1. Genetic-Environmental Interaction: Implications for Osteoporosis Prevention Strategies

2. How many Australians have osteoporosis? Current Increased BMD by 10% x1000

3. Annual incidence of fractures in Australia? All fractures Hip fractures x1000 Year

4. Can we predict, reduce, prevent, eliminate osteoporosis and fractures?

5. Aetiology Mendelian Chromosomal aetiology Multifactorial aetiology with high heritability Multifactorial aetiology with low heritability Infectious aetiology Environmental aetiology

6. Determinants of BMD GeneticsEnvironment Lumbar spine0.7780.222 Femoral neck0.7640.236 Total body0.7860.214

7. Can we use environmental factors to predict fracture? Can we use genetic factors to predict fracture?

8. Criteria Validity and available of tests Public health impact Magnitude of association between risk factor and fracture Interaction between known environmental factors and genes Availability of safe and efficacious treatment Confidentiality, ethics

9. Risk Factors for Hip Fx in Females Osteoporosis 1 (Y/N)7.9 (3.9 - 16.1)0.260.65 Body sway (75th pct)3.6 (1.8 - 7.0)0.250.48 Previous falls (Y/N)3.5 (1.8 - 6.9)0.310.44 Any of the three factors 22.9 (3.1 - 34.7)0.600.93 Risk factor Relative Risk Prevalence AR 1 : Defined by FNBMD

10. Distribution of BMD & incidence of fractures

11. Familial Relative Risk of Fracture Intraclass correlation RR of BMDr=0.8r=0.9 _________________________________________________ 51.141.16 61.171.20 71.211.24 81.241.28 _________________________________________________

12. Strategies for Prevention of Osteoporosis Population-based strategy High risk strategy Genetic-environmental based strategy ?

13. Population Attributable Risk (PAF) proportion by which the incidence rate of disease in the population would be reduced if the risk factors were eliminated Positive Predictive Value (PPV) Risk of disease among individuals with the presence of a risk factor Some Epidemiological Concepts

14. General Formulation of a Screening Model Parameters Lifetime risk of fracture (d) Prevalence of risk factor (e) Relative risk of risk factor (R) Sensitivity, Specificity and PPV Sensitivity = R / [(1 + e(R-1)] Specificity = [(1-e)/(1-d)] [1 - Rd/(1 + e(R-1))] PPV = Rd / (1 + e(R-1))

15. Effectiveness _______________________________________________________________ Population-based 1 20%0.6250.4670.714 High risk 2 9%0.9520.2750.476 _______________________________________________________________ Assumptions: Lifetime risk = 0.4; RR = 5 1 Shift the whole distribution by 10% increase 2 Selecting only osteoporotic subjects and increase BMD by 10% Strategy Fx Reduction SensSpecPPV

16. What about an genetic-environmental approach ?

17. Effects of high risk genotypes vary depending on environmental exposure or restricted to exposed subjects Effects of environmental risk factor vary depending on susceptible genotypes What is Gene-Environment Interaction?

18. ... more emphasis has been placed on the concept of "effect" rather than on "interaction". There is no reason to believe that VDR gene would act in isolation from other genetic and environmental factors

19. A single, simple observation of differential effect between genotypes of a genetic marker across different environmental milieu is not sufficient evidence for genetic-environmental interaction A statistical interaction is not necessary the same with a GxE interaction Some Misunderstanding

20. Twin modelling Regression analysis Sibling interaction analysis Detection of GxE Interaction?

21. Heritability of Bone Density AgerMZrDZH 2 LSBMD Slemenda et al440.850.330.97 Pocock et al470.920.360.92 Nguyen et al500.740.430.78 Spector et al600.680.290.78 Flicker et al690.700.330.74

22. Formulation of G x E Models: Parameters Lifetime risk of fracture (d) Prevalence of risk factor (e) Relative risk of risk factor (R) Prevalence of genotype (g) Formulation GenotypeRiskPrevalenceRR AbsenceAbsence(1-g)(1-e)1 AbsencePresence(1-g)eR e PresenceAbsence(1-e)gR g PresencePresencegeR ge

23. Model I: R e = R g = 1 Model II: R e > 1, R g = 1 Model III: R g > 1, R e = 1 Model IV: R e > 1, R g > 1 Models of Interaction

24. Effects of GxE on PPV and PAF g No GxE Model 1 Model 2 Model 3 Multiplicative _____________________________________________________________________________________ 0.10.221.00 (0.23)0.75 (0.12)0.56 (0.15)0.82 (0.14) 0.150.230.89 (0.23)0.56 (0.12)0.27 (0.09)0.72 (0.18) 0.200.230.69 (0.23)0.46 (0.12)0.15 (0.04)0.64 (0.21) 0.300.230.50 (0.23)0.37 (0.13)0.06 (0.02)0.52 (0.23) 0.400.230.40 (0.23)0.32 (0.13)0.03 (0.01)0.44 (0.25) d=0.15, R = 2, e = 0.30

25. Summary For a RR=2 or 3, low PPV and PAF Introduction of GxE increases PPV, but decreases PAF High prevalence of susceptible genotype increases PAF, but decreases PPV

26. Future Directions Description of osteoporosis/fx in population: gene frequencies, prevalence of risk factors Determinants of osteo/fx in population: risk factors, genetic markers, population genetics. Determination of osteo/fx in families: familial aggregation, heritability studies, segregation studies Gene environmental studies

27. Future Directions Natural history of osteporosis Intervention: clinical trials, genetic differences in response to treatments Prevention: screening, counselling, carrier detection Impact of osteoporosis: mortality, morbidity, QoL