Question: You are an expert researcher providing comprehensive, well-cited information.

Provide detailed information focusing on: 1. Key concepts and definitions with current understanding 2. Recent developments and latest research (prioritize 2023-2024 sources) 3. Current applications and real-world implementations 4. Expert opinions and analysis from authoritative sources 5. Relevant statistics and data from recent studies

Format as a comprehensive research report with proper citations. Include URLs and publication dates where available. Always prioritize recent, authoritative sources and provide specific citations for all major claims.

Disease Characteristics Research Template

Target Disease

• Disease Name: Dilated Cardiomyopathy 1JJ
• MONDO ID: (if available)
• Category: Mendelian

Research Objectives

Please provide a comprehensive research report on Dilated Cardiomyopathy 1JJ covering all of the disease characteristics listed below. This report will be used to populate a disease knowledge base entry. Be thorough and cite primary literature (PMID preferred) for all claims.

For each section, suggested databases/resources are listed. These are the first places you should search for information on each topic.

1. Disease Information

Search first: OMIM, Orphanet, ICD-10/ICD-11, MeSH, PubMed

• What is the disease? Provide a concise overview.
• What are the key identifiers? (OMIM, Orphanet, ICD-10/ICD-11, MeSH, Mondo)
• What are the common synonyms and alternative names?
• Is the information derived from individual patients (e.g., EHR) or aggregated disease-level resources?

2. Etiology

• Disease Causal Factors: What are the primary causes? (genetic, environmental, infectious, mechanistic)
• Risk Factors:

  Search first: PubMed, Cochrane Library, UpToDate, clinical guidelines, ClinVar, ClinGen, GWAS Catalog, PheGenI, CTD, CDC, WHO, epidemiological databases

• Genetic risk factors (causal variants, susceptibility loci, modifier genes)
• Environmental risk factors (toxins, lifestyle, occupational exposures, age, sex, family history)
• Protective Factors:

  Search first: PubMed, Cochrane Library, clinical trial databases, GWAS Catalog, gnomAD, WHO, CDC, nutrition databases

• Genetic protective factors (protective variants, modifier alleles)
• Environmental protective factors (diet, lifestyle, exposures that reduce risk)
• Gene-Environment Interactions: How do genetic and environmental factors interact to influence disease?

  Search first: CTD, PubMed, PheGenI, GxE databases

3. Phenotypes

Search first: HPO (Human Phenotype Ontology), OMIM, Orphanet, PubMed, clinicaltrials.gov, MedDRA, SNOMED CT, DECIPHER, LOINC

For each phenotype, provide: - Phenotype type: symptoms, clinical signs, physical manifestations, behavioral changes, or laboratory abnormalities

For symptoms/signs: HPO, OMIM, Orphanet, PubMed For behavioral changes: HPO, DSM, RDoC (Research Domain Criteria), PubMed For laboratory abnormalities: LOINC, SNOMED CT, LabTests Online, PubMed - Phenotype characteristics: Search first: OMIM, Orphanet, HPO, PubMed - Age of symptom onset (neonatal, childhood, adult-onset, late-onset) - Symptom severity (mild, moderate, severe, variable) - Symptom progression (stable, progressive, episodic, fluctuating) - Frequency among affected individuals (percentage or qualitative) - Quality of life impact: Effects on daily functioning and well-being (per-phenotype when possible) Search first: EQ-5D database, SF-36, WHO QOL databases, PubMed - Suggest HPO (Human Phenotype Ontology) terms for each phenotype

4. Genetic/Molecular Information

• Causal Genes: Gene mutations or chromosomal abnormalities responsible for disease (gene symbols, OMIM IDs)

  Search first: OMIM, ClinVar, HGMD, Ensembl, NCBI Gene

• Pathogenic Variants:
• Affected genes (gene symbols, HGNC IDs) > Search first: OMIM, NCBI Gene, Ensembl, HGNC, UniProt, GeneCards
• Variant classification (pathogenic, likely pathogenic, VUS per ACMG/AMP guidelines) > Search first: ClinVar, ClinGen, ACMG/AMP guidelines, VarSome
• Variant type/class (missense, frameshift, nonsense, splice-site, structural)
• Allele frequency in population databases > Search first: gnomAD, 1000 Genomes, ExAC, TOPMed, dbSNP
• Somatic vs germline origin > Search first: COSMIC (somatic), ClinVar, ICGC, TCGA
• Functional consequences (loss of function, gain of function, dominant negative)
• Modifier Genes: Genes that modify disease severity or expression
• Epigenetic Information: DNA methylation, histone modifications, chromatin changes affecting disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Chromosomal Abnormalities: Large-scale genetic changes (aneuploidy, translocations, inversions)

  Search first: DECIPHER, ClinVar, ECARUCA, UCSC Genome Browser

5. Environmental Information

• Environmental Factors: Non-genetic contributing factors (toxins, radiation, pollution, occupational exposure)

  Search first: CTD (Comparative Toxicogenomics Database), TOXNET, PubMed, EPA databases

• Lifestyle Factors: Behavioral factors (smoking, diet, exercise, alcohol consumption)

  Search first: CDC databases, WHO, PubMed, NHANES

• Infectious Agents: If applicable, pathogens causing or triggering disease (bacteria, viruses, fungi, parasites)

  Search first: NCBI Taxonomy, ViPR, BV-BRC, MicrobeDB, GIDEON

6. Mechanism / Pathophysiology

• Molecular Pathways: Specific signaling cascades or biochemical pathways involved (Wnt, MAPK, mTOR, PI3K-AKT, etc.)

  Search first: KEGG, Reactome, WikiPathways, PathBank, BioCyc

• Cellular Processes: Cell-level mechanisms (apoptosis, autophagy, cell cycle dysregulation, inflammation, etc.)

  Search first: Gene Ontology (GO), Reactome, KEGG, PubMed

• Protein Dysfunction: How protein structure or function is altered (misfolding, aggregation, loss of function, gain of function)

  Search first: UniProt, PDB (Protein Data Bank), InterPro, Pfam, AlphaFold

• Metabolic Changes: Alterations in metabolic processes (energy metabolism, lipid metabolism, amino acid metabolism)

  Search first: KEGG, BioCyc, HMDB (Human Metabolome Database), BRENDA

• Immune System Involvement: Role of immune response (autoimmunity, immunodeficiency, chronic inflammation)

  Search first: ImmPort, Immunome Database, IEDB, Gene Ontology

• Tissue Damage Mechanisms: How tissues/ are injured (oxidative stress, ischemia, fibrosis, necrosis)

  Search first: PubMed, Gene Ontology, Reactome

• Biochemical Abnormalities: Specific molecular defects (enzyme deficiencies, receptor dysfunction, ion channel defects)

  Search first: BRENDA, UniProt, KEGG, OMIM, PubMed

• Epigenetic Changes: DNA methylation, histone modifications affecting gene expression in disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Molecular Profiling (if available):
• Transcriptomics/gene expression changes > Search first: GEO (Gene Expression Omnibus), ArrayExpress, GTEx, Human Cell Atlas, SRA
• Proteomics findings > Search first: PRIDE, ProteomeXchange, Human Protein Atlas, STRING, BioGRID
• Metabolomics signatures > Search first: MetaboLights, Metabolomics Workbench, HMDB, METLIN
• Lipidomics alterations > Search first: LIPID MAPS, SwissLipids, LipidHome, Metabolomics Workbench
• Genomic structural features > Search first: UCSC Genome Browser, Ensembl, NCBI, dbVar, DGV
• Advanced Technologies (if applicable):
• Single-cell analysis findings (cell-type specific mechanisms, cellular heterogeneity) > Search first: Human Cell Atlas, Single Cell Portal, GEO, CELLxGENE
• Spatial transcriptomics findings > Search first: GEO, Spatial Research, Vizgen, 10x Genomics data
• Multi-omics integration results > Search first: TCGA, ICGC, cBioPortal, LinkedOmics, PubMed
• Functional genomics screens (CRISPR, RNAi) > Search first: DepMap, GenomeRNAi, PubMed, BioGRID ORCS

For each mechanism, describe: - The causal chain from initial trigger to clinical manifestation - Which mechanisms are upstream vs downstream - What cell types and biological processes are involved - Suggest GO terms for biological processes and CL terms for cell types

7. Anatomical Structures Affected

• Organ Level:
• Primary organs directly affected
• Secondary organ involvement (complications, secondary effects)
• Body systems involved (cardiovascular, nervous, digestive, respiratory, endocrine, etc.)

  Search first: Uberon, FMA (Foundational Model of Anatomy), OMIM, HPO, ICD-11, MeSH, SNOMED CT

• Tissue and Cell Level:
• Specific tissue types affected (epithelial, connective, muscle, nervous)
• Specific cell populations targeted (with Cell Ontology terms)

  Search first: Uberon, Human Protein Atlas, Cell Ontology, Human Cell Atlas, CellMarker, PanglaoDB

• Subcellular Level:
• Cellular compartments involved (mitochondria, nucleus, ER, lysosomes) (with GO Cellular Component terms)

  Search first: Gene Ontology (Cellular Component), UniProt, Human Protein Atlas

• Localization:
• Specific anatomical sites (with UBERON terms) > Search first: FMA, Uberon, NeuroNames (for brain), SNOMED CT
• Lateralization (unilateral, bilateral, asymmetric) > Search first: HPO, clinical literature, imaging databases

8. Temporal Development

• Onset:
• Typical age of onset (congenital, pediatric, adult, geriatric)
• Onset pattern (acute, subacute, chronic, insidious)

  Search first: OMIM, Orphanet, HPO, PubMed

• Progression:
• Disease stages (early, intermediate, advanced, end-stage) > Search first: Cancer Staging Manual (AJCC), WHO classifications, PubMed
• Progression rate (rapid, slow, variable)
• Disease course pattern (episodic, relapsing-remitting, progressive, stable)
• Disease duration (self-limited, chronic lifelong)

  Search first: Disease registries, longitudinal cohort databases, natural history studies, PubMed, Orphanet, OMIM

• Patterns:
• Remission patterns (spontaneous, treatment-induced) > Search first: Clinical trial databases, disease registries, PubMed
• Critical periods (time windows of vulnerability or opportunity for intervention) > Search first: PubMed, developmental biology databases, clinical guidelines

9. Inheritance and Population

• Epidemiology:
• Prevalence (cases per 100,000 at given time)
• Incidence (new cases per 100,000 per year)

  Search first: Orphanet, CDC, WHO, GBD (Global Burden of Disease), national registries, SEER, disease registries

• For Genetic Etiology:
• Inheritance pattern (AD, AR, X-linked, mitochondrial, multifactorial, polygenic) > Search first: OMIM, Orphanet, ClinVar, GTR (Genetic Testing Registry)
• Penetrance (complete, incomplete, age-dependent) > Search first: ClinVar, OMIM, PubMed, ClinGen
• Expressivity (variable, consistent) > Search first: OMIM, ClinVar, PubMed
• Genetic anticipation (increasing severity in successive generations) > Search first: OMIM, PubMed (especially for repeat expansion disorders)
• Germline mosaicism > Search first: ClinVar, OMIM, genetic counseling literature, PubMed
• Founder effects (population-specific mutations) > Search first: gnomAD, population genetics databases, PubMed
• Consanguinity role > Search first: OMIM, population studies, genetic counseling resources
• Carrier frequency > Search first: gnomAD, carrier screening databases, GeneReviews, GTR
• Population Demographics:
• Affected populations (ethnic or demographic groups with higher prevalence) > Search first: gnomAD, 1000 Genomes, PAGE Study, PubMed, population registries
• Geographic distribution (endemic areas, regional variation) > Search first: WHO, CDC, GBD, Orphanet, geographic epidemiology databases
• Geographic distribution of specific variants
• Sex ratio (male:female) > Search first: Disease registries, OMIM, PubMed, epidemiological databases
• Age distribution of affected individuals > Search first: CDC, disease registries, SEER, Orphanet

10. Diagnostics

• Clinical Tests:
• Laboratory tests (blood, urine, tissue chemistry, specific enzyme assays) > Search first: LOINC, LabTests Online, PubMed
• Biomarkers (proteins, metabolites, genetic markers, circulating biomarkers) > Search first: FDA Biomarker List, BEST (Biomarkers, EndpointS, and other Tools), PubMed
• Imaging studies (X-ray, CT, MRI, PET, ultrasound) > Search first: RadLex, DICOM, Radiopaedia, imaging databases
• Functional tests (pulmonary function, cardiac stress tests) > Search first: LOINC, clinical guidelines, PubMed
• Electrophysiology (EEG, EMG, ECG, nerve conduction studies) > Search first: LOINC, clinical neurophysiology databases, PubMed
• Biopsy findings (histopathology, immunohistochemistry) > Search first: SNOMED CT, College of American Pathologists resources, PubMed
• Pathology findings (microscopic examination) > Search first: SNOMED CT, Digital Pathology databases, PubMed
• Genetic Testing:

  Search first: GTR (Genetic Testing Registry), GeneReviews, ClinGen

• Overview of recommended genetic testing approach
• Whole genome sequencing (WGS) utility > Search first: GTR, ClinVar, GEL (Genomics England), gnomAD
• Whole exome sequencing (WES) utility > Search first: GTR, ClinVar, OMIM, GeneMatcher
• Gene panels (which panels, which genes) > Search first: GTR, ClinVar, laboratory-specific databases
• Single gene testing > Search first: GTR, ClinVar, OMIM, GeneReviews
• Chromosomal microarray (CMA) > Search first: DECIPHER, ClinVar, dbVar, ECARUCA
• Karyotyping > Search first: Chromosome Abnormality Database, ClinVar, cytogenetics resources
• FISH > Search first: ClinVar, cytogenetics databases, PubMed
• Mitochondrial DNA testing > Search first: MITOMAP, MSeqDR, ClinVar, GTR
• Repeat expansion testing > Search first: GTR, ClinVar, repeat expansion databases, PubMed
• Omics-Based Diagnostics (if applicable):
• RNA sequencing / transcriptomics > Search first: GEO, ArrayExpress, GTEx, RNA-seq databases
• Proteomics > Search first: PRIDE, ProteomeXchange, FDA Biomarker database
• Metabolomics > Search first: MetaboLights, Metabolomics Workbench, HMDB
• Epigenomics > Search first: GEO, ENCODE, Roadmap Epigenomics, MethBase
• Liquid biopsy > Search first: COSMIC, ClinVar, liquid biopsy databases, PubMed
• Clinical Criteria:
• Standardized diagnostic criteria (DSM, ICD, society guidelines) > Search first: DSM-5, ICD-11, clinical society guidelines, UpToDate
• Differential diagnosis (other conditions to rule out, with distinguishing features) > Search first: DynaMed, UpToDate, clinical decision support systems
• Screening:
• Screening methods for asymptomatic individuals (newborn screening, carrier screening, cascade screening) > Search first: ACMG recommendations, CDC newborn screening, GTR

11. Outcome/Prognosis

• Survival and Mortality:
• Survival rate (5-year, 10-year, overall) > Search first: SEER, cancer registries, disease-specific registries, PubMed
• Life expectancy (with and without treatment if applicable) > Search first: Orphanet, disease registries, actuarial databases, PubMed
• Mortality rate > Search first: CDC, WHO, GBD, national mortality databases
• Disease-specific mortality (deaths directly attributable to disease) > Search first: Disease registries, CDC Wonder, GBD, PubMed
• Morbidity and Function:
• Morbidity (disease-related disability and health impacts) > Search first: GBD, WHO, disability databases, PubMed
• Disability outcomes (long-term functional impairments) > Search first: ICF (International Classification of Functioning), disability registries
• Quality of life measures (EQ-5D, SF-36, PROMIS, disease-specific tools) > Search first: EQ-5D database, SF-36, PROMIS, PubMed
• Disease Course:
• Complications (secondary problems: infections, organ failure, etc.) > Search first: ICD codes, disease registries, clinical databases, PubMed
• Recovery potential (likelihood and extent of recovery, with vs without treatment) > Search first: Natural history studies, rehabilitation databases, PubMed
• Prediction:
• Prognostic factors (age, disease severity, biomarkers, treatment response) > Search first: Prognostic models databases, clinical calculators, PubMed
• Prognostic biomarkers (molecular markers predicting disease course) > Search first: FDA Biomarker database, PubMed, cancer prognostic databases

12. Treatment

• Pharmacotherapy:
• Pharmacological treatments (drug names, drug classes, mechanisms of action) > Search first: DrugBank, RxNorm, ATC classification, DailyMed, FDA databases
• Pharmacogenomics (how genetic variants affect drug metabolism, efficacy, toxicity) > Search first: PharmGKB, CPIC (Clinical Pharmacogenetics), FDA Table of PGx Biomarkers
• Advanced Therapeutics:
• Gene therapy (viral vectors, CRISPR, gene replacement, gene editing) > Search first: ClinicalTrials.gov, FDA gene therapy database, ASGCT resources
• Cell therapy (stem cell transplant, CAR-T, cellular therapeutics) > Search first: ClinicalTrials.gov, FDA cell therapy database, FACT standards
• RNA-based therapies (ASOs, siRNA, mRNA therapies) > Search first: ClinicalTrials.gov, FDA approvals, PubMed
• Targeted therapies (treatments directed at specific molecular targets) > Search first: My Cancer Genome, OncoKB, ClinicalTrials.gov, FDA approvals
• Immunotherapies (checkpoint inhibitors, monoclonal antibodies) > Search first: Cancer Immunotherapy Database, FDA approvals, ClinicalTrials.gov
• Surgical and Interventional:
• Surgical interventions (types of surgery, timing, outcomes) > Search first: CPT codes, surgical registries, clinical guidelines, PubMed
• Supportive and Rehabilitative:
• Supportive care (symptom management, pain control, nutrition) > Search first: Clinical guidelines, Cochrane Library, PubMed
• Rehabilitation (physical therapy, occupational therapy, speech therapy) > Search first: Rehabilitation medicine databases, clinical guidelines, PubMed
• Experimental:
• Experimental treatments in clinical trials (with NCT identifiers if available) > Search first: ClinicalTrials.gov, EU Clinical Trials Register, WHO ICTRP
• Treatment Outcomes:
• Treatment response rates > Search first: Clinical trial databases, FDA reviews, systematic reviews, PubMed
• Side effects and adverse events > Search first: FDA Adverse Event Reporting System (FAERS), MedWatch, PubMed
• Treatment Strategy:
• Treatment algorithms (clinical pathways, decision trees) > Search first: Clinical practice guidelines, NCCN Guidelines, UpToDate
• Combination therapies > Search first: ClinicalTrials.gov, treatment guidelines, PubMed
• Personalized medicine approaches (genotype-guided treatment) > Search first: My Cancer Genome, CIViC, PharmGKB, precision medicine databases

For each treatment, suggest NCIT (NCI Thesaurus) clinical-intervention terms where applicable.

13. Prevention

• Prevention Levels:
• Primary prevention (preventing disease occurrence: vaccination, risk factor modification) > Search first: CDC, WHO, USPSTF recommendations, Cochrane Library
• Secondary prevention (early detection and treatment: screening programs, early intervention) > Search first: USPSTF, CDC screening guidelines, WHO
• Tertiary prevention (preventing complications in those with disease) > Search first: Clinical guidelines, disease management protocols, PubMed
• Immunization: Vaccine strategies (if applicable)

  Search first: CDC vaccine schedules, WHO immunization, FDA vaccine database

• Screening and Early Detection:
• Screening programs (population-based: newborn screening, cancer screening) > Search first: CDC screening programs, USPSTF, cancer screening databases
• Genetic screening (carrier screening, preimplantation genetic diagnosis, prenatal testing) > Search first: ACMG recommendations, ACOG guidelines, GTR
• Risk stratification (identifying high-risk individuals for targeted prevention) > Search first: Risk prediction models, clinical calculators, PubMed
• Behavioral Interventions: Lifestyle modifications to reduce risk

  Search first: CDC, WHO, behavioral intervention databases, Cochrane Library

• Counseling: Genetic counseling (risk assessment, family planning guidance)

  Search first: NSGC resources, ACMG guidelines, GeneReviews

• Public Health:
• Public health interventions (sanitation, vector control, health education) > Search first: CDC, WHO, public health databases, PubMed
• Environmental interventions (reducing environmental risk factors) > Search first: EPA databases, WHO environmental health, PubMed
• Prophylaxis: Preventive medications or procedures

  Search first: Clinical guidelines, FDA approvals, PubMed

14. Other Species / Natural Disease

• Taxonomy: Species affected (with NCBI Taxon identifiers)

  Search first: NCBI Taxonomy

• Breed: Specific breeds affected (with VBO identifiers if applicable)

  Search first: VBO (Vertebrate Breed Ontology)

• Gene: Orthologous genes in other species (with NCBI Gene IDs)

  Search first: NCBI Gene

• Natural Disease:
• Naturally occurring disease in other species (companion animals, wildlife) > Search first: OMIA (Online Mendelian Inheritance in Animals), VetCompass, PubMed
• Veterinary relevance and importance in animal health > Search first: OMIA, veterinary databases, PubMed
• Comparative Biology:
• Comparative pathology (similarities and differences across species) > Search first: OMIA, comparative pathology databases, PubMed
• Evolutionary conservation of disease mechanisms > Search first: HomoloGene, OrthoMCL, Alliance of Genome Resources
• Transmission (if applicable):
• Zoonotic potential > Search first: CDC zoonotic diseases, WHO zoonoses, GIDEON
• Cross-species susceptibility > Search first: NCBI Taxonomy, veterinary databases, PubMed

15. Model Organisms

• Model Types:
• Model organism type (mammalian, invertebrate, cellular, in vitro) > Search first: Alliance of Genome Resources, model organism databases
• Specific model systems (mouse, rat, zebrafish, Drosophila, C. elegans, yeast, cell lines, organoids, iPSCs) > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, SGD, ATCC, Cellosaurus
• Induced models (drug treatment, surgical intervention, environmental manipulation) > Search first: MGI, model organism databases, PubMed
• Genetic Models:
• Types available (knockout, knock-in, transgenic, conditional, humanized) > Search first: MGI, IMPC, KOMP, EuMMCR, IMSR
• Model Characteristics:
• Phenotype recapitulation (how well model reproduces human disease features) > Search first: Model organism databases, comparative studies, PubMed
• Model limitations (aspects of human disease not captured) > Search first: Model organism databases, PubMed, review articles
• Applications:
• Research applications (what aspects of disease can be studied) > Search first: Model organism databases, PubMed
• Resources:
• Model databases > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, IMSR, EMMA, MMRRC

Citation Requirements

• Cite primary literature (PMID preferred) for all mechanistic and clinical claims
• Prioritize recent reviews and landmark papers
• Include direct quotes from abstracts where possible to support key statements
• Distinguish evidence source types: human clinical, model organism, in vitro, computational

Output Format

Structure your response as a comprehensive narrative organized by the sections above. For each section, provide: - Factual content with specific details (numbers, percentages, gene names, variant nomenclature) - Ontology term suggestions (HPO, GO, CL, UBERON, CHEBI, NCIT, MONDO) where applicable - Evidence citations with PMIDs - Direct quotes from abstracts to support key claims - Clear indication when information is not available or not applicable for this disease

This report will be used to populate a disease knowledge base entry with: - Pathophysiology descriptions with causal chains - Gene/protein annotations (HGNC, GO terms) - Phenotype associations (HP terms) with frequencies - Cell type involvement (CL terms) - Anatomical locations (UBERON terms) - Chemical entities (CHEBI terms) - Treatment annotations (NCIT terms) - Evidence items with PMIDs and exact abstract quotes - Epidemiology, prognosis, diagnostic, and prevention information - Animal model descriptions with phenotype recapitulation details

Dilated Cardiomyopathy 1JJ (DCM1JJ): comprehensive disease-characteristics report

Executive assessment and evidence boundary

Dilated cardiomyopathy 1JJ is an ultra-rare, historically defined Mendelian DCM subtype attributed to heterozygous variants in LAMA4, encoding laminin subunit α4. The current MONDO identifier is MONDO:0014095. Open Targets maps this disease to LAMA4 and traces its literature evidence to PMID 17646580. However, contemporary literature treats LAMA4 as a minor/limited-evidence cardiomyopathy gene, not as one of the most securely validated core DCM genes. Accordingly, a LAMA4 variant should not be assumed causal without rigorous ACMG/AMP interpretation, phenotype concordance, population-frequency review, segregation analysis, and preferably functional evidence. This distinction is essential for a knowledge base: the historical DCM1JJ assertion is real, but disease-specific clinical evidence is sparse and much of the clinical guidance below is extrapolated from genetic/nonischemic DCM generally. (OpenTargets Search: Dilated cardiomyopathy 1JJ, micolonghi2024unveilingthespectrum pages 14-15)

The principal evidence and its limitations are summarized below.

Table: This table condenses the currently retrievable evidence for Dilated Cardiomyopathy 1JJ, separating disease-specific findings from broader dilated cardiomyopathy guidance. It is useful for knowledge-base curation because it highlights both what is supported and what remains uncertain.

1. Disease information

Definition. DCM1JJ is a proposed autosomal-dominant, LAMA4-associated form of dilated cardiomyopathy. DCM itself is defined by left-ventricular or biventricular dilatation and systolic dysfunction not explained solely by coronary artery disease or abnormal loading conditions. Early disease can consist of isolated LV dilatation with preserved ejection fraction. Contemporary thresholds include LVEF <50% and LV dimensions or volumes >2 SD above body-size-, age-, and sex-adjusted norms. (arnautu2024riskassessmentand pages 2-4)

Identifiers and synonyms.

• MONDO: MONDO:0014095.
• Causal-gene assertion: LAMA4; Ensembl ENSG00000112769; protein name laminin subunit α4; gene MIM 600133. (OpenTargets Search: Dilated cardiomyopathy 1JJ, micolonghi2024unveilingthespectrum pages 14-15)
• Common labels: dilated cardiomyopathy 1JJ, cardiomyopathy, dilated, 1JJ, CMD1JJ, and LAMA4-related dilated cardiomyopathy.
• OMIM disease number: the retrieved evidence did not expose a reliable disease-entry number; it should be verified directly in OMIM before database ingestion.
• Orphanet: no DCM1JJ-specific identifier was established in the retrieved evidence.
• ICD-10/ICD-11 and MeSH do not ordinarily encode this molecular subtype separately; it falls under generic dilated cardiomyopathy/cardiomyopathy categories.

The information is primarily aggregated disease-level evidence from MONDO/Open Targets and review literature, ultimately based on a very small historical human genetic report—not EHR-derived population data. Open Targets records four association evidence items, including PMID 17646580 and ClinVar records RCV005860793 and RCV005860860. (OpenTargets Search: Dilated cardiomyopathy 1JJ)

2. Etiology, risk, protection, and gene–environment interaction

Genetic cause

The asserted cause is a germline heterozygous LAMA4 variant. Two historical protein changes are repeatedly cited:

• p.Pro943Leu, a missense substitution.
• p.Arg1073Ter, a nonsense/truncating substitution, also written p.Arg1073*.

Both were described within or near an integrin-interacting region and proposed to impair laminin–integrin interaction. Their precise current ClinVar classifications, transcript-level HGVS expressions, allele frequencies, and ACMG criteria should be checked against the current reference transcript and ClinVar/gnomAD release before clinical use. The retrieved literature does not justify assigning all rare LAMA4 variants as pathogenic. (micolonghi2024unveilingthespectrum pages 14-15)

Other risk factors and second hits

No DCM1JJ-specific quantitative risk-factor study exists. Factors that can precipitate or worsen DCM generally include viral or inflammatory myocardial injury, sustained tachyarrhythmia, pregnancy, alcohol, cardiotoxic chemotherapy, illicit drugs, thyroid disease, and other hemodynamic stressors. In broader inherited DCM, pregnancy can uncover latent disease; up to 15% of peripartum cardiomyopathy patients in cited contemporary literature carry pathogenic cardiomyopathy variants. These are plausible modifiers of LAMA4-related susceptibility but have not been demonstrated specifically for DCM1JJ. (arnautu2024riskassessmentand pages 2-4)

Family history, young onset, unexplained syncope, ventricular arrhythmia, conduction disease, and associated muscle disease increase suspicion of a genetic DCM. Broader DCM studies identify a genetic cause in approximately 20–35% of presumed idiopathic cases. (arnautu2024riskassessmentand pages 2-4)

Protective factors

No genetic protective variant, modifier allele, diet, drug, or exposure has been validated specifically for DCM1JJ. Avoidance of cardiotoxins, prompt treatment of hypertension and arrhythmias, guideline-directed heart-failure treatment, and individualized exercise are rational tertiary-prevention measures but should not be encoded as LAMA4-specific protection.

Gene–environment model

A biologically plausible model is: inherited weakening of the laminin-rich cardiac/vascular basement membrane → reduced tolerance of mechanical or inflammatory stress → impaired cell–matrix signaling and myocardial remodeling → ventricular dilatation and systolic failure. This remains a mechanistic hypothesis supported by models rather than a quantified human LAMA4 gene–environment interaction. (micolonghi2024unveilingthespectrum pages 14-15)

3. Phenotypes

Disease-specific frequencies and onset distributions are unavailable. Suggested phenotypes therefore combine the defining DCM phenotype with recognized downstream manifestations; frequencies must be coded as unknown for DCM1JJ.

• Dilated cardiomyopathy / LV dilatation — clinical sign/imaging abnormality; HPO HP:0001644. Likely progressive but variably expressed.
• Reduced LV systolic function — imaging/functional abnormality; HP:0005162 or the current HPO term for decreased LV ejection fraction. Severity ranges from subclinical dysfunction to end-stage failure.
• Congestive heart failure — sign/syndrome; HP:0001635. Associated symptoms include dyspnea (HP:0002094), fatigue (HP:0012378), exercise intolerance (HP:0003546), peripheral edema (HP:0012398), and orthopnea (HP:0012764).
• Cardiomegaly — imaging/physical sign; HP:0001640.
• Arrhythmia/palpitations — symptom/electrophysiological phenotype; HP:0011675 and HP:0001962. Ventricular arrhythmia, atrial arrhythmia, syncope, or sudden cardiac death are possible in DCM generally but were not quantified for DCM1JJ.
• Elevated BNP/NT-proBNP — laboratory abnormality reflecting myocardial wall stress; an exact HPO term should be selected from the current release.
• Intracardiac thrombus/systemic embolism — complication of severe LV dysfunction; not documented as a recurrent LAMA4-specific feature.

General DCM presentation ranges from asymptomatic disease found by family screening to severe heart failure, life-threatening arrhythmia, stroke, or sudden death. Typical adult genetic DCM often becomes apparent in the third or fourth decade, but this cannot be assigned as the characteristic onset of DCM1JJ because the reported LAMA4 cohort is too small. (arnautu2024riskassessmentand pages 2-4)

Quality of life. No DCM1JJ-specific PROM data exist. Heart failure can restrict activity, employment, sleep, and social participation. In inherited cardiac conditions broadly, a 2024 systematic review found clinically significant anxiety in 17–47% and depression in 8.3–28%, but these figures are not DCM1JJ-specific. Appropriate instruments include KCCQ, Minnesota Living with Heart Failure Questionnaire, SF-36/SF-12, EQ-5D, HADS, PHQ-9, and GAD-7.

4. Genetic and molecular information

Gene and protein

LAMA4 encodes laminin α4, a large extracellular-matrix glycoprotein incorporated into laminin heterotrimers historically called laminins 8 and 9. These laminins are major cardiac and vascular basement-membrane constituents and participate in tissue architecture, endothelial integrity, cell adhesion, mechanotransduction, and survival signaling. (micolonghi2024unveilingthespectrum pages 14-15)

Suggested annotations include extracellular matrix structural constituent, integrin binding, basement-membrane organization, cell adhesion, and extracellular-matrix–receptor interaction. Useful GO suggestions are extracellular matrix organization (GO:0030198), cell adhesion (GO:0007155), integrin-mediated signaling pathway (GO:0007229), and basement membrane (GO:0005604).

Variant interpretation

The two historically implicated variants are germline, heterozygous, missense p.Pro943Leu and nonsense p.Arg1073Ter. The proposed consequence is impaired laminin–integrin interaction; for the truncating allele, loss of function or production of a shortened protein is plausible, but transcript-specific nonsense-mediated decay was not established in the retrieved evidence. A dominant-negative versus haploinsufficiency mechanism remains unresolved. (micolonghi2024unveilingthespectrum pages 14-15)

No reliable DCM1JJ-specific data were retrieved for:

• current gnomAD/TOPMed allele counts;
• de novo status or germline mosaicism;
• penetrance by age or sex;
• variant-specific expressivity;
• founder effects or carrier frequency;
• validated modifier genes;
• disease-specific methylation, histone, or chromatin signatures;
• recurrent CNVs, translocations, inversions, or aneuploidies.

The reported interaction with ILK is mechanistically relevant because ILK connects integrin adhesion complexes to intracellular signaling, but it should not be encoded as an established DCM1JJ modifier gene. (micolonghi2024unveilingthespectrum pages 14-15, micolonghi2024unveilingthespectrum pages 15-16)

5. Environmental information

No toxin, lifestyle factor, or infectious agent causes DCM1JJ; it is a proposed genetic disorder. Nevertheless, acquired myocardial stressors can modify generic DCM expression. Clinically relevant exposures to assess include alcohol, cocaine/amphetamines, anthracyclines, trastuzumab and other cardiotoxic therapies, radiation, uncontrolled hypertension, sustained tachycardia, pregnancy, myocarditis, endocrine disease, and nutritional deficiency. Broader DCM evaluation specifically requires excluding coronary disease, abnormal loading, valvular/congenital disease, thyroid disease, inflammatory/infectious disease, radiation, and toxins. (arnautu2024riskassessmentand pages 2-4)

Smoking, obesity, inactivity, excessive alcohol, and poorly controlled metabolic disease contribute to overall cardiovascular and heart-failure risk, although none is proven to alter LAMA4 penetrance. Viral infection is best classified as a potential trigger/alternative etiology, not an infectious cause of DCM1JJ.

6. Mechanism and pathophysiology

Proposed causal chain

1. Upstream genetic lesion: a functionally damaging LAMA4 allele alters laminin α4 quantity or an integrin-interacting region.
2. Matrix/receptor defect: cardiac and microvascular basement-membrane organization and laminin–integrin binding are impaired.
3. Cellular consequences: weaker endothelial/cardiomyocyte adhesion, abnormal mechanotransduction, and disturbed integrin–ILK–AKT survival/stress signaling reduce tissue resilience.
4. Tissue response: vascular instability, cardiomyocyte stress or loss, compensatory hypertrophy, extracellular-matrix remodeling, and fibrosis develop.
5. Organ phenotype: ventricular wall stress rises; the ventricle dilates and systolic contractility falls.
6. Clinical consequences: heart failure, exercise intolerance, arrhythmia, thromboembolism, transplantation, or premature death may follow.

The strongest disease-specific support is at steps 1–3 and in animal phenocopy; downstream events are established DCM biology but not uniquely profiled in DCM1JJ. The 2024 review states that the variants “disrupt the interaction between laminins and integrin receptors,” affecting adhesion and signal transduction. (micolonghi2024unveilingthespectrum pages 14-15)

Cells, tissues, and ontology suggestions

Relevant cell types include cardiomyocytes (CL:0000746), vascular endothelial cells (CL:0000115), cardiac fibroblasts, vascular smooth-muscle cells, and pericytes. Suggested biological-process terms include cardiac muscle contraction (GO:0060048), regulation of cell–matrix adhesion, response to mechanical stimulus (GO:0009612), angiogenesis (GO:0001525), and extracellular-matrix organization (GO:0030198).

At the subcellular level, the primary compartment is extracellular rather than mitochondrial or nuclear: basement membrane (GO:0005604), extracellular matrix (GO:0031012), and integrin-containing focal-adhesion complexes. Downstream sarcomeric dysfunction, mitochondrial energy deficiency, oxidative stress, inflammation, and fibrosis may occur in failing myocardium but no DCM1JJ-specific multi-omic study validates them.

Profiling and advanced technologies

No DCM1JJ-specific human cardiac transcriptomic, proteomic, metabolomic, lipidomic, single-cell, spatial-transcriptomic, CRISPR-screen, or integrated multi-omic dataset was identified. These should be represented as not available, not as negative findings.

7. Anatomical structures affected

The primary organ is the heart (UBERON UBERON:0000948), especially ventricular myocardium and the left ventricle. The right ventricle can be secondarily involved in general DCM but is not required for diagnosis. Relevant structures include myocardium (UBERON:0002349), cardiac ventricle, interventricular septum, cardiac microvasculature, and vascular basement membranes. (arnautu2024riskassessmentand pages 2-4)

Secondary involvement can include lungs through pulmonary congestion, liver through venous congestion, kidneys through reduced perfusion/congestion, and brain or systemic arteries through embolism. These are complications of advanced heart failure rather than primary LAMA4 organ phenotypes.

No lateralization applies. The disease is diffuse rather than unilateral. Mouse LAMA4 deficiency can also affect vascular and renal basement membranes, but these findings should not automatically be added to the human DCM1JJ phenotype. (micolonghi2024unveilingthespectrum pages 14-15)

8. Temporal development

DCM1JJ-specific age of onset, latency, and progression rate are unknown. Genetic DCM can remain preclinical for years and then evolve from genotype-positive/phenotype-negative status to subtle electrical or imaging abnormalities, LV enlargement, systolic dysfunction, symptomatic heart failure, and end-stage disease. The course can be slowly progressive, episodically worsened by stressors, or partially reversible with therapy.

Critical opportunities are:

• before symptoms, through cascade testing and ECG/imaging surveillance;
• at detection of LV dysfunction, through rapid initiation of guideline-directed therapy;
• during pregnancy, cardiotoxic exposure, systemic infection, or sustained arrhythmia;
• after apparent recovery, because genetic susceptibility persists and therapy withdrawal can permit relapse.

No disease-specific spontaneous-remission rate is available. Reverse remodeling in general DCM is possible, but it is not equivalent to genetic cure.

9. Inheritance and population

The historical classification is autosomal dominant, implying a theoretical 50% transmission probability from a heterozygous affected parent. Nevertheless, penetrance and expressivity are likely variable and have not been quantified for LAMA4. There is no evidence of anticipation, consanguinity dependence, a recurrent founder allele, or a defined carrier frequency.

No prevalence, incidence, ethnic enrichment, geographic clustering, sex ratio, or age distribution exists for DCM1JJ. Generic DCM epidemiology should not be assigned to this subtype. In DCM cohorts, systematic family evaluation historically identifies familial disease in about 20–30%; one multicenter analysis estimated >30% after relatives were evaluated, while 20–35% of presumed idiopathic DCM carries an identifiable related variant. These values concern DCM broadly. (arnautu2024riskassessmentand pages 2-4)

10. Diagnostics

Clinical diagnosis

Evaluation begins with history, three-generation pedigree, examination, ECG, ambulatory rhythm monitoring when indicated, echocardiography, and laboratory testing. Echocardiography is first-line for chamber size and ventricular function. CMR provides high-resolution morphology, function, and tissue characterization; in DCM it distinguishes ischemic scar from nonischemic mid-wall, patchy, or subepicardial fibrosis. (gasior2024advancesincardiac pages 2-5, gasior2024advancesincardiac pages 5-7)

Laboratory testing commonly includes BNP/NT-proBNP, troponin, blood count, electrolytes, renal and liver function, thyroid studies, iron indices, and cause-directed infectious, autoimmune, metabolic, or toxicology studies. Endomyocardial biopsy is reserved for selected suspected inflammatory, infiltrative, or rapidly progressive presentations. Coronary assessment is required when ischemic disease is plausible. (arnautu2024riskassessmentand pages 2-4)

Genetic testing

A phenotype-driven cardiomyopathy multigene panel using validated genes is generally preferable to isolated LAMA4 sequencing. Testing must cover SNVs and small indels, with deletion/duplication analysis where appropriate. WES/WGS can be considered after negative panel testing, syndromic presentations, complex pedigrees, or suspected structural/noncoding variants; RNA sequencing can clarify selected splice variants but is not a routine DCM1JJ diagnostic.

Because LAMA4 has limited/minor-gene evidence, a VUS must not drive predictive testing, ICD implantation, reproductive decisions, or exclusion of relatives from surveillance. Only a convincingly pathogenic/likely pathogenic familial variant should be used for cascade genetic testing. Variant reinterpretation over time is important. (micolonghi2024unveilingthespectrum pages 14-15)

CMA, karyotyping, FISH, mitochondrial sequencing, and repeat-expansion testing are not routine for isolated DCM1JJ, but may be appropriate when the phenotype suggests a chromosomal, mitochondrial, neuromuscular, or syndromic disorder.

Differential diagnosis

Exclude ischemic cardiomyopathy, hypertensive/valvular/congenital disease, myocarditis, tachycardia-induced cardiomyopathy, alcohol/toxic cardiomyopathy, peripartum cardiomyopathy, cardiac sarcoidosis, hemochromatosis, amyloidosis, endocrine/nutritional disease, muscular dystrophy, arrhythmogenic cardiomyopathy, LV noncompaction trait, and other genetic DCMs. (arnautu2024riskassessmentand pages 2-4, gasior2024advancesincardiac pages 5-7)

Screening

First-degree relatives require genetic counseling and baseline ECG plus echocardiography; CMR and ambulatory monitoring are used when findings, genotype, or family history warrant. Serial evaluation is appropriate because penetrance can be age-dependent. There is no newborn population-screening program for DCM1JJ.

11. Outcome and prognosis

No LAMA4-specific survival curve, transplant rate, recovery rate, or prognostic biomarker has been reported. Prognosis should therefore be estimated from phenotype severity, LVEF trajectory, symptoms, ventricular arrhythmias, conduction disease, CMR scar, right-ventricular dysfunction, biomarkers, exercise capacity, and response to therapy—not from the DCM1JJ label alone.

The strongest recent quantitative evidence is the 2024 JAMA meta-analysis of 103 studies and 29,687 patients with nonischemic DCM. Presence of CMR late gadolinium enhancement was associated with all-cause mortality (HR 1.81), cardiovascular mortality (HR 2.43), arrhythmic events (HR 2.69), and heart-failure events (HR 1.98). Each additional 1% LGE extent also increased risk. The authors concluded: “The presence and extent of LGE were associated with various adverse clinical outcomes,” whereas LVEF was not significantly associated with mortality or arrhythmic endpoints. These data strongly support CMR-based risk assessment but are not LAMA4-specific. Publication: 19 September 2024; DOI https://doi.org/10.1001/jama.2024.13946. (eichhorn2024riskstratificationin pages 1-2, eichhorn2024riskstratificationin pages 2-3)

In pediatric DCM generally, a 2024 review reports that nearly 40% undergo transplantation or die within two years. This is useful context only; the onset of DCM1JJ is not established as pediatric. Publication: 19 June 2024; DOI https://doi.org/10.3389/fped.2024.1404942. (malinow2024pediatricdilatedcardiomyopathy pages 1-2)

Complications include progressive heart failure, malignant ventricular arrhythmia, sudden cardiac death, atrial fibrillation, intracardiac thrombus, embolic stroke, secondary mitral regurgitation, pulmonary hypertension, renal/hepatic dysfunction, hospitalization, mechanical circulatory support, and transplantation.

12. Treatment

There is no approved LAMA4-directed therapy, gene therapy, RNA therapy, or variant-specific pharmacotherapy, and no DCM1JJ-specific clinical trial was identified.

For symptomatic DCM with reduced EF, current care follows HFrEF guideline-directed treatment:

• ARNI, ACE inhibitor, or ARB;
• evidence-based β-blocker;
• mineralocorticoid-receptor antagonist;
• SGLT2 inhibitor;
• loop diuretic for congestion;
• selected use of ivabradine, hydralazine–isosorbide dinitrate, digoxin, vericiguat, and intravenous iron according to phenotype and guideline criteria.

Suggested NCIt intervention concepts include pharmacotherapy, angiotensin-receptor neprilysin inhibitor therapy, beta-blocker therapy, mineralocorticoid-receptor antagonist therapy, SGLT2-inhibitor therapy, diuretic therapy, implantable cardioverter-defibrillator placement, cardiac resynchronization therapy, ventricular-assist device placement, and heart transplantation. Exact NCIt codes should be resolved against the current NCIt release.

ICD and CRT decisions use standard heart-failure and arrhythmic-risk criteria, integrating EF, symptoms, QRS morphology/duration, ventricular arrhythmia, syncope, genotype, and CMR fibrosis. LAMA4 is not currently an established high-arrhythmic-risk genotype comparable to LMNA, FLNC, RBM20, PLN, or desmosomal disease. The 2024 CMR evidence argues against relying on EF alone. (eichhorn2024riskstratificationin pages 1-2, eichhorn2024riskstratificationin pages 2-3)

Advanced disease may require LVAD or transplantation. Cardiac rehabilitation, sodium/fluid counseling when indicated, vaccination, psychosocial care, pregnancy counseling, and individualized exercise are supportive measures. Competitive or very high-intensity exercise decisions should be personalized to ventricular function, scar and arrhythmia burden.

13. Prevention

Primary prevention of the genotype is not possible after conception. Reproductive options for a confirmed pathogenic familial allele include preconception counseling, prenatal diagnosis, donor gametes, adoption, and preimplantation genetic testing. Such decisions require strong variant classification; PGT is inappropriate for a VUS.

Secondary prevention consists of pedigree assessment, cascade genetic testing for a pathogenic familial variant, and serial ECG/imaging surveillance of at-risk relatives. Early recognition permits treatment before advanced remodeling.

Tertiary prevention includes guideline-directed therapy, arrhythmia surveillance, ICD/CRT where indicated, management of blood pressure and metabolic disease, avoidance of excess alcohol and illicit stimulants, prompt treatment of sustained tachyarrhythmias, and minimizing cardiotoxic exposure. Influenza, COVID-19, and pneumococcal vaccination follow routine heart-failure recommendations; no vaccine prevents DCM1JJ.

14. Other species and natural disease

No naturally occurring veterinary disorder definitively equivalent to human DCM1JJ was identified. Therefore, no breed-specific VBO term, prevalence, zoonotic risk, or cross-species transmission applies. The disorder is noninfectious and nonzoonotic.

LAMA4 orthologues are conserved in mammals and fish. Relevant research species include Mus musculus (NCBI Taxonomy 10090) and Danio rerio (7955). Orthologue identifiers should be retrieved directly from NCBI Gene/Alliance before database loading.

Naturally occurring canine DCM is important in veterinary medicine, but breed-associated canine DCM should not be attributed to LAMA4 without direct evidence.

15. Model organisms and experimental systems

Mouse

Global Lama4-deficient mice show disrupted vascular endothelial basement membranes, hemorrhage and anemia, followed by cardiac hypertrophy and heart failure. This supports a requirement for laminin α4 in vascular and cardiac integrity. Limitations include a systemic null state that may be more severe and mechanistically broader than heterozygous human missense/truncating disease. (micolonghi2024unveilingthespectrum pages 14-15)

Zebrafish

LAMA4 knockdown produces hemorrhage and severe cardiac dysfunction, providing rapid in-vivo support for vascular/cardiac developmental roles. Limitations include transient knockdown, developmental effects, and anatomical/physiological differences from adult human DCM. (micolonghi2024unveilingthespectrum pages 14-15)

Cellular models

The ideal disease-specific system would be CRISPR knock-in or patient-derived iPSC cardiomyocytes combined with endothelial cells and engineered cardiac tissue. Readouts should include laminin secretion/deposition, basement-membrane ultrastructure, integrin binding, ILK–AKT signaling, adhesion under mechanical load, contractile force, conduction, cell survival, and rescue by wild-type LAMA4. No well-validated DCM1JJ iPSC or organoid model was identified.

Key recent developments and expert interpretation

The major 2023–2024 development is not a LAMA4-specific therapy, but a change in how cardiomyopathy is evaluated: deep phenotyping, CMR tissue characterization, and cautious gene-validity/variant interpretation are increasingly integrated. Echocardiography remains first-line, while CMR is central for etiology and fibrosis assessment. NGS is routine, but the discovery of rare variants in “minor genes” creates a substantial risk of overdiagnosis. (gasior2024advancesincardiac pages 2-5, gasior2024advancesincardiac pages 5-7, micolonghi2024unveilingthespectrum pages 14-15)

For DCM1JJ, the most defensible expert conclusion is therefore: retain the disease–gene association as historically supported but limited; do not treat a rare LAMA4 variant as diagnostic by itself; and manage confirmed cardiomyopathy according to contemporary DCM/HFrEF standards while pursuing segregation, functional validation, and periodic variant reinterpretation.

Selected sources, dates, and URLs

1. Knöll et al., original LAMA4/ILK human DCM report, 2007, PMID 17646580: https://pubmed.ncbi.nlm.nih.gov/17646580/ . This is the primary historical evidence linked by Open Targets. (OpenTargets Search: Dilated cardiomyopathy 1JJ)
2. Micolonghi et al., “Unveiling the Spectrum of Minor Genes in Cardiomyopathies,” published September 2024; DOI: https://doi.org/10.3390/ijms25189787 . (micolonghi2024unveilingthespectrum pages 14-15)
3. Eichhorn et al., “Risk Stratification in Nonischemic Dilated Cardiomyopathy Using CMR Imaging,” published online 19 September 2024; DOI: https://doi.org/10.1001/jama.2024.13946 . (eichhorn2024riskstratificationin pages 1-2)
4. Malinow et al., “Pediatric dilated cardiomyopathy,” published 19 June 2024; DOI: https://doi.org/10.3389/fped.2024.1404942 . (malinow2024pediatricdilatedcardiomyopathy pages 1-2)
5. Gasior, “Advances in Cardiac Imaging and Genetic Testing…2024 Update,” published November 2024; DOI: https://doi.org/10.3390/jcm13237166 . (gasior2024advancesincardiac pages 2-5, gasior2024advancesincardiac pages 5-7)
6. Arnautu et al., “Risk Assessment and Personalized Treatment Options in Inherited Dilated Cardiomyopathies,” published July 2024; DOI: https://doi.org/10.3390/biomedicines12081643 . (arnautu2024riskassessmentand pages 2-4)

Knowledge-base curation cautions

The following fields should explicitly be marked unknown/not established, rather than inferred: DCM1JJ prevalence, incidence, penetrance, sex ratio, onset distribution, phenotype frequencies, variant carrier frequency, founder effect, anticipation, germline mosaicism, protective factors, validated modifiers, disease-specific biomarkers, omics signatures, quality-of-life estimates, survival rates, treatment-response rates, and targeted clinical trials. The mechanistic chain is biologically coherent, but human evidence remains sparse and animal null/knockdown phenotypes do not by themselves prove that every heterozygous human LAMA4 variant causes DCM.

References

1. (OpenTargets Search: Dilated cardiomyopathy 1JJ): Open Targets Query (Dilated cardiomyopathy 1JJ, 1 results). Buniello, A. et al. (2025). Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery. Nucleic Acids Research.

2. (micolonghi2024unveilingthespectrum pages 14-15): Caterina Micolonghi, Federica Perrone, Marco Fabiani, Silvia Caroselli, Camilla Savio, Antonio Pizzuti, Aldo Germani, Vincenzo Visco, Simona Petrucci, Speranza Rubattu, and Maria Piane. Unveiling the spectrum of minor genes in cardiomyopathies: a narrative review. International Journal of Molecular Sciences, 25:9787, Sep 2024. URL: https://doi.org/10.3390/ijms25189787, doi:10.3390/ijms25189787. This article has 11 citations.

3. (arnautu2024riskassessmentand pages 2-4): Diana-Aurora Arnautu, Dragos Cozma, Ioan-Radu Lala, Sergiu-Florin Arnautu, Mirela-Cleopatra Tomescu, and Minodora Andor. Risk assessment and personalized treatment options in inherited dilated cardiomyopathies: a narrative review. Biomedicines, 12:1643, Jul 2024. URL: https://doi.org/10.3390/biomedicines12081643, doi:10.3390/biomedicines12081643. This article has 9 citations.

4. (gasior2024advancesincardiac pages 2-5): Tomasz Gasior. Advances in cardiac imaging and genetic testing for diagnosis and risk stratification in cardiomyopathies: 2024 update. Journal of Clinical Medicine, 13:7166, Nov 2024. URL: https://doi.org/10.3390/jcm13237166, doi:10.3390/jcm13237166. This article has 12 citations.

5. (gasior2024advancesincardiac pages 5-7): Tomasz Gasior. Advances in cardiac imaging and genetic testing for diagnosis and risk stratification in cardiomyopathies: 2024 update. Journal of Clinical Medicine, 13:7166, Nov 2024. URL: https://doi.org/10.3390/jcm13237166, doi:10.3390/jcm13237166. This article has 12 citations.

6. (eichhorn2024riskstratificationin pages 1-2): Christian Eichhorn, David Koeckerling, Rohin K Reddy, Maddalena Ardissino, Marek Rogowski, Bernadette Coles, Lukas Hunziker, Simon Greulich, Isaac Shiri, Norbert Frey, Jens Eckstein, Stephan Windecker, Raymond Y Kwong, George C M Siontis, and Christoph Gräni. Risk stratification in nonischemic dilated cardiomyopathy using cmr imaging: a systematic review and meta-analysis. JAMA, Sep 2024. URL: https://doi.org/10.1001/jama.2024.13946, doi:10.1001/jama.2024.13946. This article has 44 citations.

7. (eichhorn2024riskstratificationin pages 2-3): Christian Eichhorn, David Koeckerling, Rohin K Reddy, Maddalena Ardissino, Marek Rogowski, Bernadette Coles, Lukas Hunziker, Simon Greulich, Isaac Shiri, Norbert Frey, Jens Eckstein, Stephan Windecker, Raymond Y Kwong, George C M Siontis, and Christoph Gräni. Risk stratification in nonischemic dilated cardiomyopathy using cmr imaging: a systematic review and meta-analysis. JAMA, Sep 2024. URL: https://doi.org/10.1001/jama.2024.13946, doi:10.1001/jama.2024.13946. This article has 44 citations.

8. (malinow2024pediatricdilatedcardiomyopathy pages 1-2): Ian Malinow, Daniel C. Fong, Matthew Miyamoto, Sarah Badran, and Charles C. Hong. Pediatric dilated cardiomyopathy: a review of current clinical approaches and pathogenesis. Frontiers in Pediatrics, Jun 2024. URL: https://doi.org/10.3389/fped.2024.1404942, doi:10.3389/fped.2024.1404942. This article has 41 citations.

9. (micolonghi2024unveilingthespectrum pages 15-16): Caterina Micolonghi, Federica Perrone, Marco Fabiani, Silvia Caroselli, Camilla Savio, Antonio Pizzuti, Aldo Germani, Vincenzo Visco, Simona Petrucci, Speranza Rubattu, and Maria Piane. Unveiling the spectrum of minor genes in cardiomyopathies: a narrative review. International Journal of Molecular Sciences, 25:9787, Sep 2024. URL: https://doi.org/10.3390/ijms25189787, doi:10.3390/ijms25189787. This article has 11 citations.

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