kruX:Matrix-based non-parametric eQTL discovery

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. In summary, kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure.Comment: minor revision; 6 pages, 5 figures; software available at http://krux.googlecode.co

Genetic susceptibility loci for cardiovascular disease and their impact on atherosclerotic plaques

Background: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms. Methods: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression. Results: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10−6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood. Conclusions: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics

Human Validation of Genes Associated With a Murine Atherosclerotic Phenotype

ObjectiveThe genetically modified mouse is the most commonly used animal model for studying the pathogenesis of atherosclerotic disease. We aimed to assess if mice atherosclerosis-related genes could be validated in human disease through examination of results from genome-wide association studies. Approach and ResultsWe performed a systematic review to identify atherosclerosis-causing genes in mice and carried out gene-based association tests of their human orthologs for an association with human coronary artery disease and human large artery ischemic stroke. Moreover, we investigated the association of these genes with human atherosclerotic plaque characteristics. In addition, we assessed the presence of tissue-specific cis-acting expression quantitative trait loci for these genes in humans. Finally, using pathway analyses we show that the putative atherosclerosis-causing genes revealed few associations with human coronary artery disease, large artery ischemic stroke, or atherosclerotic plaque characteristics, despite the fact that the majority of these genes have cis-acting expression quantitative trait loci. ConclusionsA role for genes that has been observed in mice for atherosclerotic lesion development could scarcely be confirmed by studying associations of disease development with common human genetic variants. The value of murine atherosclerotic models for selection of therapeutic targets in human disease remains unclear

Inherited Risk Enrichment Analysis ofgene sets using Genome-wide AssociationStudies for Coronary Artery Disease

Genome-wide association studies (GWAS) has been in the heartof medical research for the last 5 years. These studies seek forcommon variants in the genome that are linked to risk for commoncomplex diseases (CCDs). Although GWAS has defined a numberof interesting genetic loci for a range of CCDs, the current GWASanalysis has limitation such as investigating the DNA variantsone-by-one focusing on the most significant DNA variants. As aconsequence, most risk variants for CCDs are, in my belief, stillhidden in the GWAS data. Herein, I use a method of GWASanalysis that considers risk-enrichment for groups of functionallyassociated genes defined by for example gene networks, believedto play a role in CCDs.In this method, a set of expression SNP (single nucleotidepolymorphism) was selected from genes which are known to berelated to coronary artery disease (CAD) in a way that a singleeSNP was chosen for each gene. Then using the data availablefrom the International HapMap Project and a GWAS data available,it is possible to find SNPs which are in strong linkage withthe initial set, which we call it expanded set. Depending on theassociation of the initial set to the CAD, expanded set can showan enrichment score greater or smaller compared to the null distributionset of SNPs with same properties of the expanded set.In conclusions, CCDs are not a consequence of isolated geneticvariants/genes in isolated pathways but instead sets of geneticvariants/genes acting in conjunction, cause CAD. Genetic riskenrichment analysis is a fairly simple and straightforward methodto determine to what extent a group of functionally associatedgenetic variants/genes are enriched for a given CCD. In addition,this analysis can perhaps help to decipher some of the 90-85% ofrisk variation in populations that remains unaccounted

Sensitive Detection of Cell-Free Tumour DNA Using Optimised Targeted Sequencing Can Predict Prognosis in Gastro-Oesophageal Cancer

In this longitudinal study, cell-free tumour DNA (a liquid biopsy) from plasma was explored as a prognostic biomarker for gastro-oesophageal cancer. Both tumour-informed and tumour-agnostic approaches for plasma variant filtering were evaluated in 47 participants. This was possible through sequencing of DNA from tissue biopsies from all participants and cell-free DNA from plasma sampled before and after surgery (n = 42), as well as DNA from white blood cells (n = 21) using a custom gene panel with and without unique molecular identifiers (UMIs). A subset of the plasma samples (n = 12) was also assayed with targeted droplet digital PCR (ddPCR). In 17/31 (55%) diagnostic plasma samples, tissue-verified cancer-associated variants could be detected by the gene panel. In the tumour-agnostic approach, 26 participants (59%) had cancer-associated variants, and UMIs were necessary to filter the true variants from the technical artefacts. Additionally, clonal haematopoietic variants could be excluded using the matched white blood cells or follow-up plasma samples. ddPCR detected its targets in 10/12 (83%) and provided an ultra-sensitive method for follow-up. Detectable cancer-associated variants in plasma correlated to a shorter overall survival and shorter time to progression, with a significant correlation for the tumour-informed approaches. In summary, liquid biopsy gene panel sequencing using a tumour-agnostic approach can be applied to all patients regardless of the presence of a tissue biopsy, although this requires UMIs and the exclusion of clonal haematopoietic variants. However, if sequencing data from tumour biopsies are available, a tumour-informed approach improves the value of cell-free tumour DNA as a negative prognostic biomarker in gastro-oesophageal cancer patients

Additional file 5: Table S6. of Systematic analysis of chromatin interactions at disease associated loci links novel candidate genes to inflammatory bowel disease

Upstream regulators. (XLSX 135 kb

Additional file 7: Table S3. of Systematic analysis of chromatin interactions at disease associated loci links novel candidate genes to inflammatory bowel disease

Publicly available datasets. (XLSX 11 kb