A general framework for identifying oligogenic combinations of rare variants in complex disorders

Vijay Kumar Pounraja, Santhosh Girirajan

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Genetic studies of complex disorders such as autism and intellectual disability (ID) are often based on enrichment of individual rare variants or their aggregate burden in affected individuals compared to controls. However, these studies overlook the influence of combinations of rare variants that may not be deleterious on their own due to statistical challenges resulting from rarity and combinatorial explosion when enumerating variant combinations, limiting our ability to study oligogenic basis for these disorders. Here, we present RareComb, a framework that combines the Apriori algorithm and statistical inference to identify specific combinations of mutated genes associated with complex phenotypes. RareComb overcomes computational barriers and exhaustively evaluates variant combinations to identify nonadditive relationships between simultaneously mutated genes. Using RareComb, we analyzed 6189 individuals with autism and identified 718 combinations significantly associated with ID, and carriers of these combinations showed lower IQ than expected in an independent cohort of 1878 individuals. These combinations were enriched for nervous system genes such as NIN and NGF, showed complex inheritance patterns, and were depleted in unaffected siblings. We found that an affected individual can carry many oligogenic combinations, each contributing to the same phenotype or distinct phenotypes at varying effect sizes. We also used this framework to identify combinations associated with multiple comorbid phenotypes, including mutations of COL28A1 and MFSD2B for ID and schizophrenia and ABCA4, DNAH10 and MC1R for ID and anxiety/depression. Our framework identifies a key component of missing heritability and provides a novel paradigm to untangle the genetic architecture of complex disorders.

Original languageEnglish (US)
Pages (from-to)904-915
Number of pages12
JournalGenome research
Volume32
Issue number5
DOIs
StatePublished - May 1 2022

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

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