Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults.
Esther C Gallegos-CabrialesErnesto Rodriguez-AyalaHugo A Laviada-MolinaEdna Judith Nava-GonzálezRocío A Salinas-OsornioLorena Orozco-OrozcoIrene Leal-BerumenJuan Carlos Castillo-PinedaLaura Gonzalez-LopezClaudia Escudero-LourdesJudith Cornejo-BarreraFabiola Escalante-AraizaEira E Huerta-ÁvilaFatima A Buenfil-RelloVanessa-Giselle PeschardEliud SilvaRosa A Veloz-GarzaAngélica Martinez-HernandezFrancisco M Barajas-OlmosFernanda Molina-SeguiLucia Gonzalez-RamirezRuy D Arjona-VillicañaVictor M Hernandez-EscalanteJaneth F Gaytan-SaucedoZoila VaqueraMonica Acebo-MartinezAreli Murillo-RamirezSara P Diaz-TenaBenigno Figueroa-NuñezMelesio E Valencia-RendonRafael Garzon-ZamoraJuan Manuel Viveros ParedesSalvador B Valdovinos-ChavezAnthony G ComuzzieKarin HaackAshley A ThorsellXianlin HanShelley A ColeRaul A BastarracheaPublished in: Biology (2021)
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)). We classified them with the presence/absence of AT dysfunction: low (<1) or high (>1) ALR. We also examined the presence of metabolically healthy (MH)/unhealthy (MUH) individuals through low-grade chronic subclinical inflammation (high sensitivity C-reactive protein (hsCRP)), whole body insulin sensitivity (Matsuda Index) and Metabolic Syndrome criteria in people with/without AT dysfunction. Molecular data directly measured from three tissues in a subset of participants allowed fine-scale multi-OMIC profiling of individual postprandial responses (RNA-seq in SKM and SQAT, miRNA from plasma exosomes and shotgun lipidomics in blood). Dynamic postprandial immunometabolic molecular endophenotypes were obtained to move towards a personalized, patient-defined medicine. This study offers an example of integrative translational research, which applies bench-to-bedside research to clinical medicine. Our F/P study design has the potential to characterize CV/immunometabolic early risk detection in support of precision medicine and discovery in SF individuals.
Keyphrases
- low grade
- adipose tissue
- insulin resistance
- oxidative stress
- data analysis
- gene expression
- metabolic syndrome
- blood glucose
- high grade
- rna seq
- single cell
- skeletal muscle
- electronic health record
- high fat diet
- mesenchymal stem cells
- dna methylation
- stem cells
- machine learning
- cardiovascular disease
- blood pressure
- single molecule
- young adults
- case report
- climate change
- glycemic control
- patient reported
- sensitive detection
- cardiovascular risk factors
- network analysis
- high throughput
- loop mediated isothermal amplification