Abstract

UPADHATU DYSFUNCTION AS EARLY BIOMARKERS OF SYSTEMIC PATHOPHYSIOLOGY: A TRANSLATIONAL PERSPECTIVE FROM CLASSICAL AYURVEDA TO MODERN DIAGNOSTICS

Dr. Vraj Vihari Mishra, Dr. Prasad Kalya, Dr. Soumya Madabhavi, Dr. Dushyant D. Patil*

Abstract

Background: Upadhatu (subsidiary tissue systems) in Ayurvedic medicine represent a sophisticated understanding of secondary metabolic products that maintain physiological equilibrium. Despite their clinical significance, these entities remain inadequately integrated with contemporary biomedical knowledge. Objective: This integrative review examines the traditional conceptualization of Upadhatu within classical Ayurvedic literature and establishes evidence-based correlations with modern tissue physiology and pathophysiology. Methods: A comprehensive analysis was conducted using primary Ayurvedic texts (Brihat Trayi and selected Laghu Trayi) alongside peer-reviewed biomedical literature from 2000-2024. Each Upadhatu Kandara (tendons), Sira (vascular structures), Snayu (ligaments), Rajju (fascial networks), Aartava (menstrual physiology), and Stanya (lactation) was systematically evaluated for anatomical, physiological, and pathological correlations. Results: The analysis reveals significant concordance between Upadhatu concepts and established biomedical understanding of connective tissue matrices, vascular physiology, reproductive endocrinology, and lactation biology. These correlations suggest that Upadhatu dysfunction may serve as early biomarkers for systemic pathophysiology, offering predictive diagnostic value in integrative healthcare approaches. Conclusions: This synthesis provides a scientific framework for understanding Upadhatu as functionally relevant tissue derivatives with diagnostic and therapeutic implications. The findings support the potential integration of Ayurvedic Upadhatu assessment in contemporary clinical practice and suggest avenues for translational research.

Keywords: Ayurvedic physiology, Upadhatu, tissue metabolism, integrative medicine, biomedical correlations, systems biology.