Systematic reviews of genetic association

studiesRobert Walton

Fiona Fong

15 March 2013

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

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!

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

Human Genome Epidemiology Network

• Provides online resources – links to suitable papers

• Guidelines for performing and writing genetic systematic reviews

• Center for disease control - Atlanta

What's so different about a genetic

systematic review?

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

Specific genetic factors to consider when performing a

review• Linkage disequilibrium • Hardy Weinberg equilibrium• Different models of gene action

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

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

Assessment of bias

• Confounding– Population stratification

• Family studies TDT• Genomic controls• But how much of a problem is it really?

– Other

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

A practical example of a genetic systematic review in

progress

An example

• Our topic: Genetic factors and pre-eclampsia

• Register with PROSPERO• Our new topic: Genetics factors and

complications of pre-eclampsia

Design

• Protocol• Comprehensive

search • Data extraction• Validity of studies• Meta-analysis

Inclusion criteriaCase control/cohort studiesComplications of pre-eclampsiaMaternal genotype(s) tested Can extract data into 2x2 tableExclusion criteriaGenome wide association studies

MedlineEmbaseCochraneHandsearching of referencesfrom reviews / included studiesHuGENavigator

2 independent reviewers3rd reviewer if discrepancyNo gold standard!Study design – Newcastle Ottawa ScaleGenetically ‘sound’ – STREGA(STrengthening the REporting of Genetic Association Studies)

Additional elements – Data extraction

Traditional meta-analysis

Intervention Control

Observe

Pre-eclampsia No pre-eclampsia

Intervention

Control

Outcome 1

Outcome 2

Genetic meta-analysis

TT TC

Observe

Pre-eclampsia No pre-eclampsia

CC

CC + TC TT

Outcome 1

Outcome 2

Dominant

CC TT + TC

Outcome 1

Outcome 2

Recessive

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)

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

Additional elements - HWEHardy WeinbergEquilibriumA concept of populationgenetics

p2 + 2pq + q2 =1

p2 = genotype AA2pq = genotype Aaq2 = genotype aa

Our methodological quality assessment table

Processing the results

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)

The systematic review process

Formulate research /

policy conclusions

Search bibliographi

c databases

Identify possible papers

from titles/abstracts

Retrieve papers

Extract data

Further selection of

primary studies using inclusion

criteria

Synthesi

s

Formulate

research question

Design search

strategy

Quality

appraisal

STREGA

Nomenclature

Genetic model(dominant?)

HUGE

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