The Neuropsychological Predictive bridge: mapping Manas Gunas via Standard and Advanced PNEI biomarkers for Adaptive Systems Medicine

This research paper introduces the GAP (Guna-Adaptive-Predictive) methodology, a pioneering theoretical framework that bridges ancient Ayurvedic psychology with modern Psychoneuroendocrinology and Immunology (PNEI) and Systems Medicine. The author proposes a quantitative model to map the three Manas Gunas—Sattva, Rajas, and Tamas—onto measurable biological signatures. The core of the work is the Guna Biological Score (GBS), a mathematically formalized index that integrates dual-tier biomarkers, including standard neuroendocrine markers (Cortisol/DHEA-S ratio, HRV, inflammatory cytokines) and advanced omics (BDNF, epigenetic clocks, microRNA signatures, and Ayurgenomics). By applying machine learning logic (Random Forests and LSTM networks), the framework aims to identify "Predictive Bridges"—biological precursors that anticipate neuropsychological state transitions before clinical symptoms emerge. This paper provides a scalable clinical algorithm for personalized, preventive, and adaptive health interventions. Key Features: Mathematical Formalization: definition of the GBS via weighted Z-scores and logistic normalization. Multi-Omic Integration: strategic alignment of Ayurgenomics (COMT, MAO-A, DRD2) with epigenetic and gut-brain axis markers. Predictive Modeling: use of temporal velocity calculations to forecast phenotypic shifts. Bioethical Governance: strict compliance with GDPR and international genomic data standards. Summary Disclaimer & Disclosure Status: phase 5 (Theoretical Framework & Pre-Validation). Legal Notice: this work represents an original theoretical synthesis and the exclusive intellectual property of the author, Valentina Luongo. The methodology presented is for research and educational purposes only and does not constitute medical advice, diagnosis, or prescription. Requirement for Supervision: any future clinical application or validation of the GAP framework and GBS scoring must be conducted under the strict supervision of licensed medical professionals and authorized research institutions. The author disclaims all liability for any unauthorized or unsupervised use of the information contained herein. Disclosure: the author declares no conflicts of interest. Generative AI was utilized solely for linguistic refinement and academic structuring; all conceptual logic and original integration are the property of the author.