ArticleBMC rheumatology2026
Machine learning reveals X chromosome transcriptional signatures that classify systemic lupus erythematosus in females.
Article in BMC rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- The application of artificial intelligence in systemic lupus erythematosus: a bibliometric analysis of current trends and future directions.Frontiers in medicine · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSystemic lupus erythematosus (SLE) has a significant female bias; however, it remains unclear whether X-chromosomal dysregulation increases the risk in females. Furthermore, while the role of X-linked genes in SLE pathogenesis is recognised, the analysis of genetic risks in SLE has largely focussed on autosomal genes.
methodsHere, we analysed a public single-cell RNA sequencing (scRNA-seq) dataset of peripheral blood mononuclear cells using machine learning to test whether X-linked gene expression classifies female SLE in a cell type-specific manner. Using pseudobulked expression profiles from 1.1 million cells across 228 female donors, we trained an ensemble of classifiers on all X-chromosomal genes or a literature-derived set of SLE-associated genes.
resultsIn CD4
conclusionsThese findings demonstrate that X-linked transcriptional programs, enriched for known XCI escape genes and concentrated in activated T cells, encode a reproducible transcriptional signal of female SLE and provide a framework for dissecting the contributions of sex chromosomes to autoimmunity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.