BACKGROUND AND PURPOSE The contribution of genetics to stroke risk, and whether this differs for different stroke subtypes, remainsuncertain. Genomewide complex trait analysis allows heritability to be assessed from genomewide association study (GWAS) data. Previous candidate gene studies have identified many associations with stoke but whether these are important requires replication in large ...

Genome-Wide Association studies (GWAS) have brought a revolutionary change or paradigm shift in detecting novel variants for complex disorders and shifting the burden of finding the biological relevance of these newly discovered variants on biochemists and physiologists, hence it is a movement from forward to reverse genetics. Here we discuss the role of such studies with GWAS designs from anth...

Parkinson’s Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods detect associations between variants the phenotypes ...

We present results from a genomewide association study (GWAS) and a single-marker association study. The GWAS was performed with the Illumina PorcineSNP60 BeadChip from which 5 markers were selected for a validation analysis. Genetic effects were estimated for feed intake, weight gain, and traits of fat and muscle tissue in German Landrace boars kept on performance test stations. The GWAS was p...

By identifying regions of the human genome linked to complex traits, genome-wide association studies (GWAS) are revolutionizing how researchers investigate common diseases, such as cancer and cardiovascular disease. However, as with many great scientific breakthroughs, skeptics have questioned the usefulness of this approach and whether GWAS can provide insights into the molecular mechanisms un...

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the 'missing heritability problem'. Several sources for the missing heritability have been proposed, including the contribution of ...

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits....

BACKGROUND Genome-wide association studies (GWAS) have shown a polygenic component to the risk of schizophrenia. The disorder is associated with impairments in general cognitive ability that also have a substantial genetic contribution. No study has determined whether cognitive impairments can be attributed to schizophrenia's polygenic architecture using data from GWAS. METHODS Members of the...

The aftermath of the Human Genome Project has generated new revolutionary techniques and equipment such as high throughput measurement tools for collecting biological information. One notable tool is a microarray that can be used to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) in one run. This highthroughput SNP genotypes along with phenotypic measurements can be use...

Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT an...