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PSYCHOSIS IN SYSTEMIC LUPUS ERYTHEMATOSUS

2025· article· en· W4410513007 on OpenAlexvenueno aff
So‐Young Bang, Soojin Cha, Ga Young Ahn, Hye‐Soon Lee, Sang‐Cheol Bae

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychosisSystemic diseaseLupus erythematosusConnective tissue diseaseSystemic lupusDermatologySystemic lupus erythematosusImmunopathologyImmunologyAutoimmune diseasePsychiatryInternal medicineDiseaseAntibody

Abstract

fetched live from OpenAlex

PV042 / #281 Poster Topic: AS05 - CNS Lupus Background/Purpose Neuropsychiatric (NP) events are a major cause of morbidity in patients with systemic lupus erythematosus (SLE) and are associated with high mortality. The infrequent occurrence of psychosis has limited the number of clinical studies conducted on this condition, leaving the development of SLE with psychosis poorly defined. We aimed to identify clinical and genetic factors associated with psychosis in SLE patients through a genome-wide association study (GWAS) conducted within a prospective lupus cohort. Methods This study included 960 Korean patients diagnosed with SLE, all meeting the 1997 American College of Rheumatology (ACR) classification criteria. The neuropsychiatric SLE (NPSLE) was defined using a modified version of the 19 ACR criteria excluding minor neuropsychiatric events. Clinical features were collected annually, and genotyping was performed on all SLE patients. A generalized mixed model within the SAIGE was conducted to assess the association of SLE with psychosis, compared to SLE patients without neuropsychiatric manifestations (non-NPSLE), adjusting for age, sex, and 10 genetic principal components. Results Of the cohort, 26 patients (2.71%) exhibited psychosis, with a mean onset-age of 24.5 years, a mean disease duration of 13.5 years, and a predominance of females (96.2%). The SLE patients with psychosis had more clinical manifestations based on the 1997 ACR criteria compared to 934 non-NPSLE patients (7.1 vs. 5.8, p = 1.21×10^-5), as shown in Table 1. A higher SLICC/ACR Damage Index score was observed in patients with psychosis compared to non-NPSLE patients (p = 0.03). We identified 9 genetic variants significantly associated with psychosis compared to non-NPSLE at a suggestive significance level (p < 5 × 10^-6), with a notable variant on chromosome 19 (p = 1.13 × 10^-6) showing eQTL effects in the brain cortex based on the GTEx v8 dataset. Table 1. Association between clinical manifestations and psychosis in SLE patients a a Neuropsychiatric (NP) manifestations: a revised version that did not include minor NP event of American Colleague of Rheumatology (ACR) case definitions for 19 NP syndromes. b Demographic variables are analyzed by Wilcoxon rank-sum test and Chisquare test for continuous and categorical variables, respectively. c P values are derived from logistic regression analysis adjusting for age and sex. d Clinical manifestation based on the 1997 revised American College of Rheumatology (ACR) criteria for SLE e SLEDAI-2K NP: seizure, psychosis, organic brain syndrome, cranial nerve disorder, cardiovascular events, lupus headache Mean (±SD) and percentage were used for continuous and categorical variables, respectively. Conclusions SLE patients with psychosis exhibited more diverse clinical phenotypes and increased organ damage. Our identification of genetic risk variants provides valuable insights into the pathogenesis of psychosis in SLE.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.313
Teacher spread0.295 · 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 designNot applicable
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

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