Genotypic-based classification of cardiomyopathies (CMPs) shows a higher precision in predicting patient outcomes than phenotype-based classification, according to an analysis of new registry data. The study, published online Monday and in the Nov. 22 issue of Journal of the American College of Cardiology, noted that CMPs are a heterogeneous group of primary heart diseases characterized by structural and electrical abnormalities that are frequently associated with mutations in disease-related genes. The team, led by Alessia Paldino, MD, and Matteo Dal Ferro, MD, from the University of Trieste, Italy – a member of the European Reference Network for rare, low-prevalence, or complex diseases of the Heart (ERN GUARD-Heart) – noted that currently, CMPs are classified clinically based on observed phenotypic expression as hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), arrhythmogenic right ventricle cardiomyopathy (ARVC), restrictive cardiomyopathy, and other rare forms – each with specific guidelines for treatment. “In the last few years, however, a deeper understanding of the clinical characteristics of these conditions has revealed a more complex scenario,” said the team, noting that although HCM represents a distinct disease in terms of pathophysiology, therapeutic treatment, and prognostic assessment, DCM and ARVC frequently present overlapping aspects that challenge the conventional classification. This has led to the proposal of a single definition of arrhythmogenic cardiomyopathy (ACM), which incorporates ARVC, left-dominant arrhythmogenic cardiomyopathy (ALVC), and biventricular ACM (BiV), noted Paldino, Dal Ferro, and colleagues. “Next-generation sequencing technologies allow the identification of the underlying causative monogenic variant in approximately 30% to 45% of cases of DCM and ACM,” they added, noting that the correlation between genetic mutations and disease expression is helpful for early diagnosis, improving survival, and reducing morbidity. “We sought to define differences in outcome prediction when stratifying patients based on phenotype at presentation compared with genotype in a large cohort of patients with CMPs and positive genetic testing,” they said. Study setup Using data from the Familial Cardiomyopathy Registry – a multicenter registry between the University of Trieste, Italy, and University of Colorado, Aurora –Paldino, Dal Ferro and colleagues compared the effectiveness of genotype-based versus phenotype-based classification at diagnosis for prediction of clinical outcomes. In the selected period, a total of 834 patients affected by DCM (n = 690; 83%), ARVC (n = 70; 8%), and ALVC/BiV (n = 74; 9%) were subjected to genetic testing. Of those patients, 315 (38%) were carriers of P/LP variants, including 253 DCM (DCM genetic yield: 37%), 30 ARVC (ARVC genetic yield: 43%), and 32 ALVC/BiV (ALVC/BiV genetic yield: 43%). Meanwhile, a total of nine genes (PLN, BAG3, RMB20, SCN5A, DMD, DES, DSG2, DSC2, and NEXN), counting <7 carriers each, were excluded from further analysis, giving a final study population of 281 patients (218 probands [78%]; 63 affected relatives [22%] belonging to 33 families). Median age at enrollment was 42 years (interquartile range [IQR]: 31-52 years), and 70% of the patients were men. The phenotypic distribution at presentation was characterized predominantly by DCM (n = 224; 80%), followed by ARVC (n = 28; 10%) and ALVC/BiV (n = 29; 10%). The team collated demographic and clinical data, including heart failure (HF) symptoms (New York Heart Association functional class), previous myocardial injury events, and competitive sport activity levels, were collected at the baseline evaluation. The primary outcome of the analysis was declared as all-cause mortality (D) and heart transplantation (HT), while secondary outcome included sudden cardiac death (SCD), major ventricular arrhythmias (MVA), heart failure–related death (DHF), HF, and left ventricular assist device (LVAD). Key findings Over a median follow-up of 118 months (IQR: 50-188 months), 46 D/HT, 23 DHF/HT/LVAD, and 62 SCD/MVA events were recorded, revealed Paldino, Dal Ferro and colleagues, noting that each phenotype was associated with multiple causative genes. “Survival analysis revealed that SCD/MVA events occurred more frequently in patients without a DCM phenotype and in carriers of DSP, PKP2, LMNA, and FLNC variants,” they reported. “However, after adjustment for age and sex, genotype-based classification, but not phenotype-based classification, was predictive of SCD/MVA.” Analysis found that patients with DCM phenotype showed more prominent LV dilatation and LV systolic dysfunction (left ventricular ejection fraction ≤ 35%) (ARVC, n = 0; ALVC/BiV, n = 0; DCM, n = 138 [62%]; P < 0.001), more frequently with left bundle branch block (LBBB) (ARVC, n = 0; ALVC/BiV, n = 0; DCM, n = 38 [17%]; P < 0.001), and were more likely to have moderate-severe mitral regurgitation (ARVC, n = 2 [7%]; ALVC/BiV, n = 3 [10%]; DCM, n = 46 [20%]; P < 0.001). Meanwhile, patients with ARVC and ALVC/BiV had a family history of SCD (ARVC, n = 11 [39%]; ALVC/BiV, n = 14 [48%]; DCM, n = 46 [20%]; P = 0.006), reported engaging in competitive sports (ARVC n = 7 [25%]; ALVC/BiV n = 7 [24%]; DCM n = 5 [2%]; P < 0.001), or had right ventricular dysfunction (ARVC, n = 12 [43%]; ALVC/BiV, n = 12 [41%]; DCM, n = 36 [16%]; P < 0.001). When analyzed by genotype, Paldino, Dal Ferro and colleagues reported that the six gene groups differed with respect to D/HT (D/HT: LMNA n = 11 [41%]; DSP n = 6 [23%]; PKP2 n = 3 [10%]; FLNC n = 6 [18%]; SARC n = 9 [15%]; TTN n = 11 [12%]; P = 0.04) and SCD/MVA outcomes (SCD/MVA: LMNA n = 9 [33%]; DSP n = 8 [31%]; PKP2 n = 10 [33%]; FLNC n = 11 [33%]; SARC n = 8 [13%]; TTN n = 16 [18%]; P = 0.023), whereas no significant differences were observed in the risk of DHT/HT/LVAD. They added that LMNA carriers were at the highest risk of developing D/HT and DHF/HT/LVAD, while carriers of DSP, PKP2, FLNC, and LMNA showed a higher and more comparable number of SCD/MVA events: “These 4 genes, if grouped together (‘arrhythmic genes’), were associated with a significantly higher risk of D/HT (P = 0.031) and SCD/MVA (P < 0.001) compared with TTN and SARC variants,” said Paldino, Dal Ferro and colleagues. “In patients with genetically determined, monogenic, nonhypertrophic cardiomyopathy, genotype-based classification improves risk stratification compared with phenotypic characteristics alone,” they added, noting that data from the study also showed that the LMNA, FLNC, DSP, and PKP2 genotypes are associated with a high risk of arrhythmic events regardless of the severity of LV dysfunction, whereas the LMNA genotype is associated with the highest risk of nonarrhythmic adverse events. “The pathogenic mechanisms mediating the associations between specific genotypes with adverse outcomes in patients with cardiomyopathies requires further investigation,” they concluded. Novel prognostic value? Writing in an accompanying editorial comment, Cynthia A. James, PhD, CGC, and Alessio Gasperetti, MD, from the Johns Hopkins School of Medicine, Baltimore, noted that while genetic testing has historically been used after a clinical diagnosis – with genotype testing used for family screening – it has been less often used for diagnostic confirmation or management. “However, in recent years, overlapping characteristics among different CMP phenotypes, patient evolution among CMP classifications with disease progression, as well as the fulfillment of different phenotypes in patients harboring variants in the same gene have been increasingly recognized,” they said. The editorialists noted that although the genotype to phenotype observations are “useful,” the main novelty of the study is its “ambitious goal” of defining the relative prognostic weight of phenotype-based vs genotype-based classification. “The authors showed clinically meaningful differences in arrhythmic outcomes, mortality, and heart transplantation rates across the 6 gene groups,” they said, noting that “as expected,” LMNA carriers were more prone to death/transplant and HF-associated outcomes, whereas DSP, PKP2, FLNC, and LMNA (combined in the paper as “arrhythmic genes”) were associated with MVAs. “We found it particularly interesting that the incidence of arrhythmic events in patients with DSP, LMNA, and FLNC variants were similar, regardless of clinical diagnosis, given the dearth of data on these genotypes.” “As is the case for some of the best clinical research, their findings both have immediate implications for clinical care and also suggest additional lines of research—in this case the potential for genotype-specific risk prediction,” they noted, adding that in the era of precision medicine, the new data pave the way to providing answers on how to best integrate genotype and phenotype in the management of familial cardiomyopathies. Sources: Paldino A, Dal Ferro M, Stolfo D, et al. Prognostic Prediction of Genotype vs Phenotype in Genetic Cardiomyopathies. J Am Coll Cardiol 2022;80:1981-1994. James CA, Gasperetti A. Genotype-Based Risk Stratification Can Outperform Phenotype-Based Practice for Inherited Cardiomyopathies: Not All Paths Are Equal. J Am Coll Cardiol 2022;80:1995-1997. Image Credit: tashatuvango – stock.adobe.com