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.
Original language | English |
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Pages (from-to) | 223-231 |
Number of pages | 9 |
Journal | American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics |
Volume | 180 |
Issue number | 3 |
DOIs | |
Publication status | Published - Apr 1 2019 |
Bibliographical note
Funding Information:We wish to thank all patients and their support staff, and all healthy volunteers for participating in the data collection on which this manuscript is based. Recruitment, genotyping, and analysis were supported by Science Foundation Ireland grants (12/IP/1670, 12/IP/1359, and 08/IN.1/B1916), US National Institutes of Health grants (R01-MH083094 and R01-MH041953) and the Wellcome Trust Case Control Consortium 2 project grant (085475/B/08/Z). We thank EMI author Yu Qian for providing a script to convert EMI cluster files to plink format. CSHL funding was from a generous gift of The Stanley Family. We acknowledge the support of the Trinity Biobank in providing control samples for this analysis.
Funding Information:
National Institutes of Health, Grant/Award Numbers: R01-MH041953, R01-MH083094; Science Foundation Ireland, Grant/Award Numbers: 08/IN.1/B1916, 12/IP/1359, 12/ IP/1670; Wellcome Trust, Grant/Award Number: 085475/B/08/Z
Funding Information:
We wish to thank all patients and their support staff, and all healthy volunteers for participating in the data collection on which this manuscript is based. Recruitment, genotyping, and analysis were supported by Science Foundation Ireland grants (12/IP/1670, 12/IP/1359, and 08/IN.1/ B1916), US National Institutes of Health grants (R01-MH083094 and R01-MH041953) and the Wellcome Trust Case Control Consortium 2 project grant (085475/B/08/Z). We thank EMI author Yu Qian for providing a script to convert EMI cluster files to plink format. CSHL funding was from a generous gift of The Stanley Family. We acknowledge the support of the Trinity Biobank in providing control samples for this analysis.
Publisher Copyright:
© 2019 Wiley Periodicals, Inc.
ASJC Scopus Subject Areas
- Genetics(clinical)
- Psychiatry and Mental health
- Cellular and Molecular Neuroscience