Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits

Sarah M Brotman, Anniina Oravilahti, Jonathan D Rosen, Marcus Alvarez, Sini Heinonen, Birgitta W van der Kolk, Lilian Fernandes Silva, Hannah J Perrin, Swarooparani Vadlamudi, Cortney Pylant, Sonia Deochand, Patricia V Basta, Jordan M Valone, Morgan N Narain, Heather M Stringham, Michael Boehnke, Johanna Kuusisto, Michael I Love, Kirsi H Pietiläinen, Päivi Pajukanta, Markku Laakso, Karen L Mohlke.
Diabetes. 2023-11-01;72(11):1707-1718.

Summary

Accession
DP8A376043
Abstract
Understanding differences in adipose gene expression between individuals with different levels of clinical traits may reveal the genes and mechanisms leading to cardiometabolic diseases. However, adipose is a heterogeneous tissue. To account for cell-type heterogeneity, we estimated cell-type proportions in 859 subcutaneous adipose tissue samples with bulk RNA sequencing (RNA-seq) using a reference single-nuclear RNA-seq data set. Cell-type proportions were associated with cardiometabolic traits; for example, higher macrophage and adipocyte proportions were associated with higher and lower BMI, respectively. We evaluated cell-type proportions and BMI as covariates in tests of association between >25,000 gene expression levels and 22 cardiometabolic traits. For >95% of genes, the optimal, or best-fit, models included BMI as a covariate, and for 79% of associations, the optimal models also included cell type. After adjusting for the optimal covariates, we identified 2,664 significant associations (P ≤ 2e-6) for 1,252 genes and 14 traits. Among genes proposed to affect cardiometabolic traits based on colocalized genome-wide association study and adipose expression quantitative trait locus signals, 25 showed a corresponding association between trait and gene expression levels. Overall, these results suggest the importance of modeling cell-type proportion when identifying gene expression associations with cardiometabolic traits.
Consortium data used in this publication
The full trait-gene expression associations are available at https://mohlke.web.unc.edu/data/. METSIM data are available in dbGaP phs000743.v3. The snRNA-seq data counts are available on Gene Expression Omnibus GSE236708.