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Record W4207071945 · doi:10.1093/ecco-jcc/jjab232.218

P089 Long ncRNA Landscape in the Rectum of Treatment Naïve Early Onset Ulcerative Colitis Highlights Association with Severity and Early and Late Disease Outcome, with Potential Role in Epithelial Metabolic Functions

2022· article· en· W4207071945 on OpenAlexaff
Yael Ziv, T Braun, Katya E. Sosnovski, Amnon Amir, Kelli L. VanDussen, Igor Ulitsky, Anne M. Griffiths, Thomas D. Walters, D Mack, B Boyle, Subra Kugathasan, Anil G. Jegga, Jeffrey S. Hyams, Lee A. Denson

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsChildren's Hospital of Eastern OntarioHospital for Sick Children
Fundersnot available
KeywordsRectumUlcerative colitisTranscriptomeColectomyInternal medicineDiseaseBiologyMedicineOncologyGeneGastroenterologyGene expressionGenetics

Abstract

fetched live from OpenAlex

Abstract Background Long non-coding RNAs (lncRNAs) are tissue-specific and regulate cellular functions. We previously reported a dramatic inhibition of epithelial metabolic mitochondrial functions in mucosal biopsies from the UC PROTECT cohort. We aimed to define lncRNAs that are dysregulated in UC, linked with attenuated epithelial metabolic functions, and associated with worse outcome. Methods Transcriptomics of pre-treatment rectal biopsies in PROTECT UC [206 UC and 20 controls (Ctl)]. Weighted gene co-expression network analysis (WGCNA) to identify modules and gens associated with UC severity, week 4 remission after 5-ASA/steroids (W4R), week 52 steroid-free remission (W52SFR), and colectomy within 3 years. Epithelial mechanistic data of prioritized lncRNA. Results PROTECT transriptomics included 2,826 lncRNA genes with TPM>1 in 20% of samples. Principal components analysis (PCA, Fig 1) using these lncRNA showed distinct clusters of UC and Ctl, and PC2 values were linked (p<0.01) with endoscopic (Mayo score) and clinical (PUCAI) disease severities. Random forest classifiers using the 2,826 lncRNA trained to distinguish UC from Ctl using PROTECT, predicted the correct diagnosis in PROTECT (AUC=1) and in RISK (AUC=0.88) connecting lncRNA to UC pathogenesis in two independent cohorts. WGCNA on the 2,826 lncRNA resulted in 6 modules (M1-M6) associated with UC (p<0.01, Fig 2). M1, which contained lncRNA reduced in UC, was associated with lessW4R (p=0.01) less W52SFR (p=0.04) and increased colectomy (p=0.02). In contrast, M6, which contained lncRNA elevated in UC, was linked with W4R (p=0.008). The hub genes in the M1 and M6 modules included GATA6-AS1 and LINC01272 lncRNAs, respectively. Re-analysis of single cell datasets supported epithelial expression of GATA6-AS1 and myeloid expression of LINC01272. GATA6-AS1 co-expression with protein-coding genes in PROTECT showed significant enrichment for mitochondrial functions (p<1E-40). Reduction of GATA6-AS1 expression with 2 shRNAs resulted in reduced mitochondrial complex IV MT-CO2 mRNA and protein and reduction of LGR5, linking mitochondrial genes and function with epithelial renewal. We recently showed pronounced reduction of the mitochondrial membrane potential (MMP) by JC-1 staining in UC epithelia. Consistent with this finding, GATA6-AS1 inhibition reduced MMP levels from 0.22 in control to 0.08 (p=0.01), similarly to MMP of cells treated with CCCP that is known to depolarize and reduce MMP. Conclusion LncRNA are significantly linked with UC and disease severity, and the M1 epithelial enriched module shows significant association with worse outcome. GATA6-AS1 within the M1 hub genes show potential role in epithelial metabolic functions and renewal.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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
Published2022
Admission routes1
Has abstractyes

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