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.

中文翻译：

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识别复杂疾病中罕见变异的寡基因组合的一般框架

与对照组相比，自闭症和智力障碍 (ID) 等复杂疾病的遗传研究通常基于个体罕见变异的富集或受影响个体的总体负担。然而，这些研究忽略了罕见变体组合的影响，由于在枚举变体组合时稀有性和组合爆炸导致的统计挑战，这些组合本身可能不会有害，从而限制了我们研究这些疾病的寡基因基础的能力。在这里，我们提出了 RareComb，一个结合 Apriori 算法和统计推断的框架，以识别与复杂表型相关的突变基因的特定组合。RareComb 克服了计算障碍并详尽地评估了变体组合，以识别同时突变的基因之间的非加性关系。使用 RareComb，我们分析了 6189 名自闭症患者，并确定了 718 种与 ID 显着相关的组合，这些组合的携带者在 1878 名独立队列中的智商低于预期。这些组合富含神经系统基因，例如NIN和NGF显示出复杂的遗传模式，并且在未受影响的兄弟姐妹中被耗尽。我们发现受影响的个体可以携带许多寡基因组合，每种组合都会导致相同的表型或不同影响大小的不同表型。我们还使用该框架来识别与多种共病表型相关的组合，包括ID 和精神分裂症的COL28A1和MFSD2B突变以及ID 和焦虑/抑郁症的ABCA4、DNAH10和MC1R突变。我们的框架确定了缺失遗传力的一个关键组成部分，并提供了一种新的范式来解开复杂疾病的遗传结构。