Genetic Risk Score vs Other Predictors for Type 2 Diabetes

Transcription

1 Genetic Risk Score vs Other Predictors for Type 2 Diabetes Vincent Mooser MD Expert Forum on Diabetes Rueschlikon, October 10th, 2017

2 Risk prediction for T2DM : Why we shall bother 1. High prevalence in the (elderly) population 2. Major cause of morbidity/mortality 3. Partly preventable (i.e. not a fate) Unité VDE

3 Cohorte Lausanne CoLaus participants Age at enrollment : years Representative of population Very extensive cardiometabolic + psychiatry + sleep phenotype GWAS 15-year follow-up 350+ publications

4 Prevalence (%) Prevalence of T2DM in CoLaus Men Women Age (years) Kaiser et al. Diabet Med. 2012;29:190 Unité VDE 4

5 Conventional Risk Predictors for T2DM Age Gender BMI Family history for T2DM Fasting blood glucose / HOMA Smoking Others

6 Specificity Testing 7 T2DM Predictive Models in CoLaus Incident cases of T2DM over 5 year follow-up : 169 / Wilson Balkau Kahn 90 Kahn Swiss Diabetes Association 85 Griffin FINDRISC Sensitivity Schmid et al. Arch Intern Med. 2012;172:188

7 Predictive performance of conventional T2DM risk scores limited and variable Need for new, better predictive tests Opportunities : *Omic technologies 1. Genomics genetic biomarkers 2. Metabolomics non-genetic biomarkers Unité VDE 7

8 1. Genomics genetic biomarkers Unité VDE 8

9 New genomic technologies T2DM is highly heritable 100% Environment 50% 0% Genes GWAS NGS T2DM H 2 = 72% same-sexe twins Willemsen G et al - Twin Research and Human Genetics 2015 Elucidation of genetic basis of T2DM Genetic risk score (GRS)

10 GWAS for T2DM in European Populations 56 published studies in GWAS Catalog 113 genomic regions, 128 independent signals Variance explained < 10% Scott RA et al - Diabetes 2017, online

11 GWAS for T2DM in European and Other Ethnic Populations participants Zhao et al - Nature Genetics 49; 141, 2017

12 NGS in T2DM : The Genetic Architecture of T2DM Variance explained Common variants (MAF > 0.05) Rare variants (0.001<MAF<0.05) Other «Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes MacCarthy et al; Nature 2016; 536: 41-46

13 Prediction of T2DM using GRS in CoLaus Lin R et al. Diabetologia 52: , 2009

14 AUC T2DM Risk Prediction using GRS AUC with conventional risk model (CRM) and combination of CRM + GRS < 10 SNPs SNPs SNPs * * : CoLaus CRM CRM+GRS 0 CRM CRM+GRS 0 CRM CRM+GRS Adapted from Wang X et al, J Diabetes 2016; 8 : 24-35

15 No clinically relevant benefit of GRS in predicting T2DM GRS to predict complications of T2DM? 07/10/2017 Unité VDE 15

16 GRS for CAD in General Population : CoLaus Antiochos P. et al, Atherosclerosis, 2016:244:59-65

17 GRS for CAD in T2DM Population Look AHEAD Study; Diabetologia. 2015, 58(8):

18 1. Metabolomics and Lipidomics Non-genetic biomarkers Unité VDE 18

19 Wigger et all 2017, Cell Reports 18:

20 Mice with different genetic backgrounds High Fat High sucrose diet In mice several sphingolipids correlate with diabetes like traits Wigger et all 2017, Cell Reports 18:

21 CoLaus Targeted lipidomic Certain dihydroceramides are elevated 5 years before incident diabetes in CoLaus Replication in independent dataset (DESIR) Wigger et all 2017, Cell Reports 18:

22 Biomarkers of diabetes risk prediction in CoLaus Wigger et all 2017, Cell Reports 18:

23 Targeted metabolomic analysis of food intake and nutrient status for T2DM risk prediction Targeted metabolomic-analysis of food intake and nutrient status for T2DM risk prediction Serum adiponectin HOMA-IR Smoking Fasting blood glucose Same + dietary and nutritional biomarkers Savolainen et al Am J Clin Nutr; 2017

24 Conclusion No clinically relevant benefit from GWASderived GRS to predictt2dm No major gain to be expected from WGS Need for additional, non-genetic markers Lipidomic and nutrition status biomarkers promising 07/10/2017 Unité VDE 24

25 Acknowledgments : CoLaus The participants The CHUV crew : Gérard Waeber, Peter Vollenweider, Pedro Marques Vidal,Martin Preisig, Julien Vaucher, François Bastardot, Vladimir Mayor, Mathieu Firmann, Yolande Barreau, Fred Paccaud, Remy Schmid, Murielle Bochud,Toby Johnson, Sven Bergmann, Zoltan Kutalik and their collaborators The GSK crew : Dawn Waterworth, Andrew Lin, Kijoung Song, Lon Cardon, Paul Matthews and their collaborators 07/10/2017 Unité VDE 25

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