Format

Send to

Choose Destination
Nat Genet. 2017 Oct;49(10):1421-1427. doi: 10.1038/ng.3954. Epub 2017 Sep 11.

Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection.

Author information

1
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
2
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
3
Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
4
23andMe, Inc., Mountain View, California, USA.
5
Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
6
Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
7
Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
8
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Abstract

Recent work has hinted at the linkage disequilibrium (LD)-dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) have larger per-SNP heritability. Here we analyzed summary statistics from 56 complex traits (average N = 101,401) by extending stratified LD score regression to continuous annotations. We determined that SNPs with low LLD have significantly larger per-SNP heritability and that roughly half of this effect can be explained by functional annotations negatively correlated with LLD, such as DNase I hypersensitivity sites (DHSs). The remaining signal is largely driven by our finding that more recent common variants tend to have lower LLD and to explain more heritability (P = 2.38 × 10-104); the youngest 20% of common SNPs explain 3.9 times more heritability than the oldest 20%, consistent with the action of negative selection. We also inferred jointly significant effects of other LD-related annotations and confirmed via forward simulations that they jointly predict deleterious effects.

PMID:
28892061
PMCID:
PMC6133304
DOI:
10.1038/ng.3954
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center