The metabolomics of human aging: Advances, challenges, and opportunities

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

A Single-Cell Metabolic Profiling Characterizes Human Aging via SlipChip-SERS

Metabolic dysregulation is a key driver of cellular senescence, contributing to the progression of systemic aging. The heterogeneity of senescent cells and their metabolic shifts are complex and unexplored. A microfluidic SlipChip integrated with surface-enhanced Raman spectroscopy (SERS), termed SlipChip-SERS, is developed for single-cell metabolism analysis. This SlipChip-SERS enables compartmentalization of single cells, parallel delivery of saponin and nanoparticles to release intracellular metabolites and to realize SERS detection with simple slipping operations. Analysis of different cancer cell lines using SlipChip-SERS demonstrated its capability for sensitive and multiplexed metabolic profiling of individual cells. When applied to human primary fibroblasts of different ages, it identified 12 differential metabolites, with spermine validated as a potent inducer of cellular senescence. Prolonged exposure to spermine can induce a classic senescence phenotype, such as increased senescence-associated β-glactosidase activity, elevated expression of senescence-related genes and reduced LMNB1 levels. Additionally, the senescence-inducing capacity of spermine in HUVECs and WRL-68 cells is confirmed, and exogenous spermine treatment increased the accumulation and release of H2O2. Overall, a novel SlipChip-SERS system is developed for single-cell metabolic analysis, revealing spermine as a potential inducer of senescence across multiple cell types, which may offer new strategies for addressing ageing and ageing-related diseases.

Does Microbiome Contribute to Longevity? Compositional and Functional Differences in Gut Microbiota in Chinese Long-Living (>90 Years) and Elderly (65-74 Years) Adults

The study of longevity and its determinants has been revitalized with the rise of microbiome scholarship. The gut microbiota have been established to play essential protective, metabolic, and physiological roles in human health and disease. The gut dysbiosis has been identified as an important factor contributing to the development of multiple diseases. Accordingly, it is reasonable to hypothesize that the gut microbiota of long-living individuals have healthy antiaging-associated gut microbes, which, by extension, might provide specific molecular targets for antiaging treatments and interventions. In the present study, we compared the gut microbiota of Chinese individuals in two different age groups, long-living adults (aged over 90 years) and elderly adults (aged 65-74 years) who were free of major diseases. We found significantly lower relative abundances of bacteria in the genera Sutterella and Megamonas in the long-living individuals. Furthermore, we established that while biological processes such as autophagy (GO:0006914) and telomere maintenance through semiconservative replication (GO:0032201) were enhanced in the long-living group, response to lipopolysaccharide (GO:0032496), nicotinamide adenine dinucleotide oxidation (GO:0006116), and S-adenosyl methionine metabolism (GO:0046500) were weakened. Moreover, the two groups were found to differ with respect to amino acid metabolism. We suggest that these compositional and functional differences in the gut microbiota may potentially be associated with mechanisms that contribute to determining longevity or aging.

Potential implications of natural compounds on aging and metabolic regulation

Aging is generally accompanied by a progressive loss of metabolic homeostasis. Targeting metabolic processes is an attractive strategy for healthy-aging. Numerous natural compounds have demonstrated strong anti-aging effects. This review summarizes recent findings on metabolic pathways involved in aging and explores the anti-aging effects of natural compounds by modulating these pathways. The potential anti-aging effects of natural extracts rich in biologically active compounds are also discussed. Regulating the metabolism of carbohydrates, proteins, lipids, and nicotinamide adenine dinucleotide is an important strategy for delaying aging. Furthermore, phenolic compounds, terpenoids, alkaloids, and nucleotide compounds have shown particularly promising effects on aging, especially with respect to metabolism regulation. Moreover, metabolomics is a valuable tool for uncovering potential targets against aging. Future research should focus on identifying novel natural compounds that regulate human metabolism and should delve deeper into the mechanisms of metabolic regulation using metabolomics methods, aiming to delay aging and extend lifespan.

Exploring the heterogeneous targets of metabolic aging at single-cell resolution

Our limited understanding of metabolic aging poses major challenges to comprehending the diverse cellular alterations that contribute to age-related decline, and to devising targeted interventions. This review provides insights into the heterogeneous nature of cellular metabolism during aging and its response to interventions, with a specific focus on cellular heterogeneity and its implications. By synthesizing recent findings using single-cell approaches, we explored the vulnerabilities of distinct cell types and key metabolic pathways. Delving into the cell type-specific alterations underlying the efficacy of systemic interventions, we also discuss the complexity of integrating single-cell data and advocate for leveraging computational tools and artificial intelligence to harness the full potential of these data, develop effective strategies against metabolic aging, and promote healthy aging.

Mass Spectrometry-Based Multiomics Identifies Metabolic Signatures of Sarcopenia in Rhesus Monkey Skeletal Muscle

Sarcopenia is a progressive disorder characterized by age-related loss of skeletal muscle mass and function. Although significant progress has been made over the years to identify the molecular determinants of sarcopenia, the precise mechanisms underlying the age-related loss of contractile function remains unclear. Advances in "omics" technologies, including mass spectrometry-based proteomic and metabolomic analyses, offer great opportunities to better understand sarcopenia. Herein, we performed mass spectrometry-based analyses of the vastus lateralis from young, middle-aged, and older rhesus monkeys to identify molecular signatures of sarcopenia. In our proteomic analysis, we identified proteins that change with age, including those involved in adenosine triphosphate and adenosine monophosphate metabolism as well as fatty acid beta oxidation. In our untargeted metabolomic analysis, we identified metabolites that changed with age largely related to energy metabolism including fatty acid beta oxidation. Pathway analysis of age-responsive proteins and metabolites revealed changes in muscle structure and contraction as well as lipid, carbohydrate, and purine metabolism. Together, this study discovers new metabolic signatures and offers new insights into the molecular mechanisms underlying sarcopenia for the evaluation and monitoring of a therapeutic treatment of sarcopenia.

The role of estrogen in Alzheimer's disease pathogenesis and therapeutic potential in women

Estrogens are pivotal regulators of brain function throughout the lifespan, exerting profound effects from early embryonic development to aging. Extensive experimental evidence underscores the multifaceted protective roles of estrogens on neurons and neurotransmitter systems, particularly in the context of Alzheimer's disease (AD) pathogenesis. Studies have consistently revealed a greater risk of AD development in women compared to men, with postmenopausal women exhibiting heightened susceptibility. This connection between sex factors and long-term estrogen deprivation highlights the significance of estrogen signaling in AD progression. Estrogen's influence extends to key processes implicated in AD, including amyloid precursor protein (APP) processing and neuronal health maintenance mediated by brain-derived neurotrophic factor (BDNF). Reduced BDNF expression, often observed in AD, underscores estrogen's role in preserving neuronal integrity. Notably, hormone replacement therapy (HRT) has emerged as a sex-specific and time-dependent strategy for primary cardiovascular disease (CVD) prevention, offering an excellent risk profile against aging-related disorders like AD. Evidence suggests that HRT may mitigate AD onset and progression in postmenopausal women, further emphasizing the importance of estrogen signaling in AD pathophysiology. This review comprehensively examines the physiological and pathological changes associated with estrogen in AD, elucidating the therapeutic potential of estrogen-based interventions such as HRT. By synthesizing current knowledge, it aims to provide insights into the intricate interplay between estrogen signaling and AD pathogenesis, thereby informing future research directions and therapeutic strategies for this debilitating neurodegenerative disorder.

Alterations in metabolome and lipidome in patients with in-stent restenosis

CONTEXT

In-stent restenosis (ISR) can lead to blood flow obstruction, insufficient blood supply to the brain, and may even result in serious complications such as stroke. Endothelial cell hyperproliferation and thrombosis are the primary etiologies, frequently resulting in alterations in intravascular metabolism. However, the metabolic changes related to this process are still undermined.

OBJECTIVE

We tried to characterize the serum metabolome of patients with ISR and those with non-restenosis (NR) using metabolomics and lipidomics, exploring the key metabolic pathways of this pathological phenomenon.

RESULTS

We observed that the cysteine and methionine pathways, which are associated with cell growth and oxidative homeostasis, showed the greatest increase in the ISR group compared to the NR group. Within this pathway, the levels of N-formyl-l-methionine and L-methionine significantly increased in the ISR group, along with elevated levels of downstream metabolites such as 2-ketobutyric acid, pyruvate, and taurocholate. Additionally, an increase in phosphatidylcholine (PC) and phosphatidylserine (PS), as well as a decrease in triacylglycerol in the ISR group, indicated active lipid metabolism in these patients, which could be a significant factor contributing to the recurrence of blood clots after stent placement. Importantly, phenol sulfate and PS(38:4) were identified as potential biomarkers for distinguishing ISR, with an area under the curve of more than 0.85.

CONCLUSIONS

Our study revealed significant metabolic alterations in patients with ISR, particularly in the cysteine and methionine pathways, with phenol sulfate and PS(38:4) showing promise for ISR identification.

Loss of temporal coherence in the circadian metabolome across multiple tissues during ageing in mice

Circadian clock function declines with ageing, which can aggravate ageing-related diseases such as type 2 diabetes and neurodegenerative disorders. Understanding age-related changes in the circadian system at a systemic level can contribute to the development of strategies to promote healthy ageing. The goal of this study was to investigate the impact of ageing on 24-h rhythms in amine metabolites across four tissues in young (2 months of age) and old (22-25 months of age) mice using a targeted metabolomics approach. Liver, plasma, the suprachiasmatic nucleus (SCN; the location of the central circadian clock in the hypothalamus) and the paraventricular nucleus (PVN; a downstream target of the SCN) were collected from young and old mice every 4 h during a 24-h period (n = 6-7 mice per group). Differential rhythmicity analysis revealed that ageing impacts 24-h rhythms in the amine metabolome in a tissue-specific manner. Most profound changes were observed in the liver, in which rhythmicity was lost in 60% of the metabolites in aged mice. Furthermore, we found strong correlations in metabolite levels between the liver and plasma and between the SCN and the PVN in young mice. These correlations were almost completely abolished in old mice. These results indicate that ageing is accompanied by a severe loss of the circadian coordination between tissues and by disturbed rhythmicity of metabolic processes. The tissue-specific impact of ageing may help to differentiate mechanisms of ageing-related disorders in the brain versus peripheral tissues and thereby contribute to the development of potential therapies for these disorders.

NMR metabolomic modeling of age and lifespan: A multicohort analysis

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

Biomarkers of Cellular Senescence and Aging: Current State-of-the-Art, Challenges and Future Perspectives

Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence-associated β-galactosidase staining, telomere shortening, cell-cycle arrest, DNA methylation, and senescence-associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging-associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi-omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging-associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.

Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks

Aging is a complex and time-dependent decline in physiological function that affects most organisms, leading to increased risk of age-related diseases. Investigating the molecular underpinnings of aging is crucial to identify geroprotectors, precisely quantify biological age, and propose healthy longevity approaches. This review explores pathways that are currently being investigated as intervention targets and aging biomarkers spanning molecular, cellular, and systemic dimensions. Interventions that target these hallmarks may ameliorate the aging process, with some progressing to clinical trials. Biomarkers of these hallmarks are used to estimate biological aging and risk of aging-associated disease. Utilizing aging biomarkers, biological aging clocks can be constructed that predict a state of abnormal aging, age-related diseases, and increased mortality. Biological age estimation can therefore provide the basis for a fine-grained risk stratification by predicting all-cause mortality well ahead of the onset of specific diseases, thus offering a window for intervention. Yet, despite technological advancements, challenges persist due to individual variability and the dynamic nature of these biomarkers. Addressing this requires longitudinal studies for robust biomarker identification. Overall, utilizing the hallmarks of aging to discover new drug targets and develop new biomarkers opens new frontiers in medicine. Prospects involve multi-omics integration, machine learning, and personalized approaches for targeted interventions, promising a healthier aging population.

Aging-accumulated methylmalonic acid serum levels at breast cancer diagnosis are not associated with distant metastases

PURPOSE

Recent evidence suggests that age-accumulated methylmalonic acid (MMA) promotes breast cancer progression in mice. This study aims to investigate the association between baseline serum MMA concentrations in patients with breast cancer and the development of subsequent distant metastases.

METHODS

We included 32 patients with early Luminal B-like breast cancer (LumB, median age 62.4y) and 52 patients with early triple-negative breast cancer (TNBC, median age 50.5y) who developed distant metastases within 5 years. They were matched to an equal number of early breast cancer patients (median age 62.2y for LumB and 50.5y for TNBC) who did not develop distant metastases with at least 5 years of follow-up.

RESULTS

Baseline serum MMA levels at breast cancer diagnosis showed a positive correlation with age (P < 0.001) and a negative correlation with renal function and vitamin B12 (all P < 0.02), but no statistical association was found with BMI or tumor stage (P > 0.6). Between matched pairs, no significant difference was observed in MMA levels, after adjusting for kidney function and age (P = 0.19). Additionally, in a mouse model, a significant decline in MMA levels was observed in the tumor-bearing group compared to the group without tumors before and after tumor establishment or at identical times for the control group (P = 0.03).

CONCLUSION

Baseline serum MMA levels in patients with breast cancer are not correlated with secondary distant metastasis. Evidence in the mouse model suggests that the presence of a tumor perturbates MMA levels.

Effects of short-term moderate intensity exercise on the serum metabolome in older adults: a pilot randomized controlled trial

BACKGROUND

We previously reported changes in the serum metabolome associated with impaired myocardial relaxation in an asymptomatic older community cohort. In this prospective parallel-group randomized control pilot trial, we subjected community adults without cardiovascular disease to exercise intervention and evaluated the effects on serum metabolomics.

METHODS

Between February 2019 to November 2019, thirty (83% females) middle-aged adults (53 ± 4 years) were randomized with sex stratification to either twelve weeks of moderate-intensity exercise training (Intervention) (n = 15) or Control (n = 15). The Intervention group underwent once-weekly aerobic and strength training sessions for 60 min each in a dedicated cardiac exercise laboratory for twelve weeks (ClinicalTrials.gov: NCT03617653). Serial measurements were taken pre- and post-intervention, including serum sampling for metabolomic analyses.

RESULTS

Twenty-nine adults completed the study (Intervention n = 14; Control n = 15). Long-chain acylcarnitine C20:2-OH/C18:2-DC was reduced in the Intervention group by a magnitude of 0.714 but increased in the Control group by a magnitude of 1.742 (mean difference -1.028 age-adjusted p = 0.004). Among Controls, alanine correlated with left ventricular mass index (r = 0.529, age-adjusted p = 0.018) while aspartate correlated with Lateral e' (r = -764, age-adjusted p = 0.016). C20:3 correlated with E/e' ratio fold-change in the Intervention group (r = -0.653, age-adjusted p = 0.004). Among Controls, C20:2/C18:2 (r = 0.795, age-adjusted p = 0.005) and C20:2-OH/C18:2-DC fold-change (r = 0.742, age-adjusted p = 0.030) correlated with change in E/A ratio.

CONCLUSIONS

Corresponding relationships between serum metabolites and cardiac function in response to exercise intervention provided pilot observations. Future investigations into cellular fuel oxidation or central carbon metabolism pathways that jointly impact the heart and related metabolic systems may be critical in preventive trials.

Urinary Biomarkers for Lupus Nephritis: A Systems Biology Approach

Systemic lupus erythematosus (SLE) is the prototypical systemic autoimmune disorder. Kidney involvement, termed lupus nephritis (LN), is seen in 40-60% of patients with systemic lupus erythematosus (SLE). After the diagnosis, serial measurement of proteinuria is the most common method of monitoring treatment response and progression. However, present treatments for LN-corticosteroids and immunosuppressants-target inflammation, not proteinuria. Furthermore, subclinical renal inflammation can persist despite improving proteinuria. Serial kidney biopsies-the gold standard for disease monitoring-are also not feasible due to their inherent risk of complications. Biomarkers that reflect the underlying renal inflammatory process and better predict LN progression and treatment response are urgently needed. Urinary biomarkers are particularly relevant as they can be measured non-invasively and may better reflect the compartmentalized renal response in LN, unlike serum studies that are non-specific to the kidney. The past decade has overseen a boom in applying cutting-edge technologies to dissect the pathogenesis of diseases at the molecular and cellular levels. Using these technologies in LN is beginning to reveal novel disease biomarkers and therapeutic targets for LN, potentially improving patient outcomes if successfully translated to clinical practice.

Influence of age and sex on longitudinal metabolic profiles and body weight trajectories in the UK Biobank

BACKGROUND

Accurate characterization of how age influences body weight and metabolism at different stages of life is important for understanding ageing processes. Here, we explore observational longitudinal associations between metabolic health and weight from the fifth to the seventh decade of life, using carefully adjusted statistical designs.

METHODS

Body measures and biochemical data from blood and urine (220 measures) across two visits were available from 10 104 UK Biobank participants. Participants were divided into stable (within ±4% per decade), weight loss and weight gain categories. Final subgroups were metabolically matched at baseline (48% women, follow-up 4.3 years, ages 41-70; n = 3368 per subgroup) and further stratified by the median age of 59.3 years and sex.

RESULTS

Pulse pressure, haemoglobin A1c and cystatin-C tracked ageing consistently (P < 0.0001). In women under 59, age-associated increases in citrate, pyruvate, alkaline phosphatase and calcium were observed along with adverse changes across lipoprotein measures, fatty acid species and liver enzymes (P < 0.0001). Principal component analysis revealed a qualitative sex difference in the temporal relationship between body weight and metabolism: weight loss was not associated with systemic metabolic improvement in women, whereas both age strata converged consistently towards beneficial (weight loss) or adverse (weight gain) phenotypes in men.

CONCLUSIONS

We report longitudinal ageing trends for 220 metabolic measures in absolute concentrations, many of which have not been described for older individuals before. Our results also revealed a fundamental dynamic sex divergence that we speculate is caused by menopause-driven metabolic deterioration in women.

Implications of metabolism on multi-systems healthy aging across the lifespan

Aging is increasingly thought to involve dysregulation of metabolism in multiple organ systems that culminate in decreased functional capacity and morbidity. Here, we seek to understand complex interactions among metabolism, aging, and systems-wide phenotypes across the lifespan. Among 2469 adults (mean age 74.7 years; 38% Black) in the Health, Aging and Body Composition study we identified metabolic cross-sectionally correlates across 20 multi-dimensional aging-related phenotypes spanning seven domains. We used LASSO-PCA and bioinformatic techniques to summarize metabolome-phenome relationships and derive metabolic scores, which were subsequently linked to healthy aging, mortality, and incident outcomes (cardiovascular disease, disability, dementia, and cancer) over 9 years. To clarify the relationship of metabolism in early adulthood to aging, we tested association of these metabolic scores with aging phenotypes/outcomes in 2320 participants (mean age 32.1, 44% Black) of the Coronary Artery Risk Development in Young Adults (CARDIA) study. We observed significant overlap in metabolic correlates across the seven aging domains, specifying pathways of mitochondrial/cellular energetics, host-commensal metabolism, inflammation, and oxidative stress. Across four metabolic scores (body composition, mental-physical performance, muscle strength, and physical activity), we found strong associations with healthy aging and incident outcomes, robust to adjustment for risk factors. Metabolic scores for participants four decades younger in CARDIA were related to incident cardiovascular, metabolic, and neurocognitive performance, as well as long-term cardiovascular disease and mortality over three decades. Conserved metabolic states are strongly related to domain-specific aging and outcomes over the life-course relevant to energetics, host-commensal interactions, and mechanisms of innate immunity.

A molecular index for biological age identified from the metabolome and senescence-associated secretome in humans

Unlike chronological age, biological age is a strong indicator of health of an individual. However, the molecular fingerprint associated with biological age is ill-defined. To define a high-resolution signature of biological age, we analyzed metabolome, circulating senescence-associated secretome (SASP)/inflammation markers and the interaction between them, from a cohort of healthy and rapid agers. The balance between two fatty acid oxidation mechanisms, β-oxidation and ω-oxidation, associated with the extent of functional aging. Furthermore, a panel of 25 metabolites, Healthy Aging Metabolic (HAM) index, predicted healthy agers regardless of gender and race. HAM index was also validated in an independent cohort. Causal inference with machine learning implied three metabolites, β-cryptoxanthin, prolylhydroxyproline, and eicosenoylcarnitine as putative drivers of biological aging. Multiple SASP markers were also elevated in rapid agers. Together, our findings reveal that a network of metabolic pathways underlie biological aging, and the HAM index could serve as a predictor of phenotypic aging in humans.

MGDHGS: Gene-bridged metabolite-disease relationships prediction via GraphSAGE and self-attention mechanism

Metabolites represent the underlying information of biological systems. Revealing the links between metabolites and diseases can facilitate the development of targeted drugs. Traditional biological experiments can be used to validate the relationships of metabolite-disease, but these methods are time-consuming and labor-intensive. In contrast, the prevailing computational methods have improved efficiency but primarily rely on the metabolite-disease interactions, overlooking the impact of other biological components. To remedy the problem, we present a novel computational framework (MGDHGS) based on metabolite-gene-disease heterogeneous network to forecast potential associations. Specifically, we initially integrate data from multiple sources to construct metabolite-gene-disease heterogeneous network that includes known associations and computationally-derived similarities. Then, the GraphSAGE is harnessed to learn the low dimensional neighborhood representation in the heterogeneous network and self-attention mechanism is applied to effectively capture the connectivity patterns, which contributions to combine with nodes intrinsic and extrinsic features. Finally, the ultimate relationships probability scores are predicted by linear regression based on the these characteristics. The five-fold cross-validation showcases impressive AUC (0.9734) and PR (0.9718) for MGDHGS compared with five state-of-the-art methods, and the case studies validate that the metabolite-disease associations predicted by MGDHGS can be substantiated through pertinent biological experiments. The findings of this study show great potential contribution in the development of targeted drugs as well as offering solid support for our understanding of the complex interactions between metabolites, genes and diseases.

Multi-omics characterization of partial chemical reprogramming reveals evidence of cell rejuvenation

Partial reprogramming by cyclic short-term expression of Yamanaka factors holds promise for shifting cells to younger states and consequently delaying the onset of many diseases of aging. However, the delivery of transgenes and potential risk of teratoma formation present challenges for in vivo applications. Recent advances include the use of cocktails of compounds to reprogram somatic cells, but the characteristics and mechanisms of partial cellular reprogramming by chemicals remain unclear. Here, we report a multi-omics characterization of partial chemical reprogramming in fibroblasts from young and aged mice. We measured the effects of partial chemical reprogramming on the epigenome, transcriptome, proteome, phosphoproteome, and metabolome. At the transcriptome, proteome, and phosphoproteome levels, we saw widescale changes induced by this treatment, with the most notable signature being an upregulation of mitochondrial oxidative phosphorylation. Furthermore, at the metabolome level, we observed a reduction in the accumulation of aging-related metabolites. Using both transcriptomic and epigenetic clock-based analyses, we show that partial chemical reprogramming reduces the biological age of mouse fibroblasts. We demonstrate that these changes have functional impacts, as evidenced by changes in cellular respiration and mitochondrial membrane potential. Taken together, these results illuminate the potential for chemical reprogramming reagents to rejuvenate aged biological systems and warrant further investigation into adapting these approaches for in vivo age reversal.

Integrated metabolomic and lipidomic analysis revealed the protective mechanisms of Erzhi Wan on senescent NRK cells through BRL cells

ETHNOPHARMACOLOGICAL RELEVANCE

Erzhi Wan (EZW), as a prescription of traditional Chinese medicine, has been used for tonifying the liver and kidney. Although past studies have shown that EZW has potential anti-aging effect, the mechanisms associated with cellular metabolomics and lipidomics are not fully understood.

AIM OF THE STUDY

This study aimed to evaluate the anti-aging effect of EZW and investigate the mechanisms associated with cellular metabolomics and lipidomics.

MATERIALS AND METHODS

EZW solution at dosage of 3.6 g/kg in Sprague-Dawley rats was orally administered twice a day for 7 days and serum containing EZW was then collected. NRK cell senescence model induced by D-galactose was established in vitro, and non-contact co-culture cell assay was performed between senescent NRK cells and BRL cells intervened by serum containing EZW. The anti-aging effect of EZW on NRK cells was evaluated by metabolites identification, differential metabolites screening and metabolic pathways analysis through cellular metabolomics with GC-MS and lipidomics with UHPLC-Q-Exactive Orbitrap/MS.

RESULTS

Serum containing EZW indicated a protective effect through intervening BRL cells in non-contact co-culture system with D-gal-induced senescent NRK cells. For metabolic profiles, 71 endogenous metabolites were identified, among which 24 significantly differential metabolites were screened as metabolomics potential biomarkers. For lipidic profiles, 64 lipid components were identified in NRK cell samples under positive ion mode, among which 24 potential biomarkers of lipids were screened, mainly including PC and PE. 127 lipid components were identified in NRK cell samples under negative ion mode, among which 59 potential biomarkers of lipids were screened, including FA, PC, PE, PI and PS. Metabolic pathway analysis demonstrated that the identified differential metabolites found mainly involved in amino acids metabolism, energy metabolism and phospholipid biosynthesis pathways.

CONCLUSION

Serum containing EZW exhibited protective effect on D-gal-induced senescent NRK cells through intervening BRL cells by mainly regulating amino acids metabolism, energy metabolism and phospholipid biosynthesis pathways to possess its anti-aging function, providing a theoretical basis for clinical treatment of EZW.

Protein kinase D (PKD) on the crossroad of lipid absorption, synthesis and utilization

Inappropriate lipid levels in the blood, as well as its content and composition in different organs, underlie multiple metabolic disorders including obesity, non-alcoholic fatty liver disease, type 2 diabetes, and atherosclerosis. Multiple processes contribute to the complex metabolism of triglycerides (TGs), fatty acids (FAs), and other lipid species. These consist of digestion and absorption of dietary lipids, de novo FAs synthesis (lipogenesis), uptake of TGs and FAs by peripheral tissues, TGs storage in the intracellular depots as well as lipid utilization for β-oxidation and their conversion to lipid-derivatives. A majority of the enzymatic reactions linked to lipogenesis, TGs synthesis, lipid absorption, and transport are happening at the endoplasmic reticulum, while β-oxidation takes place in mitochondria and peroxisomes. The Golgi apparatus is a central sorting, protein- and lipid-modifying organelle and hence is involved in lipid metabolism as well. However, the impact of the processes taking part in the Golgi apparatus are often overseen. The protein kinase D (PKD) family (composed of three members, PKD1, 2, and 3) is the master regulator of Golgi dynamics. PKDs are also a sensor of different lipid species in distinct cellular compartments. In this review, we discuss the roles of PKD family members in the regulation of lipid metabolism including the processes executed by PKDs at the Golgi apparatus. We also discuss the role of PKDs-dependent signaling in different cellular compartments and organs in the context of the development of metabolic disorders.

Bioinspired Fluorine Labeling for 19F NMR-Based Plasma Amine Profiling

Metabolite profiling serves as a powerful tool that advances our understanding of biological systems, disease mechanisms, and environmental interactions. In this study, we present an approach employing 19F-nuclear magnetic resonance (19F NMR) spectroscopy for plasma amine profiling. This method utilizes a highly efficient and reliable fluorine-labeling reagent, 3,5-difluorosalicylaldehyde, which effectively emulates pyridoxal phosphate, facilitating the formation of Schiff base compounds with primary amines. The fluorine labeling allows for distinct resolution of 19F NMR signals from amine mixtures, leading to precise identification and quantification of amine metabolites in human plasma. This advancement offers valuable tools for furthering metabolomics research.

Targeting Efferocytosis in Inflammaging

Rapid removal of apoptotic cells by phagocytes, a process known as efferocytosis, is key for the maintenance of tissue homeostasis, the resolution of inflammation, and tissue repair. However, impaired efferocytosis can result in the accumulation of apoptotic cells, subsequently triggering sterile inflammation through the release of endogenous factors such as DNA and nuclear proteins from membrane permeabilized dying cells. Here, we review the molecular basis of the three key phases of efferocytosis, that is, the detection, uptake, and degradation of apoptotic materials by phagocytes. We also discuss how defects in efferocytosis due to the alteration of phagocytes and dying cells can contribute to the low-grade chronic inflammation that occurs during aging, described as inflammaging. Lastly, we explore opportunities in targeting and harnessing the efferocytic machinery to limit aging-associated inflammatory diseases.

Multi-omics characterization of partial chemical reprogramming reveals evidence of cell rejuvenation

Partial reprogramming by cyclic short-term expression of Yamanaka factors holds promise for shifting cells to younger states and consequently delaying the onset of many diseases of aging. However, the delivery of transgenes and potential risk of teratoma formation present challenges for in vivo applications. Recent advances include the use of cocktails of compounds to reprogram somatic cells, but the characteristics and mechanisms of partial cellular reprogramming by chemicals remain unclear. Here, we report a multi-omics characterization of partial chemical reprogramming in fibroblasts from young and aged mice. We measured the effects of partial chemical reprogramming on the epigenome, transcriptome, proteome, phosphoproteome, and metabolome. At the transcriptome, proteome, and phosphoproteome levels, we saw widescale changes induced by this treatment, with the most notable signature being an upregulation of mitochondrial oxidative phosphorylation. Furthermore, at the metabolome level, we observed a reduction in the accumulation of aging-related metabolites. Using both transcriptomic and epigenetic clock-based analyses, we show that partial chemical reprogramming reduces the biological age of mouse fibroblasts. We demonstrate that these changes have functional impacts, as evidenced by changes in cellular respiration and mitochondrial membrane potential. Taken together, these results illuminate the potential for chemical reprogramming reagents to rejuvenate aged biological systems and warrant further investigation into adapting these approaches for in vivo age reversal.

NMR metabolomic modelling of age and lifespan: a multi-cohort analysis

Metabolomic age models have been proposed for the study of biological aging, however they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. 98 metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈ 31,000 individuals, age range 24-86 years). We used non-linear and penalised regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with ageing risk factors and phenotypes. Within the UK Biobank (N≈ 102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, chronic obstructive pulmonary disease) and all-cause mortality. Cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47-0.65 in the training set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with chronological age were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06 / metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

How do metabolic processes age: Evidence from human metabolomic studies

Metabolomics, the global profiling of small molecules in the body, has emerged as a promising analytical approach for assessing molecular changes associated with ageing at the population level. Understanding root metabolic ageing pathways may have important implications for managing age-related disease risk. In this short review, relevant studies published in the last few years that have made valuable contributions to this field will be discussed. These include large-scale studies investigating metabolic changes with age, metabolomic clocks, and metabolic pathways associated with ageing phenotypes. Recent significant advances include the use of longitudinal study designs, populations spanning the whole life course, standardised analytical platforms of enhanced metabolome coverage and development of multivariate analyses. While many challenges remain, recent studies have demonstrated the considerable promise of this field.

Plasma metabolomic profiles associated with mortality and longevity in a prospective analysis of 13,512 individuals

Experimental studies reported biochemical actions underpinning aging processes and mortality, but the relevant metabolic alterations in humans are not well understood. Here we examine the associations of 243 plasma metabolites with mortality and longevity (attaining age 85 years) in 11,634 US (median follow-up of 22.6 years, with 4288 deaths) and 1878 Spanish participants (median follow-up of 14.5 years, with 525 deaths). We find that, higher levels of N2,N2-dimethylguanosine, pseudouridine, N4-acetylcytidine, 4-acetamidobutanoic acid, N1-acetylspermidine, and lipids with fewer double bonds are associated with increased risk of all-cause mortality and reduced odds of longevity; whereas L-serine and lipids with more double bonds are associated with lower mortality risk and a higher likelihood of longevity. We further develop a multi-metabolite profile score that is associated with higher mortality risk. Our findings suggest that differences in levels of nucleosides, amino acids, and several lipid subclasses can predict mortality. The underlying mechanisms remain to be determined.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Extraction, bioactive function and application of wheat germ protein/peptides: A review

The aging population and high incidence of age-related diseases are major global societal issues. Consuming bioactive substances as part of our diet is increasingly recognized as essential for ensuring a healthy life for older adults. Wheat germ protein has a reasonable peptide structure and amino acid ratio but has not been fully utilized and exploited, resulting in wasted wheat germ resources. This review summarizes reformational extraction methods of wheat germ protein/peptides (WGPs), of which different methods can be selected to obtain various WGPs. Interestingly, except for some bioactive activities found earlier, WGPs display potential anti-aging activity, with possible mechanisms including antioxidant, immunomodulatory and intestinal flora regulation. However, there are missing in vitro and in vivo bioactivity assessments of WGPs. WGPs possess physicochemical properties of good foamability, emulsification and water retention and are used as raw materials or additives to improve food quality. Based on the above, further studies designing methods to isolate particular types of WGPs, determining their nutritional and bioactive mechanisms and verifying their activity in vivo in humans are crucial for using WGPs to improve human health.

Biomarkers of aging

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.

A Metabolic Driven Bio-Responsive Hydrogel Loading Psoralen for Therapy of Rheumatoid Arthritis

Overexpressed matrix metalloproteinases, hypoxia microenvironment, and metabolic abnormality are important pathological signs of rheumatoid arthritis (RA). Designing a delivery carrier according to the pathological characteristics of RA that can control drug release in response to disease severity may be a promising treatment strategy. Psoralen is the main active ingredient isolated from Psoralea corylifolia L. and possesses excellent anti-inflammatory activities as well as improving bone homeostasis. However, the specific underlying mechanisms, particularly the possible relationships between the anti-RA effects of psoralen and related metabolic network, remain largely unexplored. Furthermore, psoralen shows systemic side effects and has unsatisfactory solubility. Therefore, it is desirable to develop a novel delivery system to maximize psoralen's therapeutic effect. In this study, a self-assembled degradable hydrogel platform is developed that delivers psoralen and calcium peroxide to arthritic joints and controls the release of psoralen and oxygen according to inflammatory stimulation, to regulate homeostasis and the metabolic disorder of the anoxic arthritic microenvironment. Therefore, the hydrogel drug delivery system based on the responsiveness of the inflammatory microenvironment and regulation of metabolism provides a new therapeutic strategy for RA treatment.

SIRT4 in ageing

Ageing is a phenomenon in which cells, tissues and organs undergo systemic pathological changes as individuals age, leading to the occurrence of ageing-related diseases and the end of life. It is associated with many phenotypes known as ageing characteristics, such as genomic instability, nutritional imbalance, mitochondrial dysfunction, cell senescence, stem cell depletion, and an altered microenvironment. The sirtuin family (SIRT), known as longevity proteins, is thought to delay ageing and prolong life, and mammals, including humans, have seven family members (SIRT1-7). SIRT4 has been studied less among the sirtuin family thus far, but it has been reported that it has important physiological functions in organisms, such as promoting DNA damage repair, participating in the energy metabolism of three substances, inhibiting inflammatory reactions and apoptosis, and regulating mitochondrial function. Recently, some studies have demonstrated the involvement of SIRT4 in age-related processes, but knowledge in this field is still scarce. Therefore, this review aims to analyse the relationship between SIRT4 and ageing characteristics as well as some age-related diseases (e.g., cardiovascular diseases, metabolic diseases, neurodegenerative diseases and cancer).

Impact of aging on meningeal gene expression

BACKGROUND

The three-layered meninges cover and protect the central nervous system and form the interface between cerebrospinal fluid and the brain. They are host to a lymphatic system essential for maintaining fluid dynamics inside the cerebrospinal fluid-filled subarachnoid space and across the brain parenchyma via their connection to glymphatic structures. Meningeal fibroblasts lining and traversing the subarachnoid space have direct impact on the composition of the cerebrospinal fluid through endocytotic uptake as well as extensive protein secretion. In addition, the meninges are an active site for immunological processes and act as gatekeeper for immune cells entering the brain. During aging in mice, lymphatic drainage from the brain is less efficient contributing to neurodegenerative processes. Aging also affects the immunological status of the meninges, with increasing numbers of T cells, changing B cell make-up, and altered macrophage complement.

METHODS

We employed RNASeq to measure gene expression and to identify differentially expressed genes in meninges isolated from young and aged mice. Using Ingenuity pathway, GO term, and MeSH analyses, we identified regulatory pathways and cellular functions in meninges affected by aging.

RESULTS

Aging had profound impact on meningeal gene expression. Pathways related to innate as well as adaptive immunity were affected. We found evidence for increasing numbers of T and B lymphocytes and altered activity profiles for macrophages and other myeloid cells. Furthermore, expression of pro-inflammatory cytokine and chemokine genes increased with aging. Similarly, the complement system seemed to be more active in meninges of aged mice. Altered expression of solute carrier genes pointed to age-dependent changes in cerebrospinal fluid composition. In addition, gene expression for secreted proteins showed age-dependent changes, in particular, genes related to extracellular matrix composition and organization were affected.

CONCLUSIONS

Aging has profound effects on meningeal gene expression; thereby affecting the multifaceted functions meninges perform to maintain the homeostasis of the central nervous system. Thus, age-dependent neurodegenerative processes and cognitive decline are potentially in part driven by altered meningeal function.

The Aging Process: A Metabolomics Perspective

Aging process is characterized by a progressive decline of several organic, physiological, and metabolic functions whose precise mechanism remains unclear. Metabolomics allows the identification of several metabolites and may contribute to clarifying the aging-regulated metabolic pathways. We aimed to investigate aging-related serum metabolic changes using a metabolomics approach. Fasting blood serum samples from 138 apparently healthy individuals (20−70 years old, 56% men) were analyzed by Proton Nuclear Magnetic Resonance spectroscopy (1H NMR) and Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS), and for clinical markers. Associations of the metabolic profile with age were explored via Correlations (r); Metabolite Set Enrichment Analysis; Multiple Linear Regression; and Aging Metabolism Breakpoint. The age increase was positively correlated (0.212 ≤ r ≤ 0.370, p < 0.05) with the clinical markers (total cholesterol, HDL, LDL, VLDL, triacylglyceride, and glucose levels); negatively correlated (−0.285 ≤ r ≤ −0.214, p < 0.05) with tryptophan, 3-hydroxyisobutyrate, asparagine, isoleucine, leucine, and valine levels, but positively (0.237 ≤ r ≤ 0.269, p < 0.05) with aspartate and ornithine levels. These metabolites resulted in three enriched pathways: valine, leucine, and isoleucine degradation, urea cycle, and ammonia recycling. Additionally, serum metabolic levels of 3-hydroxyisobutyrate, isoleucine, aspartate, and ornithine explained 27.3% of the age variation, with the aging metabolism breakpoint occurring after the third decade of life. These results indicate that the aging process is potentially associated with reduced serum branched-chain amino acid levels (especially after the third decade of life) and progressively increased levels of serum metabolites indicative of the urea cycle.