MétaCan
Menu
Back to cohort
Record W4401314922 · doi:10.1016/j.jaut.2024.103297

Transcriptomic analyses of lung tissues reveal key genes associated with progression of systemic sclerosis-interstitial lung disease (SSc-ILD)

2024· article· en· W4401314922 on OpenAlex
Yehya Al-Adwi, Johanna Westra, Harry van Goor, Léon C.L.T. van Kempen, Mohammed Osman, C. Tji Gan, Wim Timens, Douwe J. Mulder

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Autoimmunity · 2024
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of Alberta
FundersTopconsortium voor Kennis en InnovatieSanofi Genzyme
KeywordsInterstitial lung diseaseFibrosisPathologyLungTranscriptomeMedicineScleroderma (fungus)Pulmonary fibrosisInternal medicineBiologyGene expressionGene

Abstract

fetched live from OpenAlex

OBJECTIVE: Systemic sclerosis-interstitial lung disease (SSc-ILD) is the leading cause of death in SSc, affecting around 50 % of the patients. Lung tissue of patients with early-stage SSc-ILD is characterized by a predominant inflammatory response with inconspicuous fibrosis, which may progress to honeycombing fibrosis. Hence, a better understanding of the molecular mechanisms underpinning SSc-ILD pathogenesis is needed to improve treatment options and progression prediction. This transcriptomic study aims to reveal the differential gene expression between control (ctrl) lung tissue and inflammatory, prefibrotic and fibrotic lung tissue to capture progression of early to late phase SSc-ILD. METHODS: Twelve explanted lungs from patients with SSc-ILD were used to analyze gene expression from formalin-fixed paraffin-embedded lung tissues with varying stages of ILD (n = 18) and control lung tissue (n = 6). The SSc-ILD tissues were stratified into three ROIs: inflammatory, prefibrotic, and fibrotic using histological assessments to define a longitudinal simulation of early to late phases of SSc-ILD. The nanoString (nS) nCounter Human Fibrosis Panel was used to profile the transcriptome in the regions of interest. Validation of potential targetswas performed with immunohistochemistry in the same tissues that were used for transcriptome analysis. RESULTS: To validate our simulation model, we performed subgroup analysis that showed an incremental increase in pathway scores related to the severity of fibrosis. Ctrl vs SSc-ILD comparison demonstrated 24 differentially expressed genes, two of which had the most pronounced p-values. Cyclin-dependent kinase inhibitor (cdkn2c) was overexpressed (P = 0.00052) in SSc-ILD compared to ctrl, while expression of Pellino E3 ubiquitin-protein ligase 1 (peli1) showed lower expression (P = 0.0012). Additionally, in all four groups, cdkn2c and peli1 gene expression showed an incremental increase and decrease, respectively. Immunohistochemistry of cdkn2c showed consistent results with the nS analysis. CONCLUSION: More cdkn2c and less peli1 expression were associated with more advanced stages of SSc-ILD on histologic assessment. We report the potential of the cell cycle inhibitor and senescence marker, cdkn2c (p18) to be associated with fibrosis progression.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.337
Teacher spread0.292 · 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