"Background Information Cardiomyopathy is one of the leading causes of heart failure. In cases where cardiomyopathy does not respond to guideline-directed medical therapy for heart failure, the disease may progress to a stage where heart transplantation is the only viable treatment option. According to the 2022 Korean Organ Transplant Registry (KOTRY) report, cardiomyopathy accounted for approximately 65% of heart transplant indications in Korea, making it one of the most challenging unresolved issues in modern cardiology. Furthermore, cardiomyopathy is associated with a high risk of sudden cardiac death due to ventricular fibrillation or ventricular tachycardi and implantable cardioverter-defibrillators are often recommended as a preventive measure. Given that sudden cardiac death frequently occurs in young and middle-aged individuals, it is a major public health concern in developed countries such as North America and Western/Northern Europe, prompting ongoing societal and medical efforts to reduce its burden. The risk of sudden cardiac death imposes a persistent psychological burden on family members of patients with cardiomyopathy. Because sudden death can also occur in children and adolescents, current clinical guidelines recommend early cardiac evaluation and genetic counseling for family members of affected individuals.

This study seeks to overcome the current limitations in the genetic diagnosis of cardiomyopathy, including the low diagnostic yield of currently available gene panels. To date, most genetic data on cardiomyopathy have been derived from Western populations. There is a significant lack of population-specific genomic data for East Asians, particularly Koreans, making it difficult to interpret the results of genetic testing in Korean patients.

By developing bioinformatics algorithms that comprehensively analyze whole genome sequencing (WGS) data, including single nucleotide variants (SNVs), insertions/deletions (indels), and structural variations, this study aims to generate a reference dataset tailored to the Korean population. This will directly improve the genetic diagnosis of cardiomyopathy in Korean patients. Additionally, by identifying novel pathogenic variants through WGS, this study may elucidate new disease mechanisms underlying cardiomyopathy. These findings could provide a theoretical basis for developing novel diagnostic biomarkers, therapeutic targets, and even gene-based therapies. The present study is part of a multi-phase national research project supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, conducted as a registry cohort titled the ""Korean Cardiomyopathy Cohort (KCC)"".

Objectives This study aims to establish a diagnostic research framework to elucidate the genetic architecture of rare inherited cardiomyopathies through comprehensive analysis of whole genome sequencing data, with the goal of identifying novel diagnostic approaches

"Study Design The investigator will collect data from patients diagnosed with cardiomyopathy and will utilize secondary, real-world patient data obtained from electronic medical records at participating institutions.

Study Methods

1. Blood samples will be collected after obtaining informed consent from eligible patients during outpatient visits or hospitalization. Informed consent will be obtained in a private setting to ensure patient confidentiality, with sufficient explanation provided. The study will follow standard diagnostic and treatment guidelines commonly applied to heart failure patients in Korea. Demographic information, clinical characteristics, imaging data (echocardiography, cardiac MRI), laboratory findings, and cardiovascular events will be documented separately using a case report form.
2. Following informed consent, approximately 5-10 mL of whole blood will be drawn on the same day or during the subsequent outpatient visit. The sample will be transported to SCL on the day of collection, where plasma and buffy coat will be separated and stored.
3. Genomic, laboratory, and imaging data will be integrated for comprehensive statistical analysis.
4. All study data will be stored on password-protected computers with restricted access. No personal identifiers will be included to ensure data confidentiality."

Inclusion Criteria:

patients aged 19 years or older who have provided written consent for participation, have the capability to consent voluntarily and have been diagnosed with cardiomyopathy, as defined by one of the following criteria: -Ones with suspected genetic cardiomyopathy of unknown etiology, meeting at least one of the following conditions: i) Patients with idiopathic cardiomyopathy, for whom no clear secondary causes (e.g., history of hypertension, alcohol abuse, or chemotherapy) can be identified, and in whom a genetic etiology is strongly suspected.

ii) Patients who have previously undergone genetic testing using an NGS panel, but no pathogenic variants were identified, and further evaluation with whole genome sequencing (WGS) is warranted.

iii) Patients diagnosed with cardiomyopathy before the age of 50, without known contributing factors such as hypertension or excessive alcohol consumption, raising a strong suspicion of a genetic cause.

-Patients with a family history of genetic cardiomyopathy, defined as having at least one first-degree relative (parent, sibling, or child) diagnosed with the same type of cardiomyopathy, confirming a familial genetic pattern.

Exclusion Criteria:

• Patients with confirmed ischemic cardiomyopathy (when stenosis of 75% or more of major coronary arteries is confirmed on coronary artery imaging or ischemic cardiomyopathy findings such as transmural LGE on cardiac MRI)
• Heart failure with other etiologies (e.g., valvular heart disease, endocrine disease)

Patients with cardiomyopathy in whom a genetic etiology is strongly suspected and no pathogenic variants have been identified, or those with at least one first-degree relative diagnosed with the same cardiomyopathy subtype

Access to trial IPD can be requested by qualified researchers engaging in independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). For more information or to submit a request, please contact ericjcoh@yuhs.ac