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AimsIn a retrospective analysis of dal-Outcomes, the effect of dalcetrapib on cardiovascular events was influenced by an adenylate cyclase type 9 (ADCY9) gene polymorphism. The dal-GenE study was conducted to test this pharmacogenetic hypothesis.Methods and resultsdal-GenE was a double-blind trial in patients with an acute coronary syndrome within 1-3 months and the AA genotype at variant rs1967309 in the ADCY9 gene. A total of 6147 patients were randomly assigned to receive dalcetrapib 600 mg or placebo daily. The primary endpoint was the time from randomization to first occurrence of cardiovascular death, resuscitated cardiac arrest, non-fatal myocardial infarction, or non-fatal stroke. After a median follow-up of 39.9 months, the primary endpoint occurred in 292 (9.5%) of 3071 patients in the dalcetrapib group and 327 (10.6%) of 3076 patients in the placebo group [hazard ratio 0.88; 95% confidence interval (CI) 0.75-1.03; P = 0.12]. The hazard ratios for the components of the primary endpoint were 0.79 (95% CI 0.65-0.96) for myocardial infarction, 0.92 (95% CI 0.64-1.33) for stroke, 1.21 (95% CI 0.91-1.60) for death from cardiovascular causes, and 2.33 (95% CI 0.60-9.02) for resuscitated cardiac arrest. In a pre-specified on-treatment sensitivity analysis, the primary endpoint event rate was 7.8% (236/3015) in the dalcetrapib group and 9.3% (282/3031) in the placebo group (hazard ratio 0.83; 95% CI 0.70-0.98).ConclusionDalcetrapib did not significantly reduce the risk of occurrence of the primary endpoint of ischaemic cardiovascular events at end of study. A new trial would be needed to test the pharmacogenetic hypothesis that dalcetrapib improves the prognosis of patients with the AA genotype.Clinical trial registrationTrial registration dal-GenE ClinicalTrials.gov Identifier: NCT02525939.

Following the neutral results of the dal-OUTCOMES trial, a genome-wide study identified the rs1967309 variant in the adenylate cyclase type 9 (ADCY9) gene on chromosome 16 as being associated with the risk of future cardiovascular events only in subjects taking dalcetrapib, a CETP (cholesterol ester transfer protein) modulator. Homozygotes for the minor A allele (AA) were protected from recurrent cardiovascular events when treated with dalcetrapib, while homozygotes for the major G allele (GG) had increased risk. Here, we present the current state of knowledge regarding the impact of rs1967309 in ADCY9 on clinical observations and biomarkers in dalcetrapib trials and the effects of mouse ADCY9 gene inactivation on cardiovascular physiology. Finally, we present our current model of the interaction between dalcetrapib and ADCY9 gene variants in the arterial wall macrophage, based on the intracellular role of CETP in the transfer of complex lipids from endoplasmic reticulum membranes to lipid droplets. Briefly, the concept is that dalcetrapib would inhibit CETP-mediated transfer of cholesteryl esters, resulting in a progressive inhibition of cholesteryl ester synthesis and free cholesterol accumulation in the endoplasmic reticulum. Reduced ADCY9 activity, by paradoxically leading to higher cyclic AMP levels and in turn increased cellular cholesterol efflux, could impart cardiovascular protection in rs1967309 AA patients. The ongoing dal-GenE trial recruited 6145 patients with the protective AA genotype and will provide a definitive answer to whether dalcetrapib will be protective in this population.

BackgroundThe 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.MethodsThere 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.ResultsNone 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.ConclusionsWe 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.

AimsThe COLchicine Cardiovascular Outcomes Trial (COLCOT) demonstrated the benefits of targeting inflammation after myocardial infarction (MI). We aimed to determine whether time-to-treatment initiation (TTI) influences the beneficial impact of colchicine.Methods and resultsIn COLCOT, patients were randomly assigned to receive colchicine or placebo within 30 days post-MI. Time-to-treatment initiation was defined as the length of time between the index MI and the initiation of study medication. The primary efficacy endpoint was a composite of cardiovascular death, resuscitated cardiac arrest, MI, stroke, or urgent hospitalization for angina requiring coronary revascularization. The relationship between endpoints and various TTI (8 days) was examined using multivariable Cox regression models. Amongst the 4661 patients included in this analysis, there were 1193, 720, and 2748 patients, respectively, in the three TTI strata. After a median follow-up of 22.7 months, there was a significant reduction in the incidence of the primary endpoint for patients in whom colchicine was initiated < Day 3 compared with placebo [hazard ratios (HR) = 0.52, 95% confidence intervals (CI) 0.32-0.84], in contrast to patients in whom colchicine was initiated between Days 4 and 7 (HR = 0.96, 95% CI 0.53-1.75) or > Day 8 (HR = 0.82, 95% CI 0.61-1.11). The beneficial effects of early initiation of colchicine were also demonstrated for urgent hospitalization for angina requiring revascularization (HR = 0.35), all coronary revascularization (HR = 0.63), and the composite of cardiovascular death, resuscitated cardiac arrest, MI, or stroke (HR = 0.55, all P

The objectives of precision medicine are to better match patient characteristics with the therapeutic intervention to optimize the chances of beneficial actions while reducing the exposure to unneeded adverse drug experiences. In a retrospective genome-wide association study of the overall neutral placebo-controlled dal-Outcomes trial, the effect of the cholesteryl ester transfer protein (CETP) modulator dalcetrapib on the composite of cardiovascular death, myocardial infarction or stroke was found to be influenced by a polymorphism in the adenylate cyclase type 9 (ADCY9) gene. Whereas patients with the AA genotype at position rs1967309 experienced fewer cardiovascular events with dalcetrapib, those with the GG genotype had an increased rate and the heterozygous AG genotype exhibited no difference from placebo. Measurements of cholesterol efflux and C-reactive protein (CRP) offered directionally supportive genotype-specific findings. In a separate, smaller, placebo-controlled trial, regression of ultrasonography-determined carotid intimal-medial thickness was only observed in dalcetrapib-treated patients with the AA genotype. Collectively, these observations led to the hypothesis that the cardiovascular effects of dalcetrapib may be pharmacogenetically determined, with a favorable benefit-risk ratio only for patients with this specific genotype. We describe below the design of dal-GenE, a precision medicine, placebo-controlled clinical outcome trial of dalcetrapib in patients with a recent acute myocardial infarction with the unique feature of selecting only those with the AA genotype at rs1967309 in the ADCY9 gene.

BackgroundExperimental and clinical evidence supports the role of inflammation in atherosclerosis and its complications. Colchicine is an orally administered, potent antiinflammatory medication that is indicated for the treatment of gout and pericarditis.MethodsWe performed a randomized, double-blind trial involving patients recruited within 30 days after a myocardial infarction. The patients were randomly assigned to receive either low-dose colchicine (0.5 mg once daily) or placebo. The primary efficacy end point was a composite of death from cardiovascular causes, resuscitated cardiac arrest, myocardial infarction, stroke, or urgent hospitalization for angina leading to coronary revascularization. The components of the primary end point and safety were also assessed.ResultsA total of 4745 patients were enrolled; 2366 patients were assigned to the colchicine group, and 2379 to the placebo group. Patients were followed for a median of 22.6 months. The primary end point occurred in 5.5% of the patients in the colchicine group, as compared with 7.1% of those in the placebo group (hazard ratio, 0.77; 95% confidence interval [CI], 0.61 to 0.96; P = 0.02). The hazard ratios were 0.84 (95% CI, 0.46 to 1.52) for death from cardiovascular causes, 0.83 (95% CI, 0.25 to 2.73) for resuscitated cardiac arrest, 0.91 (95% CI, 0.68 to 1.21) for myocardial infarction, 0.26 (95% CI, 0.10 to 0.70) for stroke, and 0.50 (95% CI, 0.31 to 0.81) for urgent hospitalization for angina leading to coronary revascularization. Diarrhea was reported in 9.7% of the patients in the colchicine group and in 8.9% of those in the placebo group (P = 0.35). Pneumonia was reported as a serious adverse event in 0.9% of the patients in the colchicine group and in 0.4% of those in the placebo group (P = 0.03).ConclusionsAmong patients with a recent myocardial infarction, colchicine at a dose of 0.5 mg daily led to a significantly lower risk of ischemic cardiovascular events than placebo. (Funded by the Government of Quebec and others; COLCOT ClinicalTrials.gov number, NCT02551094.).

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF

Background and Aims Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). This study introduces an ECG-AI model developed and tested at a tertiary cardiac centre, comparing its performance with clinical models and AF polygenic score (PGS). Methods Electrocardiograms in sinus rhythm from the Montreal Heart Institute were analysed, excluding those from patients with pre-existing AF. The primary outcome was incident AF at 5 years. An ECG-AI model was developed by splitting patients into non-overlapping data sets: 70% for training, 10% for validation, and 20% for testing. The performance of ECG-AI, clinical models, and PGS was assessed in the test data set. The ECG-AI model was externally validated in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) hospital data set. Results A total of 669 782 ECGs from 145 323 patients were included. Mean age was 61 ± 15 years, and 58% were male. The primary outcome was observed in 15% of patients, and the ECG-AI model showed an area under the receiver operating characteristic (AUC-ROC) curve of.78. In time-to-event analysis including the first ECG, ECG-AI inference of high risk identified 26% of the population with a 4.3-fold increased risk of incident AF (95% confidence interval: 4.02–4.57). In a subgroup analysis of 2301 patients, ECG-AI outperformed CHARGE-AF (AUC-ROC =.62) and PGS (AUC-ROC =.59). Adding PGS and CHARGE-AF to ECG-AI improved goodness of fit (likelihood ratio test P <.001), with minimal changes to the AUC-ROC (.76–.77). In the external validation cohort (mean age 59 ± 18 years, 47% male, median follow-up 1.1 year), ECG-AI model performance remained consistent (AUC-ROC =.77). Conclusions ECG-AI provides an accurate tool to predict new-onset AF in a tertiary cardiac centre, surpassing clinical and PGS. [ABSTRACT FROM AUTHOR]

Despite increased efforts to ensure diversity in genomic research, the exclusion of minority groups from data analyses and publications remains a critical issue. This paper addresses the ethical implications of these exclusions and proposes accountability for reasonableness (A4R) as a framework to promote fairness and equity in research. Originally conceived by Norman Daniels and James Sabin to guide resource allocation in the context of health policy, A4R emphasizes publicity, relevance of reasons, enforcement, and revision as essential for legitimacy and trust in the decision‐making process. The authors argue that A4R is also relevant to resource allocation in research and that, if adequately informed and incentivized by funding agencies, institutional review boards, and scientific journals, researchers are well‐positioned to assess data‐selection justifications. The A4R framework provides a promising foundation for fostering accountability in genomics and other fields, including artificial intelligence, where lack of diversity and pervasive biases threaten equitable benefit sharing. [ABSTRACT FROM AUTHOR]

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

PurposeTo investigate the clinical characteristics and genetic basis of inherited retinal degeneration (IRD) in six unrelated pedigrees from Mexico.MethodsA complete ophthalmic evaluation including measurement of visual acuities, Goldman kinetic or Humphrey dynamic perimetry, Amsler test, fundus photography, and color vision testing was performed. Family history and blood samples were collected from available family members. DNA from members of two pedigrees was examined for known mutations using the APEX ARRP genotyping microarray and one pedigree using the APEX LCA genotyping microarray. The remaining three pedigrees were analyzed using a custom-designed targeted capture array covering the exons of 233 known retinal degeneration genes. Sequencing was performed on Illumina HiSeq. Reads were mapped against hg19, and variants were annotated using GATK and filtered by exomeSuite. Segregation and ethnicity-matched control sample analyses were performed by dideoxy sequencing.ResultsSix pedigrees with IRD were analyzed. Nine rare or novel, potentially pathogenic variants segregating with the phenotype were detected in IMPDH1, USH2A, RPE65, ABCA4, and FAM161A genes. Among these, six were known mutations while the remaining three changes in USH2A, RPE65, and FAM161A genes have not been previously reported to be associated with IRD. Analysis of 100 ethnicity-matched controls did not detect the presence of these three novel variants indicating, these are rare variants in the Mexican population.ConclusionsScreening patients diagnosed with IRD from Mexico identified six known mutations and three rare or novel potentially damaging variants in IMPDH1, USH2A, RPE65, ABCA4, and FAM161A genes that segregated with disease.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

BackgroundIn addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.Methods and resultsWe performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p

Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

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. [ABSTRACT FROM AUTHOR]