This brief review provides a summary of the biological causes of genetic association between tightly linked markers--termed linkage disequilibrium--and unlinked markers--termed population structure. We also review the utility of linkage disequilibrium data in gene mapping in isolated populations, in the estimation of recombination rates and in studying the history of particular alleles, includi...

With respect to the multiple-tests problem, recently an increasing amount of attention has been paid to control the false discovery rate (FDR), the positive false discovery rate (pFDR), and the proportion of false positives (PFP). The new approaches are generally believed to be more powerful than the classical Bonferroni one. This article focuses on the PFP approach. It demonstrates via example...

Exploration of the human genome presents new challenges and opportunities for epidemiological research. Although the case-control design is quicker and cheaper for study of associations between genotype and risk of disease than the cohort design, cohort studies have been recommended because they can be used to study gene-environment interactions. Although the scientific relevance of statistical...

Genetic association studies have explained only a small proportion of the estimated heritability of complex traits, leaving the remaining heritability "missing." Genetic interactions have been proposed as an explanation for this, because they lead to overestimates of the heritability and are hard to detect. Whether this explanation is true depends on the proportion of variance attributable to g...

In genetic association studies, different complex phenotypes are often associated with the same marker. Such associations can be indicative of pleiotropy (i.e. common genetic causes), of indirect genetic effects via one of these phenotypes, or can be solely attributable to non-genetic/environmental links between the traits. To identify the phenotypes with the inducing genetic association, stati...

Genotype-imputation methods provide an essential technique for high-resolution genome-wide association (GWA) studies with millions of single-nucleotide polymorphisms. For optimal design and interpretation of imputation-based GWA studies, it is important to understand the connection between imputation error and power to detect associations at imputed markers. Here, using a 2x3 chi-square test, w...

G enetic association studies have the potential to provide a valuable insight into disease mechanisms. However, many studies submitted to journals such as Thorax are underpowered or poorly designed. This has led to a number of journals providing guidance to investigators regarding the design of studies which would be considered for publication within the journal. In the editorial which follows ...

The International HapMap Project produced a genome-wide database of human genetic variation for use in genetic association studies of common diseases. The initial output of these studies has been overwhelming, with over 150 risk loci identified in studies of more than 60 common diseases and traits. These associations have suggested previously unsuspected etiologic pathways for common diseases t...

The recent discovery that microRNAs (miRNAs) are present in the circulation sparked interest in their use as potential biomarkers. In this review, we will summarize the latest findings on circulating miRNAs and cardiovascular disease but also discuss analytical challenges. While research on circulating miRNAs is still in its infancy, high analytical standards in statistics and study design are ...

Statistical approaches to evaluate interactions between single nucleotide polymorphisms (SNPs) and SNP-environment interactions are of great importance in genetic association studies, as susceptibility to complex disease might be related to the interaction of multiple SNPs and/or environmental factors. With these methods under active development, algorithms to simulate genomic data sets are nee...