Precision Longevity: a Systems Biology framework for dynamic metabolic modulation and Healthspan optimization

This work proposes an integrative framework combining constitutional systems biology (Prakriti) with dynamic phenotypic monitoring (Vikriti) within longevity-oriented nutritional interventions. The objective is to establish a precision-based adaptive model capable of identifying individual hormetic resilience thresholds through the integration of molecular biomarkers, clinical phenotyping, and digital data streams. By mapping key nutrient-sensing pathways—including mTOR, AMPK, and IGF-1 signaling axes—this framework introduces a digitally validated phenotyping system aimed at preventing metabolic maladaptation and optimizing translational efficacy of dietary interventions. Key innovations include the Bio-Analogical Coherence Index (ICBA) and a Composite Resilience Index for real-time assessment of adaptive capacity. Validation Note This framework is currently presented as a theoretical and operational proposal. It requires further clinical validation and empirical research to correlate the proposed phenotypic indices with long-term metabolic outcomes and biological aging markers. Disclaimer This document is for informational and educational purposes only and presents a theoretical scientific framework. It does not constitute medical advice, diagnosis, or treatment. The nutritional strategies and phenotypic monitoring protocols described herein should only be implemented under the supervision of qualified healthcare professionals. The author remains independent and assumes no liability for the unauthorized application of the proposed theoretical models.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-27
DOI
https://doi.org/10.5281/zenodo.19249820
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
article
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article

Precision Longevity: a Systems Biology framework for dynamic metabolic modulation and Healthspan optimization

V. Luongo
Zenodo (CERN European Organization for Nuclear Research)
Genetics, Aging, and Longevity in Model Organisms
article

Precision Longevity: a Systems Biology framework for dynamic metabolic modulation and Healthspan optimization

V. Luongo
article en

Abstract

This work proposes an integrative framework combining constitutional systems biology (Prakriti) with dynamic phenotypic monitoring (Vikriti) within longevity-oriented nutritional interventions. The objective is to establish a precision-based adaptive model capable of identifying individual hormetic resilience thresholds through the integration of molecular biomarkers, clinical phenotyping, and digital data streams. By mapping key nutrient-sensing pathways—including mTOR, AMPK, and IGF-1 signaling axes—this framework introduces a digitally validated phenotyping system aimed at preventing metabolic maladaptation and optimizing translational efficacy of dietary interventions. Key innovations include the Bio-Analogical Coherence Index (ICBA) and a Composite Resilience Index for real-time assessment of adaptive capacity. Validation Note This framework is currently presented as a theoretical and operational proposal. It requires further clinical validation and empirical research to correlate the proposed phenotypic indices with long-term metabolic outcomes and biological aging markers. Disclaimer This document is for informational and educational purposes only and presents a theoretical scientific framework. It does not constitute medical advice, diagnosis, or treatment. The nutritional strategies and phenotypic monitoring protocols described herein should only be implemented under the supervision of qualified healthcare professionals. The author remains independent and assumes no liability for the unauthorized application of the proposed theoretical models.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 8%
Genetics, Aging, and Longevity in Model Organisms
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Precision Longevity: a Systems Biology framework for dynamic metabolic modulation and Healthspan optimization — V. Luongo · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS