Emerging Insights into the Metabolic Alterations in Aging Using Metabolomics

Metabolic changes associated with PFAS exposure in firefighters: A pilot study

This pilot study investigated the association between occupational exposure to per- and polyfluoroalkyl substances (PFASs) and metabolic profiles among two groups of aviation firefighters (n = 37), with an average of 6 and 31 years of working experience (here referred as junior and senior firefighters) at airports across Australia, with samples collected in 2013. PFAS levels in serum were determined in a previous study to be >17 times higher in the senior firefighter group, reflecting the difference in their occupational exposure to fluorosurfactants among the groups. The aim was to examine metabolic patterns across a broad range of PFAS exposure by comparing metabolic differences and their associations with PFAS levels. In this cross-sectional study, the length of firefighting experience and PFAS levels in serum were both further associated with changes in several classes of metabolites, including free fatty acids, bile acids, amino acids, lipids and metabolites related to gut microbial metabolism. The metabolites associated with the length of firefighting experience showed similarities with the metabolites associated with PFAS levels. A non-monotonic response to PFAS concentrations, particularly in saturated fatty acids, was also observed. In the junior firefighter group, the PFAS concentrations were positively associated with saturated fatty acids, i.e., the saturated fatty acid levels increased with increased PFAS levels. In the senior firefighter group, the trend was opposite, with saturated fatty acids decreasing with increasing levels of PFAS. Accounting for potential confounding factors such as BMI and age could not explain the results. While the study population was small, our results plausibly indicate that PFAS exposure can lead to a metabolic compensation strategy that is disrupted at high, long-term exposures. Our study also suggests that serum metabolites serve as better effect-based markers of the impact of exposure than the traditional clinical measurements alone, such as total triglycerides or total cholesterol.

Personalized Medicine Approach to Proteomics and Metabolomics of Cytochrome P450 Enzymes: A Narrative Review

Cytochrome P450 enzymes (CYPs) represent a diverse family of heme-thiolate proteins involved in the metabolism of a wide range of endogenous compounds and xenobiotics. In recent years, proteomics and metabolomics have been used to obtain a comprehensive insight into the role of CYPs in health and disease aspects. The objective of the present work is to better understand the status of proteomics and metabolomics in CYP research in optimizing therapeutics and patient safety from a personalized medicine approach. The literature used in this narrative review was procured by electronic search of PubMed, Medline, Embase, and Google Scholar databases. The following keywords were used in combination to identify related literature: "proteomics," "metabolomics," "cytochrome P450," "drug metabolism," "disease conditions," "proteome," "liquid chromatography-mass spectrometry," "integration," "metabolites," "pathological conditions." We reviewed studies that utilized proteomics and metabolomics approaches to explore the multifaceted roles of CYPs in identifying disease markers and determining the contribution of CYP enzymes in developing treatment strategies. The applications of various cutting-edge analytical techniques, including liquid chromatography-mass spectrometry, nuclear magnetic resonance, and bioinformatics analyses in CYP proteomics and metabolomics studies, have been highlighted. The identification of CYP enzymes through metabolomics and/or proteomics in various disease conditions provides key information in the diagnostic and therapeutic landscape. Leveraging both proteomics and metabolomics presents a powerful approach for an exhaustive exploration of the multifaceted roles played by CYP enzymes in personalized medicine. Proteomics and metabolomics have enabled researchers to unravel the complex connection between CYP enzymes and metabolic markers associated with specific diseases. As technology and methodologies evolve, an integrated approach promises to further elucidate the role of CYPs in human health and disease, potentially ushering in a new era of personalized medicine.

Discovery of novel disease-causing mutation in SSBP1 and its correction using adenine base editor to improve mitochondrial function

Mutations in nuclear genes regulating mitochondrial DNA (mtDNA) replication are associated with mtDNA depletion syndromes. Using whole-genome sequencing, we identified a heterozygous mutation (c.272G>A:p.Arg91Gln) in single-stranded DNA-binding protein 1 (SSBP1), a crucial protein involved in mtDNA replisome. The proband manifested symptoms including sensorineural deafness, congenital cataract, optic atrophy, macular dystrophy, and myopathy. This mutation impeded multimer formation and DNA-binding affinity, leading to reduced efficiency of mtDNA replication, altered mitochondria dynamics, and compromised mitochondrial function. To correct this mutation, we tested two adenine base editor (ABE) variants on patient-derived fibroblasts. One variant, NG-Cas9-based ABE8e (NG-ABE8e), showed higher editing efficacy (≤30%) and enhanced mitochondrial replication and function, despite off-target editing frequencies; however, risks from bystander editing were limited due to silent mutations and off-target sites in non-translated regions. The other variant, NG-Cas9-based ABE8eWQ (NG-ABE8eWQ), had a safer therapeutic profile with very few off-target effects, but this came at the cost of lower editing efficacy (≤10% editing). Despite this, NG-ABE8eWQ-edited cells still restored replication and improved mtDNA copy number, which in turn recovery of compromised mitochondrial function. Taken together, base editing-based gene therapies may be a promising treatment for mitochondrial diseases, including those associated with SSBP1 mutations.

The Application of Metabolomics in Hyperlipidemia: Insights into Biomarker Discovery and Treatment Efficacy Assessment

Hyperlipidemia is a lipid metabolism disorder that refers to increased levels of total triglycerides (TGs), cholesterol (TC), and low-density lipoprotein-cholesterol (LDL-C) and decreased levels of high-density lipoprotein-cholesterol (HDL-C). It is a major public health issue with increased prevalence and incidence worldwide. The ability to identify individuals at risk of this disorder before symptoms manifest will facilitate timely intervention and management to avert potential complications. This can be achieved by employing metabolomics as an early detection method for the diagnostic biomarkers of hyperlipidemia. Metabolomics is an analytical approach used to detect and quantify metabolites. This provides the ability to explain the metabolic processes involved in the development and progression of certain diseases. In recent years, interest in the use of metabolomics to identify disease biomarkers has increased, and several biomarkers have been discovered, such as docosahexaenoic acid, glycocholic acid, citric acid, betaine, and carnitine. This review discusses the primary metabolic alterations in the context of hyperlipidemia. Furthermore, we provide an overview of recent studies on the application of metabolomics to the assessment of the efficacy of traditional herbal products and common lipid-lowering medications.

Omics analysis unveils changes in the metabolome and lipidome of Caenorhabditis elegans upon polydopamine exposure

Polydopamine (PDA) is an insoluble biopolymer with a dark brown-black color that forms through the autoxidation of dopamine. Because of its outstanding biocompatibility and durability, PDA holds enormous promise for various applications, both in the biomedical and non-medical domains. To ensure human safety, protect health, and minimize environmental impacts, the assessment of PDA toxicity is important. In this study, metabolomics and lipidomics assessed the impact of acute PDA exposure on Caenorhabditis elegans (C. elegans). The findings revealed a pronounced perturbation in the metabolome and lipidome of C. elegans at the L4 stage following 24 hours of exposure to 100 µg/mL PDA. The changes in lipid composition varied based on lipid classes. Increased lipid classes included lysophosphatidylethanolamine, triacylglycerides, and fatty acids, while decreased species involved in several sub-classes of glycerophospholipids and sphingolipids. Besides, we detected 37 significantly affected metabolites in the positive and 8 in the negative ion modes due to exposure to PDA in C. elegans. The metabolites most impacted by PDA exposure were associated with purine metabolism, biosynthesis of valine, leucine, and isoleucine; aminoacyl-tRNA biosynthesis; and cysteine and methionine metabolism, along with pantothenate and CoA biosynthesis; the citrate cycle (TCA cycle); and beta-alanine metabolism. In conclusion, PDA exposure may intricately influence the metabolome and lipidome of C. elegans. The combined application of metabolomics and lipidomics offers additional insights into the metabolic perturbations involved in PDA-induced biological effects and presents potential biomarkers for the assessment of PDA safety.

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.

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.

Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank

The identification of metabolic biomarkers for aging-related diseases and mortality is of significant interest in the field of longevity. In this study, we investigated the associations between nuclear magnetic resonance (NMR) metabolomics biomarkers and aging-related diseases as well as mortality using the UK Biobank dataset. We analyzed NMR samples from approximately 110,000 participants and used multi-head machine learning classification models to predict the incidence of aging-related diseases. Cox regression models were then applied to assess the relevance of NMR biomarkers to the risk of death due to aging-related diseases. Additionally, we conducted survival analyses to evaluate the potential improvements of NMR in predicting survival and identify the biomarkers most strongly associated with negative health outcomes by dividing participants into health, disease, and death groups for all age groups. Our analysis revealed specific metabolomics profiles that were associated with the incidence of age-related diseases, and the most significant biomarker was intermediate density lipoprotein cholesteryl (IDL-CE). In addition, NMR biomarkers could provide additional contributions to relevant mortality risk prediction when combined with conventional risk factors, by improving the C-index from 0.813 to 0.833, with 17 NMR biomarkers significantly contributing to disease-related death, such as monounsaturated fatty acids (MUFA), linoleic acid (LA), glycoprotein acetyls (GlycA), and omega-3. Moreover, the value of free cholesterol in very large HDL particles (XL-HDL-FC) in the healthy control group demonstrated significantly higher values than the disease and death group across all age groups. This study highlights the potential of NMR metabolomics profiling as a valuable tool for identifying metabolic biomarkers associated with aging-related diseases and mortality risk, which could have practical implications for aging-related disease risk and mortality prediction.

Metabolites in aging and aging-relevant diseases: Frailty, sarcopenia and cognitive decline

Aging shows biologically complex features with high individual variability, which reflects the exposure to several stimuli and the adaptation to them. Among them, metabolic changes are well observed as consequences or possible causes of aging. Calorie restriction extends organismal life span in experimental models. Several metabolites; for example, resveratrol or nicotinamide mononucleotide, are reported to mimic calorie restriction effects in vivo. Metabolomic research would be useful to evaluate metabolites as biomarkers in aging-relevant events and to identify metabolic regulation of aging. We recently developed the metabolomic approach for whole blood analysis, which functions as strong tool for this purpose. We review the update findings in aging-relevant metabolites detected by this method. Geriatr Gerontol Int 2024; 24: 44-48.

Omega-3 Fatty Acids for Depression in the Elderly and Patients with Dementia: A Systematic Review and Meta-Analysis

This study aimed to evaluate the efficacy of omega-3 fatty acid supplementation interventions in improving depression in patients with dementia. To achieve this objective, randomized controlled trials (RCTs) were identified from primary electronic databases, focusing on the relationship between omega-3 fatty acids and depression in patients with dementia. The primary outcome was the impact of omega-3 fatty acids on post-intervention depression in patients with dementia, with subgroup analyses conducted based on the type of intervention (docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) combination), duration of intervention (3 months, 6 months, 12 months, ≥24 months), cognitive function (ranging from mild cognitive impairment (MCI) to severe dementia), and daily dosage (high, medium, low, applicable to both DHA and EPA). The study has been duly registered with PROSPERO (registration ID: CRD42023408744). A meta-analysis of five studies (n = 517) included in nine systematic reviews showed that omega-3 supplementation had a non-significant trend toward affecting depressive symptoms in patients with dementia (standardized mean difference (SMD): 0.147; 95% confidence interval (CI): -0.324 to 0.049; p = 0.141). Subgroup analyses revealed that DHA supplementation significantly reduced depressive symptoms (SMD: -0.247; p = 0.039). There was no significant effect for high (SMD: -0.169; 95% CI: -0.454 to 0.116; p = 0.246) or medium (SMD: -0.061; 95% CI: -0.228 to 0.105; p = 0.470) doses of EPA. However, low doses of EPA were significantly effective (SMD: -0.953; 95% CI: -1.534 to -0.373; p = 0.001), with notable improvements in patients with MCI (SMD: -0.934; p < 0.001). The study concludes that omega-3 fatty acids, particularly through DHA supplementation, may alleviate depressive symptoms in patients with MCI. Given the limited sample size, further long-term RCTs are recommended to better understand the efficacy and optimal management of omega-3 supplementation in this population using different dosages.

Metabolomics to Study Human Aging: A Review

In the last years, with the increase in the average life expectancy, the world's population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

Assessing the Biological Mechanisms Linking Smoking Behavior and Cognitive Function: A Mediation Analysis of Untargeted Metabolomics

(1) Smoking is the most significant preventable health hazard in the modern world. It increases the risk of vascular problems, which are also risk factors for dementia. In addition, toxins in cigarettes increase oxidative stress and inflammation, which have both been linked to the development of Alzheimer's disease and related dementias (ADRD). This study identified potential mechanisms of the smoking-cognitive function relationship using metabolomics data from the longitudinal Wisconsin Registry for Alzheimer's Prevention (WRAP). (2) 1266 WRAP participants were included to assess the association between smoking status and four cognitive composite scores. Next, untargeted metabolomic data were used to assess the relationships between smoking and metabolites. Metabolites significantly associated with smoking were then tested for association with cognitive composite scores. Total effect models and mediation models were used to explore the role of metabolites in smoking-cognitive function pathways. (3) Plasma N-acetylneuraminate was associated with smoking status Preclinical Alzheimer Cognitive Composite 3 (PACC3) and Immediate Learning (IMM). N-acetylneuraminate mediated 12% of the smoking-PACC3 relationship and 13% of the smoking-IMM relationship. (4) These findings provide links between previous studies that can enhance our understanding of potential biological pathways between smoking and cognitive function.

Metabolomic profiles associated with physical activity in White and African American adult men

BACKGROUND

Physical activity (PA) is associated with various health benefits, especially in improving chronic health conditions. However, the metabolic changes in host metabolism in response to PA remain unclear, especially in racially/ethnically diverse populations.

OBJECTIVE

This study is to assess the metabolic profiles associated with the frequency of PA in White and African American (AA) men.

METHODS

Using the untargeted metabolomics data collected from 698 White and AA participants (mean age: 38.0±8.0, age range: 20-50) from the Louisiana Osteoporosis Study (LOS), we conducted linear regression models to examine metabolites that are associated with PA levels (assessed by self-reported regular exercise frequency levels: 0, 1-2, and ≥3 times per week) in White and AA men, respectively, as well as in the pooled sample. Covariates considered for statistical adjustments included race (only for the pooled sample), age, BMI, waist circumstance, smoking status, and alcohol drinking.

RESULTS

Of the 1133 untargeted compounds, we identified 7 metabolites associated with PA levels in the pooled sample after covariate adjustment with a false discovery rate of 0.15. Specifically, compared to participants who did not exercise, those who exercised at a frequency ≥3 times/week showed higher abundances in uracil, orotate, 1-(1-enyl-palmitoyl)-2-oleoyl-GPE (P-16:0/18:1) (GPE), threonate, and glycerate, but lower abundances in salicyluric glucuronide and adenine in the pooled sample. However, in Whites, salicyluric glucuronide and orotate were not significant. Adenine, GPE, and threonate were not significant in AAs. In addition, the seven metabolites were not significantly different between participants who exercised ≥3 times/week and 1-2 times/week, nor significantly different between participants with 1-2 times/week and 0/week in the pooled sample and respective White and AA groups.

CONCLUSIONS

Metabolite responses to PA are dose sensitive and may differ between White and AA populations. The identified metabolites may help advance our knowledge of guiding precision PA interventions. Studies with rigorous study designs are warranted to elucidate the relationship between PA and metabolites.

Multi-omics reveals aging-related pathway in natural aging mouse liver

Aging is associated with gradual changes in liver structure, altered metabolites and other physiological/pathological functions in hepatic cells. However, its characterized phenotypes based on altered metabolites and the underlying biological mechanism are unclear. Advancements in high-throughput omics technology provide new opportunities to understand the pathological process of aging. Here, in our present study, both metabolomics and phosphoproteomics were applied to identify the altered metabolites and phosphorylated proteins in liver of young (the WTY group) and naturally aged (the WTA group) mice, to find novel biomarkers and pathways, and uncover the biological mechanism. Analysis showed that the body weights, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) increased in the WTA group. The grips decreased with age, while the triglyceride (TG) and cholesterol (TC) did not change significantly. The increase of fibrosis, accumulation of inflammatory cells, hepatocytes degeneration, the deposition of lipid droplets and glycogen, the damaged mitochondria, and deduction of endoplasmic reticulum were observed in the aging liver under optical and electron microscopes. In addition, a network of metabolites and phosphorylated proteomes of the aging liver was established. Metabolomics detected 970 metabolites in the positive ion mode and 778 metabolites in the negative ion mode. A total of 150 pathways were pooled. Phosphoproteomics identified 2618 proteins which contained 16621 phosphosites. A total of 164 pathways were detected. 65 common pathways were detected in two omics. Phosphorylated protein heat shock protein HSP 90-alpha (HSP90A) and v-raf murine viral oncogene homolog B1(BRAF), related to cancer pathway, were significantly upregulated in aged mice liver. Western blot verified that protein expression of MEK and ERK, downstream of BRAF pathway were elevated in the liver of aging mice. However, the protein expression of BRAF was not a significant difference. Overall, these findings revealed a close link between aging and cancer and contributed to our understanding of the multi-omics changes in natural aging.

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 lipoprotein subclass variation in middle-aged and older adults: Sex-stratified distributions and associations with health status and cardiometabolic risk factors

BACKGROUND

Circulating lipids and lipoproteins mediate cardiovascular risk, however routine plasma lipid biochemistry provides limited information on pro-atherogenic remnant particles.

OBJECTIVE

We analysed plasma lipoprotein subclasses including very low-density and intermediate-density lipoprotein (VLDL and IDL); and assessed their associations with health and cardiometabolic risk.

METHODS

From 1,976 community-dwelling adults aged 45-67 years, 114/1071 women (10.6%) and 153/905 men (16.9%) were categorised as very healthy. Fasting plasma lipoprotein profiles comprising 112 parameters were measured using 1H nuclear magnetic resonance (NMR) spectroscopy, and associations with health status and cardiometabolic risk factors examined.

RESULTS

HDL cholesterol was higher, and IDL and VLDL cholesterol and triglycerides lower, in very healthy women compared to other women, and women compared to men. IDL and VLDL cholesterol and triglyceride were lower in very healthy men compared to other men. HDL cholesterol and apolipoprotein (apo) A-I were inversely, and IDL and VLDL cholesterol, apoB-100, and apoB-100/apoA-I ratio directly associated with body mass index (BMI) in women and men. In women, LDL, IDL and VLDL cholesterol increased with age. Women with diabetes and cardiovascular disease had higher cholesterol, triglycerides, phospholipids and free cholesterol across IDL and VLDL fractions, with similar trends for men with diabetes.

CONCLUSION

Lipoprotein subclasses and density fractions, and their lipid and apolipoprotein constituents, are differentially distributed by sex, health status and BMI. Very healthy women and men are distinguished by favorable lipoprotein profiles, particularly lower concentrations of VLDL and IDL, providing reference intervals for comparison with general populations and adults with cardiometabolic risk factors.

The prevalence and predictors of geriatric giants in community-dwelling older adults: a cross-sectional study from the Middle East

The term "geriatric giants" refers to the chronic disabilities of senescence leading to adverse health outcomes. This study aimed to investigate the prevalence and predictors of geriatric giants in Southern Iran. The participants were selected from Bushehr city using a multistage cluster random sampling method. Demographic data were collected through interviews. Frailty, incontinence, immobility, depression, cognitive impairment, and malnutrition were measured by questionnaires and instruments. Finally, data from 2392 participants were analyzed. The prevalence of fecal incontinence was less than 1% among all participants and similar in men and women. In contrast, compared with men, women had higher prevalence of urinary incontinence (36.44% vs. 17.65%), depression (39.05% vs. 12.89%), anorexia and malnutrition (2.35% vs. 0.82%), immobility (8.00% vs. 2.5%), frailty (16.84 vs. 7.34), and pre-frailty (54.19 vs. 38.63%). The prevalence of dependence and cognitive impairment was also higher in women and considerably increased with the age of participants. In total, 12.07% of subjects were frail, and 46.76% were pre-frail. The prevalence of frailty exponentially increased in older age, ranging from 4.18% among those aged 60-64 years to 57.35% in those aged ≥ 80 years. Considering 95% confidence interval (CI), multivariate logistic regression revealed that low physical activity [odds ratio (OR) 31.73 (18.44-54.60)], cancer (OR 3.28 (1.27-8.44)), depression [OR 2.42 (1.97-2.98)], age [OR 1.11 (1.08-1.14)], waist circumference [OR 1.03 (1.01-1.06)], BMI [OR 1.07 (1.01-1.14)], MNA score [OR 0.85 (0.79-0.92)], polypharmacy [OR 2.26 (1.30-3.95)] and male gender [OR 0.63 (0.42-0.93)] were independently associated with frailty. White blood cell count (WBC), smoking, marital status, and number of comorbidities were not independently associated with frailty. Low physical activity was the strongest predictor of frailty, which may need more attention in geriatric care. Frailty, its predictors, and other components of geriatric giants were considerably more common among women and older ages.

Gut-specific telomerase expression counteracts systemic aging in telomerase-deficient zebrafish

Telomere shortening is a hallmark of aging and is counteracted by telomerase. As in humans, the zebrafish gut is one of the organs with the fastest rate of telomere decline, triggering early tissue dysfunction during normal zebrafish aging and in prematurely aged telomerase mutants. However, whether telomere-dependent aging of an individual organ, the gut, causes systemic aging is unknown. Here we show that tissue-specific telomerase expression in the gut can prevent telomere shortening and rescues premature aging of tert^-/-. Induction of telomerase rescues gut senescence and low cell proliferation, while restoring tissue integrity, inflammation and age-dependent microbiota dysbiosis. Averting gut aging causes systemic beneficial impacts, rescuing aging of distant organs such as reproductive and hematopoietic systems. Conclusively, we show that gut-specific telomerase expression extends the lifespan of tert^-/- by 40%, while ameliorating natural aging. Our work demonstrates that gut-specific rescue of telomerase expression leading to telomere elongation is sufficient to systemically counteract aging in zebrafish.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

Plasma metabolites with mechanistic and clinical links to the neurovascular disease cavernous angioma

BACKGROUND

Cavernous angiomas (CAs) affect 0.5% of the population, predisposing to serious neurologic sequelae from brain bleeding. A leaky gut epithelium associated with a permissive gut microbiome, was identified in patients who develop CAs, favoring lipid polysaccharide producing bacterial species. Micro-ribonucleic acids along with plasma levels of proteins reflecting angiogenesis and inflammation were also previously correlated with CA and CA with symptomatic hemorrhage.

METHODS

The plasma metabolome of CA patients and CA patients with symptomatic hemorrhage was assessed using liquid-chromatography mass spectrometry. Differential metabolites were identified using partial least squares-discriminant analysis (p < 0.05, FDR corrected). Interactions between these metabolites and the previously established CA transcriptome, microbiome, and differential proteins were queried for mechanistic relevance. Differential metabolites in CA patients with symptomatic hemorrhage were then validated in an independent, propensity matched cohort. A machine learning-implemented, Bayesian approach was used to integrate proteins, micro-RNAs and metabolites to develop a diagnostic model for CA patients with symptomatic hemorrhage.

RESULTS

Here we identify plasma metabolites, including cholic acid and hypoxanthine distinguishing CA patients, while arachidonic and linoleic acids distinguish those with symptomatic hemorrhage. Plasma metabolites are linked to the permissive microbiome genes, and to previously implicated disease mechanisms. The metabolites distinguishing CA with symptomatic hemorrhage are validated in an independent propensity-matched cohort, and their integration, along with levels of circulating miRNAs, enhance the performance of plasma protein biomarkers (up to 85% sensitivity and 80% specificity).

CONCLUSIONS

Plasma metabolites reflect CAs and their hemorrhagic activity. A model of their multiomic integration is applicable to other pathologies.

Aging Effects on Optic Nerve Neurodegeneration

Common risk factors for many ocular pathologies involve non-pathologic, age-related damage to the optic nerve. Understanding the mechanisms of age-related changes can facilitate targeted treatments for ocular pathologies that arise at any point in life. In this review, we examine these age-related, neurodegenerative changes in the optic nerve, contextualize these changes from the anatomic to the molecular level, and appreciate their relationship with ocular pathophysiology. From simple structural and mechanical changes at the optic nerve head (ONH), to epigenetic and biochemical alterations of tissue and the environment, multiple age-dependent mechanisms drive extracellular matrix (ECM) remodeling, retinal ganglion cell (RGC) loss, and lowered regenerative ability of respective axons. In conjunction, aging decreases the ability of myelin to preserve maximal conductivity, even with "successfully" regenerated axons. Glial cells, however, regeneratively overcompensate and result in a microenvironment that promotes RGC axonal death. Better elucidating optic nerve neurodegeneration remains of interest, specifically investigating human ECM, RGCs, axons, oligodendrocytes, and astrocytes; clarifying the exact processes of aged ocular connective tissue alterations and their ultrastructural impacts; and developing novel technologies and pharmacotherapies that target known genetic, biochemical, matrisome, and neuroinflammatory markers. Management models should account for age-related changes when addressing glaucoma, diabetic retinopathy, and other blinding diseases.

Extensive accumulation of misfolded protein aggregates during natural aging and senescence

Accumulation of misfolded protein aggregates is a hallmark event in many age-related protein misfolding disorders, including some of the most prevalent and insidious neurodegenerative diseases. Misfolded protein aggregates produce progressive cell damage, organ dysfunction, and clinical changes, which are common also in natural aging. Thus, we hypothesized that aging is associated to the widespread and progressive misfolding and aggregation of many proteins in various tissues. In this study, we analyzed whether proteins misfold, aggregate, and accumulate during normal aging in three different biological systems, namely senescent cells, Caenorhabditis elegans, and mouse tissues collected at different times from youth to old age. Our results show a significant accumulation of misfolded protein aggregates in aged samples as compared to young materials. Indeed, aged samples have between 1.3 and 2.5-fold (depending on the biological system) higher amount of insoluble proteins than young samples. These insoluble proteins exhibit the typical characteristics of disease-associated aggregates, including insolubility in detergents, protease resistance, and staining with amyloid-binding dye as well as accumulation in aggresomes. We identified the main proteins accumulating in the aging brain using proteomic studies. These results show that the aged brain contain large amounts of misfolded and likely non-functional species of many proteins, whose soluble versions participate in cellular pathways that play fundamental roles in preserving basic functions, such as protein quality control, synapsis, and metabolism. Our findings reveal a putative role for protein misfolding and aggregation in aging.

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.

Metabolite Changes during the Transition from Hyperthyroidism to Euthyroidism in Patients with Graves' Disease

BACKGRUOUND

An excess of thyroid hormones in Graves' disease (GD) has profound effects on systemic energy metabolism that are currently partially understood. In this study, we aimed to provide a comprehensive understanding of the metabolite changes that occur when patients with GD transition from hyperthyroidism to euthyroidism with methimazole treatment.

METHODS

Eighteen patients (mean age, 38.6±14.7 years; 66.7% female) with newly diagnosed or relapsed GD attending the endocrinology outpatient clinics in a single institution were recruited between January 2019 and July 2020. All subjects were treated with methimazole to achieve euthyroidism. We explored metabolomics by performing liquid chromatography-mass spectrometry analysis of plasma samples of these patients and then performed multivariate statistical analysis of the metabolomics data.

RESULTS

Two hundred metabolites were measured before and after 12 weeks of methimazole treatment in patients with GD. The levels of 61 metabolites, including palmitic acid (C16:0) and oleic acid (C18:1), were elevated in methimazole-naïve patients with GD, and these levels were decreased by methimazole treatment. The levels of another 15 metabolites, including glycine and creatinine, were increased after recovery of euthyroidism upon methimazole treatment in patients with GD. Pathway analysis of metabolomics data showed that hyperthyroidism was closely related to aminoacyl-transfer ribonucleic acid biosynthesis and branched-chain amino acid biosynthesis pathways.

CONCLUSION

In this study, significant variations of plasma metabolomic patterns that occur during the transition from hyperthyroidism to euthyroidism were detected in patients with GD via untargeted metabolomics analysis.

Metabolome profiling in the study of aging processes

Aging of a living organism is closely related to systemic metabolic changes. But due to the multilevel and network nature of metabolic pathways, it is difficult to understand these connections. Today, this problem is solved using one of the main approaches of metabolomics — untargeted metabolome profiling. The purpose of this publication is to systematize the results of metabolomic studies based on such profiling, both in animal models and in humans.

Long-Term Dietary Lycium ruthenicum Murr. Anthocyanins Intake Alleviated Oxidative Stress-Mediated Aging-Related Liver Injury and Abnormal Amino Acid Metabolism

In recent years, the relationship between Lycium ruthenicum Murr. anthocyanins (LRA) and health has attracted increasing attention. The purpose of this study is to investigate the anti-aging effect and mechanism of LRA through a D-galactose (DG)-induced aging rat model. Our results showed that the long-term intake of LRA, for 8 weeks, improved motor function, reduced serum aging markers, promoted the endogenous antioxidant system, and suppressed the serum inflammatory cytokines in aging rats. Besides, the LRA treatment alleviated DG-induced liver injuries by relieving the inflammation and inhibiting Fas/FasL-mediated cell death. More importantly, the abnormal serum metabolome profiles of the aging rats were restored by the LRA, relating to 38 metabolites and 44 pathways. Specifically, the LRA significantly affected the amino acid and protein-related metabolic pathways by regulating the levels of L-threonine, L-aspartic acid, glycine, L-histidine, D-homocysteine, L-homocitrulline, L-homoserine, guanidineacetic acid, and kynurenine. These results have important implications for the development of LRA as an anti-aging and liver-protective ingredient.

Metabolome Profiling in Aging Studies

Organism aging is closely related to systemic metabolic changes. However, due to the multilevel and network nature of metabolic pathways, it is difficult to understand these connections. Today, scientists are trying to solve this problem using one of the main approaches of metabolomics-untargeted metabolome profiling. The purpose of this publication is to review metabolomic studies based on such profiling, both in animal models and in humans. This review describes metabolites that vary significantly across age groups and include carbohydrates, amino acids, carnitines, biogenic amines, and lipids. Metabolic pathways associated with the aging process are also shown, including those associated with amino acid, lipid, and energy metabolism. The presented data reveal the mechanisms of aging and can be used as a basis for monitoring biological age and predicting age-related diseases in the early stages of their development.

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

As the global population becomes older, understanding the impact of aging on health and disease becomes paramount. Recent advancements in multiomic technology have allowed for the high-throughput molecular characterization of aging at the population level. Metabolomics studies that analyze the small molecules in the body can provide biological information across a diversity of aging processes. Here, we review the growing body of population-scale metabolomics research on aging in humans, identifying the major trends in the field, implicated biological pathways, and how these pathways relate to health and aging. We conclude by assessing the main challenges in the research to date, opportunities for advancing the field, and the outlook for precision health applications.

A machine learning-based data mining in medical examination data: a biological features-based biological age prediction model

Background

Biological age (BA) has been recognized as a more accurate indicator of aging than chronological age (CA). However, the current limitations include: insufficient attention to the incompleteness of medical data for constructing BA; Lack of machine learning-based BA (ML-BA) on the Chinese population; Neglect of the influence of model overfitting degree on the stability of the association results.

Methods and results

Based on the medical examination data of the Chinese population (45–90 years), we first evaluated the most suitable missing interpolation method, then constructed 14 ML-BAs based on biomarkers, and finally explored the associations between ML-BAs and health statuses (healthy risk indicators and disease). We found that round-robin linear regression interpolation performed best, while AutoEncoder showed the highest interpolation stability. We further illustrated the potential overfitting problem in ML-BAs, which affected the stability of ML-Bas’ associations with health statuses. We then proposed a composite ML-BA based on the Stacking method with a simple meta-model (STK-BA), which overcame the overfitting problem, and associated more strongly with CA (r = 0.66, P < 0.001), healthy risk indicators, disease counts, and six types of disease.

Conclusion

We provided an improved aging measurement method for middle-aged and elderly groups in China, which can more stably capture aging characteristics other than CA, supporting the emerging application potential of machine learning in aging research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04966-7.

Comparison of Hepatic Metabolite Profiles between Infant and Adult Male Mice Using 1H-NMR-Based Untargeted Metabolomics

Although age-related characteristics of hepatic metabolism are reported, those in infants are not fully understood. In the present study, we performed untargeted metabolomic profiling of the livers of infant (3-week-old) and adult (9-week-old) male ICR mice using ¹H-NMR spectroscopy and compared 35 abundant hepatic metabolite concentrations between the two groups. The liver/body weight ratio did not differ between the two groups; however, serum glucose, blood urea nitrogen, total cholesterol, and triglyceride concentrations were lower in infants than in adults. Hepatic carbohydrate metabolites (glucose, maltose, and mannose) were higher, whereas amino acids (glutamine, leucine, methionine, phenylalanine, tyrosine, and valine) were lower in infant mice than in adult mice. The concentrations of ascorbate, betaine, sarcosine, and ethanolamine were higher, whereas those of taurine, inosine, and O-phosphocholine were lower in infant mice than in adult mice. The differences in liver metabolites between the two groups could be due to differences in their developmental stages and dietary sources (breast milk for infants and laboratory chow for adults). The above results provide insights into the hepatic metabolism in infants; however, the exact implications of the findings require further investigation.

Inflammatory markers S100A8/A9 and metabolic alteration for evaluating signs of early phase toxicity of anticancer agent treatment

Anticancer agents can cause various side effects, including tissue damages/inflammatory reactions. Drug-responsive biomarkers are essential for evaluating drug toxicity in disease processes. S100 calcium-binding proteins A8/A9 (S100A8/A9) are highly expressed in neutrophils and monocytes/macrophages accumulated at inflammatory sites and are known to be related to tissue damage/inflammation; however, their response to drug toxicity has not been reported. Herein, we investigated the effects of anticancer agents (doxorubicin, cisplatin, and docetaxel) on S100A8/A9 gene expression profiles in four representative tissues (heart, kidney, liver, and lung) in normal C57BL/6J mice. Both S100A8/A9 expression was transiently or time-dependently elevated in four tissues within 48 h after dosing of the three anticancer agents under toxicity-inducing conditions. S100A8/A9 patterns differed among agents and tissues. This result suggests that S100A8/A9 is useful for evaluating anticancer agent-induced tissue damage. Metabolomic analysis revealed that some metabolites showed temporal patterns similar to that of S100A8/A9 expression. The amounts of fumarate (doxorubicin-treated heart), tyrosine (cisplatin-treated kidney), acetylcarnosine (doxorubicin-treated liver), and 2-phosphoglycerate (docetaxel-treated lung) showed similar patterns to that of S100A8/A9 expression. Although these metabolites showed different behaviors between tissues and serum, they may be useful marker candidates for evaluating anticancer agent-induced tissue damage at an earlier stage after dosing.

Metabolomic differences in lung function metrics: evidence from two cohorts

RATIONALE

The biochemical mechanisms underlying lung function are incompletely understood.

OBJECTIVES

To identify and validate the plasma metabolome of lung function using two independent adult cohorts: discovery-the European Prospective Investigation into Cancer-Norfolk (EPIC-Norfolk, n=10 460) and validation-the VA Normative Aging Study (NAS) metabolomic cohort (n=437).

METHODS

We ran linear regression models for 693 metabolites to identify associations with forced expiratory volume in one second (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC), in EPIC-Norfolk then validated significant findings in NAS. Significance in EPIC-Norfolk was denoted using an effective number of tests threshold of 95%; a metabolite was considered validated in NAS if the direction of effect was consistent and p<0.05.

MEASUREMENTS AND MAIN RESULTS

Of 156 metabolites that associated with FEV1 in EPIC-Norfolk after adjustment for age, sex, body mass index, height, smoking and asthma status, 34 (21.8%) validated in NAS, including several metabolites involved in oxidative stress. When restricting the discovery sample to men only, a similar percentage, 18 of 79 significant metabolites (22.8%) were validated. A smaller number of metabolites were validated for FEV1/FVC, 6 of 65 (9.2%) when including all EPIC-Norfolk as the discovery population, and 2 of 34 (5.9%) when restricting to men. These metabolites were characterised by involvement in respiratory track secretants. Interestingly, no metabolites were validated for both FEV1 and FEV1/FVC.

CONCLUSIONS

The validation of metabolites associated with respiratory function can help to better understand mechanisms of lung health and may assist the development of biomarkers.

Long-Term Mastication Changed Salivary Metabolomic Profiles

Saliva is an ideal biofluid for monitoring oral and systemic health. Repeated mastication is a typical physical stimulus that improves salivary flow and oral hygiene. Recent metabolomic studies have shown the potential of salivary metabolomic components for various disease monitoring systems. Here, we evaluated the effect of long-term mastication on salivary metabolomic profiles. Young women with good oral hygiene (20.8 ± 0.3 years, n = 17) participated. They were prohibited from chewing gum during control periods (4 weeks each) and were instructed to chew a piece of gum base seven times a day for 10 min each time during the intervention period. Paired samples of unstimulated whole saliva collected on the last day of the control and intervention period were compared. Liquid chromatography−time-of-flight mass spectrometry successfully quantified 85 metabolites, of which 41 showed significant differences (p < 0.05, Wilcoxon paired test corrected by false discovery rate). Except for a few metabolites, such as citrate, most metabolites showed lower concentrations after the intervention. The pathways related to glycogenic amino acids, such as alanine, arginine, and glutamine, altered considerably. This study suggests that long-term mastication induces unstimulated salivary component-level changes.

Batch alignment via retention orders for preprocessing large-scale multi-batch LC-MS experiments

MOTIVATION

Meticulous selection of chromatographic peak detection parameters and algorithms is a crucial step in preprocessing LC-MS data. However, as mass-to-charge ratio (m/z) and retention time shifts are larger between batches than within batches, finding apt parameters for all samples of a large-scale multi-batch experiment with the aim of minimizing information loss becomes a challenging task. Preprocessing independent batches individually can curtail said problems but requires a method for aligning and combining them for further downstream analysis.

RESULTS

We present two methods for aligning and combining individually preprocessed batches in multi-batch LC-MS experiments. Our developed methods were tested on six sets of simulated and six sets of real datasets. Furthermore, by estimating the probabilities of peak insertion, deletion, and swap between batches in authentic datasets we demonstrate that retention order swaps are not rare in untargeted LC-MS data.

AVAILABILITY

kmersAlignment and rtcorrectedAlignment algorithms are made available as an R package with raw data at https://metabocombiner.img.cas.cz.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Potential of Metabolomics in Biomedical Applications

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.

Differential Analysis of Mycelial Proteins and Metabolites From Rigidoporus Microporus During In Vitro Interaction With Hevea Brasiliensis

Rigidoporus microporus is the fungus accountable for the white root rot disease that is detrimental to the rubber tree, Hevea brasiliensis. The pathogenicity mechanism of R. microporus and the identity of the fungal proteins and metabolites involved during the infection process remain unclear. In this study, the protein and metabolite profiles of two R. microporus isolates, Segamat (SEG) and Ayer Molek (AM), were investigated during an in vitro interaction with H. brasiliensis. The isolates were used to inoculate H. brasiliensis clone RRIM 2025, and mycelia adhering to the roots of the plant were collected for analysis. Transmission electron microscope (TEM) images acquired confirms the hyphae attachment and colonization of the mycelia on the root of the H. brasiliensis clones after 4 days of inoculation. The protein samples were subjected to 2-DE analysis and analyzed using MALDI-ToF MS/MS, while the metabolites were extracted using methanol and analyzed using LC/MS-QTOF. Based on the differential analyses, upregulation of proteins that are essential for fungal evolution such as malate dehydrogenase, fructose 1,6-biphosphate aldolase, and glyceraldehyde-3-phosphate dehydrogenase hints an indirect role in fungal pathogenicity, while metabolomic analysis suggests an increase in acidic compounds which may lead to increased cell wall degrading enzyme activity. Bioinformatics analyses revealed that the carbohydrate and amino acid metabolisms were prominently affected in response to the fungal pathogenicity. In addition to that, other pathways that were significantly affected include "Protein Ubiquitination Pathway," Unfolded Protein Response," "HIFα Signaling," and "Sirtuin Signaling Pathway." The identification of responsive proteins and metabolites from this study promotes a better understanding of mechanisms underlying R. microporus pathogenesis and provides a list of potential biological markers for early recognition of the white root rot disease.

A comprehensive analysis of age-related metabolomics and transcriptomics reveals metabolic alterations in rat bone marrow mesenchymal stem cells

The functions of stem cells decline progressively with aging, and some metabolic changes occur during the process. However, the molecular mechanisms of stem cell aging remain unclear. In this study, the combined application of metabolomics and transcriptomics technologies can effectively describe the possible molecular mechanisms of rat bone marrow mesenchymal stem cell (BMSC) senescence. Metabolomic profiles revealed 23 differential metabolites which were abundant in “glycerophospholipid metabolism”, “linoleic acid metabolism” and “biosynthesis of unsaturated fatty acids”. In addition, transcriptomics analysis identified 590 genes with enormously differential expressions in young and old BMSCs. KEGG enrichment analyses showed that metabolism-related pathways in BMSC senescence had stronger responses. Furthermore, the integrated analysis of the interactions between the differentially expressed genes (DEGs) and metabolites indicated the differential genes related to lipid metabolism of Scd, Scd2, Dgat2, Fads2, Lpin1, Gpat3, Acaa2, Lpcat3, Pcyt2 and Pla2g4a may be closely associated with the aging of BMSCs. Finally, Scd2 was identified as the most significant DEG, and Scd2 over-expression could alleviate cellular senescence in aged BMSCs. In conclusion, this work provides a validated understanding that the DEGs and metabolites related to lipid metabolism present more apparent changes in the senescence of rat BMSCs.

Metabolomics Signatures and Subsequent Maternal Health among Mothers with a Congenital Heart Defect-Affected Pregnancy

Congenital heart defects (CHDs) are the most prevalent and serious of all birth defects in the United States. However, little is known about the impact of CHD-affected pregnancies on subsequent maternal health. Thus, there is a need to characterize the metabolic alterations associated with CHD-affected pregnancies. Fifty-six plasma samples were identified from post-partum women who participated in the National Birth Defects Prevention Study between 1997 and 2011 and had (1) unaffected control offspring (n = 18), (2) offspring with tetralogy of Fallot (ToF, n = 22), or (3) hypoplastic left heart syndrome (HLHS, n = 16) in this pilot study. Absolute concentrations of 408 metabolites using the AbsoluteIDQ^® p400 HR Kit (Biocrates) were evaluated among case and control mothers. Twenty-six samples were randomly selected from above as technical repeats. Analysis of covariance (ANCOVA) and logistic regression models were used to identify significant metabolites after controlling for the maternal age at delivery and body mass index. The receiver operating characteristic (ROC) curve and area-under-the-curve (AUC) are reported to evaluate the performance of significant metabolites. Overall, there were nine significant metabolites (p < 0.05) identified in HLHS case mothers and 30 significant metabolites in ToF case mothers. Statistically significant metabolites were further evaluated using ROC curve analyses with PC (34:1), two sphingolipids SM (31:1), SM (42:2), and PC-O (40:4) elevated in HLHS cases; while LPC (18:2), two triglycerides: TG (44:1), TG (46:2), and LPC (20:3) decreased in ToF; and cholesterol esters CE (22:6) were elevated among ToF case mothers. The metabolites identified in the study may have profound structural and functional implications involved in cellular signaling and suggest the need for postpartum dietary supplementation among women who gave birth to CHD offspring.

Combining Metabolomics and Experimental Evolution Reveals Key Mechanisms Underlying Longevity Differences in Laboratory Evolved Drosophila melanogaster Populations

Experimental evolution with Drosophila melanogaster has been used extensively for decades to study aging and longevity. In recent years, the addition of DNA and RNA sequencing to this framework has allowed researchers to leverage the statistical power inherent to experimental evolution to study the genetic basis of longevity itself. Here, we incorporated metabolomic data into to this framework to generate even deeper insights into the physiological and genetic mechanisms underlying longevity differences in three groups of experimentally evolved D. melanogaster populations with different aging and longevity patterns. Our metabolomic analysis found that aging alters mitochondrial metabolism through increased consumption of NAD+ and increased usage of the TCA cycle. Combining our genomic and metabolomic data produced a list of biologically relevant candidate genes. Among these candidates, we found significant enrichment for genes and pathways associated with neurological development and function, and carbohydrate metabolism. While we do not explicitly find enrichment for aging canonical genes, neurological dysregulation and carbohydrate metabolism are both known to be associated with accelerated aging and reduced longevity. Taken together, our results provide plausible genetic mechanisms for what might be driving longevity differences in this experimental system. More broadly, our findings demonstrate the value of combining multiple types of omic data with experimental evolution when attempting to dissect mechanisms underlying complex and highly polygenic traits such as aging.

Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets

Aging is closely related to the occurrence of human diseases; however, its exact biological mechanism is unclear. Advancements in high-throughput technology provide new opportunities for omics research to understand the pathological process of various complex human diseases. However, single-omics technologies only provide limited insights into the biological mechanisms of diseases. DNA, RNA, protein, metabolites, and microorganisms usually play complementary roles and perform certain biological functions together. In this review, we summarize multi-omics methods based on the most relevant biomarkers in single-omics to better understand molecular functions and disease causes. The integration of multi-omics technologies can systematically reveal the interactions among aging molecules from a multidimensional perspective. Our review provides new insights regarding the discovery of aging biomarkers, mechanism of aging, and identification of novel antiaging targets. Overall, data from genomics, transcriptomics, proteomics, metabolomics, integromics, microbiomics, and systems biology contribute to the identification of new candidate biomarkers for aging and novel targets for antiaging interventions.

Metabolomic Profiles of Mouse Tissues Reveal an Interplay between Aging and Energy Metabolism

Energy metabolism, including alterations in energy intake and expenditure, is closely related to aging and longevity. Metabolomics studies have recently unraveled changes in metabolite composition in plasma and tissues during aging and have provided critical information to elucidate the molecular basis of the aging process. However, the metabolic changes in tissues responsible for food intake and lipid storage have remained unexplored. In this study, we aimed to investigate aging-related metabolic alterations in these tissues. To fill this gap, we employed NMR-based metabolomics in several tissues, including different parts of the intestine (duodenum, jejunum, ileum) and brown/white adipose tissues (BAT, WAT), of young (9-10 weeks) and old (96-104 weeks) wild-type (mixed genetic background of 129/J and C57BL/6) mice. We, further, included plasma and skeletal muscle of the same mice to verify previous results. Strikingly, we found that duodenum, jejunum, ileum, and WAT do not metabolically age. In contrast, plasma, skeletal muscle, and BAT show a strong metabolic aging phenotype. Overall, we provide first insights into the metabolic changes of tissues essential for nutrient uptake and lipid storage and have identified biomarkers for metabolites that could be further explored, to study the molecular mechanisms of aging.

Microbiome and Human Aging: Probiotic and Prebiotic Potentials in Longevity, Skin Health and Cellular Senescence

The role of the microbiome in human aging is important: the microbiome directly impacts aging through the gastrointestinal system. However, the microbial impact on skin has yet to be fully understood. For example, cellular senescence is an intrinsic aging process that has been recently associated with microbial imbalance. With age, cells become senescent in response to stress wherein they undergo irreversible growth arrest while maintaining high metabolic activity. An accumulation of senescent cells has been linked to various aging and chronic pathologies due to an overexpression of the senescence-associated secretory phenotype (SASP) comprised of proinflammatory cytokines, chemokines, growth factors, proteases, lipids and extracellular matrix components. In particular, dermatological disorders may be promoted by senescence as the skin is a common site of accumulation. The gut microbiota influences cellular senescence and skin disruption through the gut-skin axis and secretion of microbial metabolites. Metabolomics can be used to identify and quantify metabolites involved in senescence. Moreover, novel anti-senescent therapeutics are warranted given the poor safety profiles of current pharmaceutical drugs. Probiotics and prebiotics may be effective alternatives, considering the relationship between the microbiome and healthy aging. However, further research on gut composition under a senescent status is needed to develop immunomodulatory therapies.

Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort

BACKGROUND

Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2).

METHODS

To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786).

RESULTS

For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed.

CONCLUSIONS

These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.

Hippuric acid: Could became a barometer for frailty and geriatric syndromes?

Aging is a natural biological event that has some downsides such as increased frailty, decline in cognitive and physical functions leading to chronical diseases, and lower quality of life. There is therefore a pressing need of reliable biomarkers to identify populations at risk of developing age-associated syndromes in order to improve their quality of life, promote healthy ageing and a more appropriate clinical management, when needed. Here we discuss the importance of hippuric acid, an endogenous co-metabolite, as a possible hallmark of human aging and age-related diseases, summarizing the scientific literature over the last years. Hippuric acid, the glycine conjugate of benzoic acid, derives from the catabolism by means of intestinal microflora of dietary polyphenols found in plant-based foods (e.g. fruits, vegetables, tea and coffee). In healthy conditions hippuric acid levels in blood and/or urine rise significantly during aging while its excretion drops in conditions related with aging, including cognitive impairments, rheumatic diseases, sarcopenia and hypomobility. This literature highlights the utility of hippuric acid in urine and plasma as a plausible hallmark of frailty, related to low fruit and vegetable intake and changes in gut microflora.

Metabolomic profiling of plasma from middle-aged and advanced-age male mice reveals the metabolic abnormalities of carnitine biosynthesis in metallothionein gene knockout mice

Metallothionein (MT) is a family of low molecular weight, cysteine-rich proteins that regulate zinc homeostasis and have potential protective effects against oxidative stress and toxic metals. MT1 and MT2 gene knockout (MTKO) mice show shorter lifespans than wild-type (WT) mice. In this study, we aimed to investigate how MT gene deficiency accelerates aging. We performed comparative metabolomic analyses of plasma between MTKO and WT male mice at middle age (50-week-old) and advanced age (100-week-old) using liquid chromatography with time-of-flight mass spectrometry (LC-TOF-MS). The concentration of N6,N6,N6-trimethyl-L-lysine (TML), which is a metabolic intermediate in carnitine biosynthesis, was consistently higher in the plasma of MTKO mice compared to that of WT mice at middle and advanced age. Quantitative reverse transcription PCR (RT-PCR) analysis revealed remarkably lower mRNA levels of Tmlhe, which encodes TML dioxygenase, in the liver and kidney of male MTKO mice compared to that of WT mice. L-carnitine is essential for β-oxidation of long-chain fatty acids in mitochondria, the activity of which is closely related to aging. Our results suggest that reduced carnitine biosynthesis capacity in MTKO mice compared to WT mice led to metabolic disorders of fatty acids in mitochondria in MTKO mice, which may have caused shortened lifespans.

The Impacts of Short-Term NMN Supplementation on Serum Metabolism, Fecal Microbiota, and Telomere Length in Pre-Aging Phase

Aging is a natural process with concomitant changes in the gut microbiota and associate metabolomes. Beta-nicotinamide mononucleotide, an important NAD+ intermediate, has drawn increasing attention to retard the aging process. We probed the changes in the fecal microbiota and metabolomes of pre-aging male mice (C57BL/6, age: 16 months) following the oral short-term administration of nicotinamide mononucleotide (NMN). Considering the telomere length as a molecular gauge for aging, we measured this in the peripheral blood mononuclear cells (PBMC) of pre-aging mice and human volunteers (age: 45-60 years old). Notably, the NMN administration did not influence the body weight and feed intake significantly during the 40 days in pre-aging mice. Metabolomics suggested 266 upregulated and 58 downregulated serum metabolites. We identified 34 potential biomarkers linked with the nicotinamide, purine, and proline metabolism pathways. Nicotinamide mononucleotide significantly reduced the fecal bacterial diversity (p < 0.05) with the increased abundance of Helicobacter, Mucispirillum, and Faecalibacterium, and lowered Akkermansia abundance associated with nicotinamide metabolism. We propose that this reshaped microbiota considerably lowered the predicated functions of aging with improved immune and cofactors/vitamin metabolism. Most notably, the telomere length of PBMC was significantly elongated in the NMN-administered mice and humans. Taken together, these findings suggest that oral NMN supplementation in the pre-aging stage might be an effective strategy to retard aging. We recommend further studies to unravel the underlying molecular mechanisms and comprehensive clinical trials to validate the effects of NMN on aging.

Comparative Metabolomic Study of Drosophila Species with Different Lifespans

The increase in life expectancy, leading to a rise in the proportion of older people, is accompanied by a prevalence of age-related disorders among the world population, the fight against which today is one of the leading biomedical challenges. Exploring the biological insights concerning the lifespan is one of the ways to provide a background for designing an effective treatment for the increase in healthy years of life. Untargeted direct injection mass spectrometry-based metabolite profiling of 12 species of Drosophila with significant variations in natural lifespans was conducted in this research. A cross-comparison study of metabolomic profiles revealed lifespan signatures of flies. These signatures indicate that lifespan extension is associated with the upregulation of amino acids, phospholipids, and carbohydrate metabolism. Such information provides a metabolome-level view on longevity and may provide a molecular measure of organism age in age-related studies.

1H NMR metabolomic profiling of human cerebrospinal fluid in aging process

The molecular process of biological aging might be accompanied by significant metabolic derangement, especially in the central nervous system (CNS), since the brain has an enormous energy demand. However, the metabolic signature of the aging process in cerebrospinal fluid (CSF) has not been thoroughly investigated, especially in the Asian population. In this prospective cohort study on CSF metabolomics using proton nuclear magnetic resonance (NMR) spectroscopy, fasting CSF samples from 75 cognitively unimpaired patients aged 20-92 years without diabetes or obesity, undergoing spinal anesthesia for elective surgery were analyzed. Several metabolites in CSF samples were identified as having a significant association with the aging process in cerebral circulation; among the metabolites, the levels of alanine, citrate, creatinine, lactate, leucine, tyrosine, and valine significantly increased in old patients compared to those in young patients. The combined CSF metabolite alterations in citrate, lactate, leucine, tyrosine, and valine had a superior correlation with the aging process in all age groups. In conclusion, our pilot study of aging CSF metabolomics in the Taiwanese population presents significantly altered CSF metabolites with potential relevance to the aging process. These metabolic alterations in CSF samples might imply increasing anaerobic glycolysis, mitochondrial dysfunction, and decreasing glucose utilization in cerebral circulation in aged patients.

Human age-declined saliva metabolic markers determined by LC-MS

Metabolites in human biofluids reflect individual physiological states influenced by various factors. Using liquid chromatography-mass spectrometry (LC–MS), we conducted non-targeted, non-invasive metabolomics using saliva of 27 healthy volunteers in Okinawa, comprising 13 young (30 ± 3 year) and 14 elderly (76 ± 4 year) subjects. Few studies have comprehensively identified age-dependent changes in salivary metabolites. Among 99 salivary metabolites, 21 were statistically age-related. All of the latter decline in abundance with advancing age, except ATP, which increased 1.96-fold in the elderly, possibly due to reduced ATP consumption. Fourteen age-linked and highly correlated compounds function in a metabolic network involving the pentose-phosphate pathway, glycolysis/gluconeogenesis, amino acids, and purines/pyrimidines nucleobases. The remaining seven less strongly correlated metabolites, include ATP, anti-oxidation-related glutathione disulfide, muscle-related acetyl-carnosine, N-methyl-histidine, creatinine, RNA-related dimethyl-xanthine and N-methyl-adenosine. In addition, glutamate and N-methyl-histidine are related to taste, so their decline suggests that the elderly lose some ability to taste. Reduced redox metabolism and muscle activity are suggested by changes in glutathione and acetyl-carnosine. These age-linked salivary metabolites together illuminate a metabolic network that reflects a decline of oral functions during human aging.