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Abstract 18325: Functional Relationship of the COL4A1/COL4A2 Locus on Chromosome 13q34 to Coronary Artery Disease (CAD)

2013· article· en· W210462639 on OpenAlexaff
Adam W. Turner, Majid Nikpay, Paulina Lau, Sébastien Soubeyrand, Ruth McPherson

Bibliographic record

VenueCirculation · 2013
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineCoronary artery diseaseCADCardiologyLocus (genetics)DiseaseInternal medicineAnatomyPathologyGeneticsGene

Abstract

fetched live from OpenAlex

Background: The COL4A1/COL4A2 locus has been linked to CAD in recent large GWAS meta-analyses. The COL4A1 and COL4A2 proteins constitute the major structural component of basement membranes, have important functional roles in angiogenesis, and mutations have been associated with diverse vascular abnormalities. We performed epistasis analysis for CAD-associated SNPs at the COL4A1/COL4A2 locus; this revealed genetic interaction with members of the TGFβ/Smad signalling pathway. Furthermore, pathway analysis of GWAS has implicated TGFβ and Smad signaling as well as the extracellular matrix as enriched CAD pathways. Bioinformatic analysis also predicted binding of Smad3 and Smad4 to the promoter region of COL4A1/COL4A2 . We sought to address the hypothesis that the TGFβ-mediated regulation of COL4A1 and COL4A2 is via Smad3/Smad4 and that this pathway is relevant to the pathogenesis of CAD. Methods and Results: Under basal conditions, HT-1080 fibroblast cells treated with TGFβ1 for 16h produced 5 fold and 3 fold increases in COL4A1 and COL4A2 mRNA respectively as measured by qRT-PCR. In contrast, 16h treatment with TGFβ1 in the presence of the specific Smad pathway inhibitor SB431542 (10nM) abolished COL4A1/COL4A2 upregulation (p<0.001). To rule out the possibility that TGFβ1 regulates COL4A1 and COL4A2 expression indirectly via a non-Smad pathway, we showed that inhibition of the JNK, p38 MAPK, and ERK pathways had no effect on COL4A1 and COL4A2 levels basally or in response to TGFβ1. siRNA knockdown (>85%) of SMAD3 in HT-1080 cells diminished the TGFβ1 upregulation of both COL4A1 and COL4A2 mRNA levels in comparison to nontarget siRNA (p<0.001). The effect of TGFβ1 on COL4A1 and COL4A2 mRNA expression was completely abolished when SMAD3 and SMAD4 were knocked-down in concert. These effects on COL4A1 and COL4A2 mRNA expression were recapitulated at the protein level by Western blotting. Conclusions: These data suggest that Smad3 and Smad4 are the downstream mediators by which TGFβ1 upregulates COL4A1 and COL4A2 expression in HT-1080 cells. This work further highlights the importance of the extracellular matrix and TGFβ/Smad signalling in the pathogenesis of CAD.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0280.001

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 head0.043
GPT teacher head0.282
Teacher spread0.239 · 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
Published2013
Admission routes1
Has abstractyes

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