Theory of Omics-Integrated Aging Networks

David Aphkhazava, Zanda Bedinashvili, Ketevan Chakhnashvili, Irma Jikia, Maia Nozadze



Background:  The Theory of Omics-Integrated Aging Networks represents a groundbreaking and comprehensive approach to unraveling the intricate process of human aging. Aging, a universal biological phenomenon, remains a complex and multifaceted subject of scientific inquiry. This theory offers a holistic perspective by integrating insights from various omics disciplines, encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and lipidomics. Aging, rather than being solely attributed to isolated factors, is viewed as a dynamic network of molecular events and interactions. This article expounds upon the core principles of this theory and underscores its significance for both current research and future practical applications in understanding aging and age-related diseases. The Theory of Omics-Integrated Aging Networks redefines the aging process as a network phenomenon, where genes, proteins, metabolites, and epigenetic modifications are interconnected elements, engaging in intricate dialogues, and influencing each other's functions, shaping the trajectory of aging. This holistic perspective offers a fresh lens through which we can unravel the complexities of aging. Central to this theory is the call for omics integration. To holistically understand aging, researchers must consider the collective insights from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and lipidomics. These omics disciplines provide unique layers of information, and their convergence allows us to construct a comprehensive and interconnected picture of aging. By merging these data sources, we gain a more profound understanding of how genetic variations, gene expression patterns, protein-protein interactions, metabolic pathways, and epigenetic changes collectively contribute to the aging process. The Theory of Omics-Integrated Aging Networks posits that aging-related traits and conditions are emergent properties of this intricate network. By examining how various elements within the network evolve with age, we can identify critical nodes and pathways responsible for the emergence of age-related phenotypes. This approach holds great promise for uncovering the underlying causes of age-related diseases, allowing us to develop more targeted interventions. Recognizing the uniqueness of each individual's aging network is also a pivotal aspect of this theory. An individual's aging process is influenced by a combination of genetics, environmental factors, and lifestyle choices. Applying omics approaches at a personalized level empowers us to understand the specific factors that drive an individual's aging journey, potentially leading to the development of tailored anti-aging strategies.

Conclusion: In conclusion, the Theory of Omics-Integrated Aging Networks presents a revolutionary perspective on human aging, one that holds the promise of not only deepening our understanding but also transforming our approach to promoting healthier aging and extending lifespans. This holistic framework, while inspiring, also necessitates careful consideration of ethical and privacy concerns in the era of personalized omics data. As this theory continues to evolve, it offers hope for a future where individuals can age in better health and with enhanced quality of life.


Aging; Omics; Genomics; Epigenomics; Transcriptomics; Proteomics; Lipidomics.

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