Comparative prognostic importance of measures of left atrial structure and function in non-ischaemic dilated cardiomyopathy.

AIMS: To compare the association between measures of left atrial (LA) structure and function, derived from cardiovascular magnetic resonance (CMR), with cardiovascular (CV) death or non-fatal heart failure (HF) events in patients with non-ischaemic dilated cardiomyopathy (DCM). METHODS AND RESULTS: CMR studies of 580 prospectively recruited patients with DCM in sinus rhythm (median age 54 [interquartile range 44-64] years, 61% men, median LVEF 42% [30-51%]) were analysed for measures of LA structure (left atrial maximum volume index [LAVImax], left atrial minimum volume index [LAVImin]) and function (left atrial emptying fraction [LAEF], left atrial reservoir strain [LARS], left atrial conduit strain [LACS] and left atrial booster strain [LABS]). Over median follow-up of 7.4 years, 103 patients (18%) met the primary endpoint. Apart from LACS, each measure of LA structure and function was associated with the primary endpoint after adjusting for other important prognostic variables. The addition of each LA metric to a baseline model containing the same important prognostic covariates improved model discrimination, with LAVImin providing the greatest improvement (C-statistic improvement: 0.702 to 0.738; χ2 test comparing likelihood ratio p < 0.0001; categorical net reclassification index: 0.210 (95% CI 0.023-0.392)). Patients in the highest tercile of LAVImin had similar event rates to those with persistent atrial fibrillation. Measures of LA strain did not enhance model discrimination above LA volumetric measures. CONCLUSION: Measure of left atrial structure and function offer important prognostic information in patients with DCM and enhance prediction of adverse outcomes. LA strain was not incremental to volumetric analysis for risk prediction.

Assessing the association between genetic and phenotypic features of dilated cardiomyopathy and outcome in patients with coronary artery disease.

AIMS: To examine the relevance of genetic and cardiovascular magnetic resonance (CMR) features of dilated cardiomyopathy (DCM) in individuals with coronary artery disease (CAD). METHODS AND RESULTS: This study includes two cohorts. First, individuals with CAD recruited into the UK Biobank (UKB) were evaluated. Second, patients with CAD referred to a tertiary centre for evaluation with late gadolinium enhancement (LGE)-CMR were recruited (London cohort); patients underwent genetic sequencing as part of the research protocol and long-term follow-up. From 31 154 individuals with CAD recruited to UKB, rare pathogenic variants in DCM genes were associated with increased risk of death or major adverse cardiac events (hazard ratio 1.57, 95% confidence interval [CI] 1.22-2.01, p < 0.001). Of 1619 individuals with CAD included from the UKB CMR substudy, participants with a rare variant in a DCM-associated gene had lower left ventricular ejection fraction (LVEF) compared to genotype negative individuals (mean 47 ± 10% vs. 57 ± 8%, p < 0.001). Of 453 patients in the London cohort, 63 (14%) had non-infarct pattern LGE (NI-LGE) on CMR. Patients with NI-LGE had lower LVEF (mean 38 ± 18% vs. 48 ± 16%, p < 0.001) compared to patients without NI-LGE, with no significant difference in the burden of rare protein altering variants in DCM-associated genes between groups (9.5% vs. 6.7%, odds ratio 1.5, 95% CI 0.4-4.3, p = 0.4). NI-LGE was not independently associated with adverse clinical outcomes. CONCLUSION: Rare pathogenic variants in DCM-associated genes impact left ventricular remodelling and outcomes in stable CAD. NI-LGE is associated with adverse remodelling but is not an independent predictor of outcome and had no rare genetic basis in our study.

Sex Differences in the Clinical Presentation and Natural History of Dilated Cardiomyopathy.

BACKGROUND: Biological sex has a diverse impact on the cardiovascular system. Its influence on dilated cardiomyopathy (DCM) remains unresolved. OBJECTIVES: This study aims to investigate sex-specific differences in DCM presentation, natural history, and prognostic factors. METHODS: The authors conducted a prospective observational cohort study of DCM patients assessing baseline characteristics, cardiac magnetic resonance imaging, biomarkers, and genotype. The composite outcome was cardiovascular mortality or major heart failure (HF) events. RESULTS: Overall, 206 females and 398 males with DCM were followed for a median of 3.9 years. At baseline, female patients had higher left ventricular ejection fraction, smaller left ventricular volumes, less prevalent mid-wall myocardial fibrosis (23% vs 42%), and lower high-sensitivity cardiac troponin I than males (all P < 0.05) with no difference in time from diagnosis, age at enrollment, N-terminal pro-B-type natriuretic peptide levels, pathogenic DCM genetic variants, myocardial fibrosis extent, or medications used for HF. Despite a more favorable profile, the risk of the primary outcome at 2 years was higher in females than males (8.6% vs 4.4%, adjusted HR: 3.14; 95% CI: 1.55-6.35; P = 0.001). Between 2 and 5 years, the effect of sex as a prognostic modifier attenuated. Age, mid-wall myocardial fibrosis, left ventricular ejection fraction, left atrial volume, N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin I, left bundle branch block, and NYHA functional class were not sex-specific prognostic factors. CONCLUSIONS: The authors identified a novel paradox in prognosis for females with DCM. Female DCM patients have a paradoxical early increase in major HF events despite less prevalent myocardial fibrosis and a milder phenotype at presentation. Future studies should interrogate the mechanistic basis for these sex differences.

Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy.

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.

Your Heart Function Has Normalized-What Next After TRED-HF?

PURPOSE OF REVIEW: With the widespread implementation of contemporary disease-modifying heart failure therapy, the rates of normalization of ejection fraction are continuously increasing. The TRED-HF trial confirmed that heart failure remission rather than complete recovery is typical in patients with dilated cardiomyopathy who respond to therapy. The present review outlines key points related to the management and knowledge gaps of this growing patient group, focusing on patients with non-ischaemic dilated cardiomyopathy. RECENT FINDINGS: There is substantial heterogeneity among patients with normalized ejection fraction. The specific etiology is likely to affect the outcome, although a multiple-hit phenotype is frequent and may not be identified without comprehensive characterization. A monogenic or polygenic genetic susceptibility is common. Ongoing pathophysiological processes may be unraveled with advanced cardiac imaging, biomarkers, multi-omics, and machine learning technologies. There are limited studies that have investigated the withdrawal of specific heart failure therapies in these patients. Diuretics may be safely withdrawn if there is no evidence of congestion, while continued therapy with at least some disease-modifying therapy is likely to be required to reduce myocardial workload and sustain remission for the vast majority. Understanding the underlying disease mechanisms of patients with normalized ejection fraction is crucial in identifying markers of myocardial relapse and guiding individualized therapy in the future. Ongoing clinical trials should inform personalized approaches to therapy.

Phenotype, outcomes and natural history of early-stage non-ischaemic cardiomyopathy.

AIMS: To characterize the phenotype, clinical outcomes and rate of disease progression in patients with early-stage non-ischaemic cardiomyopathy (early-NICM). METHODS AND RESULTS: We conducted a prospective observational cohort study of patients with early-NICM assessed by late gadolinium enhancement cardiovascular magnetic resonance (CMR). Cases were classified into the following subgroups: isolated left ventricular dilatation (early-NICM H-/D+), non-dilated left ventricular cardiomyopathy (early-NICM H+/D-), or early dilated cardiomyopathy (early-NICM H+/D+). Clinical follow-up for major adverse cardiovascular events (MACE) included non-fatal life-threatening arrhythmia, unplanned cardiovascular hospitalization or cardiovascular death. A subset of patients (n = 119) underwent a second CMR to assess changes in cardiac structure and function. Of 254 patients with early-NICM (median age 46 years [interquartile range 36-58], 94 [37%] women, median left ventricular ejection fraction [LVEF] 55% [52-59]), myocardial fibrosis was present in 65 (26%). There was no difference in the prevalence of fibrosis between subgroups (p = 0.90), however fibrosis mass was lowest in early-NICM H-/D+, higher in early-NICM H+/D- and highest in early-NICM H+/D+ (p = 0.03). Over a median follow-up of 7.9 (5.5-10.0) years, 28 patients (11%) experienced MACE. Non-sustained ventricular tachycardia (hazard ratio [HR] 5.1, 95% confidence interval [CI] 2.36-11.00, p < 0.001), myocardial fibrosis (HR 3.77, 95% CI 1.73-8.20, p < 0.001) and diabetes mellitus (HR 5.12, 95% CI 1.73-15.18, p = 0.003) were associated with MACE in a multivariable model. Only 8% of patients progressed from early-NICM to dilated cardiomyopathy with LVEF <50% over a median of 16 (11-34) months. CONCLUSION: Early-NICM is not benign. Fibrosis develops early in the phenotypic course. In-depth characterization enhances risk stratification and might aid clinical management.

Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. We here report results from the largest HCM genome-wide association study (GWAS) and multi-trait analysis (MTAG) including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We identified a total of 70 loci (50 novel) associated with HCM, and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants cause HCM. Mendelian randomization analyses support a causal role of increased LV contractility in both obstructive and non-obstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.

Machine learning analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic events.

Background: Machine learning analysis of complex myocardial scar patterns affords the potential to enhance risk prediction of life-threatening arrhythmia in stable coronary artery disease (CAD). Objective: To assess the utility of computational image analysis, alongside a machine learning (ML) approach, to identify scar microstructure features on late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) that predict major arrhythmic events in patients with CAD. Methods: Patients with stable CAD were prospectively recruited into a CMR registry. Shape-based scar microstructure features characterizing heterogeneous ('peri-infarct') and homogeneous ('core') fibrosis were extracted. An ensemble of machine learning approaches were used for risk stratification, in addition to conventional analysis using Cox modeling. Results: Of 397 patients (mean LVEF 45.4 ± 16.0) followed for a median of 6 years, 55 patients (14%) experienced a major arrhythmic event. When applied within an ML model for binary classification, peri-infarct zone (PIZ) entropy, peri-infarct components and core interface area outperformed a model representative of the current standard of care (LVEF<35% and NYHA>Class I): AUROC (95%CI) 0.81 (0.81-0.82) vs. 0.64 (0.63-0.65), p = 0.002. In multivariate cox regression analysis, these features again remained significant after adjusting for LVEF<35% and NYHA>Class I: PIZ entropy hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.38-2.56, p < 0.001; number of PIZ components HR 1.34, 95% CI 1.08-1.67, p = 0.009; core interface area HR 1.6, 95% CI 1.29-1.99, p = <0.001. Conclusion: Machine learning models using LGE-CMR scar microstructure improved arrhythmic risk stratification as compared to guideline-based clinical parameters; highlighting a potential novel approach to identifying candidates for implantable cardioverter defibrillators in stable CAD.

Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease.

BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD). OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD). METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD. RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models. CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

Assessment of left ventricular tissue mitochondrial bioenergetics in patients with stable coronary artery disease.

Recurrent myocardial ischemia can lead to left ventricular (LV) dysfunction in patients with coronary artery disease (CAD). In this observational cohort study, we assessed for chronic metabolomic and transcriptomic adaptations within LV myocardium of patients undergoing coronary artery bypass grafting. During surgery, paired transmural LV biopsies were acquired on the beating heart from regions with and without evidence of inducible ischemia on preoperative stress perfusion cardiovascular magnetic resonance. From 33 patients, 63 biopsies were acquired, compared to analysis of LV samples from 11 donor hearts. The global myocardial adenosine triphosphate (ATP):adenosine diphosphate (ADP) ratio was reduced in patients with CAD as compared to donor LV tissue, with increased expression of oxidative phosphorylation (OXPHOS) genes encoding the electron transport chain complexes across multiple cell types. Paired analyses of biopsies obtained from LV segments with or without inducible ischemia revealed no significant difference in the ATP:ADP ratio, broader metabolic profile or expression of ventricular cardiomyocyte genes implicated in OXPHOS. Differential metabolite analysis suggested dysregulation of several intermediates in patients with reduced LV ejection fraction, including succinate. Overall, our results suggest that viable myocardium in patients with stable CAD has global alterations in bioenergetic and transcriptional profile without large regional differences between areas with or without inducible ischemia.

Precision therapy in dilated cardiomyopathy: Pipedream or paradigm shift?

Precision medicine for cardiomyopathies holds great promise to improve patient outcomes costs by shifting the focus to patient-specific treatment decisions, maximising the use of therapies most likely to lead to benefit and minimising unnecessary intervention. Dilated cardiomyopathy (DCM), characterised by left ventricular dilatation and impairment, is a major cause of heart failure globally. Advances in genomic medicine have increased our understanding of the genetic architecture of DCM. Understanding the functional implications of genetic variation to reveal genotype-specific disease mechanisms is the subject of intense investigation, with advanced cardiac imaging and mutliomics approaches playing important roles. This may lead to increasing use of novel, targeted therapy. Individualised treatment and risk stratification is however made more complex by the modifying effects of common genetic variation and acquired environmental factors that help explain the variable expressivity of rare genetic variants and gene elusive disease. The next frontier must be expanding work into early disease to understand the mechanisms that drive disease expression, so that the focus can be placed on disease prevention rather than management of later symptomatic disease. Overcoming these challenges holds the key to enabling a paradigm shift in care from the management of symptomatic heart failure to prevention of disease.

The addition of genetic testing and cardiovascular magnetic resonance to routine clinical data for stratification of etiology in dilated cardiomyopathy.

Background: Guidelines recommend genetic testing and cardiovascular magnetic resonance (CMR) for the investigation of dilated cardiomyopathy (DCM). However, the incremental value is unclear. We assessed the impact of these investigations in determining etiology. Methods: Sixty consecutive patients referred with DCM and recruited to our hospital biobank were selected. Six independent experts determined the etiology of each phenotype in a step-wise manner based on (1) routine clinical data, (2) clinical and genetic data and (3) clinical, genetic and CMR data. They indicated their confidence (1-3) in the classification and any changes to management at each step. Results: Six physicians adjudicated 60 cases. The addition of genetics and CMR resulted in 57 (15.8%) and 26 (7.2%) changes in the classification of etiology, including an increased number of genetic diagnoses and a reduction in idiopathic diagnoses. Diagnostic confidence improved at each step (p < 0.0005). The number of diagnoses made with low confidence reduced from 105 (29.2%) with routine clinical data to 71 (19.7%) following the addition of genetics and 37 (10.3%) with the addition of CMR. The addition of genetics and CMR led to 101 (28.1%) and 112 (31.1%) proposed changes to management, respectively. Interobserver variability showed moderate agreement with clinical data (κ = 0.44) which improved following the addition of genetics (κ = 0.65) and CMR (κ = 0.68). Conclusion: We demonstrate that genetics and CMR, frequently changed the classification of etiology in DCM, improved confidence and interobserver variability in determining the diagnosis and had an impact on proposed management.

Genetic Architecture of Acute Myocarditis and the Overlap With Inherited Cardiomyopathy.

BACKGROUND: Acute myocarditis is an inflammatory condition that may herald the onset of dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM). We investigated the frequency and clinical consequences of DCM and ACM genetic variants in a population-based cohort of patients with acute myocarditis. METHODS: This was a population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterized cardiomyopathy-associated genes with comparison to healthy controls (n=1053) sequenced on the same platform. Case ascertainment in England was assessed against national hospital admission data. The primary outcome was all-cause mortality. RESULTS: Variants that would be considered pathogenic if found in a patient with DCM or ACM were identified in 8% of myocarditis cases compared with <1% of healthy controls (P=0.0097). In the London cohort (n=230; median age, 33 years; 84% men), patients were representative of national myocarditis admissions (median age, 32 years; 71% men; 66% case ascertainment), and there was enrichment of rare truncating variants (tv) in ACM-associated genes (3.1% of cases versus 0.4% of controls; odds ratio, 8.2; P=0.001). This was driven predominantly by DSP-tv in patients with normal LV ejection fraction and ventricular arrhythmia. In Maastricht (n=106; median age, 54 years; 61% men), there was enrichment of rare truncating variants in DCM-associated genes, particularly TTN-tv, found in 7% (all with left ventricular ejection fraction <50%) compared with 1% in controls (odds ratio, 3.6; P=0.0116). Across both cohorts over a median of 5.0 years (interquartile range, 3.9-7.8 years), all-cause mortality was 5.4%. Two-thirds of deaths were cardiovascular, attributable to worsening heart failure (92%) or sudden cardiac death (8%). The 5-year mortality risk was 3.3% in genotype-negative patients versus 11.1% for genotype-positive patients (Padjusted=0.08). CONCLUSIONS: We identified DCM- or ACM-associated genetic variants in 8% of patients with acute myocarditis. This was dominated by the identification of DSP-tv in those with normal left ventricular ejection fraction and TTN-tv in those with reduced left ventricular ejection fraction. Despite differences between cohorts, these variants have clinical implications for treatment, risk stratification, and family screening. Genetic counseling and testing should be considered in patients with acute myocarditis to help reassure the majority while improving the management of those with an underlying genetic variant.

State of the art: multimodality imaging in dilated cardiomyopathy.

Dilated cardiomyopathy represents a common phenotype expressed in individuals with a family of overlapping myocardial diseases due to acquired and/or genetic susceptibility. Disease trajectory, response to therapy and outcomes vary widely; therefore, further refinement of the diagnosis can help guide therapy and inform prognosis. Multimodality imaging plays a key role in this process, as well as excluding alternative causes which may mimic a primary myocardial disease. The following article discusses the role of different imaging modalities as well as what the future may look like in the context of recent research innovations.

Maintaining Success for Patients With Dilated Cardiomyopathy and Remission of Heart Failure.

Remission of heart failure, defined by resolution of symptoms, normalization of left ventricular ejection fraction, and plasma concentrations of natriuretic peptides and by the ability to withdraw diuretic agents without recurrence of congestion is increasingly recognized among patients with dilated cardiomyopathy. Once remission has been achieved, it is unclear which treatments need to be continued long term. The durability of remission and likelihood of relapse are likely to be determined by intrinsic myocardial susceptibility, the persistence or recurrence of any acquired triggers, and current and future myocardial workload. Each of these should be addressed to enable personalized therapy to delay or prevent relapse. Management should be informed by evidence from randomized trials of targeted therapeutic strategies.

Precision Phenotyping of Dilated Cardiomyopathy Using Multidimensional Data.

BACKGROUND: Dilated cardiomyopathy (DCM) is a final common manifestation of heterogenous etiologies. Adverse outcomes highlight the need for disease stratification beyond ejection fraction. OBJECTIVES: The purpose of this study was to identify novel, reproducible subphenotypes of DCM using multiparametric data for improved patient stratification. METHODS: Longitudinal, observational UK-derivation (n = 426; median age 54 years; 67% men) and Dutch-validation (n = 239; median age 56 years; 64% men) cohorts of DCM patients (enrolled 2009-2016) with clinical, genetic, cardiovascular magnetic resonance, and proteomic assessments. Machine learning with profile regression identified novel disease subtypes. Penalized multinomial logistic regression was used for validation. Nested Cox models compared novel groupings to conventional risk measures. Primary composite outcome was cardiovascular death, heart failure, or arrhythmia events (median follow-up 4 years). RESULTS: In total, 3 novel DCM subtypes were identified: profibrotic metabolic, mild nonfibrotic, and biventricular impairment. Prognosis differed between subtypes in both the derivation (P < 0.0001) and validation cohorts. The novel profibrotic metabolic subtype had more diabetes, universal myocardial fibrosis, preserved right ventricular function, and elevated creatinine. For clinical application, 5 variables were sufficient for classification (left and right ventricular end-systolic volumes, left atrial volume, myocardial fibrosis, and creatinine). Adding the novel DCM subtype improved the C-statistic from 0.60 to 0.76. Interleukin-4 receptor-alpha was identified as a novel prognostic biomarker in derivation (HR: 3.6; 95% CI: 1.9-6.5; P = 0.00002) and validation cohorts (HR: 1.94; 95% CI: 1.3-2.8; P = 0.00005). CONCLUSIONS: Three reproducible, mechanistically distinct DCM subtypes were identified using widely available clinical and biological data, adding prognostic value to traditional risk models. They may improve patient selection for novel interventions, thereby enabling precision medicine.