Abstract
Case-control genome-wide association studies (CC-GWAS) might provide valuable clues to the underlying pathophysiologic mechanisms of complex diseases, such as neurodegenerative disease and cancer. A commonly overlooked complication is that multiple distinct disease states might present with the same set of symptoms and hence share a clinical diagnosis. These disease states can only be distinguished based on a biomarker evaluation that might not be feasible in the whole set of cases in the large number of samples that are typically needed for CC-GWAS. Instead, the biomarkers are measured on a subset of cases. Or an external reliability study estimates the frequencies of the disease states of interest within the clinically diagnosed set of cases. These frequencies often vary by the genetic and/or nongenetic variables. We derive a simple approximation that relates the genetic effect estimates obtained in a traditional logistic regression model with the clinical diagnosis as the outcome variable to the genetic effect estimates in the relationship to the true disease state of interest. We performed simulation studies to assess the accuracy of the approximation that we have derived. We next applied the derived approximation to the analysis of the genetic basis of the innate immune system of Alzheimer's disease.
Highlights
Case-control genome-wide analyses scan (CC-GWAS) is a tool that is widely used to elucidate the genetic basis of complex diseases
We derive a simple approximation that relates the genetic effect estimates obtained in a traditional logistic regression model with the clinical diagnosis as the outcome variable to the genetic effect estimates in the relationship to the true disease state of interest
It is possible that the Alzheimer’s disease (AD)-symptoms with and without amyloid evidence have the same genetic basis and the clinical diagnosis is a surrogate of the disease states
Summary
Case-control genome-wide analyses scan (CC-GWAS) is a tool that is widely used to elucidate the genetic basis of complex diseases. If the disease states have distinct genetic basses, the analyses with a clinical diagnosis as an outcome variable might be substantially biased (Carroll et al, 2006). It is possible that the AD-symptoms with and without amyloid evidence have the same genetic basis and the clinical diagnosis is a surrogate of the disease states. It is possible, that the AD-symptoms underlined by the amyloid evidence and the ADsymptoms with no amyloid evidence have distinct genetic bases. We compare the estimates in a practical setting of an Alzheimer’s disease study that aims to investigate the genetic basis of innate immune system in the relationship to the AD symptoms underlined by amyloid pathology.
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