Precision geronutrition: personalized nutritional strategies to extend healthy lifespan

Abstract

Aging is a multifactorial and heterogeneous biological process, where chronological age alone does not accurately reflect an individual’s functional or physiological state. The emerging discipline of precision geronutrition integrates the principles of geroscience with precision nutrition, aiming to delay the onset of age-related functional decline by modulating fundamental molecular mechanisms, such as nutrient-sensing pathways (mTOR, AMPK, and sirtuins), inflammaging, and oxidative stress. A major barrier to progress has been the absence of validated biomarkers that can quantify biological aging and assess intervention efficacy. Recent advances in biological aging clocks, in particular DNA methylation–based epigenetic clocks, provide powerful tools to objectively measure biological age, and evaluate the impact of nutritional interventions. This review outlines the conceptual framework of precision geronutrition, highlights molecular targets relevant to dietary modulation, and discusses the role of aging clocks as tools for assessing biological aging in preventive and personalized nutrition. The integration of dynamic aging clocks into nutritional intervention frameworks will be essential to transition from a disease-oriented model to a preventive, healthspan-centered paradigm. Future challenges include large-scale clinical validation, standardization of aging biomarkers, cost reduction, and translation into public health and clinical applications.

INTRODUCTION

During the period 1950-2023, global life expectancy increased by 25.1 years for female, and 23.6 years for male (1). This has resulted in a rapid demographic shift towards older populations. Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function, and increased vulnerability to death. However, the aging process is not homogenous. While chronological age—the number of years lived—is a primary risk factor for functional impairments, chronic diseases, and mortality, it is a poor predictor of an individual's functional capacity, resilience, or disease susceptibility. Thus, this underscores the need to elucidate the biological aging process and the determinants of healthy aging. Biological aging reflects the cumulative, progressive decline in physiological integrity driven by molecular and cellular damage, which varies significantly between individuals (2).

Healthy ageing is the process of developing and maintaining the functional ability that enables wellbeing in older age (3). Nutrition is a fundamental pillar of health, and diet is the modifiable factor that exerts the greatest impact on human health and wellbeing (4). For decades, dietary guidelines for healthy aging have largely followed a “one-size-fits-all” approach. However, it is now evident from the advancement of precision nutrition that inter-individual variability in responses to diet is substantial, influenced by a complex interplay of genetics, epigenetics, gut microbiome, and metabolic phenotype (5).

Concurrently, the field of geroscience has provided a powerful framework by positing that targeting the fundamental biological mechanisms of aging itself—the “hallmarks of aging”—could simultaneously delay the onset of multiple age-related conditions, and thereby extend healthspan (6). These hallmarks, which include epigenetic alterations, deregulated nutrient-sensing, and chronic inflammation —referred to as inflammaging— provide a molecular roadmap for interventions.

The convergence of these two fields is giving rise to a new, integrative paradigm, that of precision geronutrition. This approach leverages personalized nutritional strategies to modulate core aging pathways. To date, translation to clinical practice has been limited by the lack of robust, dynamic biomarkers to quantify biological aging and objectively measure intervention efficacy. Recent advances in biological aging clocks, particularly those based on epigenetic markers—such as DNA methylation—have begun to address this gap (7, 8). These clocks provide quantitative estimates of biological age, enabling the validation and refinement of personalized nutritional strategies.

In this review, we introduce the conceptual framework of precision geronutrition, including its molecular targets, and the evidence for nutritional modulation. We describe the pivotal role of multi-omics data and biological aging clocks in personalizing dietary interventions and monitoring their effectiveness. Overall, this review discusses the translational potential and future challenges of integrating these approaches to promote a shift from disease treatment to healthspan-focused preventive medicine.

DEFINITION OF PRECISION GERONUTRITION

Precision geronutrition is an evidence-based discipline that integrates individualized biological information into the design of targeted nutritional interventions, thereby modulating the fundamental mechanisms of aging. This approach integrates principles from geroscience with the analytical frameworks of precision nutrition, utilizing genomic, epigenetic, metabolomic, proteomic, and microbiome data to guide personalized dietary strategies (9).

Unlike conventional geriatric nutrition, which primarily focuses on correcting nutrient deficiencies or managing age-related functional decline, precision geronutrition emphasizes the proactive modulation of biological processes that drive aging, including dysregulated nutrient-sensing, inflammaging, mitochondrial dysfunction, gut microbiome, and the loss of proteostasis. Positioned at the interface of systems biology, nutrition science, and preventive medicine, this emerging field aims to maintain metabolic resilience and physiological integrity through molecularly informed dietary strategies (9).

The association between dietary factors and healthy aging has been demonstrated in longitudinal cohorts with more than 100,000 participants over the last three decades (10). This study has suggested a score for dietary factors that are associated with healthy aging. Healthy aging has been defined by preserved cognitive, physical, and mental health, and by survival to age 70 free of major chronic disease. However, interindividual variability in response to specific dietary components has not been considered—representing a key limitation.

To develop personalized diet strategies, individual variability in dietary response needs to be measured. These individual-level responses to the same foods can then be used to build predictive algorithms for personalized dietary recommendations. Among candidate readouts, postprandial glycemic responses to identical foods are prioritized, because they vary widely across individuals, and respond promptly on an individual basis (11). This led to early personalized nutrition programs that target cardiometabolic health, and recent studies have shown the improved efficacy of personalized advice over standard dietary guidance in this domain (12).

Because personalized nutrition should be developed based on biological phenotype, multi-omics profiling is needed to interrogate the physiological and molecular basis of interindividual differences. Epigenomic, metabolomic, and microbiome data can be used to characterize aging phenotypes, which can in turn inform the contribution of physiological and metabolic factors to aging-clock measures. In parallel, dietary assessment should evaluate diet-derived features that may modulate aging clocks, including degree of food processing, macronutrient composition, and meal timing. Study of how these characteristics interact with aging-clock dynamics remains incomplete.

Integration of multi-omics data, individual food-response profiles, and diet features linked to healthy aging will enable the development of prediction models for personalized dietary recommendations. These models should be validated through clinical studies, using changes in aging-clock measures alongside functional and metabolic outcomes. Fig. 1 shows an overview of the developmental strategy for precision geronutrition:

Fig. 1.

Developing personalized dietary recommendations for healthy aging in precision geronutrition.

FUNDAMENTAL MECHANISMS OF PRECISION GERONUTRITION

The efficacy of precision geronutrition depends on its ability to target the biological process of aging. The key molecular pathways through which nutritional components can modulate these processes can provide the scientific basis for targeted dietary interventions.

Nutrient-sensing pathways

Nutrient-sensing pathways constitute a central regulatory network that links nutrient availability to cellular metabolism, stress adaptation, and longevity (13, 14). Among these, mTOR, AMPK, and the Sirtuin family form a tightly interconnected signaling axis that integrates energy status with molecular mechanisms of aging. Imbalances within this axis, which are often driven by nutrient excess, mitochondrial stress, or chronic inflammation, accelerate biological aging, whereas dietary or pharmacological interventions that restore its homeostasis promote longevity across diverse organisms (15-18). The mTOR pathway functions as a key anabolic regulator that promotes cellular growth, protein synthesis, and lipid biosynthesis in response to nutrient abundance (19). In senescent cells, mTORC1 activity remains chronically elevated, leading to impaired autophagy and accelerated cellular aging (20, 21). Dietary interventions and bioactive phytochemical supplements have been shown to inhibit mTORC1 signaling and extend lifespan. For example, curcumin has been reported to inhibit TORC1—the yeast ortholog of mammalian mTORC1— activity and extend lifespan in yeast, while Epigallocatechin gallate has been shown to suppress cellular senescence by the inhibition of mTOR pathway (22, 23). Moreover, caloric restriction (CR) has been shown to suppress activated mTOR signaling in aged skeletal muscle, suggesting a potential link between the anti-aging effects of CR, and the modulation of mTOR signaling (24).

In contrast, AMPK acts as a metabolic checkpoint activated by increased AMP/ATP ratios under nutrient stress. AMPK suppresses mTORC1 signaling, stimulates mitochondrial biogenesis via PGC−1α, and enhances autophagy, thereby preserving cellular energy balance (25). Vitamin D has been shown to enhance AMPK activity in both cellular and animal models (26, 27). In addition, resveratrol, a bioactive phytochemical known to activate AMPK, has been shown to activate AMPK and attenuate oxidative stress–induced cellular senescence, as well as to suppress skin aging in mice (28, 29). The Sirtuin family (SIRT1-SIRT7) serves as a set of NAD^＋–dependent deacetylases that regulate DNA repair, chromatin remodeling, and mitochondrial function (30). Declining NAD^＋ levels with age impair Sirtuin activity, leading to loss of genomic stability and reduced metabolic efficiency (31). Essential nutrients that support NAD^＋ biosynthesis—such as niacin (vitamin B3), nicotinamide, and the essential amino acid tryptophan tryptophan—contribute to the maintenance of Sirtuin activity (32). In addition, CR and various bioactive compounds, including resveratrol and quercetin, can enhance NAD^＋ levels and thereby promote SIRT1 activation (33-36).

Inflammaging

Inflammaging is a systemic chronic inflammation that is accompanied by cellular senescence, immunosenescence, organ dysfunction, and age-related diseases (37). Factors secreted by senescent cells, known as the senescence-associated secretory phenotype (SASP), promote chronic inflammation, and can induce senescence in normal cells (38). In addition, chronic inflammation accelerates the senescence of immune cells, resulting in weakened immune function, and an inability to clear senescent cells (39). Vitamin D has been shown to exert anti-inflammaging effects in human gingival fibroblasts, and omega-3 reduced inflammation in various diseases (40, 41). Furthermore, Several dietary phytochemicals including curcumin, anthocyanins, catechin/epicatechin, and oleuropein exhibit neuroprotective activity through the modulation of neuro-inflammaging (42).

Mitochondrial function and oxidative stress

Mitochondria are central regulators of cellular energy metabolism and redox balance. During aging, mitochondrial dysfunction leads to impaired ATP production, excessive generation of reactive oxygen species (ROS), and subsequent oxidative damage to DNA, proteins, and lipids. These changes contribute to cellular senescence and tissue functional decline. Precision geronutrition aims to restore mitochondrial homeostasis through personalized nutritional strategies that target mitochondrial metabolism and antioxidant defense. Key interventions include the optimization of NAD^＋ metabolism to support sirtuin–mediated mitochondrial maintenance, supplementation with coenzyme Q10 (CoQ10) to enhance electron transport efficiency, and dietary inclusion of polyphenols and antioxidant vitamins to mitigate oxidative stress. Furthermore, bioactive nutrients, such as omega–3 fatty acids, polyphenol-rich foods, and vitamins C and E, exhibit synergistic effects in reducing pro-inflammatory cytokine secretion and enhancing endogenous antioxidant systems (e.g., glutathione and superoxide dismutase) (43-45). Collectively, these approaches highlight the potential of precision nutritional modulation to counteract mitochondrial dysfunction and oxidative stress, thereby sustaining metabolic resilience while delaying biological aging.

Modulation of the gut microbiome

The gut microbiome undergoes dysbiosis with age, characterized by reduced diversity and an increase in pro-inflammatory taxa (46, 47). Dietary fibers reaching the colon are anaerobically fermented by the gut bacteria, which produce short-chain fatty acids (SCFAs) as metabolic by-products, such as acetate, propionate, and butylate. Among SCFAs, acetate typically accounts for about 60-75% of the total fecal SCFAs (48). Butyrate is a histone deacetylase inhibitor with potent anti-inflammatory activity and mitigates neuroinflammation in aged mice (49). CR has been shown to prevent age-related alterations in the gut microbiome, while adherence to a Mediterranean diet modulates the gut microbial composition to promote a healthy lifespan (50, 51). Thus, targeting the microbiome through personalized dietary strategies represents a promising avenue within precision geronutrition to promote a healthy lifespan.

Proteostasis and cellular maintenance

Proteostasis refers to the dynamic balance of protein synthesis, folding, repair, and degradation that ensures proper protein function and cellular integrity. Aging disrupts this tightly regulated network, leading to the accumulation of misfolded or damaged proteins, activation of endoplasmic reticulum (ER) stress, and a progressive decline in cellular function. Precision geronutrition seeks to restore proteostatic balance through nutritional modulation tailored to individual metabolic profiles. Adjusting both the quantity and quality of protein intake is critical to maintain protein turnover, while bioactive dietary components, such as spermidine and resveratrol, stimulate autophagy, facilitating the removal of damaged proteins and organelles to enhance cellular housekeeping. Moreover, amino acid balance, including methionine restriction and the regulation of branched-chain amino acids (BCAAs), can fine-tune mTOR signaling, and reduce age-related proteotoxic stress (52, 53). Maintaining proteostasis and cellular maintenance thus constitutes a pivotal target of precision geronutrition, linking nutritional regulation to molecular mechanisms that preserve cellular homeostasis and promote healthy longevity.

DIETARY INFLUENCE ON BIOLOGICAL AGING ASSESSED BY AGING CLOCK

Aging clocks

The paradigm for measuring aging has shifted from chronological years to biological age. Aging clocks are used to quantity biological age, which is more informative than chronological age to reflect an organism’s aging condition (54). Molecular ageing clocks are machine learning algorithms that are trained from specific molecular omics data, including genomic, epigenomic, proteomic, and metabolomic biomarkers (Table 1). These clocks can be used to monitor and evaluate the efficacy of dietary strategy to delay biological aging in precision geronutrition.

Table 1.

Representative epigenomic, transcriptomic, proteomic, and metabolomic aging clocks

	Clock name	Biomarkers	Predictive accuracy	Key features	Reference
Epigenetic clock	Horvath Clock (2013)	353 CpG sites	r = 0.96; MAE: 3.6 years	Pan-tissue clock; applicable across 51 tissue and cell types	(7)
	Hannum Clock (2013)	71 CpG sites	r = 0.91; MAE: ∼4.9 years	Blood-specific; focuses on intrinsic aging	(55)
	DNAm PhenoAge (Levine)	513 CpG sites and Gompertz cofficients	HR = 0.98, P = 2.72E-2	Predicts multiple aging-related endpoints	(57)
	DNAm GrimAge	1,030 CpG sites (7 DNAm plasma protein surrogates + smoking pack-years)	HR = 1.12, P = 8.6E-5	Best mortality and aging outcomes predictor using plasma protein surrogates and smoking years	(56)
	DunedinPACE	173 CpG sites	HR = 1.26, 95% CI for mortality 1.14–1.40	Tracks pace of aging over time to measures rate of biological aging; sensitive to interventions	(59)
Proteomic clock	Lehallier Ultra-Predictive Clock	491 proteins (SOMAmers)	r = 0.98 (learning); r = 0.96 (test); MAE: 2.44 years (test)	Most accurate proteomic clock	(70)
	Tanaka Age Signature	76-protein signature (from 1,301 proteins analyzed)	HR = 1.03, 95% CI 1.02-1.04	PROage (estimated biological age) and PROaccel (biological age acceleration)	(69)
	Menni Age Signature	11 circulating proteins	Clear relationship with age	Identifies circulating age-associated proteins	(66)
	ProtAge	204 age-related proteins	r = 0.94, MAE = 2.24	Associated with 18 major chronic disease and biological, physical, and cognitive function	(68)
Metabolomic clock	Metabolic Age Score (Hertel)	59 urinary metabolites	r = 0.96 for women; r = 0.93 for men	1H NMR spectroscopy; urine-based metabolomics	(74)
	LC-MS Metabolome Clock (Lassen)	Untargeted metabolite measurement using UHPLC-QATOF	RMSE: 5.88 years; r2 = 0.63	Whole blood samples, neural network model,	(75)
	MileAge	168 plasma metabolites	HR = 1.51; 95% CI, 1.43-1.59	More predictive of all-casue of mortality and strongly associated with health and aging markers	(76)

r, Correlation; MAE, Mean Absolute Error; HR, Hazard ratio; CI, Confident Interval; RMSE, Root Mean Square Error.

Epigenetic clocks

Epigenetic clocks are the most established ageing clocks, and use DNA methylation (DNAm) features at CpG dinucleotides (7, 55). DNAm clocks yield estimates of biological age acceleration, termed DNAm age. These clocks can accurately predict age across a wide range of different tissue types. To increase the predictive accuracy of biological age, non-epigenic ageing biomarkers, such as inflammatory and metabolic markers in blood plasma, and smoking years, are included for machine learning training either at a single time point (PhenoAge and GrimAge clocks), or from successive longitudinal measurements of ageing biomarkers aimed at capturing the pace of ageing (DunedinPoAm and DunedinPACE clocks) (8, 56-59). Nutritional interventions have been shown to modulate DNA methylation patterns that are associated with biological age. Dietary interventions significantly reduce epigenetic aging (60, 61). In a study of twins, an 8-week vegan diet intervention resulted in a significantly slower rate of epigenetic aging, compared to the omnivorous diet group (62). In addition, polyphenolic modulators of DNA methylation, such as garlic, berries, green tea, and oolong tea, have been reported to play a significant role in reducing epigenetic age (63). Specific nutrients, such as folate, vitamin B12, and betaine, which are involved in one-carbon metabolism, directly influence the availability of methyl groups, and thereby affect epigenetic regulation (64, 65). Collectively, these studies highlight the potential of dietary interventions and food components to modulate epigenetic age, thereby emphasizing the possibility of nutritional approaches to control biological age.

Proteomic clocks

Proteomic clocks quantify biological age based on age-associated plasma proteins. Technical advances in mass spectrometry-based, antibody-based, and aptamer-based proteomics have led to the development of multiple proteomic ageing clocks that use human plasma and cerebrospinal fluids (66-68). The plasma protein-based ageing clock showed association with mortality, multi-morbidity, healthspan, and lifespan, while many proteins in this clock were modulated by parabiosis in mice and exercise in humans, two rejuvenation paradigms (69, 70). Healthy dietary patterns can modulate proteomic profiles in the human body, and these proteomic alterations may contribute to the regulation of various age-related diseases (71, 72). However, the limitations remain that plasma protein concentrations can be affected by the function of many organs, such as the kidney (73).

Metabolomic clocks

Metabolomic clocks employ small-molecule metabolites that reflect mitochondrial function, lipid metabolism, and redox balance (74-76). As aging progresses, mitochondrial dysfunction, altered energy metabolism, oxidative stress, and the dysregulation of lipid and amino acid metabolism occur; these changes are directly reflected in circulating metabolite profiles, such as NAD^＋, lactate, branched-chain amino acids, and SCFAs (77). Although studies that directly demonstrate improvements in metabolomic clocks through nutritional or dietary interventions remain limited, evidence suggests that metabolomic changes induced by dietary supplementation and gut microbiome modulation through polyphenol-rich diets may represent promising strategies to modulate metabolomic aging trajectories (78, 79).

PRECISION GERONUTRITION IN PRACTICE: THE PERSONALIZED CYCLE

Multi-omics profiling and biomarker-based nutrition integrate diverse biological data sets, including genomics, epigenomics, metabolomics, transcriptomics, and metagenomics, to generate a holistic view of an individual's health and aging status. By collecting and analyzing data across these molecular layers, researchers can identify genetic predispositions, metabolic activities, and microbiome compositions that influence diet–health interactions (80, 81). Advanced bioinformatics and machine-learning techniques are then applied to merge these data, uncovering biomarkers and pathways that reflect metabolic dysfunctions or inflammatory processes. For example, specific microbial metabolites identified through metabolomics and metagenomics may serve as biomarkers for insulin resistance or chronic inflammation (82). This systems-level integration allows for the precise identification of biological targets, such as altered NAD^＋ metabolism or aberrant immune signaling, that contribute to age-related physiological decline (83). Once these molecular targets are defined, the data guide the design of personalized nutritional interventions that are aimed at restoring homeostasis and promoting healthy aging. For example, individuals showing NAD^＋ metabolic dysfunction may benefit from diets or supplements that enhance NAD^＋ synthesis, while those exhibiting chronic inflammation may be recommended anti-inflammatory dietary patterns, such as a modified Mediterranean diet (84). Similarly, in cases of gut microbiota imbalance, specific prebiotics or probiotics can be prescribed to promote microbial diversity and improve metabolic function (85).

TRANSLATIONAL PERSPECTIVES AND CHALLENGES

The integration of biological aging clocks with precision geronutrition offers a framework for converting molecular aging science into actionable healthcare. However, several challenges must be addressed before these approaches can be effectively implemented in clinical and public health contexts. A major limitation is the lack of standardized methodologies to assess biological age. Since the first report of an epigenetic aging clock, several clocks have been developed using cohort data to estimate biological age relative to chronological age. As summarized in Table 1, these models draw on diverse inputs—including the methylome, metabolome, and transcriptome. However, their performance characteristics and intended endpoints differ across clocks (e.g., accuracy, calibration, and prognostic validity), limiting comparability and hindering uniform interpretation. At this point, multi-omics approaches have emerged as a powerful complementary strategy to enhance biological age estimation. Integrating genomic, epigenomic, transcriptomic, proteomic, metabolomic, and microbiome data enables a more comprehensive characterization of aging biology, while machine-learning–based modeling can reveal biomarker networks associated with healthspan and exceptional longevity (86, 87). By capturing regulatory changes across multiple molecular layers, multi-omics–derived aging measures provide greater sensitivity and mechanistic resolution than single-omic clocks, and importantly, allow evaluation of how nutritional interventions modulate aging trajectories—thereby supporting precision geronutrition as a clinically actionable framework. Collectively, these advancements establish multi-omics aging clocks as a practical foundation for precision geronutrition, enabling quantifiable assessment of dietary effects on biological aging. However, to translate this potential into clinical utility, standardized reference frameworks and large-scale, longitudinal validation across diverse populations remain essential. Another important challenge is accessibility. Comprehensive multi-omics profiling remains largely confined to research settings, limiting its applicability to everyday healthcare. To make biological-age assessment feasible for routine health monitoring, advances in high-throughput sequencing, single-cell omics, and metabolomic technologies are required. Integrating these tools into digital health platforms could further reduce accessibility barriers by enabling remote sampling, real-time data integration, and automated interpretation. Ethical and social considerations are equally important (88, 89). The ability to quantify biological age raises concerns about data privacy, potential discrimination, and psychological burden. Misuse of biological-age information by employers or insurers could exacerbate inequities. Therefore, ethical and regulatory frameworks must evolve alongside scientific progress to ensure data protection, informed consent, and equitable access. Biological age should be viewed as a dynamic, modifiable health indicator, rather than a determinant of personal worth or potential. The complexity of individual nutritional responses adds another layer of challenge. Factors such as genetics, gut microbiome composition, lifestyle, medication use, and environmental exposure shape personalized dietary outcomes. Consequently, precision geronutrition must rely on AI-driven, multivariate models, rather than single-variable approaches (90). Systems biology and digital–twin simulations—virtual models of individual metabolic systems—offer promising tools to predict optimal interventions and minimize trial-and-error in personalized dietary strategies (90). Finally, clinical integration and public-health adaptation are critical for successful translation. Healthcare professionals must be trained to interpret biological-age data, and apply it effectively in patient management. At a population level, early identification of accelerated aging through biological clocks could guide targeted dietary recommendations to prevent disease onset. Policymakers should promote education, accessibility, and the cost-effective implementation of geronutritional strategies to ensure that the benefits of precision nutrition are equitably distributed across socioeconomic groups.

CONCLUSION AND FUTURE DIRECTIONS

Precision geronutrition represents an emerging and transformative paradigm that integrates molecular geroscience with personalized nutrition to decelerate biological aging and extend healthspan. By harnessing multi-omics profiling and biological aging clocks, this approach enables individualized, data-driven nutritional interventions that can be objectively monitored over time. The integration of nutrition science with dynamic, quantifiable biomarkers marks a critical step toward preventive, precision-based health management. Rather than addressing diseases after their onset, precision geronutrition seeks to modulate the molecular mechanisms that precede pathological aging, positioning nutrition as a proactive determinant of longevity. Biological aging clocks, particularly multi-omics models, provide essential tools to evaluate the efficacy of interventions and reframe aging as a modifiable biological process. Future efforts should prioritize large-scale clinical validation linking aging-clock metrics to measurable health outcomes; the development of integrative platforms that unify genomic, metabolic, and dietary data for real-time analysis; and the translation of these precision approaches into public health frameworks. Ensuring accessibility and cost-effectiveness will be crucial for broad implementation. Ultimately, the convergence of precision nutrition, multi-omics technologies, and biological aging clocks will enable a new era of proactive health management, in which the pace of aging itself becomes a measurable and modifiable target for lifelong wellbeing.