1. Systematic reviews of genetic association studies Robert Walton Fiona Fong 15 March 2013

2. Outline of session Reasons for doing a systematic review Differences in methods between genetic systematic review and conventional Assessment of bias Meta analysis A practical example of a genetic systematic review in progress – Fiona Fong

3. Why do a genetic systematic review? Identify genes previously studied and positive or negative associations with different outcomes Standardise statistical analysis Make sub group analyses Plan future work Make grant applications Publish!

4. Citations per year The genetic basis for smoking behavior: a systematic review and meta-analysis Marcus R Munafò, Taane G Clark, Elaine C Johnstone, Michael FG Murphy, Robert T Walton Cited by 213 Genetic systematic reviews are generally well cited in the literature

5. Human Genome Epidemiology Network Provides online resources – links to suitable papers Guidelines for performing and writing genetic systematic reviews Center for disease control - Atlanta

6. What's so different about a genetic systematic review?

7. Genetic systematic reviews are very similar to systematic reviews of observational studies Very important to work out the question fully and precisely Abstract reviewing paper selection and data extraction are the same Meta analysis is very similar need to consider the genetic question carefully too Interpretation of the results may need to take into account an understanding of how genes work

8. Specific genetic factors to consider when performing a review Linkage disequilibrium Hardy Weinberg equilibrium Different models of gene action

9. Assessment of bias Selection bias – Extreme vs unselected cases – Use of prevalent cases – Using a phenotypic test – Biased selection of controls – Differential participation and dropout

10. Assessment of bias Information bias – Misclassification of genotype – Were the laboratory staff blind? – Using a phenotypic test – Biased selection of controls – Differential participation and dropout – Genotyping error

11. Assessment of bias Confounding – Population stratification Family studies TDT Genomic controls But how much of a problem is it really? – Other

12. Meta analysis of genetic studies Useful not just for summary estimate but to investigate heterogeneity Meta regression Odds ratios, differences in means and standardised mean differences Choice of genetic model Sensitivity analysis – Hardy Weinberg deviation Use of individual patient data

13. A practical example of a genetic systematic review in progress

14. An example Our topic: Genetic factors and pre-eclampsia Register with PROSPERO Our new topic: Genetics factors and complications of pre-eclampsia

15. Design Protocol Comprehensive search Data extraction Validity of studies Meta-analysis Inclusion criteria Case control/cohort studies Complications of pre-eclampsia Maternal genotype(s) tested Can extract data into 2x2 table Exclusion criteria Genome wide association studies Medline Embase Cochrane Handsearching of references from reviews / included studies HuGENavigator 2 independent reviewers 3 rd reviewer if discrepancy No gold standard! Study design – Newcastle Ottawa Scale Genetically ‘sound’ – STREGA (STrengthening the REporting of Genetic Association Studies)

16. Additional elements – Data extraction Traditional meta-analysis InterventionControl Observe Pre-eclampsiaNo pre-eclampsia InterventionControl Outcome 1 Outcome 2 Genetic meta-analysis TTTC Observe Pre-eclampsiaNo pre-eclampsia CC CC + TCTT Outcome 1 Outcome 2 Dominant CCTT + TC Outcome 1 Outcome 2 Recessive

17. Which genetic model? 3 groups+ – Dominant (CC + TC vs TT) – Recessive (CC vs TT + TC) – Co-dominant (CC vs TT, CC vs TC, TT vs TC) Choose a model based on previous evidence Look at control group genotype frequencies to determine minor allele (ie aa)

18. Additional elements – STREGA STrengthening the REporting of Genetic Association studies To enhance transparency of reporting – Methods variables Population stratification (eg ethnicity) Nomenclature system Genotyping errors – Data sources ie DNA processing – Hardy Weinberg Equilibrium

19. Additional elements - HWE Hardy Weinberg Equilibrium A concept of population genetics p 2 + 2pq + q 2 =1 p 2 = genotype AA 2pq = genotype Aa q 2 = genotype aa

20. Our methodological quality assessment table

21. Processing the results

22. What does this lead to? Successful systematic reviews of genetic studies can collate evidence across all studied genetic variants for a phenotype to form genetic association evidence databases. – Alzheimer disease (Alzgene database) – Parkinson disease (PDGene database) – Schizophrenia database (SzGene database)

23. The systematic review process Formulate research / policy conclusions Search bibliographic databases Identify possible papers from titles/abstracts Retrieve papers Extract data Further selection of primary studies using inclusion criteria Synthesis Formulate research question Design search strategy Quality appraisal STREGA Nomenclature Genetic model (dominant?) HUGE

24. Useful resources HuGENet handbook – http://www.medicine.uottawa.ca/public-health- genomics/web/assets/documents/HuGE_Review_Handbook_V1_0.pdf STREGA – http://link.springer.com/article/10.1007%2Fs00439-008-0592-7 PROSPERO – http://www.crd.york.ac.uk/Prospero/ Hardy Weinberg Equilibrium calculator – http://www.tufts.edu/~mcourt01/lab_protocols.htm