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