecht, The Netherlands
| | - Marquis P Vawter
- Department of Psychiatry and Human Behavior, School of Medicine, University of California Irvine, Irvine, CA, USA
| | | | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Center for GeoGenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Copenhagen, Denmark
| | - Dieter B Wildenauer
- School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Western Australia, Australia
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Peter A Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Andrew J Pocklington
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Panos Roussos
- Department of Psychiatry, Pamela Sklar Division of Psychiatric Genomics, Friedman Brain Institute, Department of Genetics and Genomic Science and Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, New York, NY, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Oxford Health NHS Foundation Trust, Oxford, UK
| | - Matthijs Verhage
- Department of Clinical Genetics, Center for Neurogenomics and Cognitive Research, University Medical Center Amsterdam, Amsterdam, The Netherlands
- Department of Functional Genomics, Faculty of Exact Science, Center for Neurogenomics and Cognitive Research, VU University Amsterdam and VU Medical Center, Amsterdam, The Netherlands
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Danielle Posthuma
- Department of Functional Genomics, Faculty of Exact Science, Center for Neurogenomics and Cognitive Research, VU University Amsterdam and VU Medical Center, Amsterdam, The Netherlands
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
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56
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Kundu K, Tardaguila M, Mann AL, Watt S, Ponstingl H, Vasquez L, Von Schiller D, Morrell NW, Stegle O, Pastinen T, Sawcer SJ, Anderson CA, Walter K, Soranzo N. Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases. Nat Genet 2022; 54:251-262. [PMID: 35288711 DOI: 10.1038/s41588-022-01025-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 01/31/2022] [Indexed: 12/11/2022]
Abstract
The resolution of causal genetic variants informs understanding of disease biology. We used regulatory quantitative trait loci (QTLs) from the BLUEPRINT, GTEx and eQTLGen projects to fine-map putative causal variants for 12 immune-mediated diseases. We identify 340 unique loci that colocalize with high posterior probability (≥98%) with regulatory QTLs and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping credible sets derived from regulatory QTLs are smaller compared to disease summary statistics. Further, they are enriched for more functionally interpretable candidate causal variants and for putatively causal insertion/deletion (INDEL) polymorphisms. Finally, we use massively parallel reporter assays to evaluate candidate causal variants at the ITGA4 locus associated with inflammatory bowel disease. Overall, our findings suggest that fine-mapping applied to disease-colocalizing regulatory QTLs can enhance the discovery of putative causal disease variants and enhance insights into the underlying causal genes and molecular mechanisms.
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Affiliation(s)
- Kousik Kundu
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Manuel Tardaguila
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Alice L Mann
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Stephen Watt
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Hannes Ponstingl
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Louella Vasquez
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Dominique Von Schiller
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Nicholas W Morrell
- Division of Respiratory Medicine, Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke's and Papworth Hospitals, Cambridge, UK
| | - Oliver Stegle
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.,Cellular Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Kansas City and Children's Mercy Research Institute, Kansas City, MO, USA
| | - Stephen J Sawcer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Carl A Anderson
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Klaudia Walter
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Nicole Soranzo
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. .,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK. .,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK. .,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK. .,Genomics Research Centre, Human Technopole, Milan, Italy.
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57
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Zhang S, Cooper-Knock J, Weimer AK, Shi M, Moll T, Marshall JNG, Harvey C, Nezhad HG, Franklin J, Souza CDS, Ning K, Wang C, Li J, Dilliott AA, Farhan S, Elhaik E, Pasniceanu I, Livesey MR, Eitan C, Hornstein E, Kenna KP, Veldink JH, Ferraiuolo L, Shaw PJ, Snyder MP. Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis. Neuron 2022; 110:992-1008.e11. [PMID: 35045337 PMCID: PMC9017397 DOI: 10.1016/j.neuron.2021.12.019] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/07/2021] [Accepted: 12/13/2021] [Indexed: 02/01/2023]
Abstract
Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.
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Affiliation(s)
- Sai Zhang
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Johnathan Cooper-Knock
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Annika K Weimer
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Minyi Shi
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Tobias Moll
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Jack N G Marshall
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Calum Harvey
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Helia Ghahremani Nezhad
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - John Franklin
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Cleide Dos Santos Souza
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Ke Ning
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Cheng Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, the Bakar Computational Health Sciences Institute, the Parker Institute for Cancer Immunotherapy, and the Department of Neurology, School of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jingjing Li
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, the Bakar Computational Health Sciences Institute, the Parker Institute for Cancer Immunotherapy, and the Department of Neurology, School of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Allison A Dilliott
- Department of Neurology and Neurosurgery, the Montreal Neurological Institute, McGill University, Montreal, QC H3A 1A1, Canada
| | - Sali Farhan
- Department of Neurology and Neurosurgery, the Montreal Neurological Institute, McGill University, Montreal, QC H3A 1A1, Canada
| | - Eran Elhaik
- Department of Biology, Lunds Universitet, Lund 223 62, Sweden
| | - Iris Pasniceanu
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Matthew R Livesey
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Chen Eitan
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Eran Hornstein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Kevin P Kenna
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht 3584 CX, the Netherlands
| | - Jan H Veldink
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht 3584 CX, the Netherlands
| | - Laura Ferraiuolo
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ, UK
| | - Michael P Snyder
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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58
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Fine-mapping of intracranial aneurysm susceptibility based on a genome-wide association study. Sci Rep 2022; 12:2717. [PMID: 35177760 PMCID: PMC8854430 DOI: 10.1038/s41598-022-06755-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 02/04/2022] [Indexed: 12/22/2022] Open
Abstract
In addition to conventional genome-wide association studies (GWAS), a fine-mapping analysis is increasingly used to identify the genetic function of variants associated with disease susceptibilities. Here, we used a fine-mapping approach to evaluate candidate variants based on a previous GWAS involving patients with intracranial aneurysm (IA). A fine-mapping analysis was conducted based on the chromosomal data provided by a GWAS of 250 patients diagnosed with IA and 296 controls using posterior inclusion probability (PIP) and log10 transformed Bayes factor (log10BF). The narrow sense of heritability (h2) explained by each candidate variant was estimated. Subsequent gene expression and functional network analyses of candidate genes were used to calculate transcripts per million (TPM) values. Twenty single-nucleotide polymorphisms (SNPs) surpassed a genome-wide significance threshold for creditable evidence (log10BF > 6.1). Among them, four SNPs, rs75822236 (GBA; log10BF = 15.06), rs112859779 (TCF24; log10BF = 12.12), rs79134766 (OLFML2A; log10BF = 14.92), and rs371331393 (ARHGAP32; log10BF = 20.88) showed a completed PIP value in each chromosomal region, suggesting a higher probability of functional candidate variants associated with IA. On the contrary, these associations were not shown clearly under different replication sets. Our fine-mapping analysis suggested that four functional candidate variants of GBA, TCF24, OLFML2A, and ARHGAP32 were linked to IA susceptibility and pathogenesis. However, this approach could not completely replace replication sets based on large-scale data. Thus, caution is required when interpreting results of fine-mapping analysis.
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59
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An effector index to predict target genes at GWAS loci. Hum Genet 2022; 141:1431-1447. [PMID: 35147782 DOI: 10.1007/s00439-022-02434-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 01/15/2022] [Indexed: 11/04/2022]
Abstract
Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single-nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.
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60
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Hautakangas H, Winsvold BS, Ruotsalainen SE, Bjornsdottir G, Harder AVE, Kogelman LJA, Thomas LF, Noordam R, Benner C, Gormley P, Artto V, Banasik K, Bjornsdottir A, Boomsma DI, Brumpton BM, Burgdorf KS, Buring JE, Chalmer MA, de Boer I, Dichgans M, Erikstrup C, Färkkilä M, Garbrielsen ME, Ghanbari M, Hagen K, Häppölä P, Hottenga JJ, Hrafnsdottir MG, Hveem K, Johnsen MB, Kähönen M, Kristoffersen ES, Kurth T, Lehtimäki T, Lighart L, Magnusson SH, Malik R, Pedersen OB, Pelzer N, Penninx BWJH, Ran C, Ridker PM, Rosendaal FR, Sigurdardottir GR, Skogholt AH, Sveinsson OA, Thorgeirsson TE, Ullum H, Vijfhuizen LS, Widén E, van Dijk KW, Aromaa A, Belin AC, Freilinger T, Ikram MA, Järvelin MR, Raitakari OT, Terwindt GM, Kallela M, Wessman M, Olesen J, Chasman DI, Nyholt DR, Stefánsson H, Stefansson K, van den Maagdenberg AMJM, Hansen TF, Ripatti S, Zwart JA, Palotie A, Pirinen M. Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles. Nat Genet 2022; 54:152-160. [PMID: 35115687 PMCID: PMC8837554 DOI: 10.1038/s41588-021-00990-0] [Citation(s) in RCA: 145] [Impact Index Per Article: 72.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 11/22/2021] [Indexed: 12/11/2022]
Abstract
Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.
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Affiliation(s)
- Heidi Hautakangas
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Bendik S Winsvold
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Aster V E Harder
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Lisette J A Kogelman
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Christian Benner
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Ville Artto
- Department of Neurology, Helsinki University Central Hospital, Helsinki, Finland
| | - Karina Banasik
- Novo Nordic Foundation Center for Protein Research, Copenhagen University, Copenhagen, Denmark
| | | | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Ben M Brumpton
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mona Ameri Chalmer
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Irene de Boer
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (Synergy), Munich, Germany
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | - Markus Färkkilä
- Department of Neurology, Helsinki University Central Hospital, Helsinki, Finland
| | - Maiken Elvestad Garbrielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Knut Hagen
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinical Research Unit Central Norway, St. Olavs University Hospital, Trondheim, Norway
| | - Paavo Häppölä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | | | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Marianne Bakke Johnsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Espen S Kristoffersen
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of General Practice, Institute of Health and Society, University of Oslo, Oslo, Norway
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Tobias Kurth
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Lannie Lighart
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | | | - Rainer Malik
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Ole Birger Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Nadine Pelzer
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- GGZ inGeest Specialized Mental Health Care, Amsterdam, the Netherlands
| | - Caroline Ran
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Anne Heidi Skogholt
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Henrik Ullum
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Lisanne S Vijfhuizen
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
| | - Arpo Aromaa
- National Public Health Institute (Finnish Institute for Health and Welfare - THL), Helsinki, Finland
| | | | - Tobias Freilinger
- Klinikum Passau, Department of Neurology, Passau, Germany
- Centre of Neurology, Hertie Institute for Clinical Brain Research, Tuebingen, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mikko Kallela
- Department of Neurology, Helsinki University Central Hospital, Helsinki, Finland
| | - Maija Wessman
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Jes Olesen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Dale R Nyholt
- School of Biomedical Sciences and Centre for Genomics and Personalised Health, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | | | | | - Arn M J M van den Maagdenberg
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Thomas Folkmann Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
- Novo Nordic Foundation Center for Protein Research, Copenhagen University, Copenhagen, Denmark
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - John-Anker Zwart
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.
- Department of Public Health, University of Helsinki, Helsinki, Finland.
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
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Tyrmi JS, Arffman RK, Pujol-Gualdo N, Kurra V, Morin-Papunen L, Sliz E, Piltonen TT, Laisk T, Kettunen J, Laivuori H. Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome. Hum Reprod 2022; 37:352-365. [PMID: 34791234 PMCID: PMC8804330 DOI: 10.1093/humrep/deab250] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 10/07/2021] [Indexed: 12/21/2022] Open
Abstract
STUDY QUESTION Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe? SUMMARY ANSWER We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 (CHEK2) gene and a third in myosin X (MYO10). WHAT IS KNOWN ALREADY PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects. STUDY DESIGN, SIZE, DURATION A population-based case-control GWAS was carried out. PARTICIPANTS/MATERIALS, SETTING, METHODS We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case-control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts. MAIN RESULTS AND THE ROLE OF CHANCE Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 (P = 3.6×10-8, odds ratio (OR) = 3.01 [2.02-4.50] minor allele frequency (MAF) = 0.005) and rs182075939 (P = 1.9×10-16, OR = 1.69 [1.49-1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC (r2 = 0.95) and a missense I157T (r2 = 0.83) in CHEK2. The third novel association is a common variant near MYO10 (rs9312937, P = 1.7 × 10-8, OR = 1.16 [1.10-1.23], MAF = 0.44). We also replicated four previous reported associations near the genes Erb-B2 Receptor Tyrosine Kinase 4 (ERBB4), DENN Domain Containing 1A (DENND1A), FSH Subunit Beta (FSHB) and Zinc Finger And BTB Domain Containing 16 (ZBTB16). When adding BMI as a covariate only one of the novel variants remained genome-wide significant in the meta-analysis (the EstBB lead signal in CHEK2 rs182075939, P = 1.9×10-16, OR = 1.74 [1.5-2.01]) possibly owing to reduced sample size. LARGE SCALE DATA The age- and BMI-adjusted GWAS meta-analysis summary statistics are available for download from the GWAS Catalog with accession numbers GCST90044902 and GCST90044903. LIMITATIONS, REASONS FOR CAUTION The main limitation was the low prevalence of PCOS in registers; however, the ones with the diagnosis most likely represent the most severe cases. Also, BMI data were not available for all (63% for FinnGen, 76% for EstBB), and the biobank setting limited the accessibility of PCOS phenotypes and laboratory values. WIDER IMPLICATIONS OF THE FINDINGS This study encourages the use of isolated populations to perform genetic association studies for the identification of rare variants contributing to the genetic landscape of complex diseases such as PCOS. STUDY FUNDING/COMPETING INTEREST(S) This work has received funding from the European Union's Horizon 2020 research and innovation programme under the MATER Marie Skłodowska-Curie grant agreement No. 813707 (N.P.-G., T.L., T.P.), the Estonian Research Council grant (PRG687, T.L.), the Academy of Finland grants 315921 (T.P.), 321763 (T.P.), 297338 (J.K.), 307247 (J.K.), 344695 (H.L.), Novo Nordisk Foundation grant NNF17OC0026062 (J.K.), the Sigrid Juselius Foundation project grants (T.L., J.K., T.P.), Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.). The funders had no role in study design, data collection and analysis, publishing or preparation of the manuscript. The authors declare no conflicts of interest.
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Affiliation(s)
- Jaakko S Tyrmi
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Riikka K Arffman
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Natàlia Pujol-Gualdo
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu, Oulu, Finland
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Venla Kurra
- Department of Clinical Genetics, Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University, Tampere, Finland
| | - Laure Morin-Papunen
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Eeva Sliz
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | | | - Terhi T Piltonen
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Johannes Kettunen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Hannele Laivuori
- Department of Obstetrics and Gynecology, Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University, Tampere, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
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Chong M, Mohammadi-Shemirani P, Perrot N, Nelson W, Morton R, Narula S, Lali R, Khan I, Khan M, Judge C, Machipisa T, Cawte N, O'Donnell M, Pigeyre M, Akhabir L, Paré G. GWAS and ExWAS of blood Mitochondrial DNA copy number identifies 71 loci and highlights a potential causal role in dementia. eLife 2022; 11:70382. [PMID: 35023831 PMCID: PMC8865845 DOI: 10.7554/elife.70382] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 01/11/2022] [Indexed: 12/16/2022] Open
Abstract
Background: Mitochondrial DNA copy number (mtDNA-CN) is an accessible blood-based measurement believed to capture underlying mitochondrial (MT) function. The specific biological processes underpinning its regulation, and whether those processes are causative for disease, is an area of active investigation. Methods: We developed a novel method for array-based mtDNA-CN estimation suitable for biobank-scale studies, called ‘automatic mitochondrial copy (AutoMitoC).’ We applied AutoMitoC to 395,781 UKBiobank study participants and performed genome- and exome-wide association studies, identifying novel common and rare genetic determinants. Finally, we performed two-sample Mendelian randomization to assess whether genetically low mtDNA-CN influenced select MT phenotypes. Results: Overall, genetic analyses identified 71 loci for mtDNA-CN, which implicated several genes involved in rare mtDNA depletion disorders, deoxynucleoside triphosphate (dNTP) metabolism, and the MT central dogma. Rare variant analysis identified SAMHD1 mutation carriers as having higher mtDNA-CN (beta = 0.23 SDs; 95% CI, 0.18–0.29; p=2.6 × 10-19), a potential therapeutic target for patients with mtDNA depletion disorders, but at increased risk of breast cancer (OR = 1.91; 95% CI, 1.52–2.40; p=2.7 × 10-8). Finally, Mendelian randomization analyses suggest a causal effect of low mtDNA-CN on dementia risk (OR = 1.94 per 1 SD decrease in mtDNA-CN; 95% CI, 1.55–2.32; p=7.5 × 10-4). Conclusions: Altogether, our genetic findings indicate that mtDNA-CN is a complex biomarker reflecting specific MT processes related to mtDNA regulation, and that these processes are causally related to human diseases. Funding: No funds supported this specific investigation. Awards and positions supporting authors include: Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (MC, PM); CIHR Post-Doctoral Fellowship Award (RM); Wellcome Trust Grant number: 099313/B/12/A; Crasnow Travel Scholarship; Bongani Mayosi UCT-PHRI Scholarship 2019/2020 (TM); Wellcome Trust Health Research Board Irish Clinical Academic Training (ICAT) Programme Grant Number: 203930/B/16/Z (CJ); European Research Council COSIP Grant Number: 640580 (MO); E.J. Moran Campbell Internal Career Research Award (MP); CISCO Professorship in Integrated Health Systems and Canada Research Chair in Genetic and Molecular Epidemiology (GP) Our cells are powered by small internal compartments known as mitochondria, which host several copies of their own ‘mitochondrial’ genome. Defects in these semi-autonomous structures are associated with a range of severe, and sometimes fatal conditions: easily checking the health of mitochondria through cheap, quick and non-invasive methods can therefore help to improve human health. Measuring the concentration of mitochondrial DNA molecules in our blood cells can help to estimate the number of mitochondrial genome copies per cell, which in turn act as a proxy for the health of the compartment. In fact, having lower or higher concentration of mitochondrial DNA molecules is associated with diseases such as cancer, stroke, or cardiac conditions. However, current approaches to assess this biomarker are time and resource-intensive; they also do not work well across people with different ancestries, who have slightly different versions of mitochondrial genomes. In response, Chong et al. developed a new method for estimating mitochondrial DNA concentration in blood samples. Called AutoMitoC, the automated pipeline is fast, easy to use, and can be used across ethnicities. Applying this method to nearly 400,000 individuals highlighted 71 genetic regions for which slight sequence differences were associated with changes in mitochondrial DNA concentration. Further investigation revealed that these regions contained genes that help to build, maintain, and organize mitochondrial DNA. In addition, the analyses yield preliminary evidence showing that lower concentration of mitochondrial DNA may be linked to a higher risk of dementia. Overall, the work by Chong et al. demonstrates that AutoMitoC can be used to investigate how mitochondria are linked to health and disease in populations across the world, potentially paving the way for new therapeutic approaches.
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Affiliation(s)
- Michael Chong
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada
| | | | | | - Walter Nelson
- Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, Canada
| | - Robert Morton
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - Sukrit Narula
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Ricky Lali
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Irfan Khan
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - Mohammad Khan
- Department of Medicine, McMaster University, Hamilton, Canada
| | - Conor Judge
- National University of Ireland, Galway, Galway, Ireland
| | - Tafadzwa Machipisa
- Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Nathan Cawte
- Population Health Research Institute, Hamilton, Canada
| | | | - Marie Pigeyre
- Department of Medicine, McMaster University, Hamilton, Canada
| | - Loubna Akhabir
- Department of Medicine, McMaster University, Hamilton, Canada
| | - Guillaume Paré
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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Schilder BM, Humphrey J, Raj T. echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline. Bioinformatics 2022; 38:536-539. [PMID: 34529038 PMCID: PMC10060715 DOI: 10.1093/bioinformatics/btab658] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 09/06/2021] [Accepted: 09/13/2021] [Indexed: 02/03/2023] Open
Abstract
SUMMARY echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations. AVAILABILITY AND IMPLEMENTATION echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Brian M Schilder
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
| | - Jack Humphrey
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA
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Lv Z, Cui J, Zhang J. Associations between serum urate and telomere length and inflammation markers: Evidence from UK Biobank cohort. Front Immunol 2022; 13:1065739. [PMID: 36591268 PMCID: PMC9797991 DOI: 10.3389/fimmu.2022.1065739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Objective Hyperuricemia and gout have become gradually more common. The effect of serum urate on organism aging and systematic inflammation is not determined. This study aims to evaluate whether serum urate is causally associated with cellular aging markers and serum inflammation markers. Methods A Mendelian randomization study was performed on summary-level data from the largest published genome-wide association studies. Single nucleotide polymorphisms with a genome-wide significance level were selected as instrumental variables for leukocyte telomere length (LTL), and serum soluble makers of inflammation (CRP, IL-6, TNF-α, and IGF-1). Standard inverse variance weighted (IVW) method was used as the primary statistical method. The weighted median, MR-Egger regression, and MR-PRESSO methods were used for sensitivity analysis. Results An inverse causal association of genetically predicted serum urate levels and LTL was found using IVW method (OR: 0.96, 95%CI 0.95, 0.97; β=-0.040; SE=0.0072; P=4.37×10-8). The association was also supported by MR results using MR-Egger method and weighted median method. The MR-PRESSO analysis and leave-one-out sensitivity analysis supported the robustness of the combined results. In terms of other aging-related serum biomarkers, there was no evidence supporting a causal effect of serum urate on CRP, IL-6, TNF-α, or IGF-1 levels. Conclusions Serum urate levels are negatively associated with telomere length but are not associated with serum soluble indicators of inflammation. Telomere length may be a critical marker that reflects urate-related organismal aging and may be a mechanism in the age-related pathologies and mortality caused by hyperuricemia.
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Affiliation(s)
- Zhengtao Lv
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiarui Cui
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Jiarui Cui, ; Jiaming Zhang,
| | - Jiaming Zhang
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Jiarui Cui, ; Jiaming Zhang,
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Chen W, Wu Y, Zheng Z, Qi T, Visscher PM, Zhu Z, Yang J. Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors. Nat Commun 2021; 12:7117. [PMID: 34880243 PMCID: PMC8654883 DOI: 10.1038/s41467-021-27438-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 11/17/2021] [Indexed: 01/08/2023] Open
Abstract
statistics from genome-wide association studies (GWAS) have facilitated the development of various summary data-based methods, which typically require a reference sample for linkage disequilibrium (LD) estimation. Analyses using these methods may be biased by errors in GWAS summary data or LD reference or heterogeneity between GWAS and LD reference. Here we propose a quality control method, DENTIST, that leverages LD among genetic variants to detect and eliminate errors in GWAS or LD reference and heterogeneity between the two. Through simulations, we demonstrate that DENTIST substantially reduces false-positive rate in detecting secondary signals in the summary-data-based conditional and joint association analysis, especially for imputed rare variants (false-positive rate reduced from >28% to <2% in the presence of heterogeneity between GWAS and LD reference). We further show that DENTIST can improve other summary-data-based analyses such as fine-mapping analysis.
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Affiliation(s)
- Wenhan Chen
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Epigenetics Research Laboratory, Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia
| | - Yang Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Ting Qi
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, 310024, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, 310024, China
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, 310024, China.
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, 310024, China.
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Schilder BM, Navarro E, Raj T. Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms. Neurobiol Dis 2021; 163:105580. [PMID: 34871738 PMCID: PMC10101343 DOI: 10.1016/j.nbd.2021.105580] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 11/17/2021] [Accepted: 12/02/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.
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Affiliation(s)
- Brian M Schilder
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; UK Dementia Research Institute at Imperial College London, London, United Kingdom.
| | - Elisa Navarro
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Sección Departamental de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
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Schmiedel BJ, Rocha J, Gonzalez-Colin C, Bhattacharyya S, Madrigal A, Ottensmeier CH, Ay F, Chandra V, Vijayanand P. COVID-19 genetic risk variants are associated with expression of multiple genes in diverse immune cell types. Nat Commun 2021; 12:6760. [PMID: 34799557 PMCID: PMC8604964 DOI: 10.1038/s41467-021-26888-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 10/18/2021] [Indexed: 12/20/2022] Open
Abstract
Common genetic polymorphisms associated with COVID-19 illness can be utilized for discovering molecular pathways and cell types driving disease pathogenesis. Given the importance of immune cells in the pathogenesis of COVID-19 illness, here we assessed the effects of COVID-19-risk variants on gene expression in a wide range of immune cell types. Transcriptome-wide association study and colocalization analysis revealed putative causal genes and the specific immune cell types where gene expression is most influenced by COVID-19-risk variants. Notable examples include OAS1 in non-classical monocytes, DTX1 in B cells, IL10RB in NK cells, CXCR6 in follicular helper T cells, CCR9 in regulatory T cells and ARL17A in TH2 cells. By analysis of transposase accessible chromatin and H3K27ac-based chromatin-interaction maps of immune cell types, we prioritized potentially functional COVID-19-risk variants. Our study highlights the potential of COVID-19 genetic risk variants to impact the function of diverse immune cell types and influence severe disease manifestations.
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Affiliation(s)
| | - Job Rocha
- La Jolla Institute for Immunology, La Jolla, CA, USA
- Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico
| | - Cristian Gonzalez-Colin
- La Jolla Institute for Immunology, La Jolla, CA, USA
- Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico
| | | | | | - Christian H Ottensmeier
- La Jolla Institute for Immunology, La Jolla, CA, USA
- Liverpool Head and Neck Centre, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Ferhat Ay
- La Jolla Institute for Immunology, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Vivek Chandra
- La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Pandurangan Vijayanand
- La Jolla Institute for Immunology, La Jolla, CA, USA.
- Liverpool Head and Neck Centre, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
- Department of Medicine, University of California San Diego, La Jolla, CA, USA.
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68
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Yang D, Li F, Wang J, Dong A, Wu R. A framework to model a web of linkage disequilibria for natural allotetraploid populations. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Dengcheng Yang
- Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China
| | - Fan Li
- Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China
| | - Jing Wang
- Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China
| | - Ang Dong
- Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China
| | - Rongling Wu
- Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China
- Center for Statistical Genetics Departments of Public Health Sciences and Statistics The Pennsylvania State University Hershey PA USA
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69
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A large Canadian cohort provides insights into the genetic architecture of human hair colour. Commun Biol 2021; 4:1253. [PMID: 34737440 PMCID: PMC8568909 DOI: 10.1038/s42003-021-02764-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 10/08/2021] [Indexed: 12/05/2022] Open
Abstract
Hair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.
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70
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Hernández N, Soenksen J, Newcombe P, Sandhu M, Barroso I, Wallace C, Asimit JL. The flashfm approach for fine-mapping multiple quantitative traits. Nat Commun 2021; 12:6147. [PMID: 34686674 PMCID: PMC8536717 DOI: 10.1038/s41467-021-26364-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 10/04/2021] [Indexed: 11/08/2022] Open
Abstract
Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.
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Affiliation(s)
- N Hernández
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J Soenksen
- Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK
- School of Life Sciences, University of Glasgow, Glasgow, UK
| | - P Newcombe
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - M Sandhu
- Dept of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK
| | - I Barroso
- Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK
| | - C Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK
| | - J L Asimit
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
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71
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Li B, Ritchie MD. From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveries. Front Genet 2021; 12:713230. [PMID: 34659337 PMCID: PMC8515949 DOI: 10.3389/fgene.2021.713230] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Accepted: 07/27/2021] [Indexed: 12/12/2022] Open
Abstract
Since their inception, genome-wide association studies (GWAS) have identified more than a hundred thousand single nucleotide polymorphism (SNP) loci that are associated with various complex human diseases or traits. The majority of GWAS discoveries are located in non-coding regions of the human genome and have unknown functions. The valley between non-coding GWAS discoveries and downstream affected genes hinders the investigation of complex disease mechanism and the utilization of human genetics for the improvement of clinical care. Meanwhile, advances in high-throughput sequencing technologies reveal important genomic regulatory roles that non-coding regions play in the transcriptional activities of genes. In this review, we focus on data integrative bioinformatics methods that combine GWAS with functional genomics knowledge to identify genetically regulated genes. We categorize and describe two types of data integrative methods. First, we describe fine-mapping methods. Fine-mapping is an exploratory approach that calibrates likely causal variants underneath GWAS signals. Fine-mapping methods connect GWAS signals to potentially causal genes through statistical methods and/or functional annotations. Second, we discuss gene-prioritization methods. These are hypothesis generating approaches that evaluate whether genetic variants regulate genes via certain genetic regulatory mechanisms to influence complex traits, including colocalization, mendelian randomization, and the transcriptome-wide association study (TWAS). TWAS is a gene-based association approach that investigates associations between genetically regulated gene expression and complex diseases or traits. TWAS has gained popularity over the years due to its ability to reduce multiple testing burden in comparison to other variant-based analytic approaches. Multiple types of TWAS methods have been developed with varied methodological designs and biological hypotheses over the past 5 years. We dive into discussions of how TWAS methods differ in many aspects and the challenges that different TWAS methods face. Overall, TWAS is a powerful tool for identifying complex trait-associated genes. With the advent of single-cell sequencing, chromosome conformation capture, gene editing technologies, and multiplexing reporter assays, we are expecting a more comprehensive understanding of genomic regulation and genetically regulated genes underlying complex human diseases and traits in the future.
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Affiliation(s)
- Binglan Li
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, United States.,Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, United States
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72
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Schilder BM, Raj T. Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants. Hum Mol Genet 2021; 31:888-900. [PMID: 34617105 PMCID: PMC8947317 DOI: 10.1093/hmg/ddab294] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 09/05/2021] [Accepted: 09/11/2021] [Indexed: 12/13/2022] Open
Abstract
Recent genome-wide association studies have identified 78 loci associated with Parkinson’s disease susceptibility but the underlying mechanisms remain largely unclear. To identify likely causal variants for disease risk, we fine-mapped these Parkinson’s-associated loci using four different fine-mapping methods. We then integrated multi-assay cell type–specific epigenomic profiles to pinpoint the likely mechanism of action of each variant, allowing us to identify Consensus single nucleotide polymorphism (SNPs) that disrupt LRRK2 and FCGR2A regulatory elements in microglia, an MBNL2 enhancer in oligodendrocytes, and a DYRK1A enhancer in neurons. This genome-wide functional fine-mapping investigation of Parkinson’s disease substantially advances our understanding of the causal mechanisms underlying this complex disease while avoiding focus on spurious, non-causal mechanisms. Together, these results provide a robust, comprehensive list of the likely causal variants, genes and cell-types underlying Parkinson’s disease risk as demonstrated by consistently greater enrichment of our fine-mapped SNPs relative to lead GWAS SNPs across independent functional impact annotations. In addition, our approach prioritized an average of 3/85 variants per locus as putatively causal, making downstream experimental studies both more tractable and more likely to yield disease-relevant, actionable results. Large-scale studies comparing individuals with Parkinson’s disease to age-matched controls have identified many regions of the genome associated with the disease. However, there is widespread correlation between different parts of the genome, making it difficult to tell which genetic variants cause Parkinson’s and which are simply co-inherited with causal variants. We therefore applied a suite of statistical models to identify the most likely causal genetic variants (i.e. fine-mapping). We then linked these genetic variants with epigenomic and gene expression signatures across a wide variety of tissues and cell types to identify how these variants cause disease. Therefore, this study provides a comprehensive and robust list of cellular and molecular mechanisms that may serve as targets in the development of more effective Parkinson’s therapeutics.
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Affiliation(s)
- Brian M Schilder
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.,Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
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73
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Zhang J, Schumacher FR. Evaluating the estimation of genetic correlation and heritability using summary statistics. Mol Genet Genomics 2021; 296:1221-1234. [PMID: 34586498 PMCID: PMC8550643 DOI: 10.1007/s00438-021-01817-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 08/23/2021] [Indexed: 11/07/2022]
Abstract
While novel statistical methods quantifying the shared heritability of traits and diseases between ancestral distinct populations have been recently proposed, a thorough evaluation of these approaches under differing circumstances remain elusive. Brown et al.2016 proposed the method Popcorn to estimate the shared heritability, i.e. genetic correlation, using only summary statistics. Here, we evaluate Popcorn under several parameters and circumstances: sample size, number of SNPs, sample size of external reference panel, various population pairs, inappropriate external reference panel, and admixed population involved. Our results determined the minimum sample size of the external reference panel, summary statistics, and number of SNPs required to accurately estimate both the genetic correlation and heritability. Moreover, the number of individuals and SNPs required to produce accurate and stable estimates was directly proportional with heritability in Popcorn. Misrepresentation of the reference panel overestimated the genetic correlation by 20% and heritability by 60%. Lastly, applying Popcorn to homogeneous (EUR) and admixed (ASW) populations underestimated the genetic correlation by 15%. Although statistical approaches estimating the shared heritability between ancestral populations will provide novel etiologic insight, caution is required ensuring results are based on the appropriate sample size, number of SNPs, and the generalizability of the reference panel to the discovery populations.
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Affiliation(s)
- Ju Zhang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
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74
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Mukamel RE, Handsaker RE, Sherman MA, Barton AR, Zheng Y, McCarroll SA, Loh PR. Protein-coding repeat polymorphisms strongly shape diverse human phenotypes. Science 2021; 373:1499-1505. [PMID: 34554798 PMCID: PMC8549062 DOI: 10.1126/science.abg8289] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Many human proteins contain domains that vary in size or copy number because of variable numbers of tandem repeats (VNTRs) in protein-coding exons. However, the relationships of VNTRs to most phenotypes are unknown because of difficulties in measuring such repetitive elements. We developed methods to estimate VNTR lengths from whole-exome sequencing data and impute VNTR alleles into single-nucleotide polymorphism haplotypes. Analyzing 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes identified some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. Accounting for large-effect VNTRs further enabled fine-mapping of associations to many more protein-coding mutations in the same genes. These results point to cryptic effects of highly polymorphic common structural variants that have eluded molecular analyses to date.
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Affiliation(s)
- Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Boston, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Bioinformatics and Integrative Genomics Program, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yiming Zheng
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
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75
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A functional genomics pipeline identifies pleiotropy and cross-tissue effects within obesity-associated GWAS loci. Nat Commun 2021; 12:5253. [PMID: 34489471 PMCID: PMC8421397 DOI: 10.1038/s41467-021-25614-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 08/20/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified many disease-associated variants, yet mechanisms underlying these associations remain unclear. To understand obesity-associated variants, we generate gene regulatory annotations in adipocytes and hypothalamic neurons across cellular differentiation stages. We then test variants in 97 obesity-associated loci using a massively parallel reporter assay and identify putatively causal variants that display cell type specific or cross-tissue enhancer-modulating properties. Integrating these variants with gene regulatory information suggests genes that underlie obesity GWAS associations. We also investigate a complex genomic interval on 16p11.2 where two independent loci exhibit megabase-range, cross-locus chromatin interactions. We demonstrate that variants within these two loci regulate a shared gene set. Together, our data support a model where GWAS loci contain variants that alter enhancer activity across tissues, potentially with temporally restricted effects, to impact the expression of multiple genes. This complex model has broad implications for ongoing efforts to understand GWAS.
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76
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Wightman DP, Jansen IE, Savage JE, Shadrin AA, Bahrami S, Holland D, Rongve A, Børte S, Winsvold BS, Drange OK, Martinsen AE, Skogholt AH, Willer C, Bråthen G, Bosnes I, Nielsen JB, Fritsche LG, Thomas LF, Pedersen LM, Gabrielsen ME, Johnsen MB, Meisingset TW, Zhou W, Proitsi P, Hodges A, Dobson R, Velayudhan L, Heilbron K, Auton A, Sealock JM, Davis LK, Pedersen NL, Reynolds CA, Karlsson IK, Magnusson S, Stefansson H, Thordardottir S, Jonsson PV, Snaedal J, Zettergren A, Skoog I, Kern S, Waern M, Zetterberg H, Blennow K, Stordal E, Hveem K, Zwart JA, Athanasiu L, Selnes P, Saltvedt I, Sando SB, Ulstein I, Djurovic S, Fladby T, Aarsland D, Selbæk G, Ripke S, Stefansson K, Andreassen OA, Posthuma D. A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease. Nat Genet 2021; 53:1276-1282. [PMID: 34493870 PMCID: PMC10243600 DOI: 10.1038/s41588-021-00921-z] [Citation(s) in RCA: 412] [Impact Index Per Article: 137.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/16/2021] [Indexed: 12/12/2022]
Abstract
Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.
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Affiliation(s)
- Douglas P Wightman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Iris E Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Alexey A Shadrin
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dominic Holland
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Arvid Rongve
- Department of Research and Innovation, Helse Fonna, Haugesund Hospital, Haugesund, Norway
- The University of Bergen, Institute of Clinical Medicine (K1), Bergen, Norway
| | - Sigrid Børte
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bendik S Winsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Ole Kristian Drange
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Amy E Martinsen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Anne Heidi Skogholt
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Cristen Willer
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Geir Bråthen
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Geriatrics, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ingunn Bosnes
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trust, Namsos, Norway
| | - Jonas Bille Nielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Lars G Fritsche
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Linda M Pedersen
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Maiken E Gabrielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Marianne Bakke Johnsen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tore Wergeland Meisingset
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Petroula Proitsi
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | - Angela Hodges
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | - Richard Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Latha Velayudhan
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | | | | | - Julia M Sealock
- Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chandra A Reynolds
- Department of Psychology, University of California-Riverside, Riverside, CA, USA
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | | | | | | | - Palmi V Jonsson
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jon Snaedal
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Silke Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Margda Waern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Eystein Stordal
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trust, Namsos, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - John-Anker Zwart
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Lavinia Athanasiu
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Ingvild Saltvedt
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Geriatrics, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Sigrid B Sando
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Ingun Ulstein
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Tormod Fladby
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Dag Aarsland
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
- Centre of Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Geir Selbæk
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin, Berlin, Germany
| | | | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands.
- Department of Child and Adolescent Psychiatry and Pediatric Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Center, Amsterdam, the Netherlands.
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77
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Kerimov N, Hayhurst JD, Peikova K, Manning JR, Walter P, Kolberg L, Samoviča M, Sakthivel MP, Kuzmin I, Trevanion SJ, Burdett T, Jupp S, Parkinson H, Papatheodorou I, Yates AD, Zerbino DR, Alasoo K. A compendium of uniformly processed human gene expression and splicing quantitative trait loci. Nat Genet 2021; 53:1290-1299. [PMID: 34493866 PMCID: PMC8423625 DOI: 10.1038/s41588-021-00924-w] [Citation(s) in RCA: 147] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 07/26/2021] [Indexed: 12/15/2022]
Abstract
Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.
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Affiliation(s)
- Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - James D Hayhurst
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Kateryna Peikova
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Jonathan R Manning
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Peter Walter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Liis Kolberg
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Marija Samoviča
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Manoj Pandian Sakthivel
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Ivan Kuzmin
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Stephen J Trevanion
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Tony Burdett
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Simon Jupp
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Helen Parkinson
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Irene Papatheodorou
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Andrew D Yates
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Daniel R Zerbino
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
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78
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Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, Chen WM, Santa Cruz DF, Yang H, Cutler AJ, Crouch DJM, Farber E, Bridges SL, Edberg JC, Kimberly RP, Buckner JH, Deloukas P, Divers J, Dabelea D, Lawrence JM, Marcovina S, Shah AS, Greenbaum CJ, Atkinson MA, Gregersen PK, Oksenberg JR, Pociot F, Rewers MJ, Steck AK, Dunger DB, Wicker LS, Concannon P, Todd JA, Rich SS. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet 2021; 53:962-971. [PMID: 34127860 PMCID: PMC8273124 DOI: 10.1038/s41588-021-00880-5] [Citation(s) in RCA: 113] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 05/05/2021] [Indexed: 12/13/2022]
Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.
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Affiliation(s)
- Catherine C Robertson
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - David Flores Santa Cruz
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Hanzhi Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - S Louis Bridges
- Division of Rheumatology, Department of Medicine, Hospital for Special Surgery, New York, NY, USA
- Division of Rheumatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Jeffrey C Edberg
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert P Kimberly
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jane H Buckner
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Panos Deloukas
- Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jasmin Divers
- Division of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA
| | - Dana Dabelea
- Colorado School of Public Health and Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jean M Lawrence
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Santica Marcovina
- Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA, USA
- Medpace Reference Laboratories, Cincinnati, OH, USA
| | - Amy S Shah
- Cincinnati Children's Hospital Medical Center and the University of Cincinnati, Cincinnati, OH, USA
| | - Carla J Greenbaum
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
- Diabetes Program, Benaroya Research Institute, Seattle, WA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Peter K Gregersen
- Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Jorge R Oksenberg
- Department of Neurology and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
| | - Flemming Pociot
- Department of Pediatrics, Herlev University Hospital, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Type 1 Diabetes Biology, Department of Clinical Research, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - David B Dunger
- Department of Paediatrics, University of Cambridge, Cambridge, UK
- Wellcome Trust Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Patrick Concannon
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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79
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Yonova-Doing E, Calabrese C, Gomez-Duran A, Schon K, Wei W, Karthikeyan S, Chinnery PF, Howson JMM. An atlas of mitochondrial DNA genotype-phenotype associations in the UK Biobank. Nat Genet 2021; 53:982-993. [PMID: 34002094 PMCID: PMC7611844 DOI: 10.1038/s41588-021-00868-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 04/07/2021] [Indexed: 02/03/2023]
Abstract
Mitochondrial DNA (mtDNA) variation in common diseases has been underexplored, partly due to a lack of genotype calling and quality-control procedures. Developing an at-scale workflow for mtDNA variant analyses, we show correlations between nuclear and mitochondrial genomic structures within subpopulations of Great Britain and establish a UK Biobank reference atlas of mtDNA-phenotype associations. A total of 260 mtDNA-phenotype associations were new (P < 1 × 10-5), including rs2853822 /m.8655 C>T (MT-ATP6) with type 2 diabetes, rs878966690 /m.13117 A>G (MT-ND5) with multiple sclerosis, 6 mtDNA associations with adult height, 24 mtDNA associations with 2 liver biomarkers and 16 mtDNA associations with parameters of renal function. Rare-variant gene-based tests implicated complex I genes modulating mean corpuscular volume and mean corpuscular hemoglobin. Seven traits had both rare and common mtDNA associations, where rare variants tended to have larger effects than common variants. Our work illustrates the value of studying mtDNA variants in common complex diseases and lays foundations for future large-scale mtDNA association studies.
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Affiliation(s)
- Ekaterina Yonova-Doing
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Claudia Calabrese
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Aurora Gomez-Duran
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
- Centro de Investigaciones Biológicas "Margarita Salas", Consejo Superior de Investigaciones Científicas (CIB-CSIC), Madrid, Spain
| | - Katherine Schon
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Wei Wei
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Savita Karthikeyan
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Patrick F Chinnery
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK.
| | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK.
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80
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Downregulation by CNNM2 of ATP5MD expression in the 10q24.32 schizophrenia-associated locus involved in impaired ATP production and neurodevelopment. NPJ SCHIZOPHRENIA 2021; 7:27. [PMID: 34021155 PMCID: PMC8139961 DOI: 10.1038/s41537-021-00159-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 04/21/2021] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR) <1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus. The Atp5md knockout (KO) in mice was associated with abnormal startle reflex and gait, and ATP5MD knockdown (KD) in human induced pluripotent stem cell-derived neurons disrupted the neural development and mitochondrial respiration and ATP production. Moreover, CNNM2-rs1926032 KO could induce downregulation of ATP5MD expression and disruptions of mitochondrial respiration and ATP production. This study constitutes an important mechanistic component that links schizophrenia-associated CNNM2 regions to disruption in energy adenosine system modulation and neuronal function by long-distance chromatin domain downregulation of ATP5MD. This pathogenic mechanism provides therapeutic implications for schizophrenia.
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81
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Banerjee S, Simonetti FL, Detrois KE, Kaphle A, Mitra R, Nagial R, Söding J. Tejaas: reverse regression increases power for detecting trans-eQTLs. Genome Biol 2021; 22:142. [PMID: 33957961 PMCID: PMC8101255 DOI: 10.1186/s13059-021-02361-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 04/22/2021] [Indexed: 12/18/2022] Open
Abstract
Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.
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Affiliation(s)
- Saikat Banerjee
- Quantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, 37077, Germany.
| | - Franco L Simonetti
- Quantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, 37077, Germany
| | - Kira E Detrois
- Quantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, 37077, Germany.,Georg-August University, Göttingen, 37075, Germany
| | - Anubhav Kaphle
- Quantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, 37077, Germany.,Georg-August University, Göttingen, 37075, Germany
| | | | | | - Johannes Söding
- Quantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, 37077, Germany. .,Campus-Institut Data Science (CIDAS), University of Göttingen, Göttingen, 37073, Germany. .,Cluster of Excellence "Multiscale Bioimaging" (MBExC), University of Göttingen, Göttingen, 37075, Germany.
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82
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Said MA, Yeung MW, van de Vegte YJ, Benjamins JW, Dullaart RPF, Ruotsalainen S, Ripatti S, Natarajan P, Juarez-Orozco LE, Verweij N, van der Harst P. Genome-Wide Association Study and Identification of a Protective Missense Variant on Lipoprotein(a) Concentration: Protective Missense Variant on Lipoprotein(a) Concentration-Brief Report. Arterioscler Thromb Vasc Biol 2021; 41:1792-1800. [PMID: 33730874 DOI: 10.1161/atvbaha.120.315300] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- M Abdullah Said
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Ming Wai Yeung
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Yordi J van de Vegte
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Jan Walter Benjamins
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Robin P F Dullaart
- Department of Endocrinology (R.P.F.D.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland HiLIFE (S. Ruotsalainen, S. Ripatti), University of Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland HiLIFE (S. Ruotsalainen, S. Ripatti), University of Helsinki, Finland.,Department of Public Health (S. Ripatti), University of Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA (S. Ripatti, P.N.)
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA (S. Ripatti, P.N.).,Department of Medicine, Harvard Medical School, Boston, MA (P.N.).,Cardiovascular Research Center, Massachusetts General Hospital, Boston (P.N.)
| | - Luis Eduardo Juarez-Orozco
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands.,Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, University of Utrecht, the Netherlands (L.E.J.-O., P.v.d.H.)
| | - Niek Verweij
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - P van der Harst
- Department of Cardiology (M.A.S., M.W.Y., Y.J.v.d.V., J.W.B., L.E.J.-O., N.V., P.v.d.H.), University Medical Center Groningen, University of Groningen, the Netherlands.,Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, University of Utrecht, the Netherlands (L.E.J.-O., P.v.d.H.)
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83
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Genome-wide enhancer maps link risk variants to disease genes. Nature 2021; 593:238-243. [PMID: 33828297 PMCID: PMC9153265 DOI: 10.1038/s41586-021-03446-x] [Citation(s) in RCA: 267] [Impact Index Per Article: 89.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 03/11/2021] [Indexed: 02/07/2023]
Abstract
Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease1. Many of the underlying causal variants may affect enhancers2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types4. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.
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84
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Novikova G, Andrews SJ, Renton AE, Marcora E. Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer's disease risk. Mol Neurodegener 2021; 16:27. [PMID: 33882988 PMCID: PMC8061035 DOI: 10.1186/s13024-021-00449-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 04/13/2021] [Indexed: 02/06/2023] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia, affecting millions of people worldwide; however, no disease-modifying treatments are currently available. Genome-wide association studies (GWASs) have identified more than 40 loci associated with AD risk. However, most of the disease-associated variants reside in non-coding regions of the genome, making it difficult to elucidate how they affect disease susceptibility. Nonetheless, identification of the regulatory elements, genes, pathways and cell type/tissue(s) impacted by these variants to modulate AD risk is critical to our understanding of disease pathogenesis and ability to develop effective therapeutics. In this review, we provide an overview of the methods and approaches used in the field to identify the functional effects of AD risk variants in the causal path to disease risk modification as well as describe the most recent findings. We first discuss efforts in cell type/tissue prioritization followed by recent progress in candidate causal variant and gene nomination. We discuss statistical methods for fine-mapping as well as approaches that integrate multiple levels of evidence, such as epigenomic and transcriptomic data, to identify causal variants and risk mechanisms of AD-associated loci. Additionally, we discuss experimental approaches and data resources that will be needed to validate and further elucidate the effects of these variants and genes on biological pathways, cellular phenotypes and disease risk. Finally, we discuss future steps that need to be taken to ensure that AD GWAS functional mapping efforts lead to novel findings and bring us closer to finding effective treatments for this devastating disease.
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Affiliation(s)
- Gloriia Novikova
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shea J Andrews
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alan E Renton
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Edoardo Marcora
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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85
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Dietary Habit Is Associated with Depression and Intelligence: An Observational and Genome-Wide Environmental Interaction Analysis in the UK Biobank Cohort. Nutrients 2021; 13:nu13041150. [PMID: 33807197 PMCID: PMC8067152 DOI: 10.3390/nu13041150] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 03/26/2021] [Accepted: 03/27/2021] [Indexed: 12/19/2022] Open
Abstract
Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.
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86
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Novikova G, Kapoor M, Tcw J, Abud EM, Efthymiou AG, Chen SX, Cheng H, Fullard JF, Bendl J, Liu Y, Roussos P, Björkegren JL, Liu Y, Poon WW, Hao K, Marcora E, Goate AM. Integration of Alzheimer's disease genetics and myeloid genomics identifies disease risk regulatory elements and genes. Nat Commun 2021; 12:1610. [PMID: 33712570 PMCID: PMC7955030 DOI: 10.1038/s41467-021-21823-y] [Citation(s) in RCA: 107] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 02/10/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer's disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility.
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Affiliation(s)
- Gloriia Novikova
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manav Kapoor
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julia Tcw
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edsel M Abud
- Department of Neurobiology & Behavior, University of California Irvine, Irvine, CA, USA
- Sue and Bill Gross Stem Cell Research Center, University of California Irvine, Irvine, CA, USA
| | - Anastasia G Efthymiou
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven X Chen
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yiyuan Liu
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan Lm Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Wayne W Poon
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edoardo Marcora
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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87
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Gerard D. Pairwise linkage disequilibrium estimation for polyploids. Mol Ecol Resour 2021; 21:1230-1242. [PMID: 33559321 DOI: 10.1111/1755-0998.13349] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/18/2021] [Accepted: 02/01/2021] [Indexed: 12/31/2022]
Abstract
Many tasks in statistical genetics involve pairwise estimation of linkage disequilibrium (LD). The study of LD in diploids is mature. However, in polyploids, the field lacks a comprehensive characterization of LD. Polyploids also exhibit greater levels of genotype uncertainty than diploids, yet no methods currently exist to estimate LD in polyploids in the presence of such genotype uncertainty. Furthermore, most LD estimation methods do not quantify the level of uncertainty in their LD estimates. Our study contains three major contributions. (i) We characterize haplotypic and composite measures of LD in polyploids. These composite measures of LD turn out to be functions of common statistical measures of association. (ii) We derive procedures to estimate haplotypic and composite LD in polyploids in the presence of genotype uncertainty. We do this by estimating LD directly from genotype likelihoods, which may be obtained from many genotyping platforms. (iii) We derive standard errors of all LD estimators that we discuss. We validate our methods on both real and simulated data. Our methods are implemented in the R package ldsep, available on the Comprehensive R Archive Network https://cran.r-project.org/package=ldsep.
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Affiliation(s)
- David Gerard
- Department of Mathematics and Statistics, American University, Washington, DC, USA
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88
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Schwartzentruber J, Cooper S, Liu JZ, Barrio-Hernandez I, Bello E, Kumasaka N, Young AMH, Franklin RJM, Johnson T, Estrada K, Gaffney DJ, Beltrao P, Bassett A. Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes. Nat Genet 2021; 53:392-402. [PMID: 33589840 PMCID: PMC7610386 DOI: 10.1038/s41588-020-00776-w] [Citation(s) in RCA: 235] [Impact Index Per Article: 78.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 12/23/2020] [Indexed: 01/30/2023]
Abstract
Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.
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Affiliation(s)
- Jeremy Schwartzentruber
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK.
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - Sarah Cooper
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Erica Bello
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Adam M H Young
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Robin J M Franklin
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Toby Johnson
- Target Sciences-R&D, GSK Medicines Research Centre, Stevenage, UK
| | | | - Daniel J Gaffney
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
- Genomics Plc, Oxford, UK
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Andrew Bassett
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
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89
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Rüeger S, Hammer C, Loetscher A, McLaren PJ, Lawless D, Naret O, Khanna N, Bernasconi E, Cavassini M, Günthard HF, Kahlert CR, Rauch A, Depledge DP, Morfopoulou S, Breuer J, Zdobnov E, Fellay J. The influence of human genetic variation on Epstein-Barr virus sequence diversity. Sci Rep 2021; 11:4586. [PMID: 33633271 PMCID: PMC7907281 DOI: 10.1038/s41598-021-84070-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 02/11/2021] [Indexed: 02/07/2023] Open
Abstract
Epstein-Barr virus (EBV) is one of the most common viruses latently infecting humans. Little is known about the impact of human genetic variation on the large inter-individual differences observed in response to EBV infection. To search for a potential imprint of host genomic variation on the EBV sequence, we jointly analyzed paired viral and human genomic data from 268 HIV-coinfected individuals with CD4 + T cell count < 200/mm3 and elevated EBV viremia. We hypothesized that the reactivated virus circulating in these patients could carry sequence variants acquired during primary EBV infection, thereby providing a snapshot of early adaptation to the pressure exerted on EBV by the individual immune response. We searched for associations between host and pathogen genetic variants, taking into account human and EBV population structure. Our analyses revealed significant associations between human and EBV sequence variation. Three polymorphic regions in the human genome were found to be associated with EBV variation: one at the amino acid level (BRLF1:p.Lys316Glu); and two at the gene level (burden testing of rare variants in BALF5 and BBRF1). Our findings confirm that jointly analyzing host and pathogen genomes can identify sites of genomic interactions, which could help dissect pathogenic mechanisms and suggest new therapeutic avenues.
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Affiliation(s)
- Sina Rüeger
- School of Life Sciences, EPFL, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Alexis Loetscher
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Paul J McLaren
- JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
| | - Dylan Lawless
- School of Life Sciences, EPFL, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olivier Naret
- School of Life Sciences, EPFL, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Nina Khanna
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christian R Kahlert
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St.Gallen, St.Gallen, Switzerland
- Childrens Hospital of Eastern Switzerland, St. Gallen, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Daniel P Depledge
- Division of Infection and Immunity, University College London, London, UK
| | - Sofia Morfopoulou
- Division of Infection and Immunity, University College London, London, UK
| | - Judith Breuer
- Division of Infection and Immunity, University College London, London, UK
| | - Evgeny Zdobnov
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Jacques Fellay
- School of Life Sciences, EPFL, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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90
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Foley CN, Staley JR, Breen PG, Sun BB, Kirk PDW, Burgess S, Howson JMM. A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits. Nat Commun 2021; 12:764. [PMID: 33536417 PMCID: PMC7858636 DOI: 10.1038/s41467-020-20885-8] [Citation(s) in RCA: 159] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Accepted: 12/17/2020] [Indexed: 01/30/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of genomic regions affecting complex diseases. The next challenge is to elucidate the causal genes and mechanisms involved. One approach is to use statistical colocalization to assess shared genetic aetiology across multiple related traits (e.g. molecular traits, metabolic pathways and complex diseases) to identify causal pathways, prioritize causal variants and evaluate pleiotropy. We propose HyPrColoc (Hypothesis Prioritisation for multi-trait Colocalization), an efficient deterministic Bayesian algorithm using GWAS summary statistics that can detect colocalization across vast numbers of traits simultaneously (e.g. 100 traits can be jointly analysed in around 1 s). We perform a genome-wide multi-trait colocalization analysis of coronary heart disease (CHD) and fourteen related traits, identifying 43 regions in which CHD colocalized with ≥1 trait, including 5 previously unknown CHD loci. Across the 43 loci, we further integrate gene and protein expression quantitative trait loci to identify candidate causal genes.
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Affiliation(s)
- Christopher N Foley
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, CB2 0SR, UK.
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.
| | - James R Staley
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Philip G Breen
- School of Mathematics, University of Edinburgh, Kings Buildings, Edinburgh, EH9 3JZ, UK
| | - Benjamin B Sun
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Paul D W Kirk
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, CB2 0SR, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Joanna M M Howson
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
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91
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Abstract
Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.
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92
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Barbeira AN, Bonazzola R, Gamazon ER, Liang Y, Park Y, Kim-Hellmuth S, Wang G, Jiang Z, Zhou D, Hormozdiari F, Liu B, Rao A, Hamel AR, Pividori MD, Aguet F, Bastarache L, Jordan DM, Verbanck M, Do R, Stephens M, Ardlie K, McCarthy M, Montgomery SB, Segrè AV, Brown CD, Lappalainen T, Wen X, Im HK. Exploiting the GTEx resources to decipher the mechanisms at GWAS loci. Genome Biol 2021; 22:49. [PMID: 33499903 PMCID: PMC7836161 DOI: 10.1186/s13059-020-02252-4] [Citation(s) in RCA: 130] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022] Open
Abstract
The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.
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Affiliation(s)
- Alvaro N Barbeira
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Rodrigo Bonazzola
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Eric R Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Data Science Institute, Vanderbilt University, Nashville, TN, USA
- Clare Hall, University of Cambridge, Cambridge, UK
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Yanyu Liang
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - YoSon Park
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Sarah Kim-Hellmuth
- Statistical Genetics, Max Planck Institute of Psychiatry, Munich, Germany
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Gao Wang
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Zhuoxun Jiang
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Dan Zhou
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Farhad Hormozdiari
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Boxiang Liu
- Department of Biology, Stanford University, Stanford, 94305, CA, USA
| | - Abhiram Rao
- Department of Biology, Stanford University, Stanford, 94305, CA, USA
| | - Andrew R Hamel
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ocular Genomics Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Milton D Pividori
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - François Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University, Nashville, TN, USA
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Daniel M Jordan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marie Verbanck
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Université de Paris - EA 7537 BIOSTM, Paris, France
| | - Ron Do
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew Stephens
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Kristin Ardlie
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Stephen B Montgomery
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Ayellet V Segrè
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ocular Genomics Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Christopher D Brown
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Xiaoquan Wen
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
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93
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Jiang X, Dellepiane N, Pairo-Castineira E, Boutin T, Kumar Y, Bickmore WA, Vitart V. Fine-mapping and cell-specific enrichment at corneal resistance factor loci prioritize candidate causal regulatory variants. Commun Biol 2020; 3:762. [PMID: 33311554 PMCID: PMC7732848 DOI: 10.1038/s42003-020-01497-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 11/13/2020] [Indexed: 01/08/2023] Open
Abstract
Corneal resistance factor (CRF) is altered during corneal diseases progression. Genome-wide-association studies (GWAS) indicated potential CRF and disease genetics overlap. Here, we characterise 135 CRF loci following GWAS in 76029 UK Biobank participants. Enrichment of extra-cellular matrix gene-sets, genetic correlation with corneal thickness (70% (SE = 5%)), reported keratoconus risk variants at 13 loci, all support relevance to corneal stroma biology. Fine-mapping identifies a subset of 55 highly likely causal variants, 91% of which are non-coding. Genomic features enrichments, using all associated variants, also indicate prominent regulatory causal role. We newly established open chromatin landscapes in two widely-used human cornea immortalised cell lines using ATAC-seq. Variants associated with CRF were significantly enriched in regulatory regions from the corneal stroma-derived cell line and enrichment increases to over 5 fold for variants prioritised by fine-mapping-including at GAS7, SMAD3 and COL6A1 loci. Our analysis generates many hypotheses for future functional validation of aetiological mechanisms.
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Affiliation(s)
- Xinyi Jiang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Nefeli Dellepiane
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Erola Pairo-Castineira
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Yatendra Kumar
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Wendy A Bickmore
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH42XU, UK.
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94
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Weissbrod O, Hormozdiari F, Benner C, Cui R, Ulirsch J, Gazal S, Schoech AP, van de Geijn B, Reshef Y, Márquez-Luna C, O'Connor L, Pirinen M, Finucane HK, Price AL. Functionally informed fine-mapping and polygenic localization of complex trait heritability. Nat Genet 2020; 52:1355-1363. [PMID: 33199916 PMCID: PMC7710571 DOI: 10.1038/s41588-020-00735-5] [Citation(s) in RCA: 149] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 10/02/2020] [Indexed: 01/16/2023]
Abstract
Fine-mapping aims to identify causal variants impacting complex traits. We propose PolyFun, a computationally scalable framework to improve fine-mapping accuracy by leveraging functional annotations across the entire genome-not just genome-wide-significant loci-to specify prior probabilities for fine-mapping methods such as SuSiE or FINEMAP. In simulations, PolyFun + SuSiE and PolyFun + FINEMAP were well calibrated and identified >20% more variants with a posterior causal probability >0.95 than identified in their nonfunctionally informed counterparts. In analyses of 49 UK Biobank traits (average n = 318,000), PolyFun + SuSiE identified 3,025 fine-mapped variant-trait pairs with posterior causal probability >0.95, a >32% improvement versus SuSiE. We used posterior mean per-SNP heritabilities from PolyFun + SuSiE to perform polygenic localization, constructing minimal sets of common SNPs causally explaining 50% of common SNP heritability; these sets ranged in size from 28 (hair color) to 3,400 (height) to 2 million (number of children). In conclusion, PolyFun prioritizes variants for functional follow-up and provides insights into complex trait architectures.
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Affiliation(s)
- Omer Weissbrod
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christian Benner
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ran Cui
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jacob Ulirsch
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Cambridge, MA, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Armin P Schoech
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Bryce van de Geijn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yakir Reshef
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Carla Márquez-Luna
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Luke O'Connor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Hilary K Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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95
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Knutson KA, Deng Y, Pan W. Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data. Neuroimage 2020; 223:117347. [PMID: 32898681 PMCID: PMC7778364 DOI: 10.1016/j.neuroimage.2020.117347] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Revised: 08/24/2020] [Accepted: 08/28/2020] [Indexed: 02/06/2023] Open
Abstract
Recent evidence suggests the existence of many undiscovered heritable brain phenotypes involved in Alzheimer's Disease (AD) pathogenesis. This finding necessitates methods for the discovery of causal brain changes in AD that integrate Magnetic Resonance Imaging measures and genotypic data. However, existing approaches for causal inference in this setting, such as the univariate Imaging Wide Association Study (UV-IWAS), suffer from inconsistent effect estimation and inflated Type I errors in the presence of genetic pleiotropy, the phenomenon in which a variant affects multiple causal intermediate risk phenotypes. In this study, we implement a multivariate extension to the IWAS model, namely MV-IWAS, to consistently estimate and test for the causal effects of multiple brain imaging endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the presence of pleiotropic and possibly correlated SNPs. We further extend MV-IWAS to incorporate variant-specific direct effects on AD, analogous to the existing Egger regression Mendelian Randomization approach, which allows for testing of remaining pleiotropy after adjusting for multiple intermediate pathways. We propose a convenient approach for implementing MV-IWAS that solely relies on publicly available GWAS summary data and a reference panel. Through simulations with either individual-level or summary data, we demonstrate the well controlled Type I errors and superior power of MV-IWAS over UV-IWAS in the presence of pleiotropic SNPs. We apply the summary statistic based tests to 1578 heritable imaging derived phenotypes (IDPs) from the UK Biobank. MV-IWAS detected numerous IDPs as possible false positives by UV-IWAS while uncovering many additional causal neuroimaging phenotypes in AD which are strongly supported by the existing literature.
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Affiliation(s)
- Katherine A Knutson
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota United States
| | - Yangqing Deng
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota United States
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota United States.
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96
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Hutchinson A, Asimit J, Wallace C. Fine-mapping genetic associations. Hum Mol Genet 2020; 29:R81-R88. [PMID: 32744321 PMCID: PMC7733401 DOI: 10.1093/hmg/ddaa148] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 06/04/2020] [Accepted: 07/09/2020] [Indexed: 02/07/2023] Open
Abstract
Whilst thousands of genetic variants have been associated with human traits, identifying the subset of those variants that are causal requires a further 'fine-mapping' step. We review the basic fine-mapping approach, which is computationally fast and requires only summary data, but depends on an assumption of a single causal variant per associated region which is recognized as biologically unrealistic. We discuss different ways that the approach has been built upon to accommodate multiple causal variants in a region and to incorporate additional layers of functional annotation data. We further review methods for simultaneous fine-mapping of multiple datasets, either exploiting different linkage disequilibrium (LD) structures across ancestries or borrowing information between distinct but related traits. Finally, we look to the future and the opportunities that will be offered by increasingly accurate maps of causal variants for a multitude of human traits.
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Affiliation(s)
- Anna Hutchinson
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Cambridge CB2 0SR, UK
| | - Jennifer Asimit
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Cambridge CB2 0SR, UK
| | - Chris Wallace
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Cambridge CB2 0SR, UK
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 0AW, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 2QQ, UK
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97
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Hebbar P, Abubaker JA, Abu-Farha M, Alsmadi O, Elkum N, Alkayal F, John SE, Channanath A, Iqbal R, Pitkaniemi J, Tuomilehto J, Sladek R, Al-Mulla F, Thanaraj TA. Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population. Hum Genet 2020; 140:505-528. [PMID: 32902719 PMCID: PMC7889551 DOI: 10.1007/s00439-020-02222-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 09/01/2020] [Indexed: 02/07/2023]
Abstract
While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.
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Affiliation(s)
- Prashantha Hebbar
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.,Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | | | | | - Naser Elkum
- Sidra Medical and Research Center, Doha, Qatar
| | - Fadi Alkayal
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | - Sumi Elsa John
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | | | - Rasheeba Iqbal
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | - Janne Pitkaniemi
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
| | - Robert Sladek
- McGill University and Genome Quebec Innovation Centre, Montreal, Canada
| | - Fahd Al-Mulla
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
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98
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Jakobson CM, Jarosz DF. What Has a Century of Quantitative Genetics Taught Us About Nature's Genetic Tool Kit? Annu Rev Genet 2020; 54:439-464. [PMID: 32897739 DOI: 10.1146/annurev-genet-021920-102037] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The complexity of heredity has been appreciated for decades: Many traits are controlled not by a single genetic locus but instead by polymorphisms throughout the genome. The importance of complex traits in biology and medicine has motivated diverse approaches to understanding their detailed genetic bases. Here, we focus on recent systematic studies, many in budding yeast, which have revealed that large numbers of all kinds of molecular variation, from noncoding to synonymous variants, can make significant contributions to phenotype. Variants can affect different traits in opposing directions, and their contributions can be modified by both the environment and the epigenetic state of the cell. The integration of prospective (synthesizing and analyzing variants) and retrospective (examining standing variation) approaches promises to reveal how natural selection shapes quantitative traits. Only by comprehensively understanding nature's genetic tool kit can we predict how phenotypes arise from the complex ensembles of genetic variants in living organisms.
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Affiliation(s)
- Christopher M Jakobson
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California 94305, USA;
| | - Daniel F Jarosz
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California 94305, USA; .,Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
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99
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Kiel DP, Kemp JP, Rivadeneira F, Westendorf JJ, Karasik D, Duncan EL, Imai Y, Müller R, Flannick J, Bonewald L, Burtt N. The Musculoskeletal Knowledge Portal: Making Omics Data Useful to the Broader Scientific Community. J Bone Miner Res 2020; 35:1626-1633. [PMID: 32777102 PMCID: PMC8114232 DOI: 10.1002/jbmr.4147] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/30/2020] [Accepted: 07/30/2020] [Indexed: 12/15/2022]
Abstract
The development of high-throughput genotyping technologies and large biobank collections, complemented with rapid methodological advances in statistical genetics, has enabled hypothesis-free genome-wide association studies (GWAS), which have identified hundreds of genetic variants across many loci associated with musculoskeletal conditions. Similarly, basic scientists have valuable molecular cellular and animal data based on musculoskeletal disease that would be enhanced by being able to determine the human translation of their findings. By integrating these large-scale human genomic musculoskeletal datasets with complementary evidence from model organisms, new and existing genetic loci can be statistically fine-mapped to plausibly causal variants, candidate genes, and biological pathways. Genes and pathways identified using this approach can be further prioritized as drug targets, including side-effect profiling and the potential for new indications. To bring together these big data, and to realize the vision of creating a knowledge portal, the International Federation of Musculoskeletal Research Societies (IFMRS) established a working group to collaborate with scientists from the Broad Institute to create the Musculoskeletal Knowledge Portal (MSK-KP)(http://mskkp.org/). The MSK consolidates omics datasets from humans, cellular experiments, and model organisms into a central repository that can be accessed by researchers. The vision of the MSK-KP is to enable better understanding of the biological mechanisms underlying musculoskeletal disease and apply this knowledge to identify and develop new disease interventions. © 2020 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Douglas P Kiel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife Boston, MA, USA.,Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT & Harvard, Boston and Cambridge, MA, USA
| | - John P Kemp
- The University of Queensland Diamantina Institute, University of Queensland, Woolloongabba, QLD 4102, Australia.,Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - David Karasik
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife Boston, MA, USA.,Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Emma L Duncan
- Department of Twin Research & Genetic Epidemiology, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College, London, UK
| | - Yuuki Imai
- Division of Integrated Pathophysiology, Proteo-Science Center, Department of Pathophysiology, Graduate School of Medicine, and Division of Laboratory Animal Research, Advanced Research Support Center, Ehime University, Toon, Ehime, Japan
| | - Ralph Müller
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Jason Flannick
- Harvard Medical School, Boston, MA, USA.,Division of Genetics and Genomics at Boston Children's Hospital, Boston, MA, USA
| | - Lynda Bonewald
- Indiana Center for Musculoskeletal Health, Indiana University, Indianapolis, IN, USA
| | - Noël Burtt
- Broad Institute of MIT & Harvard, Boston and Cambridge, MA, USA
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100
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Lau A, So HC. Turning genome-wide association study findings into opportunities for drug repositioning. Comput Struct Biotechnol J 2020; 18:1639-1650. [PMID: 32670504 PMCID: PMC7334463 DOI: 10.1016/j.csbj.2020.06.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 06/05/2020] [Accepted: 06/05/2020] [Indexed: 02/02/2023] Open
Abstract
Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. Numerous computational approaches to drug repositioning have been developed, but methods utilizing genome-wide association studies (GWASs) data are less explored. The past decade has observed a massive growth in the amount of data from GWAS; the rich information contained in GWAS has great potential to guide drug repositioning or discovery. While multiple tools are available for finding the most relevant genes from GWAS hits, searching for top susceptibility genes is only one way to guide repositioning, which has its own limitations. Here we provide a comprehensive review of different computational approaches that employ GWAS data to guide drug repositioning. These methods include selecting top candidate genes from GWAS as drug targets, deducing drug candidates based on drug-drug and disease-disease similarities, searching for reversed expression profiles between drugs and diseases, pathway-based methods as well as approaches based on analysis of biological networks. Each method is illustrated with examples, and their respective strengths and limitations are discussed. We also discussed several areas for future research.
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Affiliation(s)
- Alexandria Lau
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Hon-Cheong So
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Zoology Institute of Zoology and The Chinese University of Hong Kong, Hong Kong SAR, China
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
- Margaret K.L. Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong SAR, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
- Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Branch of the Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Corresponding author at: School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
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