ArticleInternational journal of laboratory hematology2026
Circadian Deregulation in Multiple Myeloma: BMAL1/CLOCK Expression Patterns and Diagnostic Performance.
Article in International journal of laboratory hematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCircadian clock disruption has emerged as a relevant axis in cancer; however, the expression patterns and diagnostic relevance of BMAL1 and CLOCK in multiple myeloma (MM) remain insufficiently defined.
methodsBMAL1 and CLOCK mRNA expression was quantified by RT-qPCR in bone marrow samples from 46 newly diagnosed MM patients and 13 healthy controls. Group comparisons, ROC analyses, multivariate logistic regression, partial correlation, and machine-learning models (logistic regression, random forest, and support-vector machine) with stratified 5-fold cross-validation (including class-weighted sensitivity analysis) were performed.
resultsBMAL1 expression was significantly higher in MM than in controls (1.12 ± 0.33 vs. 0.85 ± 0.33, p = 0.016; Cohen's d = 0.83), whereas CLOCK showed no significant univariate difference (p > 0.2). BMAL1 demonstrated moderate diagnostic performance (AUC = 0.729), while CLOCK alone showed limited discrimination (AUC = 0.617). Combined analysis modestly improved performance (AUC = 0.756). In multivariate logistic regression, BMAL1 remained a strong independent predictor of MM (OR = 3343.4, p = 0.0046), whereas CLOCK showed an inverse adjusted association (OR = 0.0037, p = 0.019). BMAL1 and CLOCK expression were strongly correlated in MM (ρ ≈ 0.80), persisting after adjustment for age, ISS stage, and β2-microglobulin (partial r = 0.847, p = 2.2 × 10-13). Among classifiers, the random forest achieved the best performance (AUC = 0.832; AUPRC = 0.952). Specificity was limited across classifiers, indicating that these performance estimates are exploratory and require validation in larger cohorts.
conclusionMM is characterized by BMAL1 upregulation within a preserved but imbalanced BMAL1/CLOCK axis rather than uniform shifts across circadian genes. Although diagnostic performance is moderate, consistent signals across statistical and machine-learning approaches support an MM-associated circadian expression pattern warranting further validation.
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