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◆ Cureus2026-07-01

Epigenomics and Ayurgenomics: Molecular Analysis of Ayurvedic Prakriti in Personalized Healthcare.

Amit R Nampalliwar, Swati N Khandale, Pooja Singh, Kavita Pradhan, Heera Chand Patel, Chandreshwar Prasad Sinha

原始摘要(英文原文)· Original abstract
Personalized healthcare increasingly requires models that explain individual variation in disease risk, prevention, and treatment response. Ayurvedic Prakriti offers a constitution-based framework for classifying human variability through Vata, Pitta, and Kapha phenotypes, while Ayurgenomics attempts to connect these traditional classifications with molecular biology. Despite growing interest, the biological relationship between Prakriti, epigenomic regulation, and precision healthcare remains insufficiently established, particularly because available evidence is limited by small cohorts, heterogeneous assessment tools, and incomplete biomarker validation. This review examines the molecular relevance of Prakriti by analyzing evidence from genomics, epigenomics, transcriptomics, proteomics, metabolomics, pharmacogenomics, and systems biology. Literature was evaluated thematically to identify constitution-specific molecular signatures, disease susceptibility patterns, lifestyle-related epigenetic influences, and translational applications in individualized healthcare. Current findings suggest that Prakriti types may be associated with distinct biological profiles involving metabolism, inflammation, immune regulation, oxidative stress, stress adaptation, and drug response. Epigenomic mechanisms may further explain how diet, lifestyle, environment, aging, and stress modify gene expression within constitution-specific contexts. Integrating Ayurgenomics with multi-omics platforms may support preventive screening, personalized nutrition, lifestyle planning, and precision therapeutics. Stronger validation through standardized tools, longitudinal studies, and clinical trials remains essential.
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Epigenomics and Ayurgenomics: Molecular Analysis of Ayurvedic Prakriti in Personalized Healthcare. — 科研速览 Science Skim