Evaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study

Objectives Chronic inflammation drives non-communicable diseases (NCDs) like diabetes, GERD, hypertension, and osteoarthritis. Ayurveda, an ancient system of medicine, emphasizes personalized treatments to restore balance and modulate immunity; however, its effects on cytokine profiles remain incompletely characterized. This study evaluated the impact of Ayurvedic interventions on pro-inflammatory cytokines (IFN-γ, IL-6, IL-17, TNF-α) and anti-inflammatory cytokines (IL-4, IL-10) in patients with non-communicable diseases (NCDs). Methods This prospective observational study included 60 patients receiving Ayurvedic treatment for various NCDs. Cytokine levels were measured pre- and post-treatment using multiplex bead-based assays. Statistical analyses included paired-sample t-tests, Wilcoxon signed-rank tests, effect size determinations, and permutation tests to assess changes in cytokine levels and ratios. Results Ayurvedic treatment was associated with significant reductions in pro-inflammatory cytokines, particularly in patients with diabetes and GERD. Anti-inflammatory cytokines increased in select subgroups, indicating a shift towards reduced inflammation. Pro-inflammatory to anti-inflammatory cytokine ratios decreased significantly, reflecting restored immune balance. Large effect sizes were observed for pro-inflammatory cytokine reductions, while anti-inflammatory cytokines showed moderate-to-small effect sizes. Permutation tests validated these findings, especially for diabetes and GERD. Conclusion Personalized Ayurvedic treatments demonstrate immunomodulatory potential by reducing pro-inflammatory cytokines and enhancing anti-inflammatory cytokines, thereby restoring immune balance in patients with NCDs. These findings support integrating Ayurveda into modern clinical practices for managing inflammatory conditions. However, larger, controlled trials are needed to validate results and explore mechanisms.