Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide association study consisting of genetic variants from chromosomes 3 and 9 and longitudinal measured p...

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scor...

The worldwide burden of tuberculosis (TB) remains an enormous problem, and is particularly severe in the admixed South African Coloured (SAC) population residing in the Western Cape. Despite evidence from twin studies suggesting a strong genetic component to TB resistance, only a few loci have been identified to date. In this work, we conduct a genome-wide association study (GWAS), meta-analysi...

In the analysis of genome-wide association (GWA) data, the aim is to detect statistical associations between single nucleotide polymorphisms (SNPs) and the disease or trait of interest. These SNPs, or the particular regions of the genome they implicate, are then considered for further study. We demonstrate through a comprehensive simulation study that the inclusion of additional, biologically r...

Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each individual person's gene...

Genetic analysis of complex diseases demands novel analytical methods to interpret data collected on thousands of variables by genome-wide association studies. The complexity of such analysis is multiplied when one has to consider interaction effects, be they among the genetic variations (G x G) or with environment risk factors (G x E). Several statistical learning methods seem quite promising ...

BACKGROUND Schizophrenia (SCZ) is a very heterogeneous disease that affects approximately 1% of the general population. Recently, the genetic complexity thought to underlie this condition was further supported by three independent studies that identified an increased number of damaging de novo mutations DNM in different SCZ probands. While these three reports support the implication of DNM in t...

Before the genomics technology revolution allowed us to do genome-wide science, genetics research relied on our limited knowledge about a subject to generate hypothesis and candidate genes to study. Despite the level of naiveté, several associations with susceptibility to a complex disease such as multiple sclerosis (MS) were discovered. Of these, HLA-DRB1 and IL7R (1) stand out as being confir...

In case-control genetic association studies, cases are subjects with the disease and controls are subjects without the disease. At the time of case-control data collection, information about secondary phenotypes is also collected. In addition to studies of primary diseases, there has been some interest in studying genetic variants associated with secondary phenotypes. In genetic association stu...

BACKGROUND Recent technologies enable genetic association studies of common clinical analytes on a genomewide basis in populations numbering thousands of individuals. The first publications using these technologies are already revealing novel biological functions for both genic and nongenic loci, and are promising to transform knowledge about the biological networks underlying disease pathophys...