Biomedical subjects

James S Ware

Publications and source records attributed to James S Ware.

4 recordsLinked to original sources

PubMed2026

An Updated Evidence Assessment of the Genetic Causes of Dilated Cardiomyopathy.

BACKGROUND: Evidence of the diverse genetic architecture of dilated cardiomyopathy (DCM) continues to emerge and requires reassessment of the clinical relevance of implicated disease genes. Building on the 2019-2020 Clinical Genome Resource evaluation, the DCM gene curation expert panel reconvened in 2024-2025 to conduct a reassessment of genes in DCM. METHODS: The Clinical Genome Resource semiquantitative clinical validity classification framework was applied with specifications to DCM to classify genes into categories on the basis of strength of published evidence for a DCM phenotype. Previously curated genes were reassessed, and newly reported gene-disease-mode of inheritance (MOI) relationships, termed "curations," were evaluated. RESULTS: Sixty-eight genes were evaluated, inclusive of 72 unique gene-disease-MOI relationships across 51 previously evaluated and 17 newly assessed genes. Thirty-five curations were classified as high evidence (16 Definitive, 10 Strong, 9 Moderate), increasing by 16 from the prior assessment. Nine newly assessed genes were classified as high evidence: BAG5, FLII, LMOD2, MYLK3, MYZAP, NRAP, PPA2, PPP1R13L, and RPL3L. Twelve genes (11 newly appraised) were rated as high evidence with an autosomal recessive (AR) MOI. Five reevaluated genes from 2019-2020 had clinically significant changes in classification. Except for JPH2, for which curation was modified to separate autosomal dominant and AR MOI curations, clinically significant changes involved upgrades from low- to high-evidence categories (PLEKHM2, PRDM16, TBX20, TNNI3K), demonstrating the robustness of the Clinical Genome Resource gene curation process over time. An additional 29 gene-disease-MOI curations were classified as Limited, including 6 newly evaluated genes and 1 new MOI for a previously evaluated gene, MYBPC3-AR; 4 were classified as No Known Disease Relationship, and remained Disputed. Four previously evaluated genes were curated for both AD and AR MOIs: JPH2 (AD-Strong, AR-Limited), LDB3 (AD-Limited, AR-Strong), MYBPC3 (AD-Limited, AR-Limited), and TNNI3 (AD- and AR- Strong). CONCLUSIONS: With substantial new evidence, the genetic architecture of DCM has rapidly expanded. This updated assessment of genes reported in DCM yielded 35 high-evidence curations, an increase from 19 only 5 years ago. The results of this evidence-based evaluation process inform clinical interpretation of genetic information in the care of DCM patients and families.

dilated cardiomyopathy↗

PubMed2026

Pangenomes aid accurate detection of large insertions and deletions from targeted sequencing: the case of cardiomyopathies.

BACKGROUND: Gene panels represent a widely used strategy for genetic testing in a vast range of Mendelian disorders. While this approach aids reliable bioinformatic detection of short coding variants, it often fails to detect many larger variants. Recent studies have recommended the adoption of pangenome references (as opposed to linear reference genomes like GRCh38) to augment detection of large variants from targeted sequencing, potentially providing diagnostic laboratories with the possibility to streamline diagnostic work-ups and reduce costs. METHODS: Here, we analyze 1969 cardiomyopathy cases and 1805 controls sequenced with the Illumina Trusight Cardio panel using a pangenome-based workflow (GRAF) and five conventional orthogonal methodologies (GATK HaplotypeCaller, GATK-gCNV, ExomeDepth, Manta and Lumpy-SV) to detect variants ≥ 20 bp in size. RESULTS: Following lab-based variant validation by means of PCR and Sanger sequencing, we show that GRAF conjugates higher precision and recall (F1 score 0.86) compared with other methods (F1 0-0.57) in detecting potentially pathogenic variants ≥ 20 bp from short-read panel data. Results were complemented by a comparison of the tools' performance in detecting ground truth variants on reference sample HG002 from Genome In A Bottle, which confirmed GRAF to outperform other tools also on exome sequencing (F1 0.97 vs. 0-0.94). Notably, in the HG002 benchmark dataset, GRAF also showed slightly improved performance compared to GATK HaplotypeCaller in the identification of small variants (1-19 bp; F1 0.975 vs. 0.968). CONCLUSIONS: Our results indicate that pangenome-based workflows aid improved detection of large variants from targeted sequencing data in the clinical context and suggest that they may contribute to more unified variant detection frameworks for all-size genetic variants in the future.

Humans↗

PubMed2025

New Genetic Loci Implicated in Cardiac Morphology and Function Using Three-Dimensional Population Phenotyping.

BACKGROUND: Cardiac remodeling occurs in the mature heart and is a cascade of adaptations in response to stress, which are primed in early life. A key question remains as to the processes that regulate the geometry and motion of the heart and how it adapts to stress. METHODS: We performed spatially resolved phenotyping using machine learning-based analysis of cardiac magnetic resonance imaging in 47 549 UK Biobank participants. We analyzed 16 left ventricular spatial phenotypes, including regional myocardial wall thickness and systolic strain in both circumferential and radial directions. In up to 40 058 participants, genetic associations across the allele frequency spectrum were assessed using genome-wide association studies with imputed genotype participants, and exome-wide association studies and gene-based burden tests using whole-exome sequencing data. We integrated transcriptomic data from the GTEx project and used pathway enrichment analyses to further interpret the biological relevance of identified loci. To investigate causal relationships, we conducted Mendelian randomization analyses to evaluate the effects of blood pressure on regional cardiac traits and the effects of these traits on cardiomyopathy risk. RESULTS: We found 42 loci associated with cardiac structure and contractility, many of which reveal patterns of spatial organization in the heart. Whole-exome sequencing revealed 3 additional variants not captured by the genome-wide association study, including a missense variant in CSRP3 (minor allele frequency 0.5%). The majority of newly discovered loci are found in cardiomyopathy-associated genes, suggesting that they regulate spatially distinct patterns of remodeling in the left ventricle in an adult population. Our causal analysis also found regional modulation of blood pressure on cardiac wall thickness and strain. CONCLUSIONS: These findings provide a comprehensive description of the pathways that orchestrate heart development and cardiac remodeling. These data highlight the role that cardiomyopathy-associated genes have on the regulation of spatial adaptations in those without known disease.

Humans↗

PubMed2025

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.

Humans↗