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Record W2058013036 · doi:10.1186/ar4637

Identification of stage-specific genes associated with lupus nephritis and response to remission induction in NZB/W and NZM2410 mice

2014· article· en· W2058013036 on OpenAlexfundno aff
Ramalingam Bethunaickan, Céline C. Berthier, Weijia Zhang, Ridvan Eksi, Hong‐Dong Li, Yuanfang Guan, Matthias Kretzler, Anne Davidson

Bibliographic record

VenueArthritis Research & Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of HealthLupus Research AllianceCanadian Arthritis NetworkNational Institute of Arthritis and Musculoskeletal and Skin DiseasesArthritis SocietyCentral New York Community FoundationMerck KGaALupus Foundation of America
KeywordsLupus nephritisRheumatologyMedicineInternal medicineStage (stratigraphy)GeneImmunologyIdentification (biology)NephritisSystemic lupus erythematosusOncologyBioinformaticsGeneticsBiologyDisease

Abstract

fetched live from OpenAlex

Lupus nephritis affects 30 to 70% of systemic lupus erythematosus (SLE) patients and its treatment remains insufficiently effective and excessively toxic. Although biomarkers for nephritis are being identified there is still no reliable way of predicting an impending renal flare or determining which patients will respond to therapy. Because human renal tissue cannot be obtained sequentially during remission and relapse, animal models are often used to study progression of lupus nephritis. To elucidate the molecular mechanisms involved in renal inflammation during the progression, remission and relapse of nephritis we performed a transcriptome analysis of renal tissue from two murine lupus models, NZB/WF1 mice that develop proliferative glomerulonephritis and NZM2410 mice that develop glomerulosclerosis with minimal inflammation. Kidneys from NZB/W F1 and NZM2410 mice were harvested at intervals during their disease course or after remission induction with either combination cyclophosphamide/costimulatory blockade or with BAFF inhibition. Genome-wide expression profiles were obtained from microarray analysis of perfused kidneys. Real-time PCR analysis for selected genes was used to validate the microarray data. Comparisons between groups using SAM, and unbiased analysis of the entire dataset using singular value decomposition and self-organizing map were performed. Few changes in the renal molecular profile were detected in pre-nephritic kidneys but a significant shift in gene expression, reflecting inflammatory cell infiltration and complement activation, occurred at proteinuria onset. Subsequent changes in gene expression predominantly affected mitochondrial dysfunction and metabolic stress pathways. Remission induction reversed most, but not all, of the inflammatory changes and progression towards relapse was associated with recurrence of inflammation, mitochondrial dysfunction and metabolic stress signatures. Endothelial cell activation, tissue remodeling and tubular damage were the major pathways associated with loss of renal function. Immune cell infiltration and activation is associated with proteinuria onset and reverses with immunosuppressive therapy but disease progression is associated with renal hypoxia and metabolic stress. Optimal therapy of SLE nephritis may therefore need to target both immune and nonimmune disease mechanisms. In addition, the overlap of a substantial subset of molecular markers with those expressed in human lupus kidneys suggests potential new biomarkers and therapeutic targets.

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 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)0.007
metaresearch head score (Gemma)0.001
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 score0.448
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.049
GPT teacher head0.343
Teacher spread0.294 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2014
Admission routes1
Has abstractyes

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