Presentatie Prof. de Graaf en Dr. Willems van Dijk

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Cardiobesity,
Unravelling the mechanistic link between obesity, metabolic disorders and cardiovascular disease

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Presentatie Prof. de Graaf en Dr. Willems van Dijk

  1. 1. Cardiobesity Unravelling the mechanistic link between obesity, metabolic disorders and cardiovascular disease Jacqueline de Graaf Ko Willems van Dijk
  2. 2. Cardiobesity Consortium Name Institute Genetics Clinical pheno- typing In vitro analysis Animal model Systems Biology Cohorts Intervention Prof. C. van Duijn ErasmusMC X X Prof. J. de Graaf UMCN X X X Dr. K. Willems van Dijk LUMC X X Prof. M. Hofker UMCG X X X X Prof. E. Feskens WUR X X X Prof. P. Slagboom LUMC X X Prof. C. Stehouwer MUMC X X Dr. B. van Ommen TNO X Prof. T. Hankemeier UL X
  3. 3. Is it possible to identify those overweight individuals who are prone to developing cardiovascular disease? Cardiobesity Health care problem Age Gender Mechanisms We will reveal novel genes and markers for improved risk stratification, personalized prevention, and new therapeutic options to decrease the CVD burden in the overweight Obesity Metabolic disorders CVD
  4. 4. Cardiobesity Research questions What markers/parameters identify those overweight subjects at increased risk for metabolic disorders and CVD WP 6 Genomics platforms and system biology What molecular mechanisms, especially in adipose tissue, are responsible for increased risk for metabolic disorders and CVD? WP1 Genetics WP2 Clinical phenotype WP 4 Molecular mechanisms WP3 Adipose tissue functionality WP 5 Cohorts / Intervention trials Novel candidate genes and markers for CV risk stratification and personalized prevention in overweight individuals
  5. 5. Integrated data warehousing Bioinformatics and biostatistics System biology Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Leiden Longevity Cohort Aging cohort with low cardiometabolic risk 420 families – 3500 subjects Available data: GWAS (n=3500) Sequence data (n=220) Metabolomics (n=3500) Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Whole exome sequencing <ul><li>Reference data bases: </li></ul><ul><li>1000 genome projects </li></ul><ul><li>250 trios in GoNL </li></ul><ul><li>ERF study (n=3000) </li></ul><ul><ul><li>GWAS </li></ul></ul><ul><ul><li>exome sequencing </li></ul></ul><ul><ul><li>metabolomics </li></ul></ul>Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals CT, MRI, DEXA Obesity-imaging Nail fold capillaroscopy Retinography Endothelial Glycocalyx Micro-vascular imaging IMT, PWV, ABI, Plaques MRI, PET/CT, CEUS for vulnerable plaques Macro-Vascular imaging Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Adipose tissue biopsies Ex vivo and in vitro Inflammasome Nod like receptors Immune cells Transcriptomics Metabolomics Proteomics Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals Nijmegen Biomedical Study N=1517 ERF and Rotterdam study N=3000 and n=12.000 Maastricht study and CODAM N= 6000 and n=574 LifeLines n>50.000 Leiden Longevity Study Trial n=60 EetMeetWeet N=300 Familial Combined Hyperlipidemia N=687 – 70 families Overweight Metabolic Disorders Premature CVD WP1: Genetics Whole exome sequencing WP3: Adipose tissue characterization In vitro analyses WP6: Genomics analysis platforms Transcriptomics, metabolomics, proteomics WP2: Obesity and vascular imaging In depth clinical phenotyping Candidate mechanisms linking obesity with CVD WP6: Systems Biology Data integration and interpretation WP4:Mouse models Mechanistic studies Leiden Longevity Cohort N=3500 – 420 families Metabolic health CVD protection Large cohorts Selection of overweight subjects - with/without CVD - with and without metabolic disorders WP5: Epidemiology Validation in large cohorts N>75.000 and by interventions Novel genes and markers for CV risk stratification and personalized prevention in overweight individuals
  6. 6. Cardiobesity Translation axis Patients: FCH, LLS, cohort subsets Basic and translational research Genetics Clinical phenotyping Systems biology Adipose tissue studies Mouse models Candidate mechanisms: Linking obesity and CVD Epidemiology: Cohorts and interventions Novel candidate genes and markers for CVD risk stratification and personalized prevention in overweight individuals
  7. 7. Focus areas Dutch Heart Foundation: Aging Gender Metabolic disorders Cardiobesity Focus areas Obesity Metabolic disorders CVD Age Gender Mechanisms
  8. 8. Cardiobesity consortium Unique in combining expertise in basic, clinical and epidemiological research resulting in integrated approach to link obesity to CVD Collaboration with (inter)national consortia: ‘ Complementary and confirmatory replication’ GoNL – BBMRI – NCHA – CHANCES – IDEAL – EAGLE EPI2 - CTMM ‘predict’ - NCSB – CMSB2 – NMC Cardiobesity (Inter)national perspectives
  9. 9. To identify those overweight individuals who are prone to develop cardiovascular disease by revealing the mechanisms linking obesity to CVD Cardiobesity Age Gender Mechanisms Obesity Metabolic disorders CVD

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