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Record W4406903919 · doi:10.1101/2025.01.20.633995

Spatial gene expression of human coronary arteries revealed the molecular features of diffuse intimal thickening in explanted hearts

2025· preprint· en· W4406903919 on OpenAlexafffund
Boaz Li, Samuel Leung, Maria Elishaev, Wan-Hei Cheng, Giuseppe Mocci, Johan Björkegren, Chi Lai, Amrit Singh, Ying Wang

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsProvidence Health CareUniversity of British Columbia
FundersProvidence Health CareHeart and Stroke Foundation of Canada
KeywordsThickeningCoronary arteriesCardiologyInternal medicineArteryPathologyAnatomyMedicineChemistry

Abstract

fetched live from OpenAlex

Abstract Background Diffuse intimal thickening (DIT) is a pre-clinical stage of atherosclerosis characterized by thickened intima. The molecular basis of its susceptibility to atherogenesis is unknown, and mechanistic investigations cannot be performed in commonly used mouse models, in which DIT does not exist. Vascular smooth muscle cells (SMCs) are the predominant cell type that occupies the intima and media of DIT. The molecular differences between these two layers may reveal the earliest phenotypic changes in SMCs to promote atherosclerosis. Methods We benchmarked the RNA quality of human coronary arteries from autopsies (n=7) and freshly explanted hearts (n=7) and performed Visium spatial gene expression on tissue sections with DIT. SMC-enriched intima and media were compared to find differentially expressed genes. The gene ontology features of SMC-enriched intima in this study were also compared to those in the atherosclerotic lesions, as previously revealed by single-cell RNA-sequencing studies. Results Although autopsy samples met the RNA quality standard for Visium (DV200 ≥ 30%), only arteries from freshly explanted hearts exhibited reliable performance. Genes enriched in TGF-β-mediated remodeling of the extracellular matrix were overrepresented in the intima, including versican and biglycan. SMCs enriched in the intima are dedifferentiated, but unlike those in the lesions, they are not proinflammatory. Conclusions Our findings indicate that autopsy samples are not ideal to distinguish subtle differences among cell phenotypes. Dedifferentiated SMCs in the DIT are distinct from the proinflammatory SMCs in atherosclerotic lesions. SMCs in thickened intima may lead to lipid retention but not necessarily the onset of atherosclerosis. Research Perspective: 1) What is New? Postmortem coronary arteries, which are frequently collected by biobanks, have degraded RNA, which are not suitable for identifying subtle differences in the transcriptome profiles. Coronary arteries from explanted hearts allow for more faithful representation of spatial gene expression across the vessel wall as compared to ones from autopsy hearts. Thickened intima in diffuse intimal thickening, which exists in everyone, is unlikely to undergo atherogenesis without additional stimuli such as inflammation. 2) What Question Should be Addressed Next? The current RNA quality standard of spatial transcriptomics needs to be carefully benchmarked in biobank samples to control sequencing performance and meaningful data interpretation. How inflammation changes smooth muscle cell phenotypes may explain why everyone has diffuse intimal thickening, but those with chronic inflammatory disease have a high risk of coronary artery disease. Future research should focus on the interplay between smooth muscle cell phenotypes and the extracellular matrix to understand the etiology of coronary artery disease.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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
Published2025
Admission routes2
Has abstractyes

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