Cell-Type Heterogeneity in Adipose Tissue Is Associated with Complex Traits and Reveals Disease-Relevant Cell-Specific eQTLs

Am J Hum Genet. 2019 Jun 6;104(6):1013-1024. doi: 10.1016/j.ajhg.2019.03.025. Epub 2019 May 23.

Abstract

Adipose tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-tissue transcriptomes. Here, we investigate cell-type heterogeneity in two population-level subcutaneous adipose-tissue RNA-seq datasets (TwinsUK, n = 766 and the Genotype-Tissue Expression project [GTEx], n = 326) by estimating the relative proportions of four distinct cell types (adipocytes, macrophages, CD4+ T cells, and micro-vascular endothelial cells). We find significant cellular heterogeneity within and between the TwinsUK and GTEx adipose datasets. We find that adipose cell-type composition is heritable and confirm the positive association between adipose-resident macrophage proportion and obesity (high BMI), but we find a stronger BMI-independent association with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits. We benchmark the impact of adipose-tissue cell composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks, and cis-eQTL discovery. Our results indicate that it is critical to account for cell-type composition when combining adipose transcriptome datasets in co-expression analysis and in differential expression analysis with obesity-related traits. We applied gene expression by cell-type proportion interaction models (G × Cell) to identify 26 cell-type-specific expression quantitative trait loci (eQTLs) in 20 genes, including four autoimmune disease genome-wide association study (GWAS) loci. These results identify cell-specific eQTLs and demonstrate the potential of in silico deconvolution of bulk tissue to identify cell-type-restricted regulatory variants.

Keywords: GTEx; TwinsUK; adipose; cell type composition; eQTL; genetics; genomics; interactions; obesity; transcriptomics.

Publication types

  • Research Support, Non-U.S. Gov't
  • Twin Study

MeSH terms

  • Adipose Tissue / metabolism
  • Adipose Tissue / pathology*
  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Gene Expression Profiling
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study
  • Humans
  • Inflammation / genetics
  • Inflammation / pathology*
  • Male
  • Middle Aged
  • Multifactorial Inheritance / genetics*
  • Obesity / genetics
  • Obesity / pathology*
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Quantitative Trait Loci*
  • Transcriptome