Woldeamanuel, Yohannes Woubishet

Background: Musculoskeletal disorders (MSKDs) are the leading cause of disability worldwide. The associations between socioeconomic and lifestyle factors and MSKDs have been widely studied in Europe and North America. However, little data are available about their relationship in Latin America. Objectives: To estimate the prevalence of chronic MSKDs in Brazil and assess their relationship with socioeconomic and lifestyle factors. Design: This is a cross-sectional study, based on a subanalysis of the open-access database from the Brazilian National Health Survey 2019. This survey was a nationwide, cross-sectional, door-to-door study that included 87,648 adults and was conducted between 2019 and 2020. Methods: Prevalence estimates were based on weighted sample strata, and the relationship between MSKD and socioeconomic and lifestyle factors was examined through network analysis and weighted Poisson regression models with robust variance. Results: The weighted prevalence of chronic MSKDs was estimated at 26.1% (95% confidence interval, 25.5%–26.8%). In the network analysis, including all socioeconomic and lifestyle variables, MSKDs prevalence was notably linked to higher body mass index, drinking, smoking, and low income. In the regression models, MSKD prevalence was associated with obesity, sleep disorders, smoking, alcohol consumption, and depression, and inversely associated with physical activity, even after controlling for the sociodemographic disparities. Conclusion: This study identifies specific socioeconomic and lifestyle factors associated with MSKDs and highlights the need for immediate national health promotion programs focused on MSKDs prevention through targeted lifestyle modifications, especially in populations belonging to the lower-income strata in Brazil.

Abstract Background Migraine patients show choroid plexus (CP) changes, impairing the blood-CSF barrier. The CP regulates circadian rhythms, but links between CP circadian genes and migraine are unexplored. Objective This study examined CP circadian gene transcriptome changes in a chronic migraine rat model versus controls to identify migraine-related pathways. Design Chronic migraine model: Sprague Dawley rats (3 females, 3 males) received nitroglycerine (NTG) every other day for 9 days; controls (3 females, 3 males) got saline. CP from the 4th ventricle was collected 2 hours post-final injection for RNAseq. Methods Migraine Behavior: Von Frey hair tests on days 1, 5, and 9, pre- and 2 hours post-NTG/saline injection, assessed basal and NTG-induced pain thresholds. RNAseq & Analysis: Differentially expressed genes (p < 0.05, fold change > 1) were identified. GO, KEGG, and Reactome enrichment analyses evaluated circadian gene expression changes. Results NTG group showed reduced basal and NTG-induced pain thresholds on days 1, 5, and 9. Females had more upregulated genes ( MT2A , SLC7A11 ), males upregulated ZBTB16 , S100A8 . SLC7A11 , SCG2 , GRIA1 showed inverse regulation (up in females, down in males). Circadian gene expression altered: 10 genes upregulated (e.g., SERPINE1, MAPK9, ATF4 ), 13 downregulated (e.g., PER2, DBP, EZH2 ). Sex-specific differences: females ( FBXL12, GPR157 ), males ( NKX2-1, ATF4, CLOCK ). GO/KEGG analyses revealed significant enrichment of circadian rhythm-related pathways, insulin resistance, and inflammatory response processes, with sex-specific differences: females showed HIF-1 signaling and hemoglobin-related pathways, while males exhibited arachidonic acid and leukotriene production. Conclusion CP transcriptomics in the rat migraine model revealed sex-specific gene regulation, with females upregulating antioxidant genes (MT2A, SLC7A11) and males upregulating inflammatory factors (ZBTB16, S100A8), alongside circadian disruption (e.g., SERPINE1 upregulated, PER2 downregulated). Pathway analyses indicate enriched circadian rhythms, HIF-1 signaling (females), inflammatory processes (males), lipid metabolism (PPARα), and heme signaling, highlighting sex-specific and circadian targets for migraine therapy.

Objective: We aimed to estimate the prevalence of cardiovascular diseases (CVDs) and cardiometabolic diseases (CMB) in Brazil, and their relationship with a healthy lifestyle score based on the six pillars of lifestyle medicine proposed by the American College of Lifestyle Medicine. Methods: Data were derived from the 2019 Brazilian National Health Survey, a nationwide cross-sectional study. The prevalence of CVDs/CMB was based on medical-endorsed, self-reported diagnoses and weighted for sample strata. A healthy lifestyle score (0-14 points; the higher the score, the better) incorporates physical activity, diet, sleep, mental health, risky substance use, and social connections. Results: Among 88,531 adults included in the analysis (mean age: 47.1 years; 52.9% female), the weighted prevalence of CVDs/CMB ranged from 1.9% (stroke) to 25.9% (hypertension). Weighted Poisson regression models, adjusted for age, sex, socioeconomic status, and geographic disparities, showed an inverse linear relationship between lifestyle score and CVDs/CMB prevalence. Participants in the highest lifestyle score quartile exhibited lower prevalence for heart diseases [0.48 (95% CI: 0.43, 0.53)], stroke [0.35 (95% CI: 0.29, 0.43)], hypertension [0.85 (95% CI: 0.80, 0.90)], diabetes [0.80 (95% CI: 0.70, 0.91)], dyslipidemia [0.73 (95% CI: 0.66, 0.80)], and obesity [0.81 (95% CI: 0.74, 0.88)], compared to the lowest quartile ( P < 0.001 for all). Conclusions: Higher scores on the six pillars of lifestyle medicine are associated with a lower prevalence of major CVDs/CMB in Brazil.

Background: Currently, there are no biomarkers for migraine. Objectives: We aimed to identify proteomic biomarker signatures for diagnosing, subclassifying, and predicting treatment response in migraine. Design: This is a cross-sectional and longitudinal study of untargeted serum and cerebrospinal fluid (CSF) proteomics in episodic migraine (EM; n = 26), chronic migraine (CM; n = 26), and healthy controls (HC; n = 26). Methods: We developed classification models for biomarker identification and natural clusters through unsupervised classification using agglomerative hierarchical clustering (AHC). Pathway analysis of differentially expressed proteins was performed. Results: Of 405 CSF proteins, the top five proteins that discriminated between migraine patients and HC were angiotensinogen, cell adhesion molecule 3, immunoglobulin heavy variable (IGHV) V-III region JON, insulin-like growth factor binding protein 6 (IGFBP-6), and IGFBP-7. The top-performing classifier demonstrated 100% sensitivity and 75% specificity in differentiating the two groups. Of 229 serum proteins, the top five proteins in classifying patients with migraine were immunoglobulin heavy variable 3-74 (IGHV 3-74), proteoglycan 4, immunoglobulin kappa variable 3D-15, zinc finger protein (ZFP)-814, and mediator of RNA polymerase II transcription subunit 12. The best-performing classifier exhibited 94% sensitivity and 92% specificity. AHC separated EM, CM, and HC into distinct clusters with 90% success. Migraine patients exhibited increased ZFP-814 and calcium voltage-gated channel subunit alpha 1F (CACNA1F) levels, while IGHV 3-74 levels decreased in both cross-sectional and longitudinal serum analyses. ZFP-814 remained upregulated during the CM-to-EM reversion but was suppressed when CM persisted. CACNA1F was pronounced in CM persistence. Pathway analysis revealed immune, coagulation, glucose metabolism, erythrocyte oxygen and carbon dioxide exchange, and insulin-like growth factor regulation pathways. Conclusion: Our data-driven study provides evidence for identifying novel proteomic biomarker signatures to diagnose, subclassify, and predict treatment responses for migraine. The dysregulated biomolecules affect multiple pathways, leading to cortical spreading depression, trigeminal nociceptor sensitization, oxidative stress, blood–brain barrier disruption, immune response, and coagulation cascades. Trial registration: NCT03231241, ClincialTrials.gov.