cLD: Rare-variant linkage disequilibrium between genomic regions identifies novel genomic interactions

Abstract

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.

LDER-GE estimates phenotypic variance component of gene–environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information

“…However, for the same simulation parameter setting, the in-sample estimation precision with SNPs has low MAFs is lower than that for SNPs with MAF > 0.05 for both LDER-GE and LDSC-based methods. While the out-sample performance of LDER-GE degrades with the inclusion of SNPs with low MAFs in terms of bias and accuracy, due to unreliable LD estimates from the small sample size of the 1000 Genomes project [ 23 ]. We recommend use MAF > 0.05 variants and an in-sample or a large sample size reference panel where applicable to ensure the best overall estimation performance.…”