Circulation: Genomic and Precision Medicine最新文献

Background: Though epidemiological studies show increased cardiovascular disease (CVD) risks among individuals with psychiatric disorders, findings on sex differences in comorbidity have been inconsistent.

Methods: This genetic epidemiology study examined the sex-specific association between the genetic risk of 3 psychiatric disorders (major depression [MD], schizophrenia, and bipolar disorder), estimated using polygenic scores (PGSs), and risks of 3 CVDs (atrial fibrillation [AF], coronary artery disease [CAD], and heart failure [HF]) in 345 169 European-ancestry individuals (UK Biobank), with analyses replicated in an independent BioVU cohort (n=49 057). Mediation analysis was conducted to determine whether traditional CVD risk factors could explain any observed sex difference.

Results: In the UK Biobank, a 1-SD increase in PGS_MD was significantly associated with the incident risks of all 3 CVDs in females after multiple testing corrections (hazard ratio [HR]_AF-female=1.04 [95% CI, 1.02-1.06]; P=1.5×10^-4; HR_CAD-female=1.07 [95% CI, 1.04-1.11]; P=2.6×10^-6; and HR_HF-female=1.09 [95% CI, 1.06-1.13]; P=9.7×10^-10), but not in males. These female-specific associations remained even in the absence of any psychiatric disorder diagnosis or psychiatric medication use. Although mediation analysis demonstrated that the association between PGS_MD and CVDs in females was partly mediated by baseline body mass index, hypercholesterolemia, hypertension, and smoking, these risk factors did not explain the higher risk compared with males. The association between PGS_MD and CAD was consistent between females who were premenopausal and postmenopausal at baseline, while the association with AF and HF was only observed in the baseline postmenopausal cohort. No significant association with CVD risks was observed for the PGS of schizophrenia or bipolar disorder. The female-specific positive association of PGS_MD with CAD risk was replicated in BioVU.

Conclusions: Genetic predisposition to MD confers a greater risk of CVDs in females versus males, even in the absence of any depression diagnosis. This study warrants further investigation into whether genetic predisposition to depression could be useful for improving cardiovascular risk prediction, especially in women.

Background: No disease-specific therapy currently exists for arrhythmogenic right ventricular cardiomyopathy (ARVC), a progressive cardiogenetic condition conferring elevated risk for ventricular arrhythmias, heart failure, and sudden cardiac death. Emerging gene therapies have the potential to fill this gap. However, little is known about how adults with ARVC, or any other inherited cardiomyopathy or arrhythmia syndrome, appraise the risks and benefits of gene therapy research and which considerations may influence their decisions about clinical trial participation.

Methods: Twenty adults with clinically diagnosed and gene-positive ARVC participated in semi-structured interviews that explored perceptions of gene therapy and hypothetical decision-making for gene therapy clinical trial participation. Interview transcripts were qualitatively coded and analyzed.

Results: Participants expressed enthusiasm for gene therapy with varied levels of personal interest in trial participation. Although clinical severity appeared to be associated with an elevated interest in early trial participation, participants anticipated weighing both personal and trial-specific factors including life stage, trial stage, risks, benefits, participation burden, study leadership, and anticipated cost of future gene therapy. Adaptation to living with ARVC and involvement in the ARVC patient community were also relevant to decision-making about trial participation. Potential ethical concerns included unquestioning trust in clinical teams collaborating on industry-led trials and vulnerability of those recently diagnosed or with high perceived severity of ARVC symptoms.

Conclusions: Several characteristics of the individual and trial warrant consideration during the informed consent process. Insights from this study may affect trial planning and communication with participants who have inherited cardiac conditions.

Background: Myocardial infarction (MI) is a complex disease caused by both lifestyle and genetic factors. This study aims to investigate the predictive value of genetic risk, in addition to traditional cardiovascular risk factors, for recurrent events following early-onset MI.

Methods: The Italian Genetic Study of Early-Onset Myocardial Infarction is a cohort study enrolling patients with MI before 45 years. Monogenic variants causing familial hypercholesterolemia were identified, and a coronary artery disease polygenic score (PGS) was calculated. Ten-fold cross-validated Cox proportional hazards models were fitted sequentially including all clinical variables, the PGS, and monogenic variants on the composite outcome of cardiovascular death, recurrent MI, stroke, or revascularization.

Results: During a 19.9-year follow-up, 847 (50.7%) patients experienced recurrent events. Each 1-SD higher PGS was associated with a 21% higher hazard of recurrent events (hazard ratio, 1.21 [95% CI, 1.13-1.31]; P=4.04×10^-6). Except for secondary prevention, PGS was the strongest determinant of recurrent event risk (C index, 0.56 [95% CI, 0.54-0.58]) compared with clinical risk factors. Overall, predictive performance of clinical risk factors (C index, 0.69 [95% CI, 0.67-0.71]) improved after adding the PGS (C index, 0.69 [95% CI, 0.68-0.71]; P=0.006). When dividing the population by PGS quintiles, the highest fifth had a 57% higher hazard of recurrent events than the lowest fifth (hazard ratio, 1.57 [95% CI, 1.26-1.96]; P=5.57×10^-5).

Conclusions: When compared with other clinical risk factors, PGS was the strongest predictor of event recurrence among patients with an early-onset MI. Though the discriminative power of recurrent event prediction in this cohort was modest, the addition of PGS significantly improved discrimination.

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.