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Background: Women are underrepresented in drug development trials and there is no sex-tailored drug regimen for most medications. It has been repeatedly shown that women have more adverse drug reactions than men for several medications. These differences could be explained by higher dose-adjusted drug concentrations in women. Thus, we aim to identify sex-related differences and to characterize the clinical and genetic predictors of these differences in drug concentrations, dosing, and adherence for 47 commonly used drugs in a large cohort. The objective of this article is to present an overview of the methods and characteristics of the study population., Methods: We performed a cross-sectional study that included 10,082 men and women of European ancestry aged ≥ 18 years from the Montreal Heart Institute Hospital Cohort taking at least one of the 47 medications regularly., Results: Of the 10,082 participants included, 36% were women. Women had lower weight, height, waist girth, and body mass index than men, but they had higher hip girth (all p < 0.001). Men had a higher level of education and annual income and were more likely to be employed full-time compared to women. Furthermore, men had a higher prevalence of hypertension, type 2 diabetes, dyslipidemia, and myocardial infarction (all p < 0.001) and were more likely receiving lipid-lowering agents, beta-blockers, antidiabetic drugs, and angiotensin-converting enzyme inhibitors. Conversely, proton pump inhibitors were more prevalent in women. Interestingly, nearly half of the women had a history of drug allergy or intolerance, compared with less than one-third of the men (p < 0.001)., Conclusion: This study has a high potential in understanding eventual sex differences in drug dosing requirements and will most likely provide useful information to personalize drug regimens in women., Competing Interests: Declarations. Ethics approval: This study is conducted according to the Management Policy of the MHI Hospital Cohort and is approved by the Management Committee of the Biobank as well as the Scientific and Ethics committees of the MHI. Consent to participate: All patients agreed to participate in the Hospital Cohort and signed a consent form. Consent for publication: Not applicable (see Ethics approval and Consent to participate). Competing interests: S. de Denus reports grants outside the submitted work from AstraZeneca and RMS/Dalcor. M.-P. Dubé has a minor equity interest in DalCor Pharmaceuticals. J.-C. Tardif has received research grants from Amarin, AstraZeneca, Ceapro, DalCor Pharmaceuticals, Esperion, Ionis, Novartis, Pfizer, RegenXBio, and Sanofi; honoraria from AstraZeneca, DalCor Pharmaceuticals, HLS Pharmaceuticals, and Pendopharm; and minor equity interest in DalCor Pharmaceuticals. M.-P. Dubé and J.-C. Tardif are authors on the following patents without royalties received: “Methods for Treating or Preventing Cardiovascular Disorders and Lowering Risk of Cardiovascular Events,” “Genetic Markers for Predicting Responsiveness to Therapy with HDL-Raising or HDL Mimicking Agent,” and “Methods for using low dose colchicine after myocardial infarction.”, (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10 -8 ). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Hotter climates have important impacts on human health and performance. Yet, the cellular and molecular responses involved in human heat stress and acclimation remain understudied. This dataset includes physiological measurements and the plasma concentration of 2,938 proteins collected from 10 healthy adults, before and during passive heat stress that was performed both prior to and after a 7-day heat acclimation protocol. Physiological measurements included body temperatures, sweat rate, cutaneous vascular conductance, blood pressure, and skin sympathetic nerve activity. The proteomic dataset was generated using the Olink Explore 3072 assay, enabling a high-multiplex antibody-based assessment of protein changes based on proximity extension assay technology. The data need to be interpreted in the context of the moderate level of body hyperthermia attained and the specific demographic of young, healthy adults. We have made this dataset publicly available to facilitate research into the cellular and molecular mechanisms involved in human heat stress and acclimation, crucial for addressing the health and performance challenges posed by rising temperatures., (© 2023. The Author(s).)

Background: Cancer survivors are at an increased risk of cardiovascular disease (CVD) compared with the general population. We sought to evaluate the impact of mosaic chromosomal alterations (mCA) on death of CVD causes, coronary artery disease (CAD) causes, and of any cause in patients with a cancer diagnosis., Methods: The study was a prospective cohort analysis of 48,919 UK Biobank participants with a cancer diagnosis. mCAs were characterized using DNA genotyping array intensity data and long-range chromosomal phase inference. Multivariable Cox regression models were used to ascertain the associations of mCAs. Exploratory endpoints included various incident cardiovascular phenotypes., Results: Overall, 10,070 individuals (20.6%) carried ≥ 1 mCA clone. In adjusted analyses, mCA was associated with an increased risk of death of CAD causes [HR, 1.37; 95% confidence interval (CI), 1.09-1.71; P = 0.006]. In sub-analyses, we found that carriers of mCAs diagnosed with kidney cancer had an increased risk of death of CVD causes (HR, 2.03; 95% CI, 1.11-3.72; P = 0.022) and CAD causes (HR, 3.57; 95% CI, 1.44-8.84; P = 0.006). Women diagnosed with breast cancer who carried a mCA also had a higher risk of death of CAD causes (HR, 2.46; 95% CI, 1.23-4.92; P = 0.011)., Conclusions: Among cancer survivors, carriers of any mCA are at an increased risk of CAD death compared with noncarriers. Mechanistic studies should be considered to better ascertain the biological mechanisms underneath the observed associations between mCAs and cardiovascular events for specific cancer types., Impact: There may be clinical relevance in considering mCAs in patients diagnosed with cancer and undergoing treatment., (©2023 The Authors; Published by the American Association for Cancer Research.)

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., (© 2023 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.)

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., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Gender captures social components beyond biological sex and can add valuable insight to health studies in populations. However, assessment of gender typically relies on questionnaires which may not be available. The aim of this study is to construct a gender metric using available variables in the UK Biobank and to apply it to the study of angina diagnosis. Proxy variables for femininity characteristics were identified in the UK Biobank and regressed on sex to construct a composite femininity score (FS) validated using tenfold cross-validation. The FS was assessed as a predictor of angina diagnosis before incident myocardial infarction (MI) events. The FS was derived for 315,937 UK Biobank participants. In 3059 individuals with no history of MI at study entry who had an incident MI event, the FS was a significant predictor of angina diagnosis prior to MI (OR 1.24, 95% CI 1.10-1.39, P < 0.001) with a significant sex-by-FS interaction effect (P = 0.003). The FS was positively associated with angina diagnosis prior to MI in men (OR 1.37, 95% CI 1.19-1.57, P < 0.001), but not in women. We have provided a new tool to conduct gender-sensitive analyses in observational studies, and applied it to study of angina diagnosis prior to MI., (© 2022. The Author(s).)

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.

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.

Background: Naturally occurring human genetic variants provide a valuable tool to identify drug targets and guide drug prioritization and clinical trial design. Ivabradine is a heart rate lowering drug with protective effects on heart failure despite increasing the risk of atrial fibrillation. In patients with coronary artery disease without heart failure, the drug does not protect against major cardiovascular adverse events prompting questions about the ability of genetics to have predicted those effects. This study evaluates the effect of a variant in HCN4, ivabradine's drug target, on safety and efficacy endpoints., Methods: We used genetic association testing and Mendelian randomization to predict the effect of ivabradine and heart rate lowering on cardiovascular outcomes., Results: Using data from the UK Biobank and large GWAS consortia, we evaluated the effect of a heart rate-reducing genetic variant at the HCN4 locus encoding ivabradine's drug target. These genetic association analyses showed increases in risk for atrial fibrillation (OR 1.09, 95% CI: 1.06-1.13, P = 9.3 ×10-9) in the UK Biobank. In a cause-specific competing risk model to account for the increased risk of atrial fibrillation, the HCN4 variant reduced incident heart failure in participants that did not develop atrial fibrillation (HR 0.90, 95% CI: 0.83-0.98, P = 0.013). In contrast, the same heart rate reducing HCN4 variant did not prevent a composite endpoint of myocardial infarction or cardiovascular death (OR 0.99, 95% CI: 0.93-1.04, P = 0.61)., Conclusion: Genetic modelling of ivabradine recapitulates its benefits in heart failure, promotion of atrial fibrillation, and neutral effect on myocardial infarction., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: A patent pertaining to pharmacogenomics-guided CETP inhibition (US20190070178A1) owned by Dalcor was granted and J.-C. Tardif and M.-P. Dubé are mentioned as authors but do not receive any royalties. J.-C. Tardif and M.-P. Dubé have a minor equity interest in DalCor. J.-C. Tardif has received research support from Amarin, AstraZeneca, DalCor, Eli-Lilly, Ionis, Pfizer, RegenexBio, Sanofi and Servier, and honoraria from DalCor, Pfizer, Sanofi and Servier. M.-P. Dubé has received honoraria from Dalcor and research support (access to samples and data) from AstraZeneca, Pfizer, Servier, Sanofi and GlaxoSmithKline. B. Tyl is an employee of Laboratoires Servier. Simon de Denus has received grants from Pfizer, AstraZeneca, Roche Molecular Science, DalCor and Novartis. R. Thomas Lumbers has received research grants from Pfizer. The remaining authors have nothing to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Little is known about the mid-term prognosis of nonelderly patients (≤60 years) after the surgical treatment of isolated aortic valve infective endocarditis (IE). Better characterization of these outcomes could help in tailoring the surgical management in these patients., Methods: From 2000 to 2015, 164 adult patients ≤60 years of age (mean 46 ± 11 years, 81% male) underwent surgical treatment for isolated aortic valve IE in 2 high-volume Canadian centers. Twenty-three patients (14%) were intravenous drug users (IVDUs). Patients with recurrent IE or concomitant endocarditis on other valves were excluded. The aortic valve was replaced with a mechanical prosthesis (44%), a tissue valve (30%), a homograft (18%), or a Ross procedure (9%). Mean follow-up was 6.2 ± 4.6 years (92% complete)., Results: Thirty-day mortality was 7%. Actuarial survival rates at 5 and 10 years were 80 ± 3% and 71 ± 4%, respectively. IVDU (hazard ratio [HR] 3.8, 95% CI 1.4-10.1; P = 0.01) and prosthetic valve endocarditis (HR 2.6, 95% CI 1.1-6.4; P = 0.04) were associated with increased mid-term mortality. Mid-term survival was best in non-IVDU patients with native valve endocarditis, yet lower than a matched elective aortic valve replacement (AVR) population. Overall, freedom from recurrence of IE at 1, 5, and 10 years was 94 ± 2%, 91 ± 3%, and 89 ± 3%, respectively. IVDU was associated with higher rates of recurrence, especially in the first year after surgery., Conclusions: In nonelderly adults undergoing surgery for aortic valve IE, mid-term survival is suboptimal. Although non-IVDU patients with native valve endocarditis have better mid-term outcomes, survival remains lower than a matched population of elective AVR in nonelderly patients., (Copyright © 2019 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)

Warfarin is primarily metabolized by cytochrome 2C9, encoded by gene CYP2C9. Here, we investigated whether variants in nuclear receptor genes which regulate the expression of CYP2C9 are associated with warfarin response. We used data from 906 warfarin users from the Quebec Warfarin Cohort (QWC) and tested the association of warfarin dose requirement at 3 months following the initiation of therapy in nine nuclear receptor genes: NR1I3, NR1I2, NR3C1, ESR1, GATA4, RXRA, VDR, CEBPA, and HNF4A. Three correlated SNPs in the VDR gene (rs4760658, rs11168292, and rs11168293) were associated with dose requirements of warfarin (P = 2.68 × 10 -5 , P = 5.81 × 10 -4 , and P = 5.94 × 10 -4 , respectively). Required doses of warfarin were the highest for homozygotes of the minor allele at the VDR variants (P < 0.0026). Variants in the VDR gene were associated with the variability in response to warfarin, emphasizing the possible clinical relevance of nuclear receptor gene variants on the inter-individual variability in drug metabolism.

Aim: We have evaluated the pharmacogenetic content of commercial human genome-wide genotyping arrays, as it is a critical determinant to enabling pharmacogenomic discoveries., Methods: Using bioinformatics approaches, we assessed 27,811 genetic variants in 3146 genes for their presence in 18 Illumina and 15 Affymetrix genome-wide arrays., Results: The pharmacogenetic content of the arrays varied greatly. The combination of the Affymetrix precision medicine array and PharmacoScan arrays (Affymetrix) had the highest coverage for a set of clinically actionable absorption, distribution, metabolism and excretion (ADME) variants, single nucleotide ADME variants and ADME insertions/deletions, with a physical coverage of 125/130 (96.2%), 9924/24,138 (41.1%) and 2252/3994 (56.4%), respectively., Conclusion: The combination of the Affymetrix precision medicine array and PharmacoScan arrays provided both genome-wide and pharmacogene coverage, which is crucial in the discovering of new variants responsible for drug adverse effects. These results will help in the design of pharmacogenomic studies and will enable a critical review of results from past studies.

Quantifying image distortions caused by strong gravitational lensing-the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures-and estimating the corresponding matter distribution of these structures (the 'gravitational lens') has primarily been performed using maximum likelihood modelling of observations. This procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. Here we report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the 'singular isothermal ellipsoid' density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

Background: In the Western world, between 1940 and 1970, more than 2 million people were exposed in utero to diethylstilbestrol (DES). In exposed individuals, and in their descendants, adverse outcomes have been linked to such exposure, including cancers, genital malformations, and less consistently, psychiatric disorders. We aimed to explore whether prenatal DES exposure would be associated with DNA methylation changes, and whether these epigenetic modifications would be associated with increased risk of psychosis., Methods: From 247 individuals born from mothers exposed to DES, we selected 69 siblings from 30 families. In each family, at least one sibling was exposed in utero to DES. We performed a methylome-wide association study using HumanMethylation450 DNA Analysis BeadChip® in peripheral blood. We analyzed methylation changes at individual CpGs or regions in exposed (n = 37) versus unexposed individuals (n = 32). We also compared exposed individuals with (n = 7) and without psychosis (n = 30)., Results: There were more individuals with schizophrenia in the DES-exposed group. We found no significant differences between exposed and unexposed individuals with respect to differentially methylated CpGs or regions. The largest difference was in a region near the promoter of an ADAMTS proteoglycanase gene (ADAMTS9). Compared to exposed individuals without psychosis, exposed individuals with psychosis had differential methylation in the region encompassing the gene encoding the zinc finger protein 57 (ZFP57)., Conclusions: In utero exposure to DES was not associated with methylation changes at specific CpG or regions. In exposed individuals, however, psychosis was associated with specific methylomic modifications that could impact neurodevelopment and neuroplasticity.

The onset of psychosis is the consequence of complex interactions between genetic vulnerability to psychosis and response to environmental and/or maturational changes. Epigenetics is hypothesized to mediate the interplay between genes and environment leading to the onset of psychosis. We believe we performed the first longitudinal prospective study of genomic DNA methylation during psychotic transition in help-seeking young individuals referred to a specialized outpatient unit for early detection of psychosis and enrolled in a 1-year follow-up. We used Infinium HumanMethylation450 BeadChip array after bisulfite conversion and analyzed longitudinal variations in methylation at 411 947 cytosine-phosphate-guanine (CpG) sites. Conversion to psychosis was associated with specific methylation changes. Changes in DNA methylation were significantly different between converters and non-converters in two regions: one located in 1q21.1 and a cluster of six CpG located in GSTM5 gene promoter. Methylation data were confirmed by pyrosequencing in the same population. The 100 top CpGs associated with conversion to psychosis were subjected to exploratory analyses regarding the related gene networks and their capacity to distinguish between converters and non-converters. Cluster analysis showed that the top CpG sites correctly distinguished between converters and non-converters. In this first study of methylation during conversion to psychosis, we found that alterations preferentially occurred in gene promoters and pathways relevant for psychosis, including oxidative stress regulation, axon guidance and inflammatory pathways. Although independent replications are warranted to reach definitive conclusions, these results already support that longitudinal variations in DNA methylation may reflect the biological mechanisms that precipitate some prodromal individuals into full-blown psychosis, under the influence of environmental factors and maturational processes at adolescence.

Genotype imputation is now commonly performed following genome-wide genotyping experiments. Imputation increases the density of analyzed genotypes in the dataset, enabling fine-mapping across the genome. However, the process of imputation using the most recent publicly available reference datasets can require considerable computation power and the management of hundreds of large intermediate files. We have developed genipe, a complete genome-wide imputation pipeline which includes automatic reporting, imputed data indexing and management, and a suite of statistical tests for imputed data commonly used in genetic epidemiology (Sequence Kernel Association Test, Cox proportional hazards for survival analysis, and linear mixed models for repeated measurements in longitudinal studies)., Availability and Implementation: The genipe package is an open source Python software and is freely available for non-commercial use (CC BY-NC 4.0) at https://github.com/pgxcentre/genipe Documentation and tutorials are available at http://pgxcentre.github.io/genipe CONTACT: louis-philippe.lemieux.perreault@statgen.org or marie-pierre.dube@statgen.orgSupplementary information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press.)

De novo mutations (DNM) are an important source of rare variants and are increasingly being linked to the development of many diseases. Recently, the paternal age effect has been the focus of a number of studies that attempt to explain the observation that increasing paternal age increases the risk for a number of diseases. Using disease-free familial quartets we show that there is a strong positive correlation between paternal age and germline DNM in healthy subjects. We also observed that germline CNVs do not follow the same trend, suggesting a different mechanism. Finally, we observed that DNM were not evenly distributed across the genome, which adds support to the existence of DNM hotspots., Competing Interests: The authors have declared that no competing interests exist.

Background: Prenatal alcohol exposure is the leading preventable cause of behavioral and cognitive deficits, which may affect between 2 and 5 % of children in North America. While the underlying mechanisms of alcohol's effects on development remain relatively unknown, emerging evidence implicates epigenetic mechanisms in mediating the range of symptoms observed in children with fetal alcohol spectrum disorder (FASD). Thus, we investigated the effects of prenatal alcohol exposure on genome-wide DNA methylation in the NeuroDevNet FASD cohort, the largest cohort of human FASD samples to date., Methods: Genome-wide DNA methylation patterns of buccal epithelial cells (BECs) were analyzed using the Illumina HumanMethylation450 array in a Canadian cohort of 206 children (110 FASD and 96 controls). Genotyping was performed in parallel using the Infinium HumanOmni2.5-Quad v1.0 BeadChip., Results: After correcting for the effects of genetic background, we found 658 significantly differentially methylated sites between FASD cases and controls, with 41 displaying differences in percent methylation change >5 %. Furthermore, 101 differentially methylated regions containing two or more CpGs were also identified, overlapping with 95 different genes. The majority of differentially methylated genes were highly expressed at the level of mRNA in brain samples from the Allen Brain Atlas, and independent DNA methylation data from cortical brain samples showed high correlations with BEC DNA methylation patterns. Finally, overrepresentation analysis of genes with up-methylated CpGs revealed a significant enrichment for neurodevelopmental processes and diseases, such as anxiety, epilepsy, and autism spectrum disorders., Conclusions: These findings suggested that prenatal alcohol exposure is associated with distinct DNA methylation patterns in children and adolescents, raising the possibility of an epigenetic biomarker of FASD.

Background: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets., Methods: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes., Results: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7))., Conclusions: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Background: Dalcetrapib did not improve clinical outcomes, despite increasing high-density lipoprotein cholesterol by 30%. These results differ from other evidence supporting high-density lipoprotein as a therapeutic target. Responses to dalcetrapib may vary according to patients' genetic profile., Methods and Results: We conducted a pharmacogenomic evaluation using a genome-wide approach in the dal-OUTCOMES study (discovery cohort, n=5749) and a targeted genotyping panel in the dal-PLAQUE-2 imaging trial (support cohort, n=386). The primary endpoint for the discovery cohort was a composite of cardiovascular events. The change from baseline in carotid intima-media thickness on ultrasonography at 6 and 12 months was evaluated as supporting evidence. A single-nucleotide polymorphism was found to be associated with cardiovascular events in the dalcetrapib arm, identifying the ADCY9 gene on chromosome 16 (rs1967309; P=2.41×10(-8)), with 8 polymorphisms providing P<10(-6) in this gene. Considering patients with genotype AA at rs1967309, there was a 39% reduction in the composite cardiovascular endpoint with dalcetrapib compared with placebo (hazard ratio, 0.61; 95% confidence interval, 0.41-0.92). In patients with genotype GG, there was a 27% increase in events with dalcetrapib versus placebo. Ten single-nucleotide polymorphism in the ADCY9 gene, the majority in linkage disequilibrium with rs1967309, were associated with the effect of dalcetrapib on intima-media thickness (P<0.05). Marker rs2238448 in ADCY9, in linkage disequilibrium with rs1967309 (r(2)=0.8), was associated with both the effects of dalcetrapib on intima-media thickness in dal-PLAQUE-2 (P=0.009) and events in dal-OUTCOMES (P=8.88×10(-8); hazard ratio, 0.67; 95% confidence interval, 0.58-0.78)., Conclusions: The effects of dalcetrapib on atherosclerotic outcomes are determined by correlated polymorphisms in the ADCY9 gene., Clinical Trial Information: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00658515 and NCT01059682., (© 2015 American Heart Association, Inc.)

Background: The advent of high throughput sequencing methods breeds an important amount of technical challenges. Among those is the one raised by the discovery of copy-number variations (CNVs) using whole-genome sequencing data. CNVs are genomic structural variations defined as a variation in the number of copies of a large genomic fragment, usually more than one kilobase. Here, we aim to compare different CNV calling methods in order to assess their ability to consistently identify CNVs by comparison of the calls in 9 quartets of identical twin pairs. The use of monozygotic twins provides a means of estimating the error rate of each algorithm by observing CNVs that are inconsistently called when considering the rules of Mendelian inheritance and the assumption of an identical genome between twins. The similarity between the calls from the different tools and the advantage of combining call sets were also considered., Results: ERDS and CNVnator obtained the best performance when considering the inherited CNV rate with a mean of 0.74 and 0.70, respectively. Venn diagrams were generated to show the agreement between the different algorithms, before and after filtering out familial inconsistencies. This filtering revealed a high number of false positives for CNVer and Breakdancer. A low overall agreement between the methods suggested a high complementarity of the different tools when calling CNVs. The breakpoint sensitivity analysis indicated that CNVnator and ERDS achieved better resolution of CNV borders than the other tools. The highest inherited CNV rate was achieved through the intersection of these two tools (81%)., Conclusions: This study showed that ERDS and CNVnator provide good performance on whole genome sequencing data with respect to CNV consistency across families, CNV breakpoint resolution and CNV call specificity. The intersection of the calls from the two tools would be valuable for CNV genotyping pipelines.

Hematological traits are important clinical parameters. To test the effects of rare and low-frequency coding variants on hematological traits, we analyzed hemoglobin concentration, hematocrit levels, white blood cell (WBC) counts and platelet counts in 31,340 individuals genotyped on an exome array. We identified several missense variants in CXCR2 associated with reduced WBC count (gene-based P = 2.6 × 10(-13)). In a separate family-based resequencing study, we identified a CXCR2 frameshift mutation in a pedigree with congenital neutropenia that abolished ligand-induced CXCR2 signal transduction and chemotaxis. We also identified missense or splice-site variants in key hematopoiesis regulators (EPO, TFR2, HBB, TUBB1 and SH2B3) associated with blood cell traits. Finally, we were able to detect associations between a rare somatic JAK2 mutation (encoding p.Val617Phe) and platelet count (P = 3.9 × 10(-22)) as well as hemoglobin concentration (P = 0.002), hematocrit levels (P = 9.5 × 10(-7)) and WBC count (P = 3.1 × 10(-5)). In conclusion, exome arrays complement genome-wide association studies in identifying new variants that contribute to complex human traits.

Background: Along with the improvement of high throughput sequencing technologies, the genetics community is showing marked interest for the rare variants/common diseases hypothesis. While sequencing can still be prohibitive for large studies, commercially available genotyping arrays targeting rare variants prove to be a reasonable alternative. A technical challenge of array based methods is the task of deriving genotype classes (homozygous or heterozygous) by clustering intensity data points. The performance of clustering tools for common polymorphisms is well established, while their performance when conducted with a large proportion of rare variants (where data points are sparse for genotypes containing the rare allele) is less known. We have compared the performance of four clustering tools (GenCall, GenoSNP, optiCall and zCall) for the genotyping of over 10,000 samples using the Illumina's HumanExome BeadChip, which includes 247,870 variants, 90% of which have a minor allele frequency below 5% in a population of European ancestry. Different reference parameters for GenCall and different initial parameters for GenoSNP were tested. Genotyping accuracy was assessed using data from the 1000 Genomes Project as a gold standard, and agreement between tools was measured., Results: Concordance of GenoSNP's calls with the gold standard was below expectations and was increased by changing the tool's initial parameters. While the four tools provided concordance with the gold standard above 99% for common alleles, some of them performed poorly for rare alleles. The reproducibility of genotype calls for each tool was assessed using experimental duplicates which provided concordance rates above 99%. The inter-tool agreement of genotype calls was high for approximately 95% of variants. Most tools yielded similar error rates (approximately 0.02), except for zCall which performed better with a 0.00164 mean error rate., Conclusions: The GenoSNP clustering tool could not be run straight "out of the box" with the HumanExome BeadChip, as modification of hard coded parameters was necessary to achieve optimal performance. Overall, GenCall marginally outperformed the other tools for the HumanExome BeadChip. The use of experimental replicates provided a valuable quality control tool for genotyping projects with rare variants.

Unlabelled: Genetic association studies making use of high-throughput genotyping arrays need to process large amounts of data in the order of millions of markers per experiment. The first step of any analysis with genotyping arrays is typically the conduct of a thorough data clean up and quality control to remove poor quality genotypes and generate metrics to inform and select individuals for downstream statistical analysis. We have developed pyGenClean, a bioinformatics tool to facilitate and standardize the genetic data clean up pipeline with genotyping array data. In conjunction with a source batch-queuing system, the tool minimizes data manipulation errors, accelerates the completion of the data clean up process and provides informative plots and metrics to guide decision making for statistical analysis., Availability and Implementation: pyGenClean is an open source Python 2.7 software and is freely available, along with documentation and examples, from http://www.statgen.org.

Left-sided congenital heart disease (CHD) encompasses a spectrum of malformations that range from bicuspid aortic valve to hypoplastic left heart syndrome. It contributes significantly to infant mortality and has serious implications in adult cardiology. Although left-sided CHD is known to be highly heritable, the underlying genetic determinants are largely unidentified. In this study, we sought to determine the impact of structural genomic variation on left-sided CHD and compared multiplex families (464 individuals with 174 affecteds (37.5%) in 59 multiplex families and 8 trios) to 1,582 well-phenotyped controls. 73 unique inherited or de novo CNVs in 54 individuals were identified in the left-sided CHD cohort. After stringent filtering, our gene inventory reveals 25 new candidates for LS-CHD pathogenesis, such as SMC1A, MFAP4, and CTHRC1, and overlaps with several known syndromic loci. Conservative estimation examining the overlap of the prioritized gene content with CNVs present only in affected individuals in our cohort implies a strong effect for unique CNVs in at least 10% of left-sided CHD cases. Enrichment testing of gene content in all identified CNVs showed a significant association with angiogenesis. In this first family-based CNV study of left-sided CHD, we found that both co-segregating and de novo events associate with disease in a complex fashion at structural genomic level. Often viewed as an anatomically circumscript disease, a subset of left-sided CHD may in fact reflect more general genetic perturbations of angiogenesis and/or vascular biology., Competing Interests: The authors have declared that no competing interests exist.

Background: Copy number variations (CNVs) and polymorphisms (CNPs) have only recently gained the genetic community's attention. Conservative estimates have shown that CNVs and CNPs might affect more than 10% of the genome and that they may be at least as important as single nucleotide polymorphisms in assessing human variability. Widely used tools for CNP analysis have been implemented in Birdsuite and PLINK for the purpose of conducting genetic association studies based on the unpartitioned total number of CNP copies provided by the intensities from Affymetrix's Genome-Wide Human SNP Array. Here, we are interested in partitioning copy number variations and polymorphisms in extended pedigrees for the purpose of linkage analysis on familial data., Results: We have developed CNGen, a new software for the partitioning of copy number polymorphism using the integrated genotypes from Birdsuite with the Affymetrix platform. The algorithm applied to familial trios or extended pedigrees can produce partitioned copy number genotypes with distinct parental alleles. We have validated the algorithm using simulations on a complex pedigree structure using frequencies calculated from a real dataset of 300 genotyped samples from 42 pedigrees segregating a congenital heart defect phenotype., Conclusions: CNGen is the first published software for the partitioning of copy number genotypes in pedigrees, making possible the use CNPs and CNVs for linkage analysis. It was implemented with the Python interpreter version 2.5.2. It was successfully tested on current Linux, Windows and Mac OS workstations.

Implications: We describe a patient scheduled for coronary artery bypass who developed carbon dioxide (CO2) embolism with acute pulmonary hypertension during endoscopic saphenectomy. Transesophageal echocardiography was useful in the diagnosis of CO2 embolism and to assess response to inhaled epoprostenol.