CAPON Association with adjusted QT interval Results of a genome wide association study in KORA S4 and 2 replication cohorts n n KORA S4 3366 4.9 msec 36% < 10 -7 Cohort N Effect MAF Adjusted p KORA F3 2646 7.9 msec 36% < 10 -11 FHS 1805 4.0 msec 39% 0.004 Arking DE, Pfeufer A, Post W et al. Nature Genetics ; published online Apr 30 2006. *QT- adjusted for age, gender and heart rate
Heritability of Left Ventricular Mass
The Framingham Heart Study
Wendy S. Post; Martin G. Larson; Richard H. Myers; Maurizio Galderisi; Daniel Levy
From the National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Mass (W.S.P., M.G.L., R.H.M., M.G., D.L.); the Division of Cardiology, Beth Israel Hospital, Boston, Mass (D.L.); the Department of Neurology (R.H.M.), Division of Epidemiology and Preventive Medicine (M.G.L., D.L.), Boston University School of Medicine; the National Heart, Lung, and Blood Institute, Bethesda, Md (D.L.), University of Naples, Italy (M.G.); and the Division of Cardiology, Johns Hopkins Hospital, Baltimore, Md (W.S.P.).
Confusing genetics nomenclature
Before rs numbers the snp names kept changing
Makes it hard to compare results to prior studies in PubMed
rs numbers (RefSNP accession ID- db SNP)
db SNP- reference database (www.dbsnp.com)
Forward strand versus reverse strand
Dominant model versus recessive model
Relative to major or minor allele?
AB+AB vs BB
Remembering my biochemistry
Exon= region of DNA transcribed into the final mRNA
Complicated authorship issues
Collaboration is key
Collaboration with other cohorts for replication/validation
Order of authorship on manuscripts is not straightforward
Decide before the work is done
What covariates to put in the model?
Epidemiologists “worry” a lot about confounding.
Confounders are associated with the outcome (phenotype) and the predictor (genotype).
most of our traditional confounders are not associated with genotype.
Might want to add covariates for “precision”
How much of the variability in the phenotype is explained by genotype after including known predictors in the model?
Choosing appropriate control groups
Cases and controls need to be collected in a similar fashion
similar environmental exposures
Dealing with population stratification
How big of an issue is it really?
Should we use AIMs or self described race/ethnicity?
AIM (ancestral informative markers)
allele frequencies of snps differ based on parental population
Can estimate the ancestral proportion of an individual
Self described race/ethnicity
When can we combine racial/ethnic groups for analyses when there is no statistical interaction?
Gene-environment and gene-gene interactions
Multiple genes and environmental interactions
Tests for interactions
Multiple testing issues
How to combine multiple genes/snps into same prediction model
Multiple testing issues
Traditionally in epidemiology, seen as “poor science”
GWAS is a really big, sophisticated, fishing expedition
Fishing in Alaska for seven different kinds of salmon, instead of fishing on the LI sound.
What p value do we use?
Bonferroni adjustment seems overly conservative
False Discovery Rate
Need for replication/validation
What cutpoint do we use to move results forward?
Lack of reproducibility
False positives versus
differences in environmental exposures or haplotype structure
different study design
Relative frequency of alleles for a snp are stable in the population (not changing over successive generations).
p 2 , 2pq, q 2
What genetic model to test
2df, additive, dominant, recessive
Again, issues of multiple testing arise
To patent or not to patent our results
Epidemiologists rarely patent findings
History of new scientific discoveries in genetics acquiring patents