Circulation: Genomic and Precision Medicine最新文献

Background: Interpretation of variants of uncertain significance (VUSs) remains a challenge in the care of patients with inherited cardiovascular diseases (CVDs); 56% of variants within CVD risk genes are VUS, and machine learning algorithms trained upon large data resources can stratify VUS into higher versus lower probability of contributing to a CVD phenotype.

Methods: We used ClinVar pathogenic/likely pathogenic and benign/likely benign variants from 47 CVD genes to build a predictive model of variant pathogenicity utilizing measures of evolutionary constraint, deleteriousness, splicogenicity, local pathogenicity, cardiac-specific expression, and population allele frequency. Performance was validated using variants for which the ClinVar pathogenicity assignment changed. Functional validation was assessed using prior studies in >900 identified VUS. The model utility was demonstrated using the Catheterization Genetics cohort.

Results: We identified a top-ranked model that accurately prioritized variants for which ClinVar clinical significance had changed (n=663; precision-recall area under the curve, 0.97) and performed well compared with conventional in silico methods. This model (CVD pathogenicity predictor) also had high accuracy in prioritizing VUS with functional effects in vivo (precision-recall area under the curve, 0.58). In Catheterization Genetics, there was a greater burden of higher CVD pathogenicity predictor scored VUS in individuals with dilated cardiomyopathy compared with controls (P=8.2×10^-15). Of individuals in Catheterization Genetics who harbored highly ranked CVD pathogenicity predictor VUS meeting clinical pathogenicity criteria, 27.6% had clinical evidence of disease. Variant prioritization using this model increased genetic diagnosis in Catheterization Genetics participants with a known clinical diagnosis of hypertrophic cardiomyopathy (7.8%-27.2%).

Conclusions: We present a cardiac-specific model for prioritizing variants underlying CVD syndromes with high performance in discriminating the pathogenicity of VUS in CVD genes. Variant review and phenotyping of individuals carrying VUS of pathogenic interest support the clinical utility of this model. This model could also have utility in filtering variants as part of large-scale genomic sequencing studies.

Background: Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.

Methods: The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.

Results: Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).

Conclusions: We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.

Background: Atrial fibrillation GWAS (genome-wide association studies) identified significant associations for rs1152591 and linked variants in the SYNE2 gene encoding Nesprin-2, which connects the nuclear membrane with the cytoskeleton.

Methods: Reporter gene vector transfection and CRISPR-Cas9 editing were used to identify the causal variant regulating the expression of SYNE2α1. After SYNE2 knockdown or SYNE2α1 overexpression in human stem cell-derived cardiomyocytes, nuclear phenotypes were assessed by imaging and atomic force microscopy. Gene expression was assessed by RNAseq and gene set enrichment analysis. Fura-2 AM staining assessed calcium transients. Optical mapping assessed action potential duration and conduction velocity.

Results: The risk allele of rs1152591 had lower promoter and enhancer activity and was significantly associated with lower expression of the short SYNE2α1 isoform in human stem cell-derived cardiomyocytes, without an effect on the expression of the full-length SYNE2 mRNA. SYNE2α1 overexpression had dominant negative effects on the nucleus with its overexpression or SYNE2 knockdown leading to increased nuclear area and decreased nuclear stiffness. Gene expression results from SYNE2α1 overexpression demonstrated both concordant and nonconcordant effects with SYNE2 knockdown. SYNE2α1 overexpression had a gain of function on electrophysiology, leading to significantly faster calcium reuptake and decreased assessed action potential duration, while SYNE2 knockdown showed both shortened assessed action potential duration and decreased conduction velocity.

Conclusions: rs1152591 was identified as a causal atrial fibrillation variant, with the risk allele decreasing SYNE2α1 expression. Downstream effects of SYNE2α1 overexpression include changes in nuclear stiffness and electrophysiology, which may contribute to the mechanism for the risk allele's association with AF.

Calmodulin, a protein critically important for the regulation of all major cardiac ion channels, is the quintessential cellular calcium sensor and plays a key role in preserving cardiac electrical stability. Its unique importance is highlighted by the presence of 3 genes in 3 different chromosomes encoding for the same protein and by their extreme conservation. Indeed, all 3 calmodulin (CALM) genes are among the most constrained genes in the human genome, that is, the observed variants are much less than expected by chance. Not surprisingly, CALM variants are poorly tolerated and accompany significant clinical phenotypes, of which the most important are those associated with increased risk for life-threatening arrhythmias. Here, we review the current knowledge about calmodulin, its specific physiological, structural, and functional characteristics, and its importance for cardiovascular disease. Given our role in the development of this knowledge, we also share some of our views about currently unanswered questions, including the rational approaches to the clinical management of the affected patients. Specifically, we present some of the most critical information emerging from the International Calmodulinopathy Registry, which we established 10 years ago. Further progress clearly requires deep phenotypic information on as many carriers as possible through international contributions to the registry, in order to expand our knowledge about Calmodulinopathies and guide clinical management.

Background: Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality. However, the current understanding of its underlying biological pathways remains limited.

Methods: In this study, we performed a cross-platform proteome- and transcriptome-wide genetic analysis aimed at evaluating the causal relevance of >2000 circulating proteins with preeclampsia, supported by data on the expression of over 15 000 genes across 36 tissues leveraging large-scale preeclampsia genetic association data from women of European ancestry.

Results: We demonstrate genetic associations of 18 circulating proteins with preeclampsia (SULT1A1 [sulfotransferase 1A1], SH2B3 [SH2B adapter protein 3], SERPINE2 [serpin family E member 2], RGS18 [regulator of G-protein signaling 18], PZP [pregnancy zone protein], NOTUM [notum, palmitoleoyl-protein carboxylesterase], METAP1 [methionyl aminopeptidase 1], MANEA [mannosidase endo-alpha], jun-D [JunD proto-oncogene], GDF15 [growth differentiation factor 15], FGL1 [fibrinogen like 1], FGF5 [fibroblast growth factor 5], FES [FES proto-oncogene], APOBR [apolipoprotein B receptor], ANP [natriuretic peptide A], ALDH-E2 [aldehyde dehydrogenase 2 family member], ADAMTS13 [ADAM metallopeptidase with thrombospondin type 1 motif 13], and 3MG [N-methylpurine DNA glycosylase]), among which 11 were either directly or indirectly supported by gene expression data, 9 were supported by Bayesian colocalization analyses, and 5 (SERPINE2, PZP, FGF5, FES, and ANP) were supported by all lines of evidence examined. Protein interaction mapping identified potential shared biological pathways through natriuretic peptide signaling, blood pressure regulation, immune tolerance, and thrombin activity regulation.

Conclusions: This investigation identified multiple targetable proteins linked to cardiovascular, inflammatory, and coagulation pathways, with SERPINE2, PZP, FGF5, FES, and ANP identified as pivotal proteins with likely causal roles in the development of preeclampsia. The identification of these potential targets may guide the development of targeted therapies for preeclampsia.

Background: Coronary atherosclerotic burden and adverse coronary heart disease events are related phenotypes with likely shared genetic cause.

Methods: We analyzed 6021 patients with available coronary angiography, genotyping, and exome sequencing data. We tested for associations of polygenic risk scores for coronary heart disease (PRS_CHD) with multiple measures of coronary artery disease (CAD) severity. We assessed the joint associations of PRS_CHD and pathogenic/likely pathogenic variants in 3 familial hypercholesterolemia genes, with CAD severity. We performed mediation analyses to explore whether CAD severity mediated the association of PRS_CHD with prevalent coronary heart disease and incident myocardial infarction.

Results: A 1-SD increase in PRS_CHD was associated with multiple measures of CAD severity, including the log Gensini score (β, 0.31 [95% CI, 0.28-0.33]). Carrying a pathogenic/likely pathogenic familial hypercholesterolemia variant was associated with a higher log Gensini score after adjustment for PRS_CHD (β, 0.21 [95% CI, 0.03-0.38]). A 1-SD increase in PRS_CHD was associated with incident myocardial infarction over a mean follow-up of 9.2 years (hazard ratio, 1.20 [95% CI, 1.13-1.27]; P=5×10^-10), and the Gensini score mediated 90% of this association.

Conclusions: PRS_CHD was associated with multiple measures of CAD severity. The association of PRS_CHD with incident myocardial infarction was almost fully mediated by CAD severity, indicating a considerable genetic overlap between the 2 phenotypes.