MétaCan
Menu
Back to cohort
Record W3112073911 · doi:10.1101/2020.12.10.20247197

An Evidence-based Assessment of Genes in Dilated Cardiomyopathy

2020· preprint· en· W3112073911 on OpenAlexaff
Elizabeth Jordan, Laiken Peterson, Tomohiko Ai, Babken Asatryan, Lucas Bronicki, Emily Brown, Rudy Celeghin, Matthew Edwards, Judy Fan, Jodie Ingles, Cynthia A. James, Olga Jarinova, Renée Johnson, Daniel P. Judge, Najim Lahrouchi, Ronald H. Lekanne Deprez, R Thomas Lumbers, Francesco Mazzarotto, Argelia Medeiros‐Domingo, Rebecca L. Miller, Ana Morales, Brittney Murray, Stacey Peters, Kalliopi Pilichou, Alexandros Protonotarios, Christopher Semsarian, Palak Shah, Petros Syrris, Courtney Thaxton, J. Peter van Tintelen, Roddy Walsh, Jessica Wang, James S Ware, Ray E. Hershberger

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersNational Heart, Lung, and Blood InstituteNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of HealthNational Human Genome Research InstituteInnovative Medicines InitiativeOhio State UniversityNational Institute for Health and Care ResearchImperial College LondonUK Research and InnovationWellcome Trust
KeywordsLMNAMYH7GeneDilated cardiomyopathyGeneticsBiologyGenetic heterogeneityGenetic testingComputational biologyMedicinePhenotypeInternal medicineHeart failure

Abstract

fetched live from OpenAlex

Background: The cardiomyopathies are classically categorized as hypertrophic (HCM), dilated (DCM), and arrhythmogenic right ventricular (ARVC), and each have a signature genetic theme. HCM and ARVC are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning more than 10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted. Methods: An international Panel with clinical and scientific expertise in DCM genetics was assembled to evaluate evidence supporting monogenic relationships of genes with idiopathic DCM. The Panel utilized the ClinGen semi-quantitative gene-disease clinical validity classification framework. Results: Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from eight gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%) (ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including two additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of the 19 genes classified as definitive, strong or moderate, six were similarly classified for HCM and three for ARVC. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of 16 commercially available genetic testing panels evaluated, most definitive genes were included, but panels also included numerous genes with minimal human evidence. Conclusions: In a systematic curation of published evidence for genes considered relevant for monogenic DCM, 12 were classified as definitive or strong and seven as moderate evidence spanning 10 gene ontologies. Notably, these 19 genes only explain a minority of DCM cases, leaving the remainder of DCM genetic architecture incompletely addressed. While clinical genetic testing panels include most high evidence genes, genes lacking robust evidence are also commonly included. Until the genetic architecture of DCM is more fully defined, care should be taken in the interpretation of variable evidence DCM genes in clinical practice.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.363
Teacher spread0.283 · 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 teacher head, not a consensus.

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

Citations41
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuemedRxivSame topicCardiomyopathy and Myosin StudiesFrench-language works237,207