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An Expanded View of Complex Traits: From Polygenic to Omnigenic.

ABSTRACT: A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome-including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways. We refer to this hypothesis as an "omnigenic" model.

SUBMITTER: Boyle EA

PROVIDER: S-EPMC5536862 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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An Expanded View of Complex Traits: From Polygenic to Omnigenic.

Boyle Evan A EA Li Yang I YI Pritchard Jonathan K JK

Cell 20170601 7

A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome-including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liabl ...[more]

PMID: 28622505

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Project description:To investigate the polygenicity of complex traits in populations of East Asian (EAS) and European (EUR) descents, we leveraged genome-wide data from Biobank Japan, UK Biobank, and FinnGen cohorts. Specifically, we analyzed up to 215 outcomes related to 18 health domains, assessing their polygenic architecture via descriptive statistics, such as the proportion of susceptibility SNPs per trait (πc). While we did not observe EAS-EUR differences in the overall distribution of polygenicity parameters across the phenotypes investigated, there were ancestry-specific patterns in the polygenicity differences between health domains. In EAS, pairwise comparisons across health domains showed enrichment for πc differences related to hematological and metabolic traits (hematological fold-enrichment = 4.45, p = 2.15 × 10-7; metabolic fold-enrichment = 4.05, p = 4.01 × 10-6). For both categories, the proportion of susceptibility SNPs was lower than that observed for several other health domains (EAS-hematological median πc = 0.15%, EAS-metabolic median πc = 0.18%) with the strongest πc difference with respect to respiratory traits (EAS-respiratory median πc = 0.50%; hematological-p = 2.26 × 10-3; metabolic-p = 3.48 × 10-3). In EUR, pairwise comparisons showed multiple πc differences related to the endocrine category (fold-enrichment = 5.83, p = 4.76 × 10-6), where these traits showed a low proportion of susceptibility SNPs (EUR-endocrine median πc = 0.01%) with the strongest difference with respect to psychiatric phenotypes (EUR-psychiatric median πc = 0.50%; p = 1.19 × 10-4). Simulating sample sizes of 1,000,000 and 5,000,000 individuals, we also showed that ancestry-specific polygenicity patterns translate into differences across health domains in the genetic variance explained by susceptibility SNPs projected to be genome-wide significant (e.g., EAS hematological-neoplasm p = 2.18 × 10-4; EUR endocrine-gastrointestinal p = 6.80 × 10-4). These findings highlight that traits related to the same health domains may present ancestry-specific variability in their polygenicity.

Dataset Information

An Expanded View of Complex Traits: From Polygenic to Omnigenic.

Publications

An Expanded View of Complex Traits: From Polygenic to Omnigenic.

Similar Datasets

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