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Record W4397043832 · doi:10.1681/asn.20233411s1299c

The IgG Glycome Predicts Nephritis and Leads to Podocyte Injury in Systemic Lupus Erythematosus (SLE)

2023· article· en· W4397043832 on OpenAlexaff
Rhea Bhargava, Rohit Upadhyay, Scott E. Wenderfer, Jing Chen, George C. Tsokos

Bibliographic record

VenueJournal of the American Society of Nephrology · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPodocyteLupus nephritisMedicineGlycomeNephritisImmunologyProteinuriaPathologyInternal medicineKidneyBiologyGlycan

Abstract

fetched live from OpenAlex

Background: Lupus nephritis (LN) occurs in 50% of patients with systemic lupus erythematosus (SLE) for which we lack biomarkers, and an understanding of its pathogenesis. We have previously demonstrated that IgG in LN is aberrantly glycosylated and can injure podocytes. Methods: We evaluated the IgG glycome by N-glycan profiling in a pediatric cohort of 40 children with SLE and 20 paired pre and post treatment LN samples using LS-MS Mass Spectrometery. We used enzymatic treatments to evaluate the role of glycans in podocyte injury. Data were analyzed using GEE analysis, Spearman test, t-test and regression analysis. Podocyte phenotype was evaluated by wound healing assay, cytoskeleton evaluation (F-actin) and podocyte specific proteins by RT-PCR and western blotting. Results: We found that the overall glycosylation was reduced 6 months post treatment in patients with LN. Furthermore, those decorated with terminal galactose were increased while those with terminal sialic acid were reduced. In addition, neutral glycans were increased after treatment while negatively charged glycans were decreased. To evaluate whether these differences were due to treatment rather than LN activity, we analyzed the IgG glycome in SLE without LN, LN, LN in remission 6-month after treatment. We found that neutral glycans and negatively charged glycan chains changed with LN activity. Furthermore, the presence or absence of sialic acid and galactose correlated with parameters that influence active nephritis (renal SLEDAI, dsDNA, C3, cellular crescents and proteinuria). A switch from tri to bi -antennary complex type N-Glycans was noted in those with decling GFR. More interestingly, treatment of IgG with PNGase- F, which removes glycan chains, prevented cytoskeleton and motility changes in podocytes that were induced in LN. In addition, nephrin expression was preserved following PNG-ase treatment. Conclusions: The IgG glycome in pediatric SLE patients is altered and is further aberrantly glycosylated in LN. The magnitude of change is associated with LN activity. More importantly, the glycans on IgG can lead to podocyte injury in LN. Our data shed light on the role of IgG glycosylation in the development of podocyte injury and propose the development of approaches using the IgG glycome to diagnose and monitor LN. Further, it highlights IgG glycosylation as an important pathogenic mechanism in LN. Funding: Other NIH Support - NIAID K99 - 7K99AI162843-02, U54 GM104940

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 score0.001
Threshold uncertainty score0.004

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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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