Unknown

Dataset Information

0

A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease.


ABSTRACT: Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10-48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.

SUBMITTER: Timmons JA 

PROVIDER: S-EPMC6125682 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications


Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RN  ...[more]

Similar Datasets

| S-EPMC4572001 | biostudies-literature
| S-EPMC11245507 | biostudies-literature
| S-EPMC7109041 | biostudies-literature
| S-EPMC5952343 | biostudies-literature
| S-EPMC7046790 | biostudies-literature
| S-EPMC5972043 | biostudies-literature
| S-EPMC7566321 | biostudies-literature
| S-EPMC3547830 | biostudies-literature
| S-EPMC165953 | biostudies-literature
| S-EPMC4732918 | biostudies-literature