WP 5: Humanization of the computational model through the direct use of clinical data

WP 5: Humanization of the computational model through  the direct use  of clinical data

WP leader: IPL; Bart Staels, PhD (Bart.Staels@pasteur-lille.fr)

The objectives of this work package are:

Humanize and calibrate the computational mouse models (WP2) using existing data sets derived from healthy and overweight humans with/without MetS:

1. Studies in overweight individuals

• Existing kinetic (stable isotopes) TRL data generated in the EU FP6 HEPADIP study consisting of carefully phenotyped obese subjects with low and high plasma TG with quantitative data on ectopic fat depots including liver, and similar data from 10 healthy controls.

• Existing data generated in a carefully phenotyped cohort consisting of obese MetS patients who underwent simultaneous TRL and HDL kinetic (stable isotopes) tests, detailed lipid regulating enzyme and protein analyses and quantitative data on ectopic  fat depots including liver.

• Existing data generated in the EU FP6 HEPADIP study consisting of overweight, drug-naive patients who were metabolically phenotyped in detail (including biochemical parameters, NASH scoring and adipose and liver tissue biopsy collection).

• Verify the identified pathways experimentally by transcriptomic analysis (adipose tissue and/or liver) and in vitro cell culture models.


2. Studies in morbidly obese patients undergoing bariatric surgery and healthy controls during feeding/fasting cycles, hypercaloric diet and conditions of high FFA

• Existing flux (glucose flux and lipolysis) -transcriptomics and targeted metabolomics data (liver, adipose tissue) sets (+ liver MRS) from 20 morbidly obese MetS patients before and after bariatric intervention.

• Existing (glucose) flux-transcriptomics and targeted metabolomics data sets from lean healthy subjects on a hypercaloric diet.

• Existing glucose flux data from  lean healthy subjects during iv lipid emulsion

• Existing glucose flux and lipolysis flux data and targeted metabolomics data from healthy  lean subjects during prolonged and intermittent  fasting