We analyzed data from the UK Biobank consisting of 152,249 samples genotyped on ~800,000 SNPs and imputed to ~73 million SNPs.
We selected 15 highly heritable phenotypes with large sample size.
For each phenotype, we computed mixed model association statistics using version 2.2 of BOLT-LMM software (Loh et al. Nat Genet 2015) with genotyping array (UK BiLEVE / UK Biobank) and assessment center as covariates. We included 607,518 directly genotyped SNPs in the mixed model (specifically, all autosomal biallelic SNPs with missingness < 2 % and consistent allele frequencies between the UK BiLEVE array and the UK Biobank arrays). Association statistics were computed from dosage data on imputed SNPs in HapMap3 (1,211,182 SNPs).
In this study we determined that SNPs with low level of LD (LLD) have significantly larger per-SNP heritability. Roughly half of the LLD signal can be explained by functional annotations that are negatively correlated with LLD, such as DNase I hypersensitivity sites (DHS) and histone marks. The remaining signal is driven by annotations related on negative selection, highlighting the effect of negative on all polygenic complex traits.
Steven Gazal, Hilary K. Finucane, Po-Ru Loh, Pier Francesco Palamara, Xuanyao Liu, Armin Schoech, Brendan Bulik-Sullivan, Benjamin M Neale, Alexander Gusev, Alkes L. Price1. Linkage disequilibrium dependent architecture of human complex traits reveals action of negative selection Nature Genetics volume 49, pages 1421 1427 (2017) doi:10.1038/ng.3954
Components of heritability in a UK Biobank cohort
We will analyze heritability of several polygenic traits. We will use existing methods and methods under development for partitioning heritability by functional annotation (e.g. cell-type-specific enhancer regions, gene pathways, etc.) to learn about underlying trait biology. We will also examine how SNP heritability varies across LD and MAF categories. Finally, we will evaluate missing heritability using new methods to estimate heritability explained by haplotypes, narrow-sense heritability (using PSMC) and epistatic components of heritability (using Hadamard products). We plan to study a wide range of health-related phenotypes, including diseases and quantitative traits like height and BMI. The data in the UK Biobank?s cohort will allow us to partition heritability at higher resolution and to evaluate missing heritability. These will inform both our understanding of trait biology and the design of future genetic studies. Both of these outcomes will benefit attempts to find actionable drug targets for human disease. Moreover, the methods we develop for partitioning heritability will be published and made open-source for use by the broader research community. We will work with annotations from Finucane et al. 2015 Nat Gen as well as gene sets and new annotations from the ENCODE and Roadmap Epigenomics Consortia and others. We will apply LD score regression [Finucane et al. 2015 Nat Genet], BOLT-REML [Loh et al. 2015 Nat Genet], and a new method under development to assess heritability enrichment of these annotations, as well as enrichment/depletion by LD and MAF, within/across traits and populations. We will also apply new methods to estimate heritability explained by haplotypes, total narrow-sense heritability and epistatic components of heritability. We will analyze the full cohort.
|Lead investigator:||Dr Alkes Price|
|Lead institution:||Harvard School of Public Health|