Abstract
Health investigators routinely collect DNA and environmental data from study participants in order to assess the impact of genetic and environmental risk factors on an outcome of interest. When planning a study, alternate study designs are evaluated to minimize bias and achieve a large enough sample size from available resources. With the enormous volumes of high-quality biomedical data housed within its numerous biobanks, Norway is particularly well-suited to spearhead the investigation of a wide array of exposures and outcomes in a systematic manner. The rich array of longitudinal phenotypic data also permits an assessment of geneenvironment- timing interactions. Maximizing the research potential inherent in Norwegian biobanks is the overarching aim of Biobank Norway, an infrastructure project recently funded by the Norwegian Research Council. The development of advanced statistical tools for the analysis of high-throughput genomic data is critical to fulfill this aim and biostatistics platforms have been key elements of major biobank harmonization initiatives. However, many of these approaches have focused on traditional case-control designs. To exploit the particular advantages inherent in the Norwegian Mother and Child Cohort Study (MoBa), we describe here models to analyze the special data configurations available with offspring-parent designs. These models and the statistical tools outlined in this review were developed through the support of Biohealth Norway, a biobank platform funded by the Norwegian Functional Genomics Research Program (FUGE).
Highlights
AND BACKGROUNDMost epidemiologists have become accustomed to modeling the effect of an allele or haplotype in just the same way as they would normally model an environmental exposure
Are the relative risk estimates for the same analysis as in the previous example, with the difference that maternal effects are included, and there is no assumption about a doseresponse relationship: haplin(“C:/work/data.dat”, marker = 1, use.missing = T, design = “cc.triad”, n.vars = 7, ccvar = 2, maternal = T)
The model is similar to the X-likelihood ratio test (LRT) approach, but we extend the model to haplotypes and a selection of geneeffect models
Summary
Most epidemiologists have become accustomed to modeling the effect of an allele or haplotype in just the same way as they would normally model an environmental exposure. We apply a novel “hybrid design” that combines the merits of the case-control and offspring-parent triad designs Does this hybrid design enhance statistical power by providing more controls per case, it allows an estimation of the main effect of an exposure. The hybrid design can be used to estimate genetic effects for loci that exhibit deviations from Mendelian transmission This is done by comparing the relative risk in the case-parent triads with the relative risk estimated from the control-parent triads. A user-friendly graphical user interface (GUI), which includes some (but not all) of the Haplin functionalities, is available at http:// haplin.fhi.no
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
