Circulation: Genomic and Precision Medicine最新文献

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.

Background: Patients with de novo chest pain, referred for evaluation of possible coronary artery disease (CAD), frequently have an absence of CAD resulting in millions of tests not having any clinical impact. The objective of this study was to investigate whether polygenic risk scores and targeted proteomics improve the prediction of absence of CAD in patients with suspected CAD, when added to the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS).

Methods: Genotyping and targeted plasma proteomics (N=368 proteins) were performed in 1440 patients with symptoms suspected to be caused by CAD undergoing coronary computed tomography angiography. Based on individual genotypes, a polygenic risk score for CAD (PRS_CAD) was calculated. The prediction was performed using combinations of PRS_CAD, proteins, and PMRS as features in models using stability selection and machine learning.

Results: Prediction of absence of CAD yielded an area under the curve of PRS_CAD-model, 0.64±0.03; proteomic-model, 0.58±0.03; and PMRS model, 0.76±0.02. No significant correlation was found between the genetic and proteomic risk scores (Pearson correlation coefficient, -0.04; P=0.13). Optimal predictive ability was achieved by the full model (PRS_CAD+protein+PMRS) yielding an area under the curve of 0.80±0.02 for absence of CAD, significantly better than the PMRS model alone (P<0.001). For reclassification purpose, the full model enabled down-classification of 49% (324 of 661) of the 5% to 15% pretest probability patients and 18% (113 of 611) of >15% pretest probability patients.

Conclusions: For patients with chest pain and low-intermediate CAD risk, incorporating targeted proteomics and polygenic risk scores into the risk assessment substantially improved the ability to predict the absence of CAD. Genetics and proteomics seem to add complementary information to the clinical risk factors and improve risk stratification in this large patient group.

Registration: URL: https://www.

Clinicaltrials: gov; Unique identifier: NCT02264717.

Background: Rapid genome sequencing (rGS) has been shown to improve care of critically ill infants. Congenital heart disease (CHD) is a leading cause of infant mortality and is often caused by genetic disorders, yet the utility of rGS has not been prospectively studied in this population.

Methods: We conducted a prospective evaluation of rGS to improve the care of infants with complex CHD in our cardiac neonatal intensive care unit.

Results: In a cohort of 48 infants with complex CHD, rGS diagnosed 14 genetic disorders in 13 (27%) individuals and led to changes in clinical management in 8 (62%) cases with diagnostic results. These included 2 cases in whom genetic diagnoses helped avert intensive, futile interventions before cardiac neonatal intensive care unit discharge, and 3 cases in whom eye disease was diagnosed and treated in early childhood.

Conclusions: Our study provides the first prospective evaluation of rGS for infants with complex CHD to our knowledge. We found that rGS diagnosed genetic disorders in 27% of cases and led to changes in management in 62% of cases with diagnostic results. Our model of care depended on coordination between neonatologists, cardiologists, surgeons, geneticists, and genetic counselors. These findings highlight the important role of rGS in CHD and demonstrate the need for expanded study of how to implement this resource to a broader population of infants with CHD.

Background: Variants in RBM20 are reported in 2% to 6% of familial cases of dilated cardiomyopathy and may be associated with fatal ventricular arrhythmia and rapid heart failure progression. We sought to determine the risk of adverse events in RBM20 variant carriers and the impact of sex on outcomes.

Methods: Consecutive probands and relatives carrying RBM20 variants were retrospectively recruited from 12 cardiomyopathy units. The primary end point was a composite of malignant ventricular arrhythmia (MVA) and end-stage heart failure (ESHF). MVA and ESHF end points were also analyzed separately and men and women compared. Left ventricular ejection fraction (LVEF) contemporary to MVA was examined. RBM20 variant carriers with left ventricular systolic dysfunction (RBM20_LVSD) were compared with variant-elusive patients with idiopathic left ventricular systolic dysfunction.

Results: Longitudinal follow-up data were available for 143 RBM20 variant carriers (71 men; median age, 35.5 years); 7 of 143 had an MVA event at baseline. Thirty of 136 without baseline MVA (22.0%) reached the primary end point, and 16 of 136 (11.8%) had new MVA with no significant difference between men and women (log-rank P=0.07 and P=0.98, respectively). Twenty of 143 (14.0%) developed ESHF (17 men and 3 women; log-rank P<0.001). Four of 10 variant carriers with available LVEF contemporary to MVA had an LVEF >35%. At 5 years, 15 of 67 (22.4%) RBM20_LVSD versus 7 of 197 (3.6%) patients with idiopathic left ventricular systolic dysfunction had reached the primary end point (log-rank P<0.001). RBM20 variant carriage conferred a 6.0-fold increase in risk of the primary end point.

Conclusions: RBM20 variants are associated with a high risk of MVA and ESHF compared with idiopathic left ventricular systolic dysfunction. The risk of MVA in male and female RBM20 variant carriers is similar, but male sex is strongly associated with ESHF.