248 research outputs found

    Genetic basis of cardiovascular diseases

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    Cardiovascular diseases are a major global health issue. This thesis focusses on the genetic basis of three cardiovascular conditions: atrial fibrillation (AF), heart failure (HF), and mitral valve prolapse (MVP). AF is widespread and mainly manifests in an irregular heartbeat, HF is a complex condition that occurs when the heart fails to pumps blood effectively, and MVP is a heart valve disorder. Genome-wide association studies (GWAS) have been instrumental in understanding the genetic basis of cardiovascular diseases. Extensive research was conducted for AF, HF, and MVP by utilizing large international consortia and analyzing data from various biobanks and cohorts. First, 250 new AF-related genetic regions were discovered in the largest genetic study for AF to date. Second, rare deleterious variants within the gene TTN, were linked to AF susceptibility. Additionally, we increased the number of HF cases studied from 6.8k to 47k, uncovering 10 new genetic regions. We expanded our analysis on MVP from 1.4k cases to 4.8k, identifying 12 new genetic regions. We carefully evaluated potential effector genes at GWAS locations by generating new functional data and using existing datasets. Overall, this research identified potential effector genes for AF and MVP and shed light on interesting biological pathways. Additionally, we developed improved and new genetic risk scores for AF and MVP, using state of the art computational methods. Although we didn't pinpoint the exact pathophysiology between every genetic variant and AF, our work demonstrated the value of genetic risk profiles in predicting disease risk, offering an improvement over clinical risk factors alone

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation

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    Background: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. / Methods: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. / Results: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk. / Conclusions: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF

    Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation.

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    BACKGROUND: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. METHODS: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. RESULTS: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk. CONCLUSIONS: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF

    MyoMiner: explore gene co-expression in normal and pathological muscle

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    International audienceBackground: High-throughput transcriptomics measures mRNA levels for thousands of genes in a biological sample. Most gene expression studies aim to identify genes that are differentially expressed between different biological conditions, such as between healthy and diseased states. However, these data can also be used to identify genes that are co-expressed within a biological condition. Gene co-expression is used in a guilt-by-association approach to prioritize candidate genes that could be involved in disease, and to gain insights into the functions of genes, protein relations, and signaling pathways. Most existing gene co-expression databases are generic, amalgamating data for a given organism regardless of tissue-type.Methods: To study muscle-specific gene co-expression in both normal and pathological states, publicly available gene expression data were acquired for 2376 mouse and 2228 human striated muscle samples, and separated into 142 categories based on species (human or mouse), tissue origin, age, gender, anatomic part, and experimental condition. Co-expression values were calculated for each category to create the MyoMiner database.Results: Within each category, users can select a gene of interest, and the MyoMiner web interface will return all correlated genes. For each co-expressed gene pair, adjusted p-value and confidence intervals are provided as measures of expression correlation strength. A standardized expression-level scatterplot is available for every gene pair r-value. MyoMiner has two extra functions: (a) a network interface for creating a 2-shell correlation network, based either on the most highly correlated genes or from a list of genes provided by the user with the option to include linked genes from the database and (b) a comparison tool from which the users can test whether any two correlation coefficients from different conditions are significantly different.Conclusions: These co-expression analyses will help investigators to delineate the tissue-, cell-, and pathology-specific elements of muscle protein interactions, cell signaling and gene regulation. Changes in co-expression between pathologic and healthy tissue may suggest new disease mechanisms and help define novel therapeutic targets. Thus, MyoMiner is a powerful muscle-specific database for the discovery of genes that are associated with related functions based on their co-expression. MyoMiner is freely available at https://www.sys-myo.com/myominer

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Genome-wide analyses identify SCN5A as a susceptibility locus for premature atrial contraction frequency.

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    Premature atrial contractions (PACs) are frequently observed on electrocardiograms and are associated with increased risks of atrial fibrillation (AF), stroke, and mortality. In this study, we aimed to identify genetic susceptibility loci for PAC frequency. We performed a genome-wide association study meta-analysis with PAC frequency obtained from ambulatory cardiac monitoring in 4,831 individuals of European ancestry. We identified a genome-wide significant locus at the SCN5A gene. The lead variant, rs7373862, located in an intron of SCN5A, was associated with an increase of 0.12 [95% CI 0.08-0.16] standard deviations of the normalized PAC frequency per risk allele. Among genetic variants previously associated with AF, there was a significant enrichment in concordance of effect for PAC frequency (n = 73/106, p = 5.1 × 10-5). However, several AF risk loci, including PITX2, were not associated with PAC frequency. These findings suggest the existence of both shared and distinct genetic mechanisms for PAC frequency and AF

    Role of SNP markers on chromosome 10 in the pathogenesis of atrial fibrillation

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    Atrial fibrillation (AF) is one of the most common tachyarrhythmias, contributing to both environmental and genetic factors, a clear understanding of which can be extremely important for determining management tactics and predicting the disease course. The article provides a brief overview of studies on genetic predictors of AF, in particular, SNP markers found on chromosome 10. Establishing a relationship between the identified SNPs on chromosome 10 and functional genes, changes in the structure or regulation of which can affect the development of AF, opens the veil of understanding how these SNPs affect the pathogenesis of AF
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