Bayesian MCPMod.

Multiple comparison procedures and modeling (MCPMod) has established itself as a method for dose-finding under model uncertainty. A downside of MCPMod is that due to its frequentist nature in particular with respect to the multiple comparison part it is tough to incorporate historical information in a systematic fashion. A typical situation where such historical information is available is existing data for the placebo group from previous trials. There are multiple Bayesian concepts for integrating historical data in a systematic and even dynamic fashion like the meta-analytic prior approach. In this article, we define Bayesian MCPMod (BMCPMod) that is build upon these two aspects. BMCPMod is able to mimic the results of the classical MCPMod for non-informative priors. At the same time, it allows for the inclusion of historical data in a systematic fashion. After the definition of BMCPMod related characteristics for a Bayesian approach similar to the MCP-testing part are derived. The BMCPMod is compared to classical MCPMod/non-informative priors via simulations. Aspects of mixture priors, optimal contrast vectors, and impact of allocation ratios are discussed and an example for designing a BMPCMod trial is given.

Triple fixed-dose combination empagliflozin, linagliptin, and metformin for patients with type 2 diabetes.

OBJECTIVES: Fixed-dose combination (FDC) therapy can improve outcomes in type 2 diabetes (T2D). We evaluated the bioequivalence of 2 doses of an FDC of extended-release metformin (metformin XR), empagliflozin, a sodium-glucose co-transporter 2 inhibitor, and linagliptin, a dipeptidyl peptidase-4 inhibitor, versus corresponding free tablet combinations. METHODS: Two randomized, open-label, two-way crossover studies in healthy adults compared: 2 FDC tablets of empagliflozin 5 mg/linagliptin 2.5 mg/metformin XR 1000 mg (Study 1; N = 30), 1 FDC tablet of empagliflozin 25 mg/linagliptin 5 mg/metformin XR 1000 mg (Study 2; N = 30) versus corresponding dose of free combinations. Subjects received study medication under fed conditions; washout was ≥35 days between treatments. Primary endpoints: area under the plasma concentration-time curve (AUC) from time 0 to last quantifiable data point for empagliflozin and metformin; AUC from time 0 to 72 hours for linagliptin, and peak plasma concentration (Cmax) for empagliflozin, linagliptin, and metformin. Bioequivalence was defined as adjusted geometric mean ratios (FDC: free combination) and two-sided 90% confidence intervals (CIs) of AUC and Cmax for each component within 80.00-125.00%. RESULTS: Study 1: 27/29 and 28/30 treated participants were included in the pharmacokinetic analysis for the FDC and free combination periods, respectively. Study 2: 29/29 treated participants were included in the pharmacokinetic analysis for both periods. The adjusted geometric mean ratios of FDCs to their respective free tablet combinations and two-sided 90% CIs were all within the predefined range. The shapes of the mean plasma concentration-time profile of empagliflozin, linagliptin, and metformin XR were similar for subjects in the FDC and free combination groups in both studies. No serious adverse events were reported. CONCLUSION: The evaluated doses of empagliflozin/linagliptin/metformin XR FDC tablets were bioequivalent to the corresponding free combinations. Based on these two bioequivalence studies and existing phase 3 data, the FDA has recently approved this triple FDC to improve glycemic control in adults with T2D.

Rheumatoid Arthritis and Coronary Artery Disease: Genetic Analyses Do Not Support a Causal Relation.

OBJECTIVE: Inflammatory diseases, specifically rheumatoid arthritis (RA), are assumed to increase the risk of coronary artery disease (CAD). More recently, multiple single-nucleotide polymorphisms (SNP) associated with RA risk were identified. If causal mechanisms affecting risks of RA and CAD are overlapping, risk alleles for RA might also increase the risk of CAD. METHODS: Sixty-one SNP associating with RA in genome-wide significant analyses were tested for association with CAD in CARDIoGRAM (Coronary ARtery DIsease Genome wide Replication and Meta-analysis), a metaanalysis including genome-wide association data (22,233 CAD cases, 64,762 controls). In parallel, a set of SNP being associated with low-density lipoprotein cholesterol (LDL-C) was tested as a positive control. RESULTS: Twenty-nine RA-associated SNP displayed a directionality-consistent association with CAD (OR range 1.002-1.073), whereas 32 RA-associated SNP were not associated with CAD (OR range 0.96-0.99 per RA risk-increasing allele). The proportion (48%) of directionality-consistent associated SNP equaled the proportion expected by chance (50%, p = 0.09). Of only 5 RA-associated SNP showing p values for CAD < 0.05, 4 loci (C5orf30, IL-6R, PTPN22, and RAD51B) showed directionality-consistent effects on CAD, and 1 (rs10774624, locus SH2B3) reached study-wide significance (p = 7.29E-06). By contrast, and as a proof of concept, 46 (74%) out of 62 LDL-C-associated SNP displayed a directionality-consistent association with CAD, a proportion that was significantly different from 50% (p = 5.9E-05). CONCLUSION: We found no evidence that RA-associated SNP as a group are associated with CAD. Even though we were not able to study potential effects of all genetic variants individually, shared nongenetic factors may more plausibly explain the observed coincidence of the 2 conditions.

No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.

In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.

Runs of Homozygosity: Association with Coronary Artery Disease and Gene Expression in Monocytes and Macrophages.

Runs of homozygosity (ROHs) are recognized signature of recessive inheritance. Contributions of ROHs to the genetic architecture of coronary artery disease and regulation of gene expression in cells relevant to atherosclerosis are not known. Our combined analysis of 24,320 individuals from 11 populations of white European ethnicity showed an association between coronary artery disease and both the count and the size of ROHs. Individuals with coronary artery disease had approximately 0.63 (95% CI: 0.4-0.8) excess of ROHs when compared to coronary-artery-disease-free control subjects (p = 1.49 × 10(-9)). The average total length of ROHs was approximately 1,046.92 (95% CI: 634.4-1,459.5) kb greater in individuals with coronary artery disease than control subjects (p = 6.61 × 10(-7)). None of the identified individual ROHs was associated with coronary artery disease after correction for multiple testing. However, in aggregate burden analysis, ROHs favoring increased risk of coronary artery disease were much more common than those showing the opposite direction of association with coronary artery disease (p = 2.69 × 10(-33)). Individual ROHs showed significant associations with monocyte and macrophage expression of genes in their close proximity-subjects with several individual ROHs showed significant differences in the expression of 44 mRNAs in monocytes and 17 mRNAs in macrophages when compared to subjects without those ROHs. This study provides evidence for an excess of homozygosity in coronary artery disease in outbred populations and suggest the potential biological relevance of ROHs in cells of importance to the pathogenesis of atherosclerosis.

Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease risk.

BACKGROUND: The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. METHODS AND RESULTS: We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD. CONCLUSIONS: Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting.

Genome-wide association study of L-arginine and dimethylarginines reveals novel metabolic pathway for symmetric dimethylarginine.

BACKGROUND: Dimethylarginines (DMA) interfere with nitric oxide formation by inhibiting nitric oxide synthase (asymmetrical DMA [ADMA]) and l-arginine uptake into the cell (ADMA and symmetrical DMA [SDMA]). In prospective clinical studies, ADMA has been characterized as a cardiovascular risk marker, whereas SDMA is a novel marker for renal function and associated with all-cause mortality after ischemic stroke. The aim of the current study was to characterize the environmental and genetic contributions to interindividual variability of these biomarkers. METHODS AND RESULTS: This study comprised a genome-wide association analysis of 3 well-characterized population-based cohorts (Framingham Heart Study [FHS; n=2992], Gutenberg Health Study [GHS; n=4354], and Multinational Monitoring of Trends and Determinants in Cardiovascular Disease Study [MONICA]/Cooperative Health Research in the Augsburg Area, Augsburg, Bavaria, Germany [KORA] F3 [n=581]) and identified replicated loci (DDAH1, MED23, Arg1, and AGXT2) associated with the interindividual variability in ADMA, l-arginine, and SDMA. Experimental in silico and in vitro studies confirmed functional significance of the identified AGXT2 variants. Clinical outcome analysis in 384 patients of the Leeds stroke study demonstrated an association between increased plasma levels of SDMA, AGXT2 variants, and various cardiometabolic risk factors. AGXT2 variants were not associated with poststroke survival in the Leeds study or were they associated with incident stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. CONCLUSIONS: These genome-wide association study support the importance of DDAH1 and MED23/Arg1 in regulating ADMA and l-arginine metabolism, respectively, and identify a novel regulatory renal pathway for SDMA by AGXT2. AGXT2 variants might explain part of the pathogenic link between SDMA, renal function, and outcome. An association between AGXT2 variants and stroke is unclear and warrants further investigation.

How to include chromosome X in your genome-wide association study.

In current genome-wide association studies (GWAS), the analysis is usually focused on autosomal variants only, and the sex chromosomes are often neglected. Recently, a number of technical hurdles have been described that add to a reluctance of including chromosome X in a GWAS, including complications in genotype calling, imputation, and selection of test statistics. To overcome this, we provide a "how to" guide for analyzing X chromosomal data within a standard GWAS. Following a general pipeline for GWAS, we highlight the steps in which the X chromosome requires specific attention, and we give tentative advice for each of these. Through this, we show that by selection of sensible algorithms and parameter settings, the inclusion of chromosome X in GWAS is manageable. Closing this gap is expected to further elucidate the genetic background of complex diseases, especially of those with sex-specific features.

A unifying framework for robust association testing, estimation, and genetic model selection using the generalized linear model.

The analysis of genome-wide genetic association studies generally starts with univariate statistical tests of each single-nucleotide polymorphism. The standard approach is the Cochran-Armitage trend test or its logistic regression equivalent although this approach can lose considerable power if the underlying genetic model is not additive. An alternative is the MAX test, which is robust against the three basic modes of inheritance. Here, the asymptotic distribution of the MAX test is derived using the generalized linear model together with the Delta method and multiple contrasts. The approach is applicable to binary, quantitative, and survival traits. It may be used for unrelated individuals, family-based studies, and matched pairs. The approach provides point and interval effect estimates and allows selecting the most plausible genetic model using the minimum P-value. R code is provided. A Monte-Carlo simulation study shows that the asymptotic MAX test framework meets type I error levels well, has good power, and good model selection properties for minor allele frequencies ≥0.3. Pearson's χ(2)-test is superior for lower minor allele frequencies with low frequencies for the rare homozygous genotype. In these cases, the model selection procedure should be used with caution. The use of the MAX test is illustrated by reanalyzing findings from seven genome-wide association studies including case-control, matched pairs, and quantitative trait data.

Genetic predisposition to higher blood pressure increases coronary artery disease risk.

Hypertension is a risk factor for coronary artery disease. Recent genome-wide association studies have identified 30 genetic variants associated with higher blood pressure at genome-wide significance (P<5 × 10(-8)). If elevated blood pressure is a causative factor for coronary artery disease, these variants should also increase coronary artery disease risk. Analyzing genome-wide association data from 22 233 coronary artery disease cases and 64 762 controls, we observed in the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) consortium that 88% of these blood pressure-associated polymorphisms were likewise positively associated with coronary artery disease, that is, they had an odds ratio >1 for coronary artery disease, a proportion much higher than expected by chance (P=4 × 10(-5)). The average relative coronary artery disease risk increase per each of the multiple blood pressure-raising alleles observed in the consortium was 3.0% for systolic blood pressure-associated polymorphisms (95% confidence interval, 1.8%-4.3%) and 2.9% for diastolic blood pressure-associated polymorphisms (95% confidence interval, 1.7%-4.1%). In substudies, individuals carrying most systolic blood pressure- and diastolic blood pressure-related risk alleles (top quintile of a genetic risk score distribution) had 70% (95% confidence interval, 50%-94%) and 59% (95% confidence interval, 40%-81%) higher odds of having coronary artery disease, respectively, as compared with individuals in the bottom quintile. In conclusion, most blood pressure-associated polymorphisms also confer an increased risk for coronary artery disease. These findings are consistent with a causal relationship of increasing blood pressure to coronary artery disease. Genetic variants primarily affecting blood pressure contribute to the genetic basis of coronary artery disease.

Genome-wide association study indicates two novel resistance loci for severe malaria.

Malaria causes approximately one million fatalities per year, mostly among African children. Although highlighted by the strong protective effect of the sickle-cell trait, the full impact of human genetics on resistance to the disease remains largely unexplored. Genome-wide association (GWA) studies are designed to unravel relevant genetic variants comprehensively; however, in malaria, as in other infectious diseases, these studies have been only partly successful. Here we identify two previously unknown loci associated with severe falciparum malaria in patients and controls from Ghana, West Africa. We applied the GWA approach to the diverse clinical syndromes of severe falciparum malaria, thereby targeting human genetic variants influencing any step in the complex pathogenesis of the disease. One of the loci was identified on chromosome 1q32 within the ATP2B4 gene, which encodes the main calcium pump of erythrocytes, the host cells of the pathogenic stage of malaria parasites. The second was indicated by an intergenic single nucleotide polymorphism on chromosome 16q22.2, possibly linked to a neighbouring gene encoding the tight-junction protein MARVELD3. The protein is expressed on endothelial cells and might therefore have a role in microvascular damage caused by endothelial adherence of parasitized erythrocytes. We also confirmed previous reports on protective effects of the sickle-cell trait and blood group O. Our findings underline the potential of the GWA approach to provide candidates for the development of control measures against infectious diseases in humans.

Genome-wide meta-analysis of common variant differences between men and women.

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.

A genome-wide association study for coronary artery disease identifies a novel susceptibility locus in the major histocompatibility complex.

BACKGROUND: Recent genome-wide association studies (GWAS) have identified several novel loci that reproducibly associate with coronary artery disease (CAD) and/or myocardial infarction risk. However, known common CAD risk variants explain only 10% of the predicted genetic heritability of the disease, suggesting that important genetic signals remain to be discovered. METHODS AND RESULTS: We performed a discovery meta-analysis of 5 GWAS involving 13 949 subjects (7123 cases, 6826 control subjects) imputed at approximately 5 million single nucleotide polymorphisms, using pilot 1000 Genomes-based haplotypes. Promising loci were followed up in an additional 5 studies with 11 032 subjects (5211 cases, 5821 control subjects). A novel CAD locus on chromosome 6p21.3 in the major histocompatibility complex (MHC) between HCG27 and HLA-C was identified and achieved genome-wide significance in the combined analysis (rs3869109; p(discovery)=3.3×10(-7), p(replication)=5.3×10(-4)p(combined)=1.12×10(-9)). A subanalysis combining discovery GWAS showed an attenuation of significance when stringent corrections for European population structure were used (P=4.1×10(-10) versus 3.2×10(-7)), suggesting that the observed signal is partly confounded due to population stratification. This gene dense region plays an important role in inflammation, immunity, and self-cell recognition. To determine whether the underlying association was driven by MHC class I alleles, we statistically imputed common HLA alleles into the discovery subjects; however, no single common HLA type contributed significantly or fully explained the observed association. CONCLUSIONS: We have identified a novel locus in the MHC associated with CAD. MHC genes regulate inflammation and T-cell responses that contribute importantly to the initiation and propagation of atherosclerosis. Further laboratory studies will be required to understand the biological basis of this association and identify the causative allele(s).

Association tests for X-chromosomal markers--a comparison of different test statistics.

OBJECTIVE: Genome-wide association studies have successfully elucidated the genetic background of complex diseases, but X chromosomal data have usually not been analyzed. A reason for this is that there is no consensus approach for the analysis taking into account the specific features of X chromosomal data. This contribution evaluates test statistics proposed for X chromosomal markers regarding type I error frequencies and power. METHODS: We performed extensive simulation studies covering a wide range of different settings. Besides characteristics of the general population, we investigated sex-balanced or unbalanced sampling procedures as well as sex-specific effect sizes, allele frequencies and prevalence. Finally, we applied the test statistics to an association data set on Crohn's disease. RESULTS: Simulation results imply that in addition to standard quality control, sex-specific allele frequencies should be checked to control for type I errors. Furthermore, we observed distinct differences in power between test statistics which are determined by sampling design and sex specificity of effect sizes. Analysis of the Crohn's disease data detects two previously unknown genetic regions on the X chromosome. CONCLUSION: Although no test is uniformly most powerful under all settings, recommendations are offered as to which test performs best under certain conditions.

Genome-wide association study identifies a new locus for coronary artery disease on chromosome 10p11.23.

AIMS: Recent genome-wide association (GWA) studies identified 10 chromosomal loci for coronary artery disease (CAD) or myocardial infarction (MI). However, these loci explain only a small proportion of the genetic variability of these pertinent diseases. We sought to identify additional CAD/MI loci by applying a three-stage approach. METHODS AND RESULTS: We genotyped n = 1157 MI cases and n = 1748 controls from a population-based study population [German MI Family Study (GerMIFS) III (KORA)] with genome-wide SNP arrays. At this first stage, n = 462 SNPs showed association with MI at P<1 × 10(-3) in two-sided logistic regression. In a second stage, 415 of these SNPs were evaluated in silico in two independent GWA samples, the GerMIFS I (875 cases/1644 controls) and GerMIFS II (1222 cases/1298 controls). Nine SNPs, representing three regions, displayed consistent replication in this in silico analysis (P<0.05 for each GWA sample): five SNPs at 9p21.3, a well-known CAD/MI locus, two SNPs at 10p11.21, and two SNPs at 2p24.3. Wet-lab replication, i.e. the third stage, of SNP rs3739998 (representing the novel locus at 10p11.21, p.S1002T in the KIAA1462 gene) in additional 5790 cases and 5302 controls confirmed the association (P=9.54 × 10(-4)), but not for the 2p24.3 locus. The combined P-value across all stages for SNP rs3739998 is P=1.27 × 10(-11) [odds ratio (OR) = 1.15 (1.11-1.20)]. CONCLUSION: Analysis of a GWA study followed by in silico and wet-lab replication steps identified the KIAA1462 gene, encoding a yet uncharacterized protein, on chromosome 10p11.23 with genome-wide significant association for CAD/MI. Further studies are needed to characterize the functional role of this locus in the aetiology of these diseases.