VAT-Dependent Inflammatory Proteomic Signatures of Cardiometabolic Traits and Central Proteins

TL;DR

This study explores how visceral fat influences inflammation and cardiometabolic health through proteomic signatures, identifying key proteins linked to these traits.

Contribution

The study identifies VAT-dependent inflammatory proteomic markers and highlights novel proteins that may serve as therapeutic targets for cardiometabolic diseases.

Findings

Proteomic markers aligned with VAT and cardiometabolic traits, except HDL-C.

Adjusting for VAT levels reduced statistical significance in most proteomic associations.

Key proteins like TGFB1 and PDLIM7 show high centrality in VAT-dependent networks.

Abstract

Visceral adiposity tissue (VAT), fat located within the abdominal cavity, may play a causal role in driving inflammation and poor cardiometabolic health. This study investigates the cross-sectional relationships between multiple cardiometabolic traits, including VAT, and proteomic-based inflammatory signatures.

Body adiposity distribution quantified using dual-energy X-ray absorptiometry (DXA), cardiometabolic traits, and plasma proteomics inflammation panel (Olink Explore 384) were measured in a discovery cohort from the Vitamin D and Omega-3 Trial (VITAL; N = 525) and a replication cohort from the Cocoa Supplement and Multivitamin Outcomes Study (COSMOS; N = 371). We derived inflammatory proteomic markers of VAT, systolic blood pressure (SBP), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), fasting glucose, and insulin resistance (Homeostasis Model Assessment of Insulin Resistance; HOMA-IR). Inflammatory proteomic markers were identified via linear regression at a false discovery rate (FDR) < 0.05. Proteomic markers showed aligned associations with VAT and the other cardiometabolic traits, except for HDL-C, which was opposite. After adjusting for VAT levels, most proteomic markers were no longer statistically significant: >97% for glucose and SBP, and 73%, 62%, and 56% for HOMA-IR, TG, and HDL-C, respectively, suggesting that VAT explains the variability of these associations. To further elucidate shared mechanisms, we examined the network architecture of 86 proteomic markers common to all cardiometabolic traits. Some of the VAT-dependent protein signatures with high centrality were TGFB1, PDLIM7, COLEC12, and LAIR1. These hub-like proteins may reflect the influence of VAT accumulation on other cardiometabolic traits and highlight novel therapeutic targets for reducing cardiometabolic risk.

Figures