Inke R. König

A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium.

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

Repeated Replication and a Prospective Meta-Analysis of the Association Between Chromosome 9p21.3 and Coronary Artery Disease

Background— Recently, genome-wide association studies identified variants on chromosome 9p21.3 as affecting the risk of coronary artery disease (CAD). We investigated the association of this locus with CAD in 7 case-control studies and undertook a meta-analysis. Methods and Results— A single-nucleotide polymorphism (SNP), rs1333049, representing the 9p21.3 locus, was genotyped in 7 case-control studies involving a total of 4645 patients with myocardial infarction or CAD and 5177 controls. The mode of inheritance was determined. In addition, in 5 of the 7 studies, we genotyped 3 additional SNPs to assess a risk-associated haplotype (ACAC). Finally, a meta-analysis of the present data and previously published samples was conducted. A limited fine mapping of the locus was performed. The risk allele (C) of the lead SNP, rs1333049, was uniformly associated with CAD in each study (P<0.05). In a pooled analysis, the odds ratio per copy of the risk allele was 1.29 (95% confidence interval, 1.22 to 1.37; P=0.0001). Haplotype analysis further suggested that this effect was not homogeneous across the haplotypic background (test for interaction, P=0.0079). An autosomal-additive mode of inheritance best explained the underlying association. The meta-analysis of the rs1333049 SNP in 12 004 cases and 28 949 controls increased the overall level of evidence for association with CAD to P=6.04×10−10 (odds ratio, 1.24; 95% confidence interval, 1.20 to 1.29). Genotyping of 31 additional SNPs in the region identified several with a highly significant association with CAD, but none had predictive information beyond that of the rs1333049 SNP. Conclusion— This broad replication provides unprecedented evidence for association between genetic variants at chromosome 9p21.3 and risk of CAD.

Strong genetic evidence of DCDC2 as a susceptibility gene for dyslexia.

We searched for linkage disequilibrium (LD) in 137 triads with dyslexia, using markers that span the most-replicated dyslexia susceptibility region on 6p21-p22, and found association between the disease and markers within the VMP/DCDC2/KAAG1 locus. Detailed refinement of the LD region, involving sequencing and genotyping of additional markers, showed significant association within DCDC2 in single-marker and haplotype analyses. The association appeared to be strongest in severely affected patients. In a second step, the study was extended to include an independent sample of 239 triads with dyslexia, in which the association--in particular, with the severe phenotype of dyslexia--was confirmed. Our expression data showed that DCDC2, which contains a doublecortin homology domain that is possibly involved in cortical neuron migration, is expressed in the fetal and adult CNS, which--together with the hypothesized protein function--is in accordance with findings in dyslexic patients with abnormal neuronal migration and maturation.

Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is a severe liver disease of unknown etiology leading to fibrotic destruction of the bile ducts and ultimately to the need for liver transplantation. We compared 3,789 PSC cases of European ancestry to 25,079 population controls across 130,422 SNPs genotyped using the Immunochip. We identified 12 genome-wide significant associations outside the human leukocyte antigen (HLA) complex, 9 of which were new, increasing the number of known PSC risk loci to 16. Despite comorbidity with inflammatory bowel disease (IBD) in 72% of the cases, 6 of the 12 loci showed significantly stronger association with PSC than with IBD, suggesting overlapping yet distinct genetic architectures for these two diseases. We incorporated association statistics from 7 diseases clinically occurring with PSC in the analysis and found suggestive evidence for 33 additional pleiotropic PSC risk loci. Together with network analyses, these findings add to the genetic risk map of PSC and expand on the relationship between PSC and other immune-mediated diseases.

Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics

The random forest (RF) algorithm by Leo Breiman has become a standard data analysis tool in bioinformatics. It has shown excellent performance in settings where the number of variables is much larger than the number of observations, can cope with complex interaction structures as well as highly correlated variables and return measures of variable importance. This paper synthesizes 10 years of RF development with emphasis on applications to bioinformatics and computational biology. Special attention is paid to practical aspects such as the selection of parameters, available RF implementations, and important pitfalls and biases of RF and its variable importance measures (VIMs). The paper surveys recent developments of the methodology relevant to bioinformatics as well as some representative examples of RF applications in this context and possible directions for future research.

On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data

MOTIVATION Genome-wide association (GWA) studies have proven to be a successful approach for helping unravel the genetic basis of complex genetic diseases. However, the identified associations are not well suited for disease prediction, and only a modest portion of the heritability can be explained for most diseases, such as Type 2 diabetes or Crohns disease. This may partly be due to the low power of standard statistical approaches to detect gene-gene and gene-environment interactions when small marginal effects are present. A promising alternative is Random Forests, which have already been successfully applied in candidate gene analyses. Important single nucleotide polymorphisms are detected by permutation importance measures. To this day, the application to GWA data was highly cumbersome with existing implementations because of the high computational burden. RESULTS Here, we present the new freely available software package Random Jungle (RJ), which facilitates the rapid analysis of GWA data. The program yields valid results and computes up to 159 times faster than the fastest alternative implementation, while still maintaining all options of other programs. Specifically, it offers the different permutation importance measures available. It includes new options such as the backward elimination method. We illustrate the application of RJ to a GWA of Crohns disease. The most important single nucleotide polymorphisms (SNPs) validate recent findings in the literature and reveal potential interactions. AVAILABILITY The RJ software package is freely available at http://www.randomjungle.org

Shared Genetic Susceptibility to Ischemic Stroke and Coronary Artery Disease A Genome-Wide Analysis of Common Variants

Background and Purpose— Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each has a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases. Methods— Genome-wide association data were obtained from the METASTROKE, Coronary Artery Disease Genome-wide Replication and Meta-analysis (CARDIoGRAM), and Coronary Artery Disease (C4D) Genetics consortia. We first analyzed common variants reaching a nominal threshold of significance (P<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2167 individuals with the ischemic large artery stroke (LAS) subtype. Results— Common variants associated with CAD at P<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, 3 and 5 loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (P<5×10−8) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Because these loci had prior evidence for genome-wide significance for CAD, we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (PIS=1.62×10−7) and ABO (PIS=2.6×10−4), as well as at HDAC9 (PLAS=2.32×10−12), 9p21 (PLAS=3.70×10−6), RAI1-PEMT-RASD1 (PLAS=2.69×10−5), EDNRA (PLAS=7.29×10−4), and CYP17A1-CNNM2-NT5C2 (PLAS=4.9×10−4). Conclusions— Our results demonstrate substantial overlap in the genetic risk of IS and particularly the LAS subtype with CAD.

Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: A Genome-Wide Association Meta-analysis Involving More Than 22 000 Cases and 60 000 Controls

Background—Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed. Methods and Results—CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2×10−20). Conclusion—CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

Biostatistical Aspects of Genome‐Wide Association Studies

To search the entire human genome for association is a novel and promising approach to unravelling the genetic basis of complex genetic diseases. In these genome-wide association studies (GWAs), several hundreds of thousands of single nucleotide polymorphisms (SNPs) are analyzed at the same time, posing substantial biostatistical and computational challenges. In this paper, we discuss a number of biostatistical aspects of GWAs in detail. We specifically consider quality control issues and show that signal intensity plots are a sine qua condition non in todays GWAs. Approaches to detect and adjust for population stratification are briefly examined. We discuss different strategies aimed at tackling the problem of multiple testing, including adjustment of p -values, the false positive report probability and the false discovery rate. Another aspect of GWAs requiring special attention is the search for gene-gene and gene-environment interactions. We finally describe multistage approaches to GWAs.

Sonothrombolysis With Transcranial Color-Coded Sonography and Recombinant Tissue-Type Plasminogen Activator in Acute Middle Cerebral Artery Main Stem Occlusion Results From a Randomized Study

Background and Purpose— Sonothrombolysis is a new treatment approach in acute ischemic stroke. The results of a monocenter, randomized clinical study are presented. Methods— Subjects with acute middle cerebral artery main stem occlusion were randomized into a target group receiving 1-hour transcranial continuous insonation using a 1.8-MHz Doppler ultrasound (US) probe or a control group. All underwent standard thrombolysis with intravenous recombinant tissue-type plasminogen activator. Results— Thirty-seven subjects were included; 19 subjects were treated in the target (US) group and 18 in the control (no-US) group, all with no residual flow in the middle cerebral artery main stem occlusion (Thrombolysis in Brain Ischemia recanalization grade 0). Compared with the no-US group, the US group showed greater improvement in National Institutes of Health Stroke Scale values at days 1 and 4 and a higher median Thrombolysis in Brain Ischemia grade 1 hour after recombinant tissue-type plasminogen activator initiation. Recanalization (complete or partial) after 1 hour occurred in 57.9% of the US group and 22.2% of the no-US group (P=0.045). After 90 days, 4 subjects from the US group had a modified Rankin Score ≤1 (none from the no-US group) and 8 had a Barthel Index ≥95 (none from the no US group; P=0.106 and P=0.003, respectively). Three subjects from the US group (15.8%) developed a symptomatic intracranial hemorrhage as did one (5.6%) in the no-US group (P=0.60). Conclusions— This small randomized study indicates a beneficial impact of transcranial ultrasound on recanalization and short-term outcome in subjects with middle cerebral artery main stem occlusion and recombinant tissue-type plasminogen activator treatment.