bioRxiv Science⌕ Search

Biology subjects

Chebbi, A.

Publications and source records attributed to Chebbi, A..

2 recordsLinked to original sources

Machine learning classification of fibromyalgia from blood transcriptomes: confounder benchmarking and implications for endometriosis-associated pain

Fibromyalgia (FM) lacks an objective biomarker, and blood transcriptomic signatures have been proposed to fill this gap. Here, the largest public peripheral blood mononuclear cell (PBMC) RNA-seq cohort of FM reporting expression subtypes (96 patients, 93 controls) was reanalysed using leakage-free nested cross-validation, with feature selection and scaling confined strictly to training folds. Gene expression discriminated patients from controls (ROC-AUC 0.821 for logistic regression and 0.825 for XGBoost), clearing a 100-repetition permutation-label null (p= 0.0099). Two simple, disease-agnostic baselines, however, reach nearly the same performance: sex alone reaches AUC 0.727, and a four-score PBMC cell-composition proxy reaches AUC 0.71-0.76. Restricting to females alone gives AUC 0.783 (0.705-0.858), and excluding X/Y-linked genes does not reduce performance, so the signal is not purely a sex-composition artifact; but the female-only expression model does not significantly exceed the composition-only proxy in the same females (0.783 vs. 0.712, paired 95% CI -0.025 to 0.175), so a composition contribution cannot be excluded. Preranked gene set enrichment analysis finds curated CLEAR/lysosomal and interferon/JAK-STAT gene sets, proxies for two subtype signatures of the original study, enriched among genes expressed lower in FM, also in females alone, but this enrichment disappears after adjusting for the composition proxies. Gynecological comorbidity, hormonal status, and medication are absent from the public metadata and remain plausible, untested contributors to the female-only estimate. These findings are hypothesis-generating, not a basis for clinical diagnosis: a single-cohort, correlational result consistent with, but not sufficient to establish, an FM-specific signal distinct from demographic, hormonal, and cell-composition confounds, pending independent replication. Future blood-based biomarker studies for FM, and for related nociplastic pain conditions such as endometriosis, should report performance relative to sex- and composition-based baselines as standard practice.

bioinformatics↗

The Silene latifolia genome and its giant Y chromosome

In some species, the Y is a tiny chromosome but the dioecious plant Silene latifolia has a giant [~]550 Mb Y chromosome, which has remained unsequenced so far. Here we used a hybrid approach to obtain a high-quality male S. latifolia genome. Using mutants for sexual phenotype, we identified candidate sex-determining genes on the Y. Comparative analysis of the sex chromosomes with outgroups showed the Y is surprisingly rearranged and degenerated for a [~]11 MY-old system. Recombination suppression between X and Y extended in a stepwise process, and triggered a massive accumulation of repeats on the Y, as well as in the non-recombining pericentromeric region of the X, leading to giant sex chromosomes. One-Sentence SummaryThis work uncovers the structure, function, and evolution of one of the largest giant Y chromosomes, that of the model plant Silene latifolia, which is almost 10 times larger than the human Y, despite similar genome sizes.

genomics↗