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

Harold, Denise, Connolly, Siobhan, Riley, Brien P., Kendler, Kenneth S., McCarthy, Shane E., McCombie, William R., Richards, Alex, Owen, Michael J. ORCID: https://orcid.org/0000-0003-4798-0862, O'Donovan, Michael C. ORCID: https://orcid.org/0000-0001-7073-2379, Walters, James ORCID: https://orcid.org/0000-0002-6980-4053, Donohoe, Gary, Gill, Michael, Corvin, Aiden, Morris, Derek W. and Hopkins, Lucinda 2019. Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 180 (3) , pp. 223-231. 10.1002/ajmg.b.32716

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Abstract

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

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Publisher:	Wiley
ISSN:	1552-4841
Date of First Compliant Deposit:	14 March 2019
Date of Acceptance:	3 December 2018
Last Modified:	13 Nov 2024 20:30
URI:	https://orca.cardiff.ac.uk/id/eprint/120710

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