1 / 14

Meena Kumari 17 November 2008

English Longitudinal Study of Ageing (ELSA): An example of data use from the ELSA DNA Repository. Meena Kumari 17 November 2008. ELSA DNA Repository (EDNAR). HSE ’98, ’99, 2001. Wave 1 (2002-3) 11391. Wave 2 (2004-5). Wave 2 nurse 7666. Wave 3 (2006-7). DNA consent 6551. Refresher

milos
Télécharger la présentation

Meena Kumari 17 November 2008

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. English Longitudinal Study of Ageing (ELSA): An example of data use from the ELSA DNA Repository Meena Kumari 17 November 2008

  2. ELSA DNA Repository (EDNAR) HSE ’98, ’99, 2001 Wave 1 (2002-3) 11391 Wave 2 (2004-5) Wave 2 nurse 7666 Wave 3 (2006-7) DNA consent 6551 Refresher 1892 issued Wave 4 (2008-9) Wave 4 nurse

  3. AIMS: EDNAR • Using genetics to understand social and psychosocial processes impact health • Gene-environment interactions • Using genetics to understand biological pathways • Mendelian randomisation approach • contribution of data to the wider academic community • Within UCL as part of London based consortium (n=35,000) • Wider academic community in the form of the repository • Genetic repository (EDNAR) • m.kumari@ucl.ac.uk

  4. Progress in the EDNAR • Funded in November 2005 by NIA • 16 applications (as of October 2008) • 1,450 SNPs measured • 2 papers published • Caulfield et al., Plos Med. 2008 • Rice et al., J. Allergy. Exp. Immunol. 2008 • 4 papers under review

  5. Randomisation to test causalitythe Mendelian randomisation approach Drug intervention Genetics RCT Mendelian randomisation Sample Population Randomisation Random allocation of alleles Intervention Control Genotype aa Genotype AA Biomarker lower Biomarker higher Biomarker lower Biomarker higher CV event rate higher CV event rate higher CV event rate lower CV event rate lower

  6. Application of mendelian randomisation • Separating the mechanism-based and off-target actions of torcetrapib using cholesteryl ester transfer protein gene polymorphisms (Sofat et al., under review) • Torcetrapib is a drug that raises ‘good’ cholesterol by its action on cholesteryl ester transfer protein (CETP) • Recently the ‘Illuminate’ trial was stopped because the drug was found to have increased adverse cardiovascular outcomes in the treatment arm compared to the control arm • Torcetrapib associated with increases in systolic and diastolic blood pressure

  7. Adverse effects of torcetrapib on CVD risk factors • Is the adverse effect due to the mechanism of the drug or something ‘off target’ about this particular drug? • Can we use genetic variation in the CETP gene to understand whether the effect of Torcetrapib is due to its mechanism of action (‘on target’) or to an idiosyncracy of the drug itself (‘off target’)? • Is genetic variation in the CETP gene associated with changes in systolic and diastolic blood pressure?

  8. Association of CETP TaqIB and CVD risk factors • Examination of the association of CETP TaqIB (B1B1, B1B2 vs B2B2) and -629C>A variants (rs708272 and rs1800775 respectively on • CETP • HDL-cholesterol (‘good’ cholesterol) • Diastolic and systolic blood pressure A total of 31 studies and 67,687 individuals of mean age 55.8 (SD 9.6) years

  9. a. Genotype stratified by ethnicity Individuals (No of studies) p value for 2 test of heterogeneity CETP Concentration Mean Difference (95% CI) B1B2* -0.23 (-0.32, -0.14) <0.001 Caucasian 2,763 (6) <0.001 -0.24 (-0.32, -0.16) 1,149 (5) Japanese B2B2* -0.47 (-0.67, -0.26) <0.001 Caucasian 4,086 (6) Japanese 750 (5) -0.52 (-0.74, -0.31) <0.001 -0.75 -0.5 -0.25 0 mg/ ml Association of genetic variation in CETP and CETP protein

  10. c. p value for 2 test of heterogeneity Mean Difference (95% CI) Individuals (No of studies) HDL-Cholesterol Group Comparisons 0.06 (0.05, 0.07) B1B2 v B1B1 Caucasian 54,971 (30) 0.003 Association of genetic variation in CETP and HDL-cholesterol 0.494 0.06 (0.05, 0.06) B1B2 v B1B1 Japanese 1,876 (6) <0.001 0.13 (0.11, 0.14) B2B2 v B1B1 Caucasian 34,432 (30) 0.198 0.16 (0.10, 0.22) 1,179 (6) B2B2 v B1B1 Japanese Stratified analyses: Caucasians only, B2B2 v B1B1 Study Size 0.002 0.13 (0.11, 0.14) >1000 31,772 (20) 0.12 (0.08, 0.15) <1000 3,664 (10) Baseline coronary disease status <0.001 0.10 (0.08, 0.13) 4,385 (9) Affected 0.14 (0.12, 0.17) Unaffected 6,538 (10) 0.13 (0.11, 0.14) Mixed-affected & unaffected 23,083 (13) Gender <0.001 0.11 (0.09, 0.13) 12,822 (16) Male only 6,343 (9) Female only 0.16 (0.14, 0.18) 16,749 (12) Males and Females 0.12 (0.10, 0.14) SNP 0.008 0.12 (0.11, 0.14) rs708272 33,208 (27) rs1800775 2,706 (3) 0.15 (0.10, 0.20) 0 0.06 0.13 mmol/L

  11. a p value for 2 test of heterogeneity Individuals (No of studies) Mean Difference (95% CI) Group Comparisons Systolic Blood Pressure 0.15 B1B2 v B1B1 46,412 (21) -0.27 (-0.64, 0.10) Is CETP variation associated with blood pressure? 29,050 (21) B2B2 v B1B1 0.46 0.16 (-0.28, 0.60) Stratified analyses B2B2 v B1B1 Study Size 0.36 28,047(16) 0.23 (-0.02, 0.69) >1000 -0.47 (-1.90, 0.95) 1,711(6) <1000 Baseline coronary disease status 0.72 -0.16 (-1.64, 1.33) 2,551(3) Affected -0.10 (-0.10, 0.90) Unaffected 4,312(5) 0.28 (-0.24, 0.80) 23,184(14) Mixed-affected & unaffected 0.65 Gender 0.15 (-0.55, 0.85) 9,489 (11) Male only -0.35 (-1.59, 0.89) 4,793 (6) Female only 0.31 (-0.38, 0.99) 15,270 (11) Males and Females SNP 0.23 (-0.22, 0.69) 0.26 27,877 (20) rs708272 -0.80 (-2.49, 0.90) 2,070 (2) rs1800775 SBP by LDL level 0.46 -0.74 (-1.86, 0.38) 6,596 (6) Low LDL 0.15 (-1.93, 2.23) High LDL 6,587 (6) -4 -2 0 2 4 mmHg

  12. b p value for 2 test of heterogeneity Individuals (No of studies) Mean Difference (95% CI) Diastolic Blood Pressure Group Comparisons B1B2 v B1B1 46,412 (21) 0.55 -0.23 (-0.43, -0.04) Is CETP variation associated with blood pressure? 29,050 (21) B2B2 v B1B1 0.10 -0.04 (-0.35, 0.28) Stratified analyses B2B2 v B1B1 Study Size 0.29 28,047(16) >1000 -0.00 (-0.27, 0.26) 1,711(6) <1000 0.02 (-0.15, 1.62) Baseline coronary disease status 2,551(3) 0.33 -0.60 (-1.42, 0.23) Affected Unaffected 4,312(5) -0.09 (-1.03, 0.86) 23,184(14) Mixed-affected & unaffected 0.08 (-0.28, 0.44) Gender 9,489 (11) 0.86 Male only -0.12 (-0.60, 0.35) 4,793 (6) Female only -0.02 (-0.07, 0.67) 15,270 (11) Males and Females -0.02 (-0.58, 0.53) SNP 27,877 (20) rs708272 0.02 0.05 (-0.26, 0.36) 2,070 (2) -1.13 (-2.08, -0.17) rs1800775 SBP by LDL level 6,596 (6) 0.21 Low LDL -0.58 (-1.69, 0.54) 6,587 (6) High LDL 0.24 (-0.37, 0.84) -4 -2 0 2 4 mmHg

  13. DBP 0.50 0.25 Diastolic Blood Pressure (mmHg) 0.00 -0.25 -0.50 5mg B1B2 allele 10mg B2B2 allele HDL-C 0.175 Observed from genetic studies 0.125 HDL (mmol/L) 0.075 Expected, as calculated from trials 0.025 5 mg B1B2 allele 10 mg B2B2 allele Comparing the effect of gene and drug 1.0 SBP 0.5 Systolic Blood Pressure (mmHg) 0.0 -0.5 -1.0 5mg B1B2 allele 10 mg B2B2 allele

  14. Conclusions • 1. Discordance in the effect of CETP SNPs and torcetrapib treatment on blood pressure, despite the concordant effects of gene variants and drug on eight blood lipid and lipoprotein traits indicates that the hypertensive effect of torcetrapib is unlikely to be due to CETP-inhibition. • 2. The findings are important for regulators and manufacturers considering randomised trials of other CETP inhibitor molecules in development. • 3. Using genetic studies as a type of natural trial could have wider application in drug development, helping to validate targets, model drug effects, and distinguish on and off-target effects in man.

More Related