XIST EXPRESSION IN MALES WITH SYSTEMIC LUPUS ERYTHEMATOSUS: BIMODAL DISTRIBUTION AND PARTIAL X-CHROMOSOME INACTIVATION
Bibliographic record
Abstract
PT022 / #742 Topic: AS12 - Genetics, Epigenetics, Transcriptomics POSTER TOUR 05: SLE PATHOGENESIS 24-05-2025 10:00 AM - 10:20 AM Background/Purpose Systemic lupus erythematosus (SLE) exhibits a pronounced female-biased imbalance in disease prevalence, with a female-to-male ratio of 9:1. Although the exact mechanisms remain unclear, the significant role of X-chromosome dosage is supported by karyotypic risks associated with SLE. This study utilizes paired transcriptomic (RNAseq), proteomic (Olink), and epigenomic (EMSeq) data from large phase 3 trials to gain mechanistic insights into the drivers behind the sexual bias in SLE. Methods Baseline RNAseq, Olink, and EMseq data were collected from the whole blood of 722 SLE patients (680 female, 42 male) and 84 healthy controls (77 female, 7 male) from 2 phase 3 clinical trials ( NCT03616964 , NCT03616912 ). Differential expression analysis was performed using a factorial design to calculate the following comparisons for each modality: i) SLE vs healthy controls in females, ii) SLE vs healthy controls in males, and iii) interaction between sex and disease. Gene set enrichment analysis (GSEA) of patient subsets was conducted using Gene Ontology (GO) biological process terms. To ensure our cohort did not contain erroneous results due to Klinefelter’s males, we inferred X-chromosome heterozygosity by calculating the read depth of the X-chromosome from the EMseq bam files. To validate our results, we performed similar differential expression analysis on EMseq data from an independent cohort of SLE patients (241 females, 13 males) from 2 additional phase 3 clinical trials ( NCT01205438 , NCT01196091 ). Results The strongest changes differentiating how sexes respond to disease were observed in the expression of lncRNA XIST (X-inactive specific transcript) and epigenetics. Specifically, we noted an increased expression of XIST in males with SLE compared to healthy controls (Figure 1A), with this expression exhibiting a bimodal distribution (Figure 1B). GSEA indicated that males with high XIST expression exhibit enrichment in biological processes (GO) related to metabolism and immunoglobulin production, such as oxidative phosphorylation, B cell mediated immunity, and immunoglobulin production compared to XIST low males. Consistent with XIST’s known role in X-chromosome inactivation, we observed corresponding hypermethylation of the X-chromosome and downregulation of X-linked genes in males with SLE (Figure 1C). Lastly, we observed similar patterns of X-chromosome hypermethylation using EMseq data from an independent cohort of SLE patients. A) Violin plots of XIST expression (RNAseq) in women (left) and men (right). B) Density plot of the bimodal expression of XIST in men with SLE. Dashed red line indicates the separation between XIST high and XIST low groups. C) Distribution plots of significant changes (|FC| > 1.5; FDR < 0.1) in gene methylation (top), promoter methylation (middle), and gene expression (bottom) on the X chromosome in females (pink), XIST high males (green), and XIST low males (blue) compared to healthy controls. Figure 1. Partial X-chromosome inactivation in males with SLE. Conclusions This study, which includes the most comprehensive and largest dataset of male SLE patients to date, shows that males with SLE express significantly higher levels of XIST, accompanied by hypermethylation of the X-chromosome and downregulation of X-linked genes compared to healthy controls, suggesting partial X-chromosome inactivation in males with SLE. Importantly, we have confirmed that these changes are not artifacts of Klinefelter’s patients within the cohort. We hypothesize that this X-chromosome inactivation may be driving SLE via several mechanisms, including: i) inactivation of immunoregulatory molecules, ii) inducing development of SLE autoantibodies, and/or iii) driving interferon production via TLR7.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".