1 / 24

Importance of data collection for inherited disease research

Importance of data collection for inherited disease research. John L. Hopper Centre for Molecular, Environmental, Genetic, and Analytic (MEGA) Epidemiology The University of Melbourne. Question of critical clinical importance.

connie
Télécharger la présentation

Importance of data collection for inherited disease research

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. Importance of data collection for inherited disease research John L. Hopper Centre for Molecular, Environmental, Genetic, and Analytic (MEGA) Epidemiology The University of Melbourne

  2. Question of critical clinical importance What are the disease risks associated with particular genetic variants? • Answering this is no simple matter • Importance of adjusting for ascertainment • Need to use valid statistical methods • Clarity about who inference is being made • Imprecision and bias of estimates

  3. Designs Population-based sampling • Case-control • Case-control-family • Family Community sampling • Cohort • Twin studies Opportunistic sampling • Multiple-case families • Tumour banks

  4. Basics of Statistical Inference RANDOM POPULATION SAMPLE PARAMETER ESTIMATE UNKNOWN PARAMETER INFERENCE

  5. DESIGN,DESIGN&DESIGN

  6. ascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainment…ascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainmentASCERTAINMENTascertainment…

  7. CONCLUSION SAMPLING ISSUES ARE IMPORTANT

  8. Australian Breast Cancer Family Study Population-based sampling - 1,600 Cases (Vic & NSW Cancer Registries) - 1,000 Controls (Electoral Rolls) Cases - unselected for family history - over-sampled for early onset (50% < age 40) Relatives (1o & 2o) of cases and controls Epidemiological data (by questionnaire) Genetic and molecular (blood, tissue) Part of NIH-funded Breast Cancer Family Registry John, Hopper, et al., Br Cancer Res 2004

  9. BRCA1 1bp del 1876 (C) 81 70 75 88 ?Breast(42) 47 65 61 57 63 74 73 53 69 42 60 64 50 61 58 _ Prostate(65) Breast(48) ?Breast(53) ?Larynx(60) ?Lung(50) 38 40 41 37 34 Breast(38) + 3159

  10. BRCA2 2bp del 6503 (TT) 64 57 75 6 6 58 0 12 60 67 59 76 78 Breast(55) Breast(38) Bowel(58) Breast(62) (+) + ?Bowel(67) 44 41 54 52 50 41 38 Breast(38) _ _ _ + + + + 12 12 10 8 3172

  11. That was the “outlier” It does not represent a “typical BRCA1/2 family”!

  12. hereditary familial sporadic

  13. >2 affected 1 in 2 <1% 2 affected 1 in 8 5% Familial 1 affected 1 in 16 35% 0 affected 1 in 20 Sporadic 60% Hereditary

  14. Penetrance • Average age-specific cumulative risk in defined sets of carriers • Risk associated with mutation(s) • Mutations rare so need family design • Estimate is of “average risk” over the (types of) mutations in the “population” • Have to take into account how mutation-segregating families were “ascertained” • Clinic-based families have about 3 times less information per carrier family than population-based families

  15. BRCA1 Multiple-case families family cancer clinics Population-based study Antoniou et al (2003)

  16. BRCA2 Multiple-case families family cancer clinics Population-based study Antoniou et al (2003)

  17. Colorectal Cancer Risk for hMLH1 and hMSH2 Mutation Carriers 100 INCORRECT ESTIMATES from MISANALYSIS of data from multiple-case families from family cancer clinics 80 60 Cumulative risk of colorectal cancer (%) 40 Population-based study Jenkins et al (2005) 20 0 20 30 40 50 60 70 Age (years)

  18. Conclusions • Population-based studies often best resource to minimise problems • Must be analysed and interpreted properly • Epidemiology provides solid theoretical basis and tools • Genetics aren’t trained in epidemiology • Multi-disciplinary approach needed • Large informative studies needed

  19. Solutions? Expert committee to gather data and estimate risks • e.g. Antoniou et al. (Cambridge) for breast cancer Jenkins et al. (Melbourne) for colorectal cancer, using Colon CFR and other resources

  20. Model/Predict Risk for Carriers Hazard ratio – increased risk cf. population • Age of individual at risk • Age at onset of proband • Mode of family ascertainment/ FH • Type & other characteristics of the mutation • Grantham scores • Functional assays • … Gives the clinician the best predictor of risk (not: Deleterious? yes, no, don’t know!)

  21. Australasian Colorectal Cancer Family Study • Population-based sampling • - 800 Cases (Vic Cancer Registry) • - 400 Controls (Electoral Rolls; spouses) • Cases - unselected for family history • - over-sampled for early onset (50% < age 45) • Relatives (1o & 2o) of cases and controls • Epidemiological data (by questionnaire) • Genetic and molecular (blood, tissue) • 500 multiple-case families from Australia & NZ Part of NIH-funded Colon Cancer Family Registry

  22. SEATTLE LOSANGELES HAWAII ADVISORY COMMITTEE MAYO STEERING COMMITTEE ONTARIO AUSTRALASIA WORKING GROUPS RESEARCH GROUPS EXTERNAL RESEARCH GROUPS INFORMATICS SUPPORT CENTER CENTRAL BIOSPECIMENS REPOSITORY NCI PROGRAM

  23. Great opportunity for Australia to show leadership …

More Related