MétaCan
Menu
Back to cohort
Record W4410513254 · doi:10.3899/jrheum.2025-0390.o019

CD38 IS OVEREXPRESSED BY IMMUNE CELLS IN CUTANEOUS LUPUS SKIN

2025· article· en· W4410513254 on OpenAlexvenueno aff
Grace Lu, Kangyi Zhang, Grant Barber, Richard C. Wang, Benjamin F. Chong

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmune systemCD38ImmunologyImmunopathologySystemic lupus erythematosusLupus erythematosusDermatologyPathologyAntibodyStem cellDiseaseCell biology

Abstract

fetched live from OpenAlex

O019 / #487 Topic: AS07 - Cutaneous Lupus ABSTRACT CONCURRENT SESSION 03: INNATE AND ADAPTIVE IMMUNITY IN SLE 22-05-2025 1:40 PM - 2:40 PM Background/Purpose Cutaneous lupus erythematosus (CLE) is an autoimmune skin disease in which metabolic abnormalities may drive immune dysregulation. An unbiased LC/MS metabolomics study showed dysregulation of nicotinamide adenine dinucleotide (NAD) metabolism in the skin of CLE patients compared to healthy controls. CD38 is a multifunctional transmembrane enzyme that plays an important role in NAD metabolism and has become an emerging therapeutic target in the treatment of systemic lupus erythematosus (SLE).[1] However, CD38 expression in CLE has not been well characterized. Methods We sought to investigate whether CD38 expression was altered in CLE lesional skin and identify the immune cell populations overexpressing CD38. Skin samples were obtained from CLE patients and normal controls seen at outpatient dermatology clinics at the University of Texas Southwestern Medical Center and Parkland Health. To compare the levels of CD38 expression between CLE vs normal skin, RNA levels were assessed by quantitative RT-PCR (qRT-PCR) from 16 CLE lesion skin biopsies and 11 control skin samples, and protein expression was assessed by immunohistochemistry on 7 CLE lesion skin biopsies and 4 control skin samples. Immunofluorescence double staining of CD38 with CD3, CD20, and CD68 was performed using 5 CLE lesion skin biopsies and 5 control skin samples to examine CD38 expression of candidate immune cell populations, including T cells (CD3), B cells (CD20), and monocytes (CD68), respectively. Manders’ coefficients M1 and M2 were determined to examine the extent of overlap between CD38 and CD3, CD20, and CD68 expression. Results qRT-PCR revealed a significant upregulation of CD38 expression in CLE patients vs controls (median log2 fold change of 6.56 vs -0.48, p<0.0001). Immunohistochemical staining of CD38 in 7 lesional and 4 normal skin samples revealed a significantly higher number of CD38 + cells in CLE skin (median: 2105.8 cells/mm2, IQR: 1164.9-2980.0) compared to normal skin (median: 238.5 cells/mm2, IQR: 181.5-426.8, p=0.02) (Figure 1). Immunofluorescence co-staining for CD38 revealed significantly increased CD3 + cells expressing CD38 in perifollicular regions (p<0.01) and CD68 + cells expressing CD38 in dermal-epidermal junctions (p<0.05) in CLE skin vs normal skin, whereas CD20 + cells were not demonstrated to have significantly increased CD38 expression (Figure 2). Figure 1 Figure 2 Conclusions qRT-PCR and immunohistochemical staining revealed that CD38 is significantly upregulated in lesional CLE skin, which supports our metabolomics data implying dysregulation of NAD + metabolism in CLE skin. In accordance with prior studies examining immune profiles of SLE,[2] immunofluorescence double staining demonstrated CD38 overexpression in a wide range of leukocytes, including T cells and monocytes. These findings support CD38 as a promising therapeutic target in patients with CLE. References: [1.] Ostendorf L. N Engl J Med 2020;383(12):1149-55. [2.] Burns M. Int J Mol Sci 2021;22(5):2424.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

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)0.0040.001

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 head0.003
GPT teacher head0.230
Teacher spread0.227 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of RheumatologySame topicmelanin and skin pigmentationFrench-language works237,207