The Genetics of Dilated Cardiomyopathy: A Prioritized Candidate Gene Study of <i><scp>LMNA</scp></i>, <i><scp>TNNT2</scp></i>, <i><scp>TCAP</scp></i>, and <scp><i>PLN</i></scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Dilated cardiomyopathy (DCM), which is characterized by left ventricular enlargement and systolic dysfunction, is divided into cases with a clear predisposing condition (eg, hypothyroidism, chemotherapeutic agents, alcoholism, ischemia) and those of unknown cause (idiopathic DCM). Many cases (20%-35%) of DCM are familial, implicating a genetic contribution to the etiology. More than 30 genes have been identified, many involving "private" mutations not shared among families. Evidence suggests that nonfamilial cases also have a genetic predisposition, again involving many genes. The goal of this study was to identify mutations in genes associated with DCM in a Québec study sample including familial and nonfamilial DCM cases. HYPOTHESIS: A prioritized gene study conducted within a framework for the classification of identified genetic variants could yield etiological information even in the absence of family data. METHODS: We sequenced 4 previously identified genes: lamin A/C (LMNA), cardiac troponin T type 2 (TNNT2), titin-cap (TCAP), and phospholamban (PLN). RESULTS: We discovered a nonsense mutation in the LMNA gene and a frameshift mutation in the TNNT2 gene, as well as other clinically significant variants that were not observed in publicly available databases or in Québec-based controls. PLN was sequenced to investigate a previously published promoter variant. However, our data confirm that this variant does not have a causal role in DCM. CONCLUSIONS: Despite high locus and allele heterogeneity, we demonstrate that a prioritized gene study, combined with next-generation exome-sequencing data, can be fruitful for the identification of DCM mutations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it