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C1q-Binding DSA Induce Distinct Molecular Phenotypes in Kidney Transplant Biopsies.

2014· article· en· W2774097585 on OpenAlexaff
Carmen Lefaucheur, Alexandre Loupy, J. Reeve, Luis Hidalgo, Konrad S. Famulski, Jessica Chang, Olivier Aubert, A. Zeevi, Xavier Jouven, Denis Glotz, Christophe Legendre, Philip F. Halloran

Bibliographic record

VenueTransplantation · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsThe Metabolomics Innovation Centre
Fundersnot available
KeywordsPhenotypeKidneyCancer researchKidney transplantationPathologyKidney transplantMedicineCell biologyBiologyInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

Background Complement binding DSA associates with risk of kidney allograft loss. We used the molecular microscope system in kidney transplant biopsies performed in DSA+ patients and investigated the molecular phenotypes according to the complement binding capacity of circulating DSA. Methods We enrolled 628 kidney transplant recipients, and assessed patients with DSA detected in the first year post-TX (n=154). All DSA+ patients were tested for C1q-binding using single-antigen beads. All patients had a biopsy performed at the time of sera evaluation. Microarray-based gene expression was assessed using relevant molecular measurements including pathogenesis-based transcript sets (PBTs): ABMR molecular Score, endothelial DSA-selective transcripts (eDSAST), macrophage associated transcripts (QCMAT), gamma-interferon response (GRIT), injury-repair response transcripts (IRRAT) and complement regulated genes (KEGGDE). Results Among the 154/628 (24.5%) patients with post-TX DSA, we identified 48 (31.2%) patients with C1q+ DSA and 106 (68.8.%) patients with C1q-neg DSA. As compared to C1q-neg DSA, patients with C1q+ DSA had higher mean Banff scores for microcirculation inflammation (1.2 vs 2.8), TG (0.13 vs 0.41) and higher rate of C4d deposition (14% vs 58%, p<0.001 for all comparisons). Gene expression analysis revealed that patients with C1q+ DSA had higher ABMR molecular Score (p=0.0032), higher expression of eDSAST (p=0.0273), QCMAT (p=0.0014), GRIT (p=0.020) and IRRAT (p=0.00072) as compared to patients with C1q-neg DSA. Many complement transcripts showed higher expression in biopsies from patients with C1q+ DSA including C3aR and C5aR (p=0.0034 and 0.011) and other complement components C1QA and B, C2, C3. Assessment in a primary human cell panel showed that complement receptor expression was restricted to macrophages while the top complement genes reflected IFN-g induction in macrophages. Conclusion Patients with C1q+DSA show a distinct phenotype characterized by higher expression of genes related to endothelial activation, injury and evidence for higher expression of genes related to classical complement activation with many reflecting macrophage activation. This study provides a link between in vitro capacity of DSA to bind C1q and their ability to induce specific allograft injury. DISCLOSURE:Halloran, P.: Other, Astellas, Lecturing, Novartis, Lecturing, One Lambda, Lecturing.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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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Citations1
Published2014
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