Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults.

We previously reported preliminary characterization of adipose tissue (AT) dysfunction through the adiponectin/leptin ratio (ALR) and fasting/postprandial (F/P) gene expression in subcutaneous (SQ) adipose tissue (AT) biopsies obtained from participants in the GEMM study, a precision medicine research project. Here we present integrative data replication of previous findings from an increased number of GEMM symptom-free (SF) adults (N = 124) to improve characterization of early biomarkers for cardiovascular (CV)/immunometabolic risk in SF adults with AT dysfunction. We achieved this goal by taking advantage of the rich set of GEMM F/P 5 h time course data and three tissue samples collected at the same time and frequency on each adult participant (F/P blood, biopsies of SQAT and skeletal muscle (SKM)).

Towards precision medicine: defining and characterizing adipose tissue dysfunction to identify early immunometabolic risk in symptom-free adults from the GEMM family study.

Interactions between macrophages and adipocytes are early molecular factors influencing adipose tissue (AT) dysfunction, resulting in high leptin, low adiponectin circulating levels and low-grade metaflammation, leading to insulin resistance (IR) with increased cardiovascular risk. We report the characterization of AT dysfunction through measurements of the adiponectin/leptin ratio (ALR), the adipo-insulin resistance index (Adipo-IRi), fasting/postprandial (F/P) immunometabolic phenotyping and direct F/P differential gene expression in AT biopsies obtained from symptom-free adults from the GEMM family study. AT dysfunction was evaluated through associations of the ALR with F/P insulin-glucose axis, lipid-lipoprotein metabolism, and inflammatory markers.

Deep Multi-OMICs and Multi-Tissue Characterization in a Pre- and Postprandial State in Human Volunteers: The GEMM Family Study Research Design.

Cardiovascular disease (CVD) and type 2 diabetes (T2D) are increasing worldwide. This is mainly due to an unhealthy nutrition, implying that variation in CVD risk may be due to variation in the capacity to manage a nutritional load. We examined the genomic basis of postprandial metabolism.

Integrating genomic analysis with the genetic basis of gene expression: preliminary evidence of the identification of causal genes for cardiovascular and metabolic traits related to nutrition in Mexicans.

Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology.