Circulation: Genomic and Precision Medicine最新文献

Background: Less than 40% of patients with dilated cardiomyopathy (DCM) have a pathogenic/likely pathogenic genetic variant identified. TBX20 has been linked to congenital heart defects; although an association with left ventricular noncompaction (LVNC) and DCM has been proposed, it is still considered a gene with limited evidence for these phenotypes. This study sought to investigate the association between the TBX20 truncating variant (TBX20tv) and DCM/LVNC.

Methods: TBX20 was sequenced by next-generation sequencing in 7463 unrelated probands with a diagnosis of DCM or LVNC, 22 773 probands of an internal comparison group (hypertrophic cardiomyopathy, channelopathies, or aortic diseases), and 124 098 external controls (individuals from the gnomAD database). Enrichment of TBX20tv in DCM/LVNC was calculated, cosegregation was determined in selected families, and clinical characteristics and outcomes were analyzed in carriers.

Results: TBX20tv was enriched in DCM/LVNC (24/7463; 0.32%) compared with internal (1/22 773; 0.004%) and external comparison groups (4/124 098; 0.003%), with odds ratios of 73.23 (95% CI, 9.90-541.45; P<0.0001) and 99.76 (95% CI, 34.60-287.62; P<0.0001), respectively. TBX20tv was cosegregated with DCM/LVNC phenotype in 21 families for a combined logarythm of the odds score of 4.53 (strong linkage). Among 57 individuals with TBX20tv (49.1% men; mean age, 35.9±20.8 years), 41 (71.9%) exhibited DCM/LVNC, of whom 14 (34.1%) had also congenital heart defects. After a median follow-up of 6.9 (95% CI, 25-75:3.6-14.5) years, 9.7% of patients with DCM/LVNC had end-stage heart failure events and 4.8% experienced malignant ventricular arrhythmias.

Conclusions: TBX20tv is associated with DCM/LVNC; congenital heart defect is also present in around one-third of cases. TBX20tv-associated DCM/LVNC is characterized by a nonaggressive phenotype, with a low incidence of major cardiovascular events. TBX20 should be considered a definitive gene for DCM and LVNC and routinely included in genetic testing panels for these phenotypes.

Background: Pathogenic autosomal-dominant missense variants in MYH7 (myosin heavy chain 7), which encodes the sarcomeric protein (β-MHC [beta myosin heavy chain]) expressed in cardiac and skeletal myocytes, are a leading cause of hypertrophic cardiomyopathy and are clinically actionable. However, ≈75% of MYH7 missense variants are of unknown significance. While human-induced pluripotent stem cells (hiPSCs) can be differentiated into cardiomyocytes to enable the interrogation of MYH7 variant effect in a disease-relevant context, deep mutational scanning has not been executed using diploid hiPSC derivates due to low hiPSC gene-editing efficiency. Moreover, multiplexable phenotypes enabling deep mutational scanning of MYH7 variant hiPSC-derived cardiomyocytes are unknown.

Methods: To overcome these obstacles, we used CRISPRa On-Target Editing Retrieval enrichment to generate an hiPSC library containing 113 MYH7 codon variants suitable for deep mutational scanning. We first established that β-MHC protein loss occurs in a hypertrophic cardiomyopathy human heart with a pathogenic MYH7 variant. We then differentiated the MYH7 missense variant hiPSC library to cardiomyocytes for multiplexed assessment of β-MHC variant abundance by massively parallel sequencing and hiPSC-derived cardiomyocyte survival.

Results: Both the multiplexed assessment of β-MHC abundance and hiPSC-derived cardiomyocyte survival accurately segregated all known pathogenic variants from synonymous variants. Functional data were generated for 4 variants of unknown significance and 58 additional MYH7 missense variants not yet detected in patients.

Conclusions: This study leveraged hiPSC differentiation into disease-relevant cardiomyocytes to enable multiplexed assessments of MYH7 missense variants for the first time. Phenotyping strategies used here enable the application of deep mutational scanning to clinically actionable genes, which should reduce the burden of variants of unknown significance on patients and clinicians.

Background: Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure.

Methods: Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed.

Results: The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%-51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9-2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3-1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno's C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP.

Conclusions: This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.

Background: To realize the potential of genome engineering therapeutics, tractable strategies must be identified that balance personalized therapy with the need for off-the-shelf availability. We hypothesized that regional clustering of pathogenic variants can inform the design of rational prime editing therapeutics to treat the majority of genetic cardiovascular diseases with a limited number of reagents.

Methods: We collated 2435 high-confidence pathogenic/likely pathogenic (P/LP) variants in 82 cardiovascular disease genes from ClinVar. We assessed the regional density of these variants by defining a regional clustering index. We then combined a highly active base editor with prime editing to demonstrate the feasibility of a P/LP hotspot-directed genome engineering therapeutic strategy in vitro.

Results: P/LP variants in cardiovascular disease genes display higher regional density than rare variants found in the general population. P/LP missense variants displayed higher average regional density than P/LP truncating variants. Following hypermutagenesis at a pathogenic hotspot, mean prime editing efficiency across introduced variants was 57±27%.

Conclusions: Designing therapeutics that target pathogenic hotspots will not only address known missense P/LP variants but also novel P/LP variants identified in these hotspots as well. Moreover, the clustering of P/LP missense rather than truncating variants in these hotspots suggests that prime editing technology is particularly valuable for dominant negative disease. Although prime editing technology in relation to cardiac health continues to improve, this study presents an approach to targeting the most impactful regions of the genome for inherited cardiovascular disease.

Dilated cardiomyopathy (DCM) is a common heart muscle disorder of nonischemic etiology associated with heart failure development and the risk of malignant ventricular arrhythmias and sudden cardiac death. A tailored approach to risk stratification and prevention of sudden cardiac death is required in genetic DCM given its variable presentation and phenotypic severity. Currently, advances in cardiogenetics have shed light on disease mechanisms, the complex genetic architecture of DCM, polygenic contributors to disease susceptibility and the role of environmental triggers. Parallel advances in imaging have also enhanced disease recognition and the identification of the wide spectrum of phenotypes falling under the DCM umbrella. Genotype-phenotype associations have been also established for specific subtypes of DCM, such as DSP (desmoplakin) or FLNC (filamin-C) cardiomyopathy but overall, they remain elusive and not readily identifiable. Also, despite the accumulated knowledge on disease mechanisms, certain aspects remain still unclear, such as which patients with DCM are at risk for disease progression or remission after treatment. Imagenetics, that is, the combination of imaging and genetics, is expected to further advance research in the field and contribute to precision medicine in DCM management and treatment. In the present article, we review the existing literature in the field, summarize the established knowledge and emerging data on the value of genetics and imaging in establishing genotype-phenotype associations in DCM and in clinical decision making for DCM patients.