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Record W2973079251 · doi:10.1093/ehjci/ehaa946.2097

Discovery and analyses of pathogenic variants in explanted hearts from primary cardiomyopathy patients

2020· article· en· W2973079251 on OpenAlexaff
Oddný Brattberg Gunnarsdóttir, Y Kim, Daniel Reichart, Quynh Nguyen, H Zhang, Anish Nikhanj, Ana Carolina Pereira, Josh Gorham, Steven R. DePalma, Jonathan G. Seidman, G. Oudit, Christine E. Seidman

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCardiomyopathyMissense mutationMedicineHypertrophic cardiomyopathySanger sequencingDilated cardiomyopathyExome sequencingPopulationGeneticsLMNAMinor allele frequencyHeart transplantationAllele frequencyInternal medicineTransplantationAlleleHeart failureMutationGeneBiology

Abstract

fetched live from OpenAlex

Abstract Background Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are disorders of the myocardium that affect the structure and function of the heart. Purpose The primary aim of this study was to discover damaging genetic variants in myocardial tissue from patients with DCM or HCM, who underwent heart transplantation. Methods Whole exome sequencing was performed on myocardial tissue from 103 explanted hearts with diagnosis of cardiomyopathy; 80 DCM and 13 HCM. Sanger sequencing was performed to confirm the loss-of-function variants in genes known to be linked to cardiomyopathy. RNA sequencing was conducted to confirm copy number variation deletions detected in the cohort. Burden analysis was performed by comparing the frequency of variants found in the study cohort to the frequency in the population database gnomAD. Results Rare (minor allele frequency <1.0E-04) loss-of-function variants, deleterious missense variants, or copy number variation deletions, collectively described as damaging variants, were identified in cardiomyopathy genes in 42 of all 93 samples (45.2%). Damaging variants were identified in 37 of 80 DCM samples (46.3%) and 5 of 13 HCM samples (38.4%). The mean read depth for normal and variant allele were comparable. All the 28 loss-of-function variants in cardiomyopathy genes found in the cardiomyopathy cases were confirmed by Sanger sequencing. Two copy number variation deletions both in titin (TTN) were also detected and confirmed. Burden analyses showed that the genes TTN and lamin A/C (LMNA) had a higher frequency of loss-of function variants in the DCM cohort (17.5% and 3.75%, respectively) compared to the reference population with genome-wide significance (p=3.45E-22 and 4.34E-07, respectively). Furthermore, our analysis showed that deleterious missense variants in osteoclast-stimulating factor 1 (OSTF1), which previously has not been associated with cardiomyopathy, was highly enriched in the DCM cohort compared to the reference population (p=2.10E-06). Conclusions The frequency of damaging variants that are likely pathogenic (46.3%) is higher in DCM cases in this cohort compared to previous studies. These data indicate that patients with end-stage DCM are more likely to have a genetic cause for their disease. As read depth of variant and normal alleles were, these are likely germline and not mosaic variants, and can enable cascade testing in family members. Moreover, our study demonstrates that CNVs in TTN that alter the reading frame can cause DCM. Funding Acknowledgement Type of funding source: None

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.063
GPT teacher head0.295
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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