# Multimodal omics approach to identify health to cardiometabolic disease transitions > **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2024 · $681,062 ## Abstract Abstract: The global obesity epidemic drives the high prevalence of cardiometabolic disorders (CMDs), including type 2 diabetes (T2D), and non-alcoholic fatty liver disease (NAFLD). Epidemiological studies have also established strong sex differences in CMDs. Obesity-induced low-grade inflammation and insulin resistance in adipose tissue (AT), their deteriorating impacts on the efficacy of adipogenesis, and subsequent ectopic fat storage into other cardiometabolic tissues, particularly liver, have been proposed as the key drivers of the CMD risks related to obesity. However, the mechanisms promoting the transitions from health-to-disease states in human fat depots have remained largely elusive. We hypothesize that there are transcriptional inflammatory markers and cell-type-specific changes in open chromatin pertinent to health-to-CMD transitions that can be discovered using single cell level and bulk omics analyses in fat cell-types and tissue. We also hypothesize that by elucidating molecular responses to obesity-related stimuli during adipogenesis we can discover candidate variants and genes with functional priors for formal identification of gene-sex and gene-environment interactions (i.e. GxSs and GxEs) underlying obesity-induced health-to-CMD transitions in large biobanks. In Aim 1, we will generate sex- and context-specific bulk and single cell level transcriptomics (RNA-seq) and epigenomics (ATAC- seq) data in two obesity-relevant fat depots, i.e. subcutaneous and visceral AT, to identify epigenetic and transcriptional markers for health-to-CMD transitions in six health-to-CMD stages comprising lean, overweight, and obese males and females with and without prediabetes, T2D, and NAFLD. We will also use existing serum samples to discover health-to-CMD transition biomarkers among the genes that differ between the six health/disease states and encode secreted proteins. We will test the top results for replication in independent omics cohorts, including Mexicans. In Aim 2, we will use a new function-to-variants omics approach to discover GxSs and GxEs involved in early transitions from health to CMD in males and females. We will generate functional genomics data in CMD-relevant human primary preadipocytes, extracted from fresh AT of normal weight, metabolically healthy males and females. These preadipocytes will be differentiated with and without key inflammatory stimuli to discover stimuli-responsive adipogenesis genes and cis-regulatory elements (CREs) that harbor regulatory variants in diverse populations. Subsequently, these variants will be fine-mapped using massively parallel reporter assay in (pre)adipocytes and functionally characterized using extensive variant-to- gene-linkage analysis and genomic perturbations (CRISPR and siRNA). The identified candidate SNPs will be tested for GxE and GxS effects on health-to-CMD transitions in large biobanks to verify their role in these critical transitions. Our preliminary results and ample previ... ## Key facts - **NIH application ID:** 10905018 - **Project number:** 5R01HL170604-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES - **Principal Investigator:** Paivi Pajukanta - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $681,062 - **Award type:** 5 - **Project period:** 2023-08-10 → 2027-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10905018 ## Citation > US National Institutes of Health, RePORTER application 10905018, Multimodal omics approach to identify health to cardiometabolic disease transitions (5R01HL170604-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10905018. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*