Abstract P322: Transcriptomic Analysis of Severe Obesity Identifies Novel Genes in Hispanic/Latino Populations With a High Burden of Disease

Abstract

The US prevalence of severe obesity [(SevO), body mass index [BMI] ≥40 kg/m 2 )] is increasing at an alarming rate; women and Hispanic Latino populations have experienced among the greatest increases. While genome-wide association studies (GWAS) have identified >1000 loci associated with body mass index, the function of much of this variation is unknown. Gene expression measures can ] link genetic variation and disease highlighting pathways for targeted therapeutic intervention, but to-date, few studies have examined the role of gene expression to identify molecular signatures associated with SevO. To this end, we leveraged extant whole blood (WB) RNA sequencing (RNAseq) data in 75 SevO cases and 116 controls (with BMI = 18-25) collected from randomly selected Mexican Americans in the Cameron County Hispanic Cohort (CCHC) to identify patterns associated with SevO. We used established protocols and alignment, yielding 18,565 genes after quality control. We applied DESeq2 to assess DE associated with SevO, using a negative binomial regression model with a gene-specific dispersion parameter, adjusted for sex, age, T2D, hypertension, hypercholesterolemia, and 10 probabilistic estimation of expression residual (PEER) factors. After FDR correction, 124 genes were significantly DE, including top genes C1RL , IL4R, and RGS16 . We identified several replications of the 124 genes in a transcriptomic follow-up study of 52 SevO cases and 59 normal weight controls- 20 genes displayed directionally consistent and FDR significant evidence of replication. We additionally identified several replications of the 124 genes in subcutaneous adipose tissue (SAT) from 19 NYC community volunteers, including for RGS16 , C1RL , and IL4R. 2- sample MR assessed causal associations between SevO and gene dysregulation, using SevO GWAS from DIAMANTE and CCHC eQTLs. Upregulated IL4R demonstrate pleiotropy, among other genes (e.g., REM2, ENGASE, and SCAP ). Collectively, these data demonstrate how transcriptomic studies may elevate understanding of SevO and inform efforts to reduce health disparities associated with SevO in HL populations.