Understanding the genetics of adult-onset dilated cardiomyopathy: what a clinician needs to know

Tayal, Upasana; Ware, James S.; Lakdawala, Neal K.; Heymans, Stéphane; Prasad, Sanjay

doi:10.1093/eurheartj/ehab286

Cited by 38 publications

(31 citation statements)

References 63 publications

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“…Cardiomyopathies are a heterogeneous group of heart muscle diseases with different clinical phenotypes. Patients diagnosed with cardiomyopathies, such as HCM and RCM ( 22 , 23 ), tend to present with HFpEF, whereas those diagnosed with DCM tend to present with HFrEF ( 24 ). However, whether the prognoses of HFpEF and HFrEF are different remains controversial.…”

Section: Discussionmentioning

confidence: 99%

Association between comorbid cardiomyopathy and composite endpoints of patients with congestive heart failure in the intensive care unit: a retrospective cohort study

Liang¹,

Sun²,

Chen³

et al. 2022

J Thorac Dis

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Background Congestive heart failure (HF) is a common condition in the intensive care unit (ICU). Cardiomyopathy is an important etiological factor in HF. However, few studies have explored the effect of cardiomyopathy on the prognosis of HF. This study explored the association between comorbid cardiomyopathy and the outcomes of critically ill patients with congestive HF. Methods A retrospective cohort study was performed using data extracted from Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All adult patients with the first ICU admission were enrolled as participants but those diagnosed with cardiomyopathy alone were excluded. The demographics, comorbidities, vital signs, laboratory tests, scoring systems, and treatments of patients were extracted to further analyze. The composite endpoints included in-hospital mortality, cardiac arrest, and re-admission to the ICU. The association between cardiomyopathy comorbidity and the composite endpoints was assessed using propensity-score matching (PSM) and multivariable logistic regression models. Results A total of 27,901 critically ill patients were enrolled, including 1,023 patients diagnosed with cardiomyopathy and congestive HF. The average age of the cohort was 64.37±17.36 years, and 58.13% of the patients were men. The ethnicity of patients was mainly white (64.67%). Multivariable logistic regression analyses found the risk of composite endpoints in patients with cardiomyopathy was higher than other groups [odds ratio (OR) =1.87; 95% confidence interval (CI): 1.62–2.15; P<0.001]. Compared to patients with congestive HF alone (OR =1.43; 95% CI: 1.26–1.62; P<0.001), patients with cardiomyopathy had a similar risk of in-hospital death (OR =1.35; 95% CI: 1.06–1.71; P=0.014). Moreover, the risks of cardiac arrest (OR =1.53; 95% CI: 1.01–2.34; P=0.029) and re-admission to the ICU (OR =1.74; 95% CI: 1.39–2.17; P<0.001) were both higher in patients with cardiomyopathy than other groups. After PSM, the risk of composite endpoints was still higher in patients with cardiomyopathy (OR =1.64; 95% CI: 1.33–2.02; P<0.001). The association was consistent among patients admitted to the coronary care unit (CCU) and medical ICU (MICU)/surgical ICU (SICU). Conclusions Comorbid cardiomyopathy increased the risk of composite endpoints in patients with congestive HF admitted to the ICU. Cardiomyopathy is related to the poor outcomes of critically ill patients with congestive HF.

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Section: Discussionmentioning

confidence: 99%

Association between comorbid cardiomyopathy and composite endpoints of patients with congestive heart failure in the intensive care unit: a retrospective cohort study

Liang¹,

Sun²,

Chen³

et al. 2022

J Thorac Dis

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“…Thanks to the development of high-throughput technologies, transcriptional analysis based on multiple datasets has been used to determine the pathological mechanisms of diseases. Disease pathogenesis and progression are not caused by a single gene but by synergistic effects in a complex network [12]. Complementary to this is weighted gene coexpression network analysis (WGCNA), a widely used systems bioinformatics technique to assess associations between genomic and external sample features by constructing scale-free gene coexpression networks.…”

Section: Introductionmentioning

confidence: 99%

Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis

Guo¹,

Qu²,

Wang³

et al. 2022

Front. Biosci. (Landmark Ed)

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Background: Dilated cardiomyopathy (DCM) is one of the main causes of systolic heart failure and frequently has a genetic component. The molecular mechanisms underlying the onset and progression of DCM remain unclear. This study aimed to identify novel diagnostic biomarkers to aid in the treatment and diagnosis of DCM. Method: The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, GSE120895 and GSE17800, which were subsequently merged into a single cohort. Differentially expressed genes were analyzed in the DCM and control groups, followed by weighted gene coexpression network analysis to determine the core modules. Core nodes were identified by gene significance (GS) and module membership (MM) values, and four hub genes were predicted by the Lasso regression model. The expression levels and diagnostic values of the four hub genes were further validated in the datasets GSE19303. Finally, potential therapeutic drugs and upstream molecules regulating genes were identified. Results: The turquoise module is the core module of DCM. Four hub genes were identified: GYPC (glycophorin C), MLF2 (myeloid leukemia factor 2), COPS7A (COP9 signalosome subunit 7A) and ARL2 (ADP ribosylation factor like GTPase 2). Subsequently, Hub genes showed significant differences in expression in both the dataset and the validation model by real-time quantitative PCR (qPCR). Four potential modulators and seven chemicals were also identified. Finally, molecular docking simulations of the gene-encoded proteins with smallmolecule drugs were successfully performed. Conclusions: The results suggested that ARL2, MLF2, GYPC and COPS7A could be potential gene biomarkers for DCM.

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“…16 However, more recent expert-consensus is to consider genetic testing in non-ischemic DCM irrespective of familial history. 17 Comparable, the American practice guidelines recommend genetic testing in all DCM patients irrespective of the presence of conduction disturbances or SCD. 15 In DCM, genetic yield is 15% to 25% in isolated cases and up to 25% to 40% in DCM patients with a positive family history.…”

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confidence: 99%

“…16,20 If a pathogenic variant is identified in a proband, strict clinical follow-up of family members carrying this variant is warranted, whereas family members without the variant can be reassured and omitted from routine controls. 15,17 Moreover, identification of asymptomatic variant-carriers allows for early diagnosis and treatment, resulting in a decrease in morbidity and mortality. 15,17 In patients that underwent HTx for non-ischemic cardiomyopathies in the past, retrospective genetic testing often has been overlooked.…”

mentioning

confidence: 99%

“…15,17 Moreover, identification of asymptomatic variant-carriers allows for early diagnosis and treatment, resulting in a decrease in morbidity and mortality. 15,17 In patients that underwent HTx for non-ischemic cardiomyopathies in the past, retrospective genetic testing often has been overlooked. This is even more true for isolated cases of DCM, for which genetic testing has not always been advised in the past.…”

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confidence: 99%

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Diagnostic yield of genetic testing in heart transplant recipients with prior cardiomyopathy

Boen¹,

Loeys²,

Alaerts³

et al. 2022

The Journal of Heart and Lung Transplantation

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Understanding the genetics of adult-onset dilated cardiomyopathy: what a clinician needs to know

Cited by 38 publications

References 63 publications

Association between comorbid cardiomyopathy and composite endpoints of patients with congestive heart failure in the intensive care unit: a retrospective cohort study

Association between comorbid cardiomyopathy and composite endpoints of patients with congestive heart failure in the intensive care unit: a retrospective cohort study

Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis

Diagnostic yield of genetic testing in heart transplant recipients with prior cardiomyopathy

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