Integrating Epidemiological Intelligence and Transcriptomic Perspectives: Advancing Biomarker-Driven Strategies Against the Global Burden of Chronic Lymphocytic Leukemia  期刊论文  

BackgroundThe global epidemiological trends of chronic lymphocytic leukemia (CLL) provide a crucial macrolevel foundation for guiding precision medicine. However, translating broad risk factors and burden disparities into actionable clinical strategies requires a bridge to molecular pathogenesis. This study analyzes the global CLL burden to not only delineate its public health landscape but also inform the development of biomarker-based prevention and early detection frameworks.MethodsLeveraging data from the Global Burden of Disease Study 2021, we evaluated primary pre-pandemic trends in CLL incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2019 using estimated annual percentage change (EAPC), joinpoint regression, and decomposition analysis to identify key drivers of trends and inequalities. Predictive modeling (ARIMA) was employed to project future burden. Critically, the epidemiological insights-particularly regarding identified risk factors (e.g., smoking, high BMI) and high-burden populations-were framed as a strategic map to prioritize hypotheses for subsequent biomarker discovery research in CLL etiology and progression. We additionally analyzed three independent Gene Expression Omnibus (GEO) transcriptomic cohorts including CLL patients and nonleukemic controls. Differential expression analysis across cohorts identified 67 overlapping CLL-related genes, which underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Using least absolute shrinkage and selection operator (LASSO)-regularized logistic regression in a training cohort, we derived a 14-gene predictive signature and validated its discriminative performance in independent datasets.ResultsThe analysis revealed a mild decline in global age-standardized incidence but significant declines in mortality (31.3%) and DALYs (32.9%), alongside marked socioeconomic disparities. Decomposition analysis quantified the dominant role of population aging in driving DALY increases in Western Europe (+11403.53%) and epidemiological factors in Central Asia (+633.72%). Smoking and high body mass index were reaffirmed as modifiable risk factors. Projections indicate declining incidence and mortality but rising prevalence through 2040. These findings pinpoint specific demographics and risk exposures as high-priority targets for biomarker investigation and stratified screening. At the molecular level, differential expression analyses across three GEO cohorts identified 67 overlapping CLL-related genes, which were significantly enriched in immune cell differentiation, leukocyte adhesion, T/B cell receptor signaling, and cytokine/growth factor pathways. A LASSO-based model further distilled these into a 14-gene signature that effectively discriminated CLL from non-CLL samples in the training cohort and retained stable predictive performance in independent validation sets.ConclusionThis study synthesizes the global epidemiology of CLL into a framework that informs clinical and translational research. By combining global burden analysis with a complementary transcriptomic investigation, it provides epidemiological context and candidate molecular features for future biomarker-based risk stratification and early identification strategies in CLL.