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Updated: Dec 29, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Enhancer Domains Predict Gene Pathogenicity and Inform Gene Discovery in Complex Disease
Xinchen Wang1, David B Goldstein2
1Institute for Genomic Medicine, Columbia University Medical Center, Hammer Health Sciences, 701 West 168th Street, New York, New York 10032, USA.
Abstract:
Non-coding transcriptional regulatory elements are critical for controlling the spatiotemporal expression of genes. Here, we demonstrate that the sizes and number of enhancers linked to a gene reflect its disease pathogenicity. Moreover, genes with redundant enhancer domains are depleted of cis-acting genetic variants that disrupt gene expression, and they are buffered against the effects of disruptive non-coding mutations. Our results demonstrate that dosage-sensitive genes have evolved a robustness to the disruptive effects of genetic variation by expanding their regulatory domains. This solves a puzzle about why genes associated with human disease are depleted of cis-eQTLs (cis-expression quantitative trait loci), suggesting that this relationship might complicate gene identification in causal genome-wide association studies (GWASs) using eQTL information, and establishes a framework for identifying non-coding regulatory variation with phenotypic consequences.
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