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NUGENOB: The study, the database, and perspectives for integration. Mid Term Review QLK1-CT-2000-00618. Focus. The interactions between macronutrient composition of the diet, and specific genetic variants in human obesity.
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NUGENOB: The study, the database, and perspectives for integration Mid Term Review QLK1-CT-2000-00618
Focus • The interactions between macronutrient composition of the diet, and specific genetic variants in human obesity. • Combining clinical/physiological response to a high-fat test meal and a long-term hypo-energetic low-fat or medium-fat diet with knowledge of genetic make up and expressionlevels of individual genes.
Aims - I • Identification and characterisation of novel nutrient-sensitive candidate genes for obesity. • Assessment of the effects of the variants and combinations of variants in nutrient-sensitive genes on the response to a high-fat test meal
Aims - II • Identification of predictors of the changes in body weight during a 10-week hypo energetic low-fat or medium-fat dietary intervention programme: • Anthropometrical characteristics, • Obesity-related life style factors, • Physiological functions observed at the test meal challenge, • Variants or combinations of variants of the nutrient-sensitive genes, • Gene expression in adipose tissue, • Gene-phenotype or gene-environment interactions based on combinations of these predictors. To identify predictors of differantial response to the two diets • Assessment of the combined effects of • variants of nutrient-sensitive genes • short- and long-term alterations in dietary fat content on the differential expression of selected genes in adipose tissue.
Study population 771 obese – 119 lean subjects • Inclusion criteria for obese subjects • BMI >= 30 • Intention to include white Europeans • Age 20-50 years • Pre-menopausal women • Exclusion criteria for obese subjects • Medical conditions and medication • Pregnant women • Alcohol or drug abuse • Weight change of > 3 kg within 3 months.
Data I - Habitual diet, life style factors • 3-day, weighed food record • Questionnaire addressing: • social variables, • physical activity, • drinking and smoking habits, • weight and dieting history, • health and illness, • family history of obesity and obesity related diseases • SF-36
10 weeks Anthropometrics Body composition Fasting blood Anthropometrics Body composition
Identification of candidate genes and gene variants
Publiched results • GAD2 on Chromosome 10p12 Is a Candidate Gene for Human Obesity. Boutin P et al. PLoS Biol. 2003 Dec;1(3):E68. Epub 2003 Nov 03 • Association studies between microsatellite markers within the gene encoding human 11 beta-hydroxysteroid dehydrogenase type 1 and body mass index, waist to hip ratio, and glucocorticoid metabolism. Draper Net al. Journal of Clinical Endocrinology and Metabolism, Vol. 87 (11) pp. 4984-4990 (2002) • Mutational analysis of the UCP2 core promoter and relationships of variants with obesity. Dalgaard LT et al. Obes Res 2003;11:1420-1427 • A genome-wide scan for childhood obesity-associated traits in French families shows significant linkage on chromosome 6q22.31-q23.2. Meyre et al.Diabetes. 2004 Mar;53(3):803-811. • The FOXC2 -512C>T variant is associated with hypertriglyceridemia and elevated serum C-peptide in glucose tolerant subjects Yanagisawa et al. Diabetologia, 2003 Nov;46(11):1576-80
Data IV – Genotyping43 SNPs in 27 genes Adipocyte secretory peptides Regulation of adiposcyte differantiation Mitocondrial proteins Nuclear receptors and transcription factors Hormones and receptors involved in appetite regulation Insulin signalling and glucose regulation Lipoprotein metabolism
Data V – Quantitative gene expression Quantitative gene expression analyses for 40 candidate genes in 2 x 25 subjects (25 from each diet group)
Data VI – Gene expression profiling • Affymetrixchip analyses on 13+10 women from a single center • Custom made metabolic chip in 25+25 selected from all centres • Data stored in local centres
Databank and statistical Analyses
The NUGENOB database – formant • The database has a simple flat format with 1 row per subject and one column per variable • SPSS, STATA, SAS...... (Not Excel)
The NUGENOB database – Content Raw data Derived measures • Percentage and avarage • Summary scores • BMI, W/H • AUC, AUCi • RQ, EE, macronutrien oxidation • Weight loss from week 0 to 10 • Percentage and avarage • BMI, W/H • Ratios • Habitual diet (not ’raw’) • Questionnaire • Anthropometrics • Appetite • Blood parameters • Vo2 and Vco2 • Weight during weight loss • Diet during weight loss • Genotypes • Quantitative gene expression • Gene expression profiling
The NUGENOB database – Selection of sub-populations • Subjects with high versus low increase in fat oxidation following the high-fat test meal • Subjects completing the weight loss intervention, and following the diet prescriptions • Subjects being successful or un-successful in loosing weight when following the dietary intervention • Subjects with no versus high improvement in insulin sensitivity following weight loss
Samples in the NUGENOB biobank • Serum and plasma samples taken in the fasting state, and every hour during a 3-hour period following a high-fat test meal. In obese subjects fasting serum and plasma samples were obtained following the 10-week intervention. • Purified DNA in 96-well master plates (two sets) from all but 10 of the 771 obese and 119 lean subjects. • Buffy coat samples from all but ~120 of the 771 obese and 119 lean subjects • Extracted mRNA from abdominal subcutaneous adipose tissue biopsies obtained in fasting before and after the 10-week dietary intervention in ~ 700 obese subjects. mRNA from biopsies obtained 3 hours after the test meal in a small group of obese subjects and mRNA from biopsies obtained in a small group of lean subjects.
SOPs of NUGENOB • Anthropometrical measurements • Questionnaire (Translated) • Blood sampling (obtaining, packing, storing, shipment) • Dietary Intervention • Needle subcutaneous abdominal adipose tissue biopsy • Preparation of the high fat liquid test meal. • Validating, calibrating and conducting indirect calorimetry (Hood). • Clinical investigation day, including blood sampling, energy and substrate metabolism in fasting and flowing a high fat test meal. • Randomisation. • Data entry and data transfer into the freeware programme EpiData • Delivery of data for analyses
Database on nutrient-sensitive genes • Database on genes for which there is a known nutrient-gene interaction and a putative role in obesity • Info on genes for which gene variatns determine response to diet • Info on genes for which the expression is changed in responds to calorie restriction, overfeeding or changes in diet composition (animal and human). • Data from quantitative gene expression • Data from micro array studies. • Animal studies on obesity, DIO or protection from DIO in KO, TG and mutation models • Human gene variants affecting gene expression (with or without in vitro functional effects) • Gene-gene interaction for nutrient sensitive genes