Common variant rs7597774 in ADD2 is associated with dilated cardiomyopathy in Chinese Han population

Abstract

Two polymorphisms, rs7597774 and rs1739843 in ADD2 and HSPB7 respectively, were found to be associated with dilated cardiomyopathy (DCM) in European cohorts but the results were not validated in the Chinese Han population. We aimed to test the association of the two variants with DCM in a cohort of Chinese Han population. DCM (399) and control (1384) individuals were identified from the GeneID database in China, and DNA was isolated from peripheral blood lymphocytes for genotyping. Alleles were amplified by PCR, and amplicons harboring polymorphisms rs1739843 and rs7597774 were directly genotyped using high-resolution melting analysis. Statistical analysis was subsequently performed to evaluate the association of the variants with DCM. Allelic analysis demonstrated that rs7597774 was significantly related to DCM (P _-adj = 0.0157), and an increased risk of DCM was specifically associated with the minor allele A (OR = 1.582). High-grade cardiac dysfunction (NYHA III/IV) was a clinical parameter significantly associated with the rs7597774 genotypes AA + AC relative to genotype CC (P = 0.021). Furthermore, DCM patients with the rs7597774 genotype AA tended to undergo more invasive medical interventions than those with the genotype CC (P = 0.008). No association was detected between rs1739843 and DCM under any allelic (P _-adj = 0.407, OR = 0.920) or genotypic model. In the Chinese Han population, rs7597774 but not rs1739843 was found to be associated with DCM. This study is the first to demonstrate that underlying genotypes of rs7597774 may assist in assessing the heart functional status of DCM patients and also in the prediction of the benefit of particular therapies for these patients.

Introduction

Dilated cardiomyopathy (DCM) is a heterogeneous heart disease with variable aetiological and clinical features. The disease is characterized by ventricular chamber enlargement and systolic dysfunction that ultimately result in sudden cardiac death or progressive heart failure with the eventual consequence of cardiac transplantation [1-4]. The pathophysiology of DCM is multifactorial with a possible implication of environmental factors and the existence of a strong genetic component as demonstrated by a high rate of familial aggregation [5]. To date, approximately 33 genes have been identified in monogenic forms of DCM, with most of them encoding cytoskeletal, sarcomeric, and regulatory proteins, or ion channels [6].

A recent genome wide association study (GWAS) revealed that two polymorphisms, ADD2 rs7597774 (adducin 2) and HSPB7 rs1739843 (heat-shock 27 kDa protein family, member 7), were associated with DCM in European populations [7]. In a second GWAS, however, HSPB7 rs1739843 was not found to be associated with sporadic DCM in various western populations [8]. Furthermore, no relationship between the HSPB7 single nucleotide polymorphisms (SNPs) and genetic susceptibility to idiopathic DCM was found in a small Chinese Han cohort [9]. An association between ADD2 rs7597774 and DCM, however, has not yet been examined in a population of non-European ancestry.

To further investigate the role of rs7597774 and rs1739843 in DCM, allelic and genotypic association analyses were performed on DNA samples from an independent case-control DCM cohort with a total of 1783 Chinese Han subjects from central and northeastern China. Specific clinical features of DCM patients were also included in the analyses in order to potentially reveal associations with the functional consequences of the disease and to provide a molecular basis for the selection of treatment options.

Materials and methods

Ethics statement

All protocols performed in this study were approved by the Ethics Committee of First Affiliated Hospital of Dalian Medical University and Huazhong University of Science and Technology. Written informed consent was obtained from all subjects participating in the study. The study conformed to the principles outlined in the Declaration of Helsinki.

Study subjects

All subjects were selected from GeneID, which is an ongoing Chinese population database. DNA samples and clinical information are collected from individuals with cardiovascular and cerebrovascular diseases national wide in an effort to identify susceptibility loci related to these diseases [10].

The study subjects were from central and northeastern China and were ethnic Chinese Han by self-description. The criteria for a diagnosis of DCM were in accordance with the guidelines established by the America Heart Association in 2006. Patients with known causes such as acute viral myocarditis, coronary artery disease, valvular disease, congenital heart defects and a positive family history of DCM were excluded. The controls were individuals without DCM as determined by echocardiography or medical history at the time of enrollment, and who underwent annual physical exams with/without any diseases.

Clinical characteristics

The clinical data included age, gender, hypertension, type 2 diabetes mellitus (T2DM), and left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD), and left atrial diameter (LAD) of echocardiographic parameters in both groups. New York Heart Association (NYHA) heart functional classification, therapeutic regimens, and serum brain natriuretic peptide (BNP) concentrations were also obtained from medical records for DCM patients. Hypertension was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. The criteria set by the American Diabetes Association was applied for a diagnosis of T2DM [11]. Serum BNP levels were determined using a high-sensitivity enzyme-linked immunosorbent assay kit (R & D Systems; Minneapolis, MN, USA).

SNP genotyping

Genomic DNA was isolated from peripheral blood lymphocytes with the TIANamp Blood DNA Kit (TiangenBiotect; Beijing, China) according to the manufacturer’s protocols. PCR was performed in a 25 μL final volume containing 1.5 mM Mg²⁺, 0.2 mM dNTPs, 0.5 μM each primer (rs1739843: forward, 5’-ACC CGC ATC CGC CCC CCT ATA G-3’, reverse, 5’-GGG GGT GGG GCT TGA GGG TG-3’; rs7597774: forward, 5’-AGC CCT GTC CAG CCC TGA G-3’, reverse, 5’-TTG GGC ACT GAG GCA CCT G-3’), 25 ng of human genomic DNA template, 5 μM SYTO9 green fluorescent intercalating agent, and 0.15 U of Taq DNA polymerase. PCR was performed on an ABI 9700 System (Life Technologies; Grand Island, NY, USA) with the following thermal profile: 95°C for 5 min; 40 cycles of 95°C for 10 s, corresponding annealing temperature (57.4°C for rs1739843, 60.3°C for rs7597774) for 10 s, and 72°C for 15 s; and a final cycle of 72°C for 10 min. PCR amplicons were directly genotyped using high-resolution melting analysis (HRM) on the Rotor-Gene 6000 System (Corbett Life Science, Australia) under standard protocols with minor modifications [12]. During each run of HRM, three positive control DNA samples with known genotypes (TT, CT, and CC for rs1739843; and AA, AC, and CC for rs7597774), as well as a negative control without DNA template were included. To validate the accuracy of HRM genotyping data, ten samples for each genotype of both SNPs were randomly selected for Sanger sequencing. Primers for sequencing the SNPs were the following: rs1739843: forward, 5’-TCC CCA CCT ACC CGC ATC C-3’ and reverse, 5’-GCC CCC TCA CTG CCT CTC TT-3’ for; rs7597774: forward, 5’-CGG CCT GTG TCT CTG CGT TT-3’ and reverse 5’-TTG GGC ACT GAG GCA CCT G-3’. All sequencing results were consistent with the genotypes as determined by HRM analysis.

Statistical analysis

Statistical power analysis of study populations was conducted with the program PS (Power and Sample size Calculations, version 3.0.43). Hardy-Weinberg linkage equilibrium was tested in the control group with PLINK, version 1.07 [13].

Pearson’s chi-squared (χ²) and unpaired student’s t tests were performed with SPSS version 22.0 software (IBM Inc.; Armonk, NY, USA) for categorical traits (gender, hypertension, T2DM, NYHA heart functional classification, and therapeutic regimens) and continuous traits (age, LVEF, LVEDD, LAD, and BNP levels), respectively. For allelic association analysis, 2 × 2 contingency tables assessed by Pearson’s chi-squared (χ²) test were used to compare differences in the frequencies of the rs1739843 and rs7597774 minor alleles between the case and control groups. Odds ratios (ORs) and corresponding 95% confidential intervals (95% CI) were also calculated. Genotypic association analysis under three genetic models (dominant, recessive, and additive) was performed using 2 × 3 contingency tables assessed by Pearson’s chi-squared (χ²) test. Multiple logistic regression analysis was used to adjust covariates such as sex, age, hypertension, T2DM. When the case-control samples were divided into several subgroups, basic statistical methods were applied as described.

For the association between age, LVEF, LVEDD, LAD, BNP levels and rs7597774, One-Way analysis of variance (ANOVA) was used. For the association between rs7597774 and NYHA heart functional classification or therapeutic regimens, a nonparametric test, Ridit analysis and the Kruskal-Wallis H test, were used, respectively. Two-tailed P < 0.05 was accepted as statistically significant.

Results

Baseline characteristics

Clinical characteristics of 399 DCM cases and 1384 non-DCM controls were examined to determine their distribution across the cohort. Clinical characteristics of DCM and control groups are compared in Table 1. Age and T2DM were two clinical features that were distributed similarly between the two groups, but a greater number of males were in the DCM (62.66%) than the control group (56.79%). Measurements of the heart were more indicative of declining function in the DCM cases. LVEDD and LAD were greater in DCM patients than controls, regardless of gender (P < 0.001), whereas LVEF was significantly lower in cases than controls (35.88 ± 11.98 versus 59.62 ± 6.358, P < 0.001). Serum BNP concentrations were 1022.55 ± 910.86 pg/ml in DCM patients. Hypertension, however, was surprisingly less frequent among cases than controls (P = 0.002, P < 0.001, respectively).

Table 1.

Baseline clinical characteristics of study groups

Characteristics	DCM Group	Control Group	P -value
Number	399	1384	N/A
Age (M ± SD, y)	55.97 ± 15.194	57.3 ± 16.074	0.67
Gender (Male)	62.66%	56.79%	0.038
Hypertension (1/0)	143/256	616/768	0.002
T2DM (1/0)	53/344	237/1149	0.076
LVEDD (M ± SD, mm)
Male	65.00 ± 9.329	44.49 ± 4.196	< 0.001
Female	60.70 ± 7.523	42.04 ± 4.481	< 0.001
LVEF (M ± SD, %)	35.88 ± 11.98	59.62 ± 6.358	< 0.001
BNP levels (M ± SD, pg/ml)	1022.55 ± 910.86	N/A	-
LAD (M ± SD, mm)
Male	44.08 ± 6.529	33.00 ± 5.144		< 0.001
Female	40.69 ± 9.160	31.84 ± 6.597		< 0.001

M ± SD, mean ± standard deviation; T2DM, type 2 diabetes mellitus; LVEDD, left ventricular end-diastolic diameter; LAD, left atrial diameter; BNP, brain natriuretic peptide; N/A, data not available.

Prior statistical power was estimated for the proposed study on the 1783 participants. A type I error of 0.05 and a minor allele frequency (MAF) of 0.256 for rs1739843 and 0.167 for rs7597774 in the Chinese Han population (NCBI data) generated odds ratios (OR) of 0.67 for rs1739843 and 1.44 for rs7597774 in DCM [7]. The statistical power was calculated to be 98.5% and 94.9% for rs1739843 and rs7597774, respectively. The SNPs were also tested and found to be in Hardy-Weinberg equilibrium (HWE) in the cohort (P > 0.05).

Allelic association between rs1739843/rs7597774 and DCM

Analyses were performed to illuminate whether either of the SNPs was related to DCM susceptibility, and more specifically to individual alleles. Analysis was also performed to identify allelic associations specific to clinical subgroup (s). Comparisons of the minor allele frequencies of rs1739843 among the subgroups are summarized in Supplementary Table 1. None of the subgroups were associated with the minor allele T of rs1739843 (Total P = 0.6159, OR 1.05). After adjusting for age, gender, hypertension, T2DM, rs1739843 still did not correlate with DCM (Total P_-adj = 0.407, OR 0.920).

Overall, the minor allele A of rs7597774 showed a significant allelic association with an increased risk of DCM (Total P = 0.0156, OR 1.457; Table 2). The association remained significant with an OR of 1.582 (P_-adj = 0.0157) after adjusting for covariates. In the subgroup analyses of males and T2DM, a significant association between the A allele of rs7597774 and DCM was found with all parameters (P = 2.205 × 10^-4 and 5.624 × 10^-3, respectively). After adjusting covariates, a correlation was also found between the A allele and DCM in the female subgroup (P_-adj = 0.006). No relationship between the A allele and DCM in the hypertension subgroup was found before or after adjustment. These results demonstrated that the A allele of rs7597774 was associated with DCM in the cohort, but this association was not specific to any subgroup based on individual clinical parameters.

Table 2.

Allelic analysis of rs7597774 association with DCM

rs7597774 (Case/Control)	Frequency of A Allele (Case/Control)	P -value	OR (95% CI)	P-adj	Exp (B) (95% CI)
Total (399/1384)	0.269/0.202	0.016	1.457 (1.215-1.748)	0.016	1.582 (1.296-1.930)
Male (250/786)	0.276/0.196	2.21 × 10-4	1.564 (1.24-1.974)	0.053	1.581 (1.234-2.025)
Female (149/598)	0.258/0.210	0.072	1.312 (0.977-1.761)	0.006	1.609 (1.150-2.253)
Hypertension (143/616)	0.234/0.221	0.637	1.080 (0.796-1.465)	0.556	1.105 (0.792-1.543)
T2DM (53/237)	0.349/0.217	5.62 × 10-3	1.931 (1.225-3.045)	0.018	1.837 (1.110-3.041)

OR, odds ratio; P_-adj, adjusted P value; Exp (B), adjusted OR; CI, confidence interval; T2DM, type 2 diabetes mellitus.

Genotypic association between rs1739843/rs7597774 and DCM

Genotypic association of the different alleles from the two SNPs with DCM was analyzed under the three common genetic models, additive, dominant and recessive (Table 3). For rs1739843, no association with DCM was revealed under the three models, even after adjusting for covariates. However, for rs7597774, a significant genotypic association was found between the A allele and an increased risk of DCM under the three models both before and after adjusting for covariates in the study groups (additive model: P = 2.79 × 10^-4, P_-adj = 1.7 × 10^-5; recessive model: P = 1.12 × 10^-3, P_-adj = 3.27 × 10^-4; dominant model: P = 1.01 × 10^-3, P_-adj = 3.19 × 10^-4).

Table 3.

Genotypic analysis of rs1739843/rs7597774 with DCM under three genetic models

Models	P -value	OR (95% CI)	P-adj	Exp (B) (95% CI)
rs1739843
Addictive	0.785	N/A	0.744	1.032 (0.856-1.244)
Recessive	0.511	1.157 (0.763-1.754)	0.601	1.124 (0.725-1.742)
Dominant	0.776	1.036 (0.829-1.296)	0.890	1.017 (0.802-1.290)
rs7597774
Addictive	2.79 × 10-4	N/A	1.7 × 10-5	1.506 (1.249-1.815)
Recessive	1.12 × 10-3	1.978 (1.304-3.001)	3.27 × 10-4	2.208 (1.433-3.402)
Dominant	1.01 × 10-3	1.465 (1.169-1.836)	3.19 × 10-4	1.557 (1.224-1.982)

OR, odds ratio; P_-adj, adjusted P value; Exp (B), adjusted OR; CI, confidence interval.

rs7597774 is significantly correlated with NYHA heart functional classification

To determine whether the any clinical parameter could be a manifestation of the underlying rs7597774 genotype, the clinical data and the genotypes were examined for associations. The distribution of rs7597774 genotypes in DCM patients was similar when age, LVEDD, LAD, BNP levels, and LVEF were examined (Supplementary Table 2). However, a significant correlation between rs7597774 genotypes and NYHA heart functional classification was found (P = 0.021, Table 4 and Figure 1). In NYHA I/II, the proportion of genotype AA (2/41 (4.8-8%)/7/41 (17.07%)) was lower than genotype CC (14/202 (6.93%)/65/202 (32.18%)). In contrast, the proportion of genotype AA in NYHA III/IV (21/41 (51.22%)/11/41 (26.83%)) was strikingly greater than genotype CC (81/202 (40.10%)/42/202 (20.79%)). The results further demonstrated that the A allele of rs7597774 was associated with an increased risk of DCM, and that patients with risk allele A displayed more severe symptoms than patients with CC.

Table 4.

Distribution of rs7597774 genotype relative to NYHA heart functional grade of DCM patients

NYHA Heart Functional Grade	rs7597774 genotype			P -value	Total
	AA	AC	CC
I	2 (4.88%)	7 (4.49%)	14 (6.93%)	P = 0.021	24 (6.02%)
II	7 (17.07%)	30 (19.23%)	65 (32.18%)		102 (25.56%)
III	21 (51.22%)	77 (49.36%)	81 (40.10%)		179 (44.86%)
IV	11 (26.83%)	42 (26.92%)	42 (20.79%)		94 (23.56%)
Total	41	156	202		399

NYHA, New York Heart Association.

Figure 1.

Patients with rs7597774 risk allele A display more severe symptoms than patients with the genotype CC. Ridit analysis was performed to establish the nature of relationship between rs7597774 genotypes and NYHA heart functional grade in DCM patients. Groups 1, 2, and 3 represent ridit values for genotypes AA, AC, and CC. The ridit value is represented as a 95% confidence interval (CI) of the mean (M). The average ridit value of groups 1 and 2 is significantly greater than group 3.

Assessment of association between rs7597774 and therapeutic regimens of DCM patients

To further characterize the clinical significance of the rs7597774 variant, the data for the method of treatment were analyzed for genotypic association under a dominant model for allele A. The therapeutic regimens of the 399 DCM patients were recorded into two groups: classified drug therapy and catheterization/surgical intervention. The latter included dual chamber pacing (DDD), implantable cardioverter defibrillator (ICD), cardiac resynchronization therapy (CRT), cardiac resynchronization therapy defibrillator (CRTD), and cardiac transplantation (CTX). Only 31/399 DCM patients (7.77%) underwent invasive therapy (Table 5). The distribution of rs7597774 genotypes (AA, AC and CC) and therapeutic regimens in the invasive therapy group were examined by nonparametric analysis in the Kruskal-Wallis H test. Analysis of the data from the 31 patients demonstrated that a greater proportion of genotype AA (3/5 (60%)) than genotype CC (5/13 (38.46%)) patients underwent more invasive interventions, including CRT, CRTD and CTX. Correspondingly, a smaller proportion of genotype AA (2/5 (40%)) than genotype CC (8/13 (61.54%)) patients received intervention with DDD and ICD (P = 0.008). These results indicated that genotypes of rs7597774 might be used to guide the selection for treatment of individual DCM patients. However, the study sample was small, and the results require further testing in a larger cohort.

Table 5.

Genotype distribution of rs7597774 relative to invasive procedure performed

Therapeutic Regimens	rs7597774 genotypes			P -value	Total
	AA	AC	CC
DDD	1 (20%)	3 (23.08%)	6 (46.15%)	0.008	10
ICD	1 (20%)	5 (38.46%)	2 (15.38%)		8
CRT	0 (0%)	0 (0%)	5 (38.46%)		5
CRTD	2 (40%)	2 (15.38%)	0 (0%)		4
CTX	1 (20%)	3 (23.08%)	0 (0%)		4
Total	5	13	13		31

DDD, dual chamber pacing; ICD, implantable cardioverter defibrillator; CRT, cardiac resynchronization therapy; CRTD, cardiac resynchronization therapy defibrillator; CTX, cardiac transplantation.

Discussion

The hope for molecular characterization of heart dysfunction is that it will contribute to the development of therapies for prevention and treatment of the disease. Here, relationships between SNPs rs1739843 and rs7597774 and DCM were examined in a cohort of Chinese Han where the statistical power was 98.5% and 94.9%, respectively. No significant association was found between rs1739843 and DCM regardless of the genetic model applied, before or after adjusting for covariates. A significant association between rs7597774 and increased risk of DCM was however revealed before and after adjusting for covariates.

Several studies have applied a 50K bead chip to reveal associations between SNPs and heart dysfunction. In one study, rs1739843 was found to be associated with heart failure [14]. A second set of studies also revealed a significant association between rs1739843 and idiopathic DCM in German populations, and the association remained statistically significant in three validation groups (Germany, France 1, and France 2) [7]. This finding revealed HSPB7 as a risk factor for idiopathic DCM at the first diagnosis. An association of 12 SNP HSPB7 polymorphisms, including rs1739843, was made with heart failure, but the diagnosis of DCM was not included in the analysis in this third study [15]. Other groups did not find an association of rs1739843 with sporadic DCM in various western populations [8]. Similar results were demonstrated in a small Chinese Han population [9]. The sample size of our study was larger than this previous study on Chinese Han, and the statistical power was greater at 98.5% for rs1739843. Our result that no association of rs1739843 with DCM exists in Chinese Han cohorts is in all probability real. The most likely reason for the different results is differences in ethnic origin (European/Caucasian versus Chinese Han). First, the minor allele frequency of rs1739843 was different among the cohorts (0.39 in Europeans; 0.256 in Chinese Han). Second, in the German population, the T allele of rs1739843 was found to be a protective allele to DCM [7], and these results were corroborated in the study where rs1739843 was associated with heart failure [14].

HSPB7 encodes the small heat shock protein cvHsp and is known to be expressed in cardiovascular and insulin-sensitive tissues [16]. In general, the expression and activation of heat shock proteins is influenced by elevated temperatures as well as ischemia, hypoxia, and acute cellular stress [17,18]. However, none of the DCM-associated SNPs identified through systematic sequencing actually affects the coding sequence of HSPB7 [14]. HSPB7 exons have also been sequenced in 168 independent index cases diagnosed with familial DCM, but no coding variant was identified [8]. Therefore, the biological function of the polymorphisms of HSPB7 in DCM/heart failure risk remains unclear.

A statistically significant association between ADD2 rs7597774 and idiopathic DCM was previously found in German populations, but the results were not validated in other samples/cohorts [7]. Our study was the first to confirm a statistically significant association between rs7597774 and DCM, with an allelic or genotypic model, before or after adjusting covariates. Interestingly, the minor allele C of rs7597774 in European ancestry conferred a risk of DCM, whereas in Chinese Han samples, it was the minor allele A of rs7597774 that was found to increase the risk of DCM. The minor allele and MAF of rs7597774 were, however, different in the two races (European C allele, MAF 0.325; Chinese Han A allele, MAF 0.167).

Adducin 2 (Add2) is a heterodimeric cytoskeletal protein. ADD2 spans 108 kb including 17 exons that are alternatively spliced to code for at least five known protein isoforms [19]. Add2 has been proposed to regulate renal tubular transport of Na⁺ reabsorption, which in turn regulates body sodium, fluid volumes, and the development of hypertension [20,21]. A series of parallel studies indicated that an altered function in Add2 might cause hypertension through enhanced constitutive tubular sodium reabsorption. A variant of ADD2 was also found to be associated with blood pressure in rats [20]. Furthermore, eight SNPs in ADD2 were found to be significantly associated with systolic blood pressure in untreated hypertensive patients, and SNPs were also identified that were associated with gene-by-drug interactions on systolic blood pressure in drug-treated hypertensive patients [22]. The mechanism underlying the association between the polymorphisms of ADD2 and DCM risk, however, still remains unclear.

Based on NYHA functional classification, the results of the study demonstrated that genotype AA DCM patients had more severe heart failure symptoms than genotypes AC + CC. Furthermore, DCM patients harboring genotype AA underwent more complicated medical interventions, although the selection of therapies is related to many additional factors such as symptoms (syncope, dyspnea), LVEF < 40%, malignant arrhythmia, NYHA grade > II, cardiac arrest, history of myocardial infarction or family history of sudden death, QRS duration > 120 ms, and even economic issues. Although many factors are involved in the selection of the right therapeutic strategy for individual patients, our ultimate goal was to determine whether the genotype of rs7597774 might assist in assessing the cardiac function during heart failure as well as to be able to identify the DCM patients who will benefit most from particular therapies.

The results require further investigation both for validation and more importantly to understand the biological function of the SNPs in DCM. First, although an association between ADD2 rs7597774 and DCM is reported for the first time in the Chinese Han population, this result as well as the association with treatment, must be validated in larger Chinese Han cohorts. Such studies can ultimately assess the utility of rs7597774 in predicting therapy for DCM patients. Second, although the analysis here revealed only rs7597774 from ADD2 to be associated with DCM, these results nevertheless implicate a genetic component to the disease, and thus highlight the importance of examining more variants, especially low-penetrance variants from other suspected DCM-susceptibility genes, such as BAG3 [8]. Third, because DCM is a multifactorial disease, the interaction of multiple variants from different chromosomes should be analyzed in order to gain better insight into the genetic component of DCM. In this study, two polymorphisms that are located on different chromosomes were assessed. However as rs1739843 was not found to be associated with DCM, the interaction between the two variants could not be calculated. Finally, the nature of functional relationship of the ADD2 polymorphisms in the etiology of DCM remains to be elucidated.

ADD2 rs7597774 but not HSPB7 rs1739843 was found to be associated with the risk of DCM in the Chinese Han population. Including the genotype of rs7597774 in the clinical data collected for DCM patients may assist in assessing heart function and predicting those who will benefit most from particular therapies.

Disclosure of conflict of interest

None.