Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics.

Scientific Reports
Armand ValsesiaMojgan Masoodi

Abstract

Weight loss aims to improve glycemic control in obese but strong variability is observed. Using a multi-omics approach, we investigated differences between 174 responders and 201 non-responders, that had lost >8% body weight following a low-caloric diet (LCD, 800 kcal/d for 8 weeks). The two groups were comparable at baseline for body composition, glycemic control, adipose tissue transcriptomics and plasma ketone bodies. But they differed significantly in their response to LCD, including improvements in visceral fat, overall insulin resistance (IR) and tissue-specific IR. Transcriptomics analyses found down-regulation in key lipogenic genes (e.g. SCD, ELOVL5) in responders relative to non-responders; metabolomics showed increase in ketone bodies; while proteomics revealed differences in lipoproteins. Findings were consistent between genders; with women displaying smaller improvements owing to a better baseline metabolic condition. Integrative analyses identified a plasma omics model that was able to predict non-responders with strong performance (on a testing dataset, the Receiving Operating Curve Area Under the Curve (ROC AUC) was 75% with 95% Confidence Intervals (CI) [67%, 83%]). This model was based on baseline parameters w...Continue Reading

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Datasets Mentioned

BETA
GSE95640

Methods Mentioned

BETA
biopsies
X-ray
PCR
RNAseq

Clinical Trials Mentioned

NCT00390637

Software Mentioned

yEd
DiOGenes
PREVIEW
PathComp
pROC
MATLAB
pROC R package

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