Circulation: Genomic and Precision Medicine最新文献

Background: The diagnosis of Fabry disease (FD) has relevant implications related to the management. Thus, a clear assignment of GLA variant pathogenicity is crucial. This systematic review and meta-analysis aimed to investigate the prevalence of FD in high-risk populations and newborns and evaluate the impact of different GLA variant classifications on the estimated prevalence of FD.

Methods: We searched the EMBASE and PubMed databases on February 21, 2023. Observational studies evaluating the prevalence of FD and reporting the identified GLA variants were included. GLA variants were re-evaluated for their pathogenicity significance using the American College of Medical Genetics and Genomics criteria and the ClinVar database. The pooled prevalence of FD among different settings was calculated. The study was registered on PROSPERO (CRD42023401663) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.

Results: Of the 3941 studies identified, 110 met the inclusion criteria. The pooled prevalence of FD was significantly different according to the clinical setting and criteria used for the pathogenicity assessment. Using the American College of Medical Genetics and Genomics criteria, the pooled prevalence was 1.2% in patients with left ventricular hypertrophy/hypertrophic cardiomyopathy (26 studies; 10 080 patients screened), 0.3% in end-stage renal disease/chronic kidney disease (38 studies; 62 050 patients screened), 0.7% in stroke (25 studies; 15 295 patients screened), 0.7% in cardiac conduction disturbance requiring pacemaker (3 studies; 1033 patients screened), 1.0% in small-fiber neuropathy (3 studies; 904 patients screened), and 0.01% in newborns (15 studies; 11 108 793 newborns screened). The pooled prevalence was different if the GLA variants were assessed using the ClinVar database, and most patients with a discrepancy in the pathogenicity assignment carried 1 of the following variants: p.A143T, p.D313Y, and p.E66Q.

Conclusions: This systematic review and meta-analysis describe the prevalence of FD among newborns and high-risk populations, highlighting the need for a periodic reassessment of the GLA variants in the context of recent clinical, biochemical, and histological data.

Registration: URL: https://crd.york.ac.uk/PROSPERO/; Unique identifier: CRD42023401663.

Background: Limiting high-intensity exercise is recommended for patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) due to its association with penetrance, arrhythmias, and structural progression. Guidelines recommend shared decision-making (SDM) for exercise level, but there is little evidence regarding its impact. Therefore, we sought to evaluate the extent and implications of SDM for exercise, decisional conflict, and decisional regret in patients with ARVC and at-risk relatives.

Methods: Adults diagnosed with ARVC or with positive genetic testing enrolled in the Johns Hopkins ARVC Registry were invited to complete a questionnaire that included exercise history and current exercise, SDM (SDM-Q-9), decisional conflict, and decisional regret.

Results: The response rate was 64.8%. Two-thirds of participants (68.0%, n=121) reported clinically significant decisional conflict regarding exercise at diagnosis/genetic testing (DCS [decisional conflict scale]≥25), and half (55.1%, n=98) in the past year. Prevalence of decisional regret was also high with 55.3% (n=99) reporting moderate to severe decisional regret (DRS [decisional regret scale]≥25). The extent of SDM was highly variable ranging from no (0) to perfect (100) SDM (mean, 59.6±25.0). Those diagnosed in adolescence (≤age 21) reported significantly more SDM (P=0.013). Importantly, SDM was associated with less decisional conflict (ß=-0.66, R²=0.567, P<0.01) and decisional regret (ß=-0.37, R²=0.180, P<0.001) and no difference in vigorous intensity aerobic exercise in the 6 months after diagnosis/genetic testing or the past year (P=0.56; P=0.34, respectively).

Conclusions: SDM is associated with lower decisional conflict and decisional regret; and no difference in postdiagnosis exercise. Our data thus support SDM as the preferred model for exercise discussions for ARVC.

Background: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D.

Methods: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test.

Results: Using a Bonferroni-corrected significance threshold of P<1.6×10^-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis.

Conclusions: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

Background: Proteomic profiling could potentially disclose new pathophysiological pathways for cardiovascular diseases (CVD) and improve prediction at the individual level. We therefore aimed to study the plasma protein profile associated with the incidence of different CVDs.

Methods: Plasma levels of 245 proteins suspected to be linked to CVD or metabolism were measured in 4 Swedish prospective population-based cohorts (SIMPLER [Swedish Infrastructure for Medical Population-Based Life-Course and Environmental Research], ULSAM (Uppsala Longitudinal Study of Adult Men), EpiHealth, and POEM [Prospective Investigation of Obesity, Energy Production, and Metabolism]) comprising 11 869 individuals, free of CVD diagnoses at baseline. Our primary CVD outcome was defined by a combined end point that included either incident myocardial infarction, stroke, or heart failure.

Results: Using a discovery/validation approach, 42 proteins were associated with our primary composite end point occurring in 1163 subjects. In separate meta-analyses for each of the 3 CVD outcomes, 49 proteins were related to myocardial infarction, 34 to ischemic stroke, and 109 to heart failure. Thirteen proteins were related to all 3 outcomes. Of those, urokinase plasminogen activator surface receptor, adrenomedullin, and KIM-1 (kidney injury molecule 1) were also related to several markers of subclinical CVD in Prospective Investigation of Obesity, Energy production and Metabolism, reflecting myocardial or arterial pathologies. In prediction analysis, a lasso selection of 11 proteins in ULSAM improved the discrimination of CVD by 3.3% (P<0.0001) in SIMPLER when added to traditional risk factors.

Conclusions: Protein profiling in multiple samples disclosed several new proteins to be associated with subsequent myocardial infarction, stroke, and heart failure, suggesting common pathophysiological pathways for these diseases. KIM-1, urokinase plasminogen activator surface receptor, and adrenomedullin were novel early markers of CVD. A selection of 11 proteins improved the discrimination of CVD.

Background: Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

Methods: In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.

Results: Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (r=0.61) and inverse association with CHD (odds ratio, 0.57 [0.49-0.65]), robust to adjustment for LE8 score and across participants with different sociodemographic and health status ([odds ratios, 0.42-0.69]; all P<0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort (r=0.49; odds ratio, 0.57 [0.46-0.69]).

Conclusions: Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Background: Hypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes, but there is no systematic framework for classifying morphology or assessing associated risks. Here, we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression.

Methods: We enrolled 436 patients with HCM (median age, 60 years; 28.8% women) with clinical, genetic, and imaging data. An independent cohort of 60 patients with HCM from Singapore (median age, 59 years; 11% women) and a reference population from the UK Biobank (n=16 691; mean age, 55 years; 52.5% women) were also recruited. We used machine learning to analyze the 3-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree.

Results: Carriers of pathogenic or likely pathogenic variants for HCM had lower left ventricular mass, but greater basal septal hypertrophy, with reduced life span (mean follow-up, 9.9 years) compared with genotype negative individuals (hazard ratio, 2.66 [95% CI, 1.42-4.96]; P<0.002). Four main phenotypic branches were identified using unsupervised learning of 3-dimensional shape: (1) nonsarcomeric hypertrophy with coexisting hypertension; (2) diffuse and basal asymmetrical hypertrophy associated with outflow tract obstruction; (3) isolated basal hypertrophy; and (4) milder nonobstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for pathogenic or likely pathogenic variants, 2.18 [95% CI, 1.93-2.28]; P=0.0001). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalizable to an independent cohort (trustworthiness, M₁: 0.86-0.88).

Conclusions: We report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk, and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.