dysfunction, and cellular senescence.[10] Classical molecular and cellular biomarkers of aging include telomere length, DNA methylation, oxidative stress markers, protein carbonyls, advanced glycation end products, and mitochondrial DNA deletions.[2] These biomarkers have been extensively studied and have shown strong correlations with age. However, they do not provide information on the specific mechanisms of aging that affect each individual. 

3. Omics-Based Biomarkers
Omics-based biomarkers have emerged as a promising approach to assess the multifactorial processes of aging. These biomarkers analyze various molecular data sets, including genomics, transcriptomics, proteomics, and metabolomics. By integrating these data sets, omics-based biomarkers can provide a more comprehensive view of the aging process than classical biomarkers.[2] 

Recent studies have identified several omics-based biomarkers that are strongly associated with age. These include epigenetic clocks based on DNA methylation patterns,[4] transcriptomic signatures of aging,[5] and proteomic profiles of aging.[6] These biomarkers have the potential to reveal novel molecular targets for anti-aging interventions and to predict health outcomes better than classical biomarkers.

4. Future Directions 
In the future, it will be essential to develop biomarker panels that can account for the heterogeneity of the aging process between individuals. Such panels could include both classical and omics-based biomarkers to provide a more comprehensive assessment of aging. Moreover, longitudinal studies are needed to determine the predictive power of these biomarkers for health outcomes. Finally, it will be critical to translate these findings into clinical practice by developing non-invasive and cost-effective methods for assessing biological age.

Overall, the development of reliable biomarkers for assessing biological age is essential for predicting health outcomes and developing effective anti-aging interventions. While classical biomarkers have shown strong correlations with age, omics-based biomarkers have the potential to provide a more comprehensive view of the aging process. In the future, a combination of classical and omics-based biomarkers will likely be used to assess aging in individuals and predict health outcomes., which cause oxidative stress and further mitochondrial damage.[26] This damage can lead to a vicious cycle of increasing oxidative stress and mitochondrial dysfunction that contributes to aging and age-related diseases.[27] Mitochondrial dysfunction can be detected by measuring ATP production, mitochondrial membrane potential, and the production of reactive oxygen species. Oxidative stress can also be measured directly by assessing levels of reactive oxygen species or indirectly by examining markers of oxidative damage to lipids, proteins, and DNA.[28] However, it should be noted that while mitochondrial dysfunction and oxidative stress are strongly associated with aging, their causal relationship with the aging process is still a matter of debate.[29] 

2.4. Dysregulated Nutrient Sensing

Nutrient sensing pathways such as insulin/insulin-like growth factor-1 (IGF-1), target of rapamycin (TOR), and sirtuins play key roles in regulating metabolism, growth, and stress response. Dysregulation of these pathways has been implicated in aging and age-related diseases.[30] For example, reduced activity of the insulin/IGF-1 pathway has been shown to increase lifespan in various organisms,[31] while overactivation of the TOR pathway has been linked to aging and age-related diseases such as cancer.[32] Sirtuins, a family of NAD+-dependent deacetylases, have also been implicated in the regulation of lifespan in various organisms.[33] Dysregulated nutrient sensing can be detected by measuring the activity of these pathways or their downstream effectors.

2.5. Cellular Senescence

Cellular senescence is a process by which cells irreversibly stop dividing in response to various stresses such as DNA damage or oncogenic signaling.[34] Senescent cells accumulate with age and contribute to tissue dysfunction through the secretion of pro-inflammatory cytokines, chemokines, growth factors, and matrix-degrading enzymes collectively known as the senescence-associated secretory phenotype (SASP).[35] Cellular senescence can be detected by measuring markers such as senescence-associated -galactosidase activity or the expression of p16INK4a and p21CIP1, which are cyclin-dependent kinase inhibitors that induce senescence.[36]

2.6. Altered Intercellular Communication