Thanatogenomic Investigation of the Hydroxymethylome and Mitochondrial Genome of Cadaveric Cardiomyocytes: Proposal for a Proof-of-Concept Study
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of death in the United Arab Emirates (UAE). One of the common CVDs is hypertrophic cardiomyopathy (HCM). Recent studies conducted in heart cells of mice have shown that this condition involves a chemical modification called hydroxymethylation of the DNA of heart cells. OBJECTIVE: Objectives of the proposed research are to profile the distribution of 5-hydroxymethylation in the cardiomyocyte (CMC) genome of cadaveric cardiac tissue and cardiac biopsy specimens; to compare the hydroxymethylome of cadaveric CMCs with that of cardiac biopsy specimens from HCM patients and/or cardiac transplant patients (control) undergoing cardiac catheterization; to histologically appraise sarcomere distribution and mitochondrial morphology of CMCs in the presence of HCM; to correlate the mitochondrial genome with the HCM phenotype; and to integrate anatomy with biochemistry and genetics into the instructional design of HCM in the core medical curriculum at Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU). METHODS: Normal and hypertrophic heart specimens will be obtained from 8 whole-body cadavers (2/8, 25% control and 6/8, 75% HCM). Myocardial biopsy specimens will be obtained from cardiothoracic and transplant units at the Cleveland Clinic in Abu Dhabi, UAE. As this is a proof-of-concept study, we plan to recruit 5 patients with HCM, where HCM has been diagnosed according to the guidelines of the 2014 European Society of Cardiology Guidelines. Patients with valvular heart disease, history of myocarditis, regular alcohol consumption, or cardiotoxic chemotherapy will be excluded. The control biopsy specimens will be obtained from patients who had received heart transplants. Three investigational approaches will then be employed: (1) gross anatomical evaluation, (2) histological analysis, and (3) profiling and analysis of the hydroxymethylome. These investigations will be pursued with minor modifications, if required, to the standard protocols and in accordance with institutional policy. The objective associated with the education of health professionals will be addressed through a strategy based on Graham's knowledge translation model. RESULTS: This study is at the protocol-development stage. The validated questionnaires have been identified in relation to the objectives. The MBRU and the Cleveland Clinic Abu Dhabi Institutional Review Board (IRB) are reviewing this study. Further clarification and information can be obtained from the MBRU IRB. There is funding in place for this study (MBRU-CM-RG2019-08). Currently, we are in the process of standardizing the protocols with respect to the various molecular techniques to be employed during the course of the study. The total duration of the proposed research is 24 months, with a provision for 6 months of a no-cost extension. CONCLUSIONS: The spectrum of CVDs has recently received significant focus from the public health sector in the UAE. HCM is a common familial heart disease, contributing to the sudden increase in the mortality rate of young Emiratis in the UAE. Incorporating artificial intelligence into the identification of epigenetic risk factors associated with HCM will promote accurate diagnosis and lead to the development of improved management plans, hence, positive patient outcomes. Furthermore, integration of these findings into the instructional design of undergraduate, postgraduate, and continuous professional development medical curricula will further contribute to the body of knowledge regarding HCM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/17241.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".