The schizophrenia genetics knowledgebase: a comprehensive update of findings from candidate gene studies.

Journal: Translational psychiatry

Volume: 9

Issue: 1

Year of Publication: 2020

Affiliated Institutions:  Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia. chl@pitt.edu. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia. Laboratory for Statistical Analysis, RIKEN Center for Integrative, Medical Sciences, Yokohama, Japan. Institute of Mental Health, Peking University Sixth Hospital, Beijing, China. Department of Psychiatry, The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China. Department of Genetic Epidemiology, SNP Genetics, Inc., Seoul, Korea. Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Japan. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan. Soon Chun Hyang University Hospital, Seoul, Korea. Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China. Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia. chad.bousman@ucalgary.ca.

Abstract summary 

Over 3000 candidate gene association studies have been performed to elucidate the genetic underpinnings of schizophrenia. However, a comprehensive evaluation of these studies' findings has not been undertaken since the decommissioning of the schizophrenia gene (SzGene) database in 2011. As such, we systematically identified and carried out random-effects meta-analyses for all polymorphisms with four or more independent studies in schizophrenia along with a series of expanded meta-analyses incorporating published and unpublished genome-wide association (GWA) study data. Based on 550 meta-analyses, 11 SNPs in eight linkage disequilibrium (LD) independent loci showed Bonferroni-significant associations with schizophrenia. Expanded meta-analyses identified an additional 10 SNPs, for a total of 21 Bonferroni-significant SNPs in 14 LD-independent loci. Three of these loci (MTHFR, DAOA, ARVCF) had never been implicated by a schizophrenia GWA study. In sum, the present study has provided a comprehensive summary of the current schizophrenia genetics knowledgebase and has made available all the collected data as a resource for the research community.

Authors & Co-authors:  Liu Chenxing C Kanazawa Tetsufumi T Tian Ye Y Mohamed Saini Suriati S Mancuso Serafino S Mostaid Md Shaki MS Takahashi Atsushi A Zhang Dai D Zhang Fuquan F Yu Hao H Doo Shin Hyoung H Sub Cheong Hyun H Ikeda Masashi M Kubo Michiaki M Iwata Nakao N Woo Sung-Il SI Yue Weihua W Kamatani Yoichiro Y Shi Yongyong Y Li Zhiqiang Z Everall Ian I Pantelis Christos C Bousman Chad C

Study Outcome 

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Statistics
Citations :  Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–427. doi: 10.1038/nature13595.
Authors :  23
Identifiers
Doi : 205
SSN : 2158-3188
Study Population
Male,Female
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Publication Country
United States