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

Am J Med Genet B Neuropsychiatr Genet. 2019 Apr;180(3):223-231. doi: 10.1002/ajmg.b.32716. Epub 2019 Feb 23.

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.

Keywords: GWAS; IBD mapping; rare variants.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Case-Control Studies
  • Chromosome Mapping
  • DNA Copy Number Variations
  • Databases, Genetic
  • Exome / genetics
  • Exome Sequencing / methods*
  • Female
  • Genetic Predisposition to Disease / genetics
  • Genome-Wide Association Study / methods
  • Genotype
  • Haplotypes
  • Humans
  • Male
  • Middle Aged
  • Risk Factors
  • Schizophrenia / genetics*
  • Schizophrenia / metabolism
  • Sequence Analysis, DNA / methods*