Pharmacogenetic meta-analysis of baseline risk factors, pharmacodynamic, efficacy and tolerability endpoints from two large global cardiovascular outcomes trials for darapladib.

Darapladib, a lipoprotein-associated phospholipase A2 (Lp-PLA2) inhibitor, failed to demonstrate efficacy for the primary endpoints in two large phase III cardiovascular outcomes trials, one in stable coronary heart disease patients (STABILITY) and one in acute coronary syndrome (SOLID-TIMI 52). No major safety signals were observed but tolerability issues of diarrhea and odor were common (up to 13%). We hypothesized that genetic variants associated with Lp-PLA2 activity may influence efficacy and tolerability and therefore performed a comprehensive pharmacogenetic analysis of both trials. We genotyped patients within the STABILITY and SOLID-TIMI 52 trials who provided a DNA sample and consent (n = 13,577 and 10,404 respectively, representing 86% and 82% of the trial participants) using genome-wide arrays with exome content and performed imputation using a 1000 Genomes reference panel. We investigated baseline and change from baseline in Lp-PLA2 activity, two efficacy endpoints (major coronary events and myocardial infarction) as well as tolerability parameters at genome-wide and candidate gene level using a meta-analytic approach. We replicated associations of published loci on baseline Lp-PLA2 activity (APOE, CELSR2, LPA, PLA2G7, LDLR and SCARB1) and identified three novel loci (TOMM5, FRMD5 and LPL) using the GWAS-significance threshold P≤5E-08. Review of the PLA2G7 gene (encoding Lp-PLA2) within these datasets identified V279F null allele carriers as well as three other rare exonic null alleles within various ethnic groups, however none of these variants nor any other loci associated with Lp-PLA2 activity at baseline were associated with any of the drug response endpoints. The analysis of darapladib efficacy endpoints, despite low power, identified six low frequency loci with main genotype effect (though with borderline imputation scores) and one common locus (minor allele frequency 0.24) with genotype by treatment interaction effect passing the GWAS-significance threshold. This locus conferred risk in placebo subjects, hazard ratio (HR) 1.22 with 95% confidence interval (CI) 1.11-1.33, but was protective in darapladib subjects, HR 0.79 (95% CI 0.71-0.88). No major loci for tolerability were found. Thus, genetic analysis confirmed and extended the influence of lipoprotein loci on Lp-PLA2 levels, identified some novel null alleles in the PLA2G7 gene, and only identified one potentially efficacious subgroup within these two large clinical trials.

Characterization of ADME gene variation in 21 populations by exome sequencing.

OBJECTIVE: Proteins involving absorption, distribution, metabolism, and excretion (ADME) play a critical role in drug pharmacokinetics. The type and frequency of genetic variation in the ADME genes differ among populations. The aim of this study was to systematically investigate common and rare ADME coding variation in diverse ethnic populations by exome sequencing. MATERIALS AND METHODS: Data derived from commercial exome capture arrays and next-generation sequencing were used to characterize coding variation in 298 ADME genes in 251 Northeast Asians and 1181 individuals from the 1000 Genomes Project. RESULTS: Approximately 75% of the ADME coding sequence was captured at high quality across the joint samples harboring more than 8000 variants, with 49% of individuals carrying at least one 'knockout' allele. ADME genes carried 50% more nonsynonymous variation than non-ADME genes (P=8.2×10) and showed significantly greater levels of population differentiation (P=7.6×10). Out of the 2135 variants identified that were predicted to be deleterious, 633 were not on commercially available ADME or general-purpose genotyping arrays. Forty deleterious variants within important ADME genes, with frequencies of at least 2% in at least one population, were identified as candidates for future pharmacogenetic studies. CONCLUSION: Exome sequencing was effective in accurately genotyping most ADME variants important for pharmacogenetic research, in addition to identifying rare or potentially de novo coding variants that may be clinically meaningful. Furthermore, as a class, ADME genes are more variable and less sensitive to purifying selection than non-ADME genes.

A phenome-wide association study of a lipoprotein-associated phospholipase A2 loss-of-function variant in 90 000 Chinese adults.

BACKGROUND: Lipoprotein-associated phospholipase A2 (Lp-PLA2) has been implicated in development of atherosclerosis; however, recent randomized trials of Lp-PLA2 inhibition reported no beneficial effects on vascular diseases. In East Asians, a loss-of-function variant in the PLA2G7 gene can be used to assess the effects of genetically determined lower Lp-PLA2 METHODS: PLA2G7 V279F (rs76863441) was genotyped in 91 428 individuals randomly selected from the China Kadoorie Biobank of 0.5 M participants recruited in 2004-08 from 10 regions of China, with 7 years' follow-up. Linear regression was used to assess effects of V279F on baseline traits. Logistic regression was conducted for a range of vascular and non-vascular diseases, including 41 ICD-10 coded disease categories. RESULTS: PLA2G7 V279F frequency was 5% overall (range 3-7% by region), and 9691 (11%) participants had at least one loss-of-function variant. V279F was not associated with baseline blood pressure, adiposity, blood glucose or lung function. V279F was not associated with major vascular events [7141 events; odds ratio (OR) = 0.98 per F variant, 95% confidence interval (CI) 0.90-1.06] or other vascular outcomes, including major coronary events (922 events; 0.96, 0.79-1.18) and stroke (5967 events; 1.00, 0.92-1.09). Individuals with V279F had lower risks of diabetes (7031 events; 0.91, 0.84-0.98) and asthma (182 events; 0.53, 0.28-0.98), but there was no association after adjustment for multiple testing. CONCLUSIONS: Lifelong lower Lp-PLA2 activity was not associated with major risks of vascular or non-vascular diseases in Chinese adults. Using functional genetic variants in large-scale prospective studies with linkage to a range of health outcomes is a valuable approach to inform drug development and repositioning.

The genetics of drug efficacy: opportunities and challenges.

Lack of sufficient efficacy is the most common cause of attrition in late-phase drug development. It has long been envisioned that genetics could drive stratified drug development by identifying those patient subgroups that are most likely to respond. However, this vision has not been realized as only a small proportion of drugs have been found to have germline genetic predictors of efficacy with clinically meaningful effects, and so far all but one were found after drug approval. With the exception of oncology, systematic application of efficacy pharmacogenetics has not been integrated into drug discovery and development across the industry. Here, we argue for routine, early and cumulative screening for genetic predictors of efficacy, as an integrated component of clinical trial analysis. Such a strategy would identify clinically relevant predictors that may exist at the earliest possible opportunity, allow these predictors to be integrated into subsequent clinical development and provide mechanistic insights into drug disposition and patient-specific factors that influence response, therefore paving the way towards more personalized medicine.

Comparing variant calling algorithms for target-exon sequencing in a large sample.

BACKGROUND: Sequencing studies of exonic regions aim to identify rare variants contributing to complex traits. With high coverage and large sample size, these studies tend to apply simple variant calling algorithms. However, coverage is often heterogeneous; sites with insufficient coverage may benefit from sophisticated calling algorithms used in low-coverage sequencing studies. We evaluate the potential benefits of different calling strategies by performing a comparative analysis of variant calling methods on exonic data from 202 genes sequenced at 24x in 7,842 individuals. We call variants using individual-based, population-based and linkage disequilibrium (LD)-aware methods with stringent quality control. We measure genotype accuracy by the concordance with on-target GWAS genotypes and between 80 pairs of sequencing replicates. We validate selected singleton variants using capillary sequencing. RESULTS: Using these calling methods, we detected over 27,500 variants at the targeted exons; >57% were singletons. The singletons identified by individual-based analyses were of the highest quality. However, individual-based analyses generated more missing genotypes (4.72%) than population-based (0.47%) and LD-aware (0.17%) analyses. Moreover, individual-based genotypes were the least concordant with array-based genotypes and replicates. Population-based genotypes were less concordant than genotypes from LD-aware analyses with extended haplotypes. We reanalyzed the same dataset with a second set of callers and showed again that the individual-based caller identified more high-quality singletons than the population-based caller. We also replicated this result in a second dataset of 57 genes sequenced at 127.5x in 3,124 individuals. CONCLUSIONS: We recommend population-based analyses for high quality variant calls with few missing genotypes. With extended haplotypes, LD-aware methods generate the most accurate and complete genotypes. In addition, individual-based analyses should complement the above methods to obtain the most singleton variants.

A low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker.

BACKGROUND: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits. METHODS AND RESULTS: Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.3×10(-6)). This variant (or proxy) was consistently associated with myeloperoxidase in the Framingham Heart Study and Cardiovascular Health Study studies (replication meta-P=0.003), leading to a meta-P value of 9.96×10(-7) in the 3 dyslipidemic groups. The variant or its proxy was then profiled in additional population-based cohorts (up to a total of 58 930 subjects) including Cohorte Lausannoise, Ely, Fenland, European Prospective Investigation of Cancer, London Life Sciences Prospective Population Study, and the Genetics of Obesity Associations study obesity case-control for up to 40 cardiovascular and metabolic traits. Overall analysis identified the same single nucleotide polymorphisms to be nominally associated consistently with glomerular filtration rate (P=0.002) and risk of obesity (body mass index ≥30 kg/m(2), P=0.004). CONCLUSIONS: As myeloperoxidase is a prognostic marker of coronary events, the MAPK14 variant may provide a mechanistic link between p38 map kinase and these events, providing information consistent with current indication of Losmapimod for acute coronary syndrome. If replicated, the association with glomerular filtration rate, along with previous biological findings, also provides support for kidney diseases as alternative indications.

An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people.

Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.

Deep resequencing unveils genetic architecture of ADIPOQ and identifies a novel low-frequency variant strongly associated with adiponectin variation.

Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E-17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91-1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.

Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe.

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

Performance of genotype imputation for rare variants identified in exons and flanking regions of genes.

Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01

Multicentre search for genetic susceptibility loci in sporadic epilepsy syndrome and seizure types: a case-control study.

BACKGROUND: The Epilepsy Genetics (EPIGEN) Consortium was established to undertake genetic mapping analyses with augmented statistical power to detect variants that influence the development and treatment of common forms of epilepsy. METHODS: We examined common variations across 279 prime candidate genes in 2717 case and 1118 control samples collected at four independent research centres (in the UK, Ireland, Finland, and Australia). Single nucleotide polymorphism (SNP) and combined set-association analyses were used to examine the contribution of genetic variation in the candidate genes to various forms of epilepsy. FINDINGS: We did not identify clear, indisputable common genetic risk factors that contribute to selected epilepsy subphenotypes across multiple populations. Nor did we identify risk factors for the general all-epilepsy phenotype. However, set-association analysis on the most significant p values, assessed under permutation, suggested the contribution of numerous SNPs to disease predisposition in an apparent population-specific manner. Variations in the genes KCNAB1, GABRR2, KCNMB4, SYN2, and ALDH5A1 were most notable. INTERPRETATION: The underlying genetic component to sporadic epilepsy is clearly complex. Results suggest that many SNPs contribute to disease predisposition in an apparently population-specific manner. However, subtle differences in phenotyping across cohorts, combined with a poor understanding of how the underlying genetic component to epilepsy aligns with current phenotypic classifications, might also account for apparent population-specific genetic risk factors. Variations across five genes warrant further study in independent cohorts to clarify the tentative association.

Disease-specific target selection: a critical first step down the right road.

Relevance of a drug target for a disease is often inferred with strong belief but fragile evidence. Here, a program for early identification of human disease-specific drug targets using high-throughput genetic associations is described. Large numbers of well-characterized patients (>1000) and matched controls are screened for genetic associations using several thousand (>7000) single nucleotide polymorphisms from more than 1500 genes. The genes were selected because they are members of target classes for which there are precedents for high-throughput chemical screening technology. This review summarizes the methods and intensive data analyses leading to target gene identification for type 2 diabetes mellitus, including the statistical permutation methodology used to correct for many variables.