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Abstract 13644: Depict Analysis Suggests Enrichment of Heart Valve Tissue Expression in African Rheumatic Heart Disease Patients From the RHDGen GWAS Study Cohort

2021· article· en· W3215532971 on OpenAlexaff
Tafadzwa Machipisa, Michael Chong, Guillaume Paré, Mark E. Engel

Bibliographic record

VenueCirculation · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsGenome-wide association studyMedicineHeart diseaseGenetic associationLocus (genetics)GeneticsInternal medicineSingle-nucleotide polymorphismBiologyGeneGenotype

Abstract

fetched live from OpenAlex

Introduction: Rheumatic heart disease (RHD) is a sequela of rheumatic fever that results in permanent heart valve damage. While it remains the primary cause of cardiac surgery in Africa, its pathophysiology is poorly understood.Genome-wide association studies (GWASs) are ‘hypothesis-free’, genetic discovery tools for common complex diseases. Recently, our African GWAS of RHD susceptibility uncovered a novel locus (11q24.1; OR=1.63; 95% CI, 1.38-1.94; P=4.36x10 -8 ) which may explain the disproportionate burden in Africans.Here we further report secondary analyses investigating tissue type expression enrichment among suggestively associated loci, to elucidate the underlying biological processes involved in RHD susceptibility. Aims and Objectives: This study sought to identify tissue types enriched in gene-set analyses associated with RHD GWAS susceptibility data in Africans. Methods: A multicenter, ethnically matched case-control GWAS was performed in 2,548 RHD cases and 2,261 controls, from eight African countries. All 4,809 participants were assessed according to the 2012 World Heart Federation (WHF) criteria for echocardiographic diagnosis of RHD. After cleaning, the GWAS data were stratified by ethnicity and an association test was run via mixed linear models in GCTA that adjusted for gender, chip type and the first ten principal components. Using the resulting GWAS summary statistics suggestive loci (P<1x10 -5 ), we conducted secondary analyses in DEPICT (Data-driven Expression Prioritized Integration for Complex Traits) to test for association with RHD and its related traits and tissues, to validate the GWAS findings. Results: DEPICT indicated promising and biologically relevant results; the most enriched tissues were heart valves (p=2.47x10 -3 ; False Discovery Rate (FDR)=<0.20). Discussion and Conclusion: Our results indicate that genetic susceptibility to RHD may involve perturbed gene expression signatures characteristic of heart valves, known for their pathogenic involvement in RHD development. Future larger studies are warranted to identify the specific genes involved.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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