Study of effect modifiers of genetically predicted CETP reduction.

Genetic variants in drug targets can be used to predict the long-term, on-target effect of drugs. Here, we extend this principle to assess how sex and body mass index may modify the effect of genetically predicted lower CETP levels on biomarkers and cardiovascular outcomes. We found sex and body mass index (BMI) to be modifiers of the association between genetically predicted lower CETP and lipid biomarkers in UK Biobank participants. Female sex and lower BMI were associated with higher high-density lipoprotein cholesterol and lower low-density lipoprotein cholesterol for the same genetically predicted reduction in CETP concentration. We found that sex also modulated the effect of genetically lower CETP on cholesterol efflux capacity in samples from the Montreal Heart Institute Biobank. However, these modifying effects did not extend to sex differences in cardiovascular outcomes in our data. Our results provide insight into the clinical effects of CETP inhibitors in the presence of effect modification based on genetic data. The approach can support precision medicine applications and help assess the external validity of clinical trials.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

Pharmacogenomic study of heart failure and candesartan response from the CHARM programme.

AIMS: The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM) programme consisted of three parallel, randomized, double-blind clinical trials comparing candesartan with placebo in patients with heart failure (HF) categorized according to left ventricular ejection fraction and tolerability to an angiotensin-converting enzyme inhibitor. We conducted a pharmacogenomic study of the CHARM trials with the objective of identifying genetic predictors of HF progression and of the efficacy and safety of treatment with candesartan. METHODS: We performed genome-wide association studies in 2727 patients of European ancestry from CHARM-Overall and stratified by CHARM study according to preserved and reduced ejection fraction and according to assignment to the interventional treatment with candesartan. We tested genetic association with the composite endpoint of cardiovascular death or hospitalization for heart failure for drug efficacy in candesartan-treated patients and for HF progression using patients from both candesartan and placebo arms. The safety endpoints for response to candesartan were hyperkalaemia, renal dysfunction, hypotension, and change in systolic blood pressure between baseline and 6 weeks of treatment. To support our observations, we conducted a genome-wide gene-level collapsing analysis from whole-exome sequencing data with the composite cardiovascular endpoint. RESULTS: We found that the A allele (14% allele frequency) of the genetic variant rs66886237 at 8p21.3 near the gene GFRA2 was associated with the composite cardiovascular endpoint in 1029 HF patients with preserved ejection fraction from the CHARM-Preserved study (hazard ratio: 1.91, 95% confidence interval: 1.55-2.35; P = 1.7 × 10-9 ). The association was independent of candesartan treatment, and the genetic variant was not associated with the cardiovascular endpoint in patients with reduced ejection fraction. None of the genome-wide association studies for candesartan safety or efficacy conducted in patients treated with candesartan passed the significance threshold. We found no significant association from the gene-level collapsing analysis. CONCLUSIONS: We have identified a candidate genetic variant potentially predictive of the progression of heart failure in patients with preserved ejection fraction. The findings require further replication, and we cannot exclude the possibility that the results may be chance findings.

Genetics of symptom remission in outpatients with COVID-19.

We conducted a genome-wide association study of time to remission of COVID-19 symptoms in 1723 outpatients with at least one risk factor for disease severity from the COLCORONA clinical trial. We found a significant association at 5p13.3 (rs1173773; P = 4.94 × 10-8) near the natriuretic peptide receptor 3 gene (NPR3). By day 15 of the study, 44%, 54% and 59% of participants with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. In 851 participants not treated with colchicine (placebo), there was a significant association at 9q33.1 (rs62575331; P = 2.95 × 10-8) in interaction with colchicine (P = 1.19 × 10-5) without impact on risk of hospitalisations, highlighting a possibly shared mechanistic pathway. By day 15 of the study, 46%, 62% and 64% of those with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. The findings need to be replicated and could contribute to the biological understanding of COVID-19 symptom remission.

Genetic meta-analysis of cancer diagnosis following statin use identifies new associations and implicates human leukocyte antigen (HLA) in women.

We sought to perform a genomic evaluation of the risk of incident cancer in statin users, free of cancer at study entry. Patients who previously participated in two phase IV trials (TNT and IDEAL) with genetic data were used (npooled = 11,196). A GWAS meta-analysis using Cox modeling for the prediction of incident cancer was conducted in the pooled cohort and sex-stratified. rs13210472 (near HLA-DOA gene) was associated with higher risk of incident cancer amongst women with prevalent coronary artery disease (CAD) taking statins (hazard ratio [HR]: 2.66, 95% confidence interval [CI]: 1.88-3.76, P = 3.5 × 10-8). Using the UK Biobank and focusing exclusively on women statin users with CAD (nfemale = 2952), rs13210472 remained significantly associated with incident cancer (HR: 1.71, 95% CI: 1.14-2.56, P = 9.0 × 10-3). The association was not observed in non-statin users. In this genetic meta-analysis, we have identified a variant in women statin users with prevalent CAD that was associated with incident cancer, possibly implicating the human leukocyte antigen pathway.

Pharmacogenomics of the Efficacy and Safety of Colchicine in COLCOT.

BACKGROUND: The randomized, placebo-controlled COLCOT (Colchicine Cardiovascular Outcomes Trial) has shown the benefits of colchicine 0.5 mg daily to lower the rate of ischemic cardiovascular events in patients with a recent myocardial infarction. Here, we conducted a post hoc pharmacogenomic study of COLCOT with the aim to identify genetic predictors of the efficacy and safety of treatment with colchicine. METHODS: There were 1522 participants of European ancestry from the COLCOT trial available for the pharmacogenomic study of COLCOT trial. The pharmacogenomic study's primary cardiovascular end point was defined as for the main trial, as time to first occurrence of cardiovascular death, resuscitated cardiac arrest, myocardial infarction, stroke, or urgent hospitalization for angina requiring coronary revascularization. The safety end point was time to the first report of gastrointestinal events. Patients' DNA was genotyped using the Illumina Global Screening array followed by imputation. We performed a genome-wide association study in colchicine-treated patients. RESULTS: None of the genetic variants passed the genome-wide association study significance threshold for the primary cardiovascular end point conducted in 702 patients in the colchicine arm who were compliant to medication. The genome-wide association study for gastrointestinal events was conducted in all 767 patients in the colchicine arm and found 2 significant association signals, one with lead variant rs6916345 (hazard ratio, 1.89 [95% CI, 1.52-2.35], P=7.41×10-9) in a locus which colocalizes with Crohn disease, and one with lead variant rs74795203 (hazard ratio, 2.51 [95% CI, 1.82-3.47]; P=2.70×10-8), an intronic variant in gene SEPHS1. The interaction terms between the genetic variants and treatment with colchicine versus placebo were significant. CONCLUSIONS: We found 2 genomic regions associated with gastrointestinal events in patients treated with colchicine. Those findings will benefit from replication to confirm that some patients may have genetic predispositions to lower tolerability of treatment with colchicine.

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes.

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, "LD-annot," designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

DSNetwork: An Integrative Approach to Visualize Predictions of Variants' Deleteriousness.

One of the most challenging tasks of the post-genome-wide association studies (GWAS) research era is the identification of functional variants among those associated with a trait for an observed GWAS signal. Several methods have been developed to evaluate the potential functional implications of genetic variants. Each of these tools has its own scoring system, which forces users to become acquainted with each approach to interpret their results. From an awareness of the amount of work needed to analyze and integrate results for a single locus, we proposed a flexible and versatile approach designed to help the prioritization of variants by aggregating the predictions of their potential functional implications. This approach has been made available through a graphical user interface called DSNetwork, which acts as a single point of entry to almost 60 reference predictors for both coding and non-coding variants and displays predictions in an easy-to-interpret visualization. We confirmed the usefulness of our methodology by successfully identifying functional variants in four breast cancer and nine schizophrenia susceptibility loci.

Association analysis identifies 65 new breast cancer risk loci.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis.

Motivation: The identification of the functional variants responsible for observed genome-wide association studies (GWAS) signals is one of the most challenging tasks of the post-GWAS research era. Several tools have been developed to annotate genetic variants by their genomic location and potential functional implications. Each of these tools has its own requirements and internal logic, which forces the user to become acquainted with each interface. Results: From an awareness of the amount of work needed to analyze a single locus, we have built a flexible, versatile and easy-to-use web interface designed to help in prioritizing variants and predicting their potential functional implications. This interface acts as a single-point of entry linking association results with reference tools and relevant experiments. Availability and Implementation: VEXOR is an integrative web application implemented through the Shiny framework and available at: http://romix.genome.ulaval.ca/vexor. Contact: arnaud.droit@crchuq.ulaval.ca. Supplementary information: Supplementary data are available at Bioinformatics online.

Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression: identification of a modifier of breast cancer risk at locus 11q22.3.

PURPOSE: Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways. METHODS: Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2. RESULTS: We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10-6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance. CONCLUSION: We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.

Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21.

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.

metagene Profiles Analyses Reveal Regulatory Element's Factor-Specific Recruitment Patterns.

ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a "gradient effect" where the regulatory factor occupancy levels follow transcription and ii) a "threshold effect" where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.

Two single-nucleotide polymorphisms in the human vitamin D receptor promoter change protein-DNA complex formation and are associated with height and vitamin D status in adolescent girls.

Numerous association studies have dealt with single-nucleotide polymorphisms (SNPs) in coding and intronic regions of the human vitamin D receptor (hVDR) gene. We have hypothesized that phenotypic traits may also be associated with variations in VDR expression due to the presence of SNPs in promoter regions. In this work, we have studied two SNPs located 1521 bp (G/C) and 1012 bp (A/G) upstream of the transcriptional start site of the main human VDR gene promoter. One base-change in any of the two variant sites led to a dramatic change in protein-DNA complex formation using nuclear extracts from HEK293, Caco-2 and COS-7 cells. Genetic analysis of 185 healthy adolescent girls evidenced two major haplotypes: 1521G/1012A and 1521C/1012G and three main genotypes: homozygous for 1521G/1012A (21.1%), homozygous for 1521C/1012G (17.3%) and heterozygous 1521CG/1012GA (57.3%). On the basis of transfection data, promoter activity was nearly 2-fold higher with the 1521G/1012A haplotype, when compared with the 1521C/1012G haplotype. Clinical and biological association study in the adolescent cohort showed that girls with a CC/GG genotype had (i) lower circulating levels of 25-dihydroxyvitamin D, with no detectable consequence on calcium metabolism, (ii) lower serum IGF-1 levels and (iii) smaller height from 11 years of age up to adult height.