Longitudinal plasma metabolomics of aging and sex

Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.

Investigating the Link between Intermediate Metabolism, Sexual Dimorphism, and Cardiac Autonomic Dysfunction in Patients with Type 1 Diabetes

Sexual dimorphism influences cardiovascular outcomes in type 1 diabetes (T1D), with women facing a higher relative risk of macrovascular events compared to men, especially after menopause. This study hypothesizes that abnormalities in intermediate metabolism may be associated with cardiac autonomic neuropathy (CAN) in T1D. We aim to assess low molecular weight metabolites (LMWM) as markers of CAN in T1D, considering the effects of sexual dimorphism and age. In this cross-sectional study, we included 323 subjects with T1D (147 women and 176 men), with a mean age of 41 ± 13 years. A total of 44 women and 41 men were over 50 years old. CAN was assessed using Ewing's tests, and serum metabolites were analyzed by proton nuclear magnetic resonance spectroscopy (1H-NMR). Patients with CAN had lower levels of valine, isoleucine, and threonine, and higher levels of lactate, compared to those without CAN. These differences persisted after adjusting for BMI and estimated glucose disposal rate (eGDR). In a logistic regression model (R² = 0.178, p < 0.001), the main determinants of CAN included isoleucine [Exp(β) = 0.972 (95% CI 0.952; 0.003)], age [Exp(β) = 1.031 (95% CI 1.010; 1.053)], A1c [Exp(β) = 1.361 (95% CI 1.058; 1.752)], and microangiopathy [Exp(β) = 2.560 (95% CI 1.372; 4.778)]. Sex influenced LMWM profiles, with over half of the metabolites differing between men and women. However, no interactions were found between CAN and sex, or between sex, age, and CAN, on metabolomics profiles. Our findings suggest an association between CAN and LMWM levels in T1D. The sexual dimorphism observed in amino acid metabolites was unaffected by the presence of CAN.

Urinary Epinephrine Sulfate Can Predict Cardiovascular Risk in Moderate-to-Severe OSA: A Metabolomics-Based Study

Purpose

There are currently no ideal indicators for predicting the cardiovascular risk of obstructive sleep apnea (OSA). This study aimed to employ urinary metabolomics to detect early cardiovascular risk in patients with moderate-to-severe OSA.

Patients and Methods

Male participants who underwent polysomnography from November 2020 to May 2021 were screened. Clinical data, polysomnography data and urine samples were collected. Untargeted metabolomics analyses of urine were performed. Multivariate analyses and receiver operating characteristic (ROC) curve analyses were subsequently performed to identify potential biomarkers. Associations between metabolites and clinical indicators and cardiovascular risk were examined through linear regression analyses with interaction and mediation analyses.

Results

Thirty-six male participants were included in the study, comprising 22 males with moderate-to-severe OSA and 14 age-matched controls, with an average age of 39.6 ± 9.2 years. We identified 65 metabolites in the study, involving pathways including pyrimidine, androgen, estrogen, vitamin B6 and sulfate/sulfite metabolism. Among them, epinephrine sulfate was the most significantly altered metabolite. ROC analyses highlighted that epinephrine sulfate had the highest area under the curve (AUC=0.883) for detecting moderate-to-severe OSA. Epinephrine sulfate was statistically correlated with OSA severity, hypoxia-related indicators (apnea-hypopnea index: r=0.685; oxygen desaturation index: r=0.743, p<0.0001), arterial stiffness (arterial augmentation index: r=0.361, p=0.031) and long-term cardiovascular risk (Framingham cardiovascular risk: r=0.375, p=0.024). Linear regression analysis revealed that epinephrine sulfate was significantly associated with an increased in the Framingham risk (β = 0.004, 95% CI = 0.000-0.009, p = 0.049), with the effect partly mediated by systolic blood pressure (27.6%) and not moderated by other factors. Additionally, it also significantly associated with the increased in the arterial augmentation index (β = 0.019, 95% CI = 0.000-0.037, p = 0.046), with the effect fully mediated by blood pressure and not moderated by other indices statistically.

Conclusion

There are significant metabolic pathway alterations in moderate-to-severe OSA patients. Urinary epinephrine sulfate markedly predicts early cardiovascular risk in OSA patients.

Identifying critical age and gender-based metabolomic shifts in a Japanese population of the Tohoku Medical Megabank cohort

Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55-59 to 60-64 years being a period of significant metabolic change, particularly in men, and from 45-49 to 50-54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.

Longitudinal Plasma Metabolome Patterns and Relation to Kidney Function and Proteinuria in Pediatric CKD

Key Points

Longitudinal untargeted metabolomics. Children with CKD have a circulating metabolome that changes over time.

Background

Understanding plasma metabolome patterns in relation to changing kidney function in pediatric CKD is important for continued research for identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There are a limited number of studies of longitudinal metabolomics and virtually none in pediatric CKD.

Methods

The CKD in Children study is a multi-institutional, prospective cohort that enrolled children aged 6 months to 16 years with eGFR 30–90 ml/min per 1.73 m2. Untargeted metabolomics profiling was performed on plasma samples from the baseline, 2-, and 4-year study visits. There were technologic updates in the metabolomic profiling platform used between the baseline and follow-up assays. Statistical approaches were adopted to avoid direct comparison of baseline and follow-up measurements. To identify metabolite associations with eGFR or urine protein-creatinine ratio (UPCR) among all three time points, we applied linear mixed-effects (LME) models. To identify metabolites associated with time, we applied LME models to the 2- and 4-year follow-up data. We applied linear regression analysis to examine associations between change in metabolite level over time (∆level) and change in eGFR (∆eGFR) and UPCR (∆UPCR). We reported significance on the basis of both the false discovery rate (FDR) <0.05 and P < 0.05.

Results

There were 1156 person-visits (N : baseline=626, 2-year=254, 4-year=276) included. There were 622 metabolites with standardized measurements at all three time points. In LME modeling, 406 and 343 metabolites associated with eGFR and UPCR at FDR <0.05, respectively. Among 530 follow-up person-visits, 158 metabolites showed differences over time at FDR <0.05. For participants with complete data at both follow-up visits (n =123), we report 35 metabolites with ∆level–∆eGFR associations significant at FDR <0.05. There were no metabolites with significant ∆level–∆UPCR associations at FDR <0.05. We report 16 metabolites with ∆level–∆UPCR associations at P < 0.05 and associations with UPCR in LME modeling at FDR <0.05.

Conclusions

We characterized longitudinal plasma metabolomic patterns associated with eGFR and UPCR in a large pediatric CKD population. Many of these metabolite signals have been associated with CKD progression, etiology, and proteinuria in previous CKD Biomarkers Consortium studies. There were also novel metabolite associations with eGFR and proteinuria detected.

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.

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.

Dietary protein and amino acid intakes for mitigating sarcopenia in humans

Adult humans generally experience a 0.5-1%/year loss in whole-body skeletal muscle mass and a reduction of muscle strength by 1.5-5%/year beginning at the age of 50 years. This results in sarcopenia (aging-related progressive losses of skeletal muscle mass and strength) that affects 10-16% of adults aged ≥ 60 years worldwide. Concentrations of some amino acids (AAs) such as branched-chain AAs, arginine, glutamine, glycine, and serine are reduced in the plasma of older than young adults likely due to insufficient protein intake, reduced protein digestibility, and increased AA catabolism by the portal-drained viscera. Acute, short-term, or long-term administration of some of these AAs or a mixture of proteinogenic AAs can enhance blood flow to skeletal muscle, activate the mechanistic target of rapamycin cell signaling pathway for the initiation of muscle protein synthesis, and modulate the metabolic activity of the muscle. In addition, some AA metabolites such as taurine, β-alanine, carnosine, and creatine have similar physiological effects on improving muscle mass and function in older adults. Long-term adequate intakes of protein and the AA metabolites can aid in mitigating sarcopenia in elderly adults. Appropriate combinations of animal- and plant-sourced foods are most desirable to maintain proper dietary AA balance.

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.

Metabolomic response to acute resistance exercise in healthy older adults by 1H-NMR

BACKGROUND

The favorable health-promoting adaptations to exercise result from cumulative responses to individual bouts of physical activity. Older adults often exhibit anabolic resistance; a phenomenon whereby the anabolic responses to exercise and nutrition are attenuated in skeletal muscle. The mechanisms contributing to age-related anabolic resistance are emerging, but our understanding of how chronological age influences responsiveness to exercise is incomplete. The objective was to determine the effects of healthy aging on peripheral blood metabolomic response to a single bout of resistance exercise and whether any metabolites in circulation are predictive of anabolic response in skeletal muscle.

METHODS

Thirty young (20-35 years) and 49 older (65-85 years) men and women were studied in a cross-sectional manner. Participants completed a single bout of resistance exercise consisting of eight sets of 10 repetitions of unilateral knee extension at 70% of one-repetition maximum. Blood samples were collected before exercise, immediately post exercise, and 30-, 90-, and 180-minutes into recovery. Proton nuclear magnetic resonance spectroscopy was used to profile circulating metabolites at all timepoints. Serial muscle biopsies were collected for measuring muscle protein synthesis rates.

RESULTS

Our analysis revealed that one bout of resistance exercise elicits significant changes in 26 of 33 measured plasma metabolites, reflecting alterations in several biological processes. Furthermore, 12 metabolites demonstrated significant interactions between exercise and age, including organic acids, amino acids, ketones, and keto-acids, which exhibited distinct responses to exercise in young and older adults. Pre-exercise histidine and sarcosine were negatively associated with muscle protein synthesis, as was the pre/post-exercise fold change in plasma histidine.

CONCLUSIONS

This study demonstrates that while many exercise-responsive metabolites change similarly in young and older adults, several demonstrate age-dependent changes even in the absence of evidence of sarcopenia or frailty.

TRIAL REGISTRATION

Clinical trial registry: ClinicalTrials.gov NCT03350906.

Plasma and serum metabolic analysis of healthy adults shows characteristic profiles by subjects' sex and age

INTRODUCTION

Pre-analytical factors like sex, age, and blood processing methods introduce variability and bias, compromising data integrity, and thus deserve close attention.

OBJECTIVES

This study aimed to explore the influence of participant characteristics (age and sex) and blood processing methods on the metabolic profile.

METHOD

A Thermo UPLC-TSQ-Quantiva-QQQ Mass Spectrometer was used to analyze 175 metabolites across 9 classes in 208 paired serum and lithium heparin plasma samples from 51 females and 53 males.

RESULTS

Comparing paired serum and plasma samples from the same cohort, out of the 13 metabolites that showed significant changes, 4 compounds related to amino acids and derivatives had lower levels in plasma, and 5 other compounds had higher levels in plasma. Sex-based analysis revealed 12 significantly different metabolites, among which most amino acids and derivatives and nitrogen-containing compounds were higher in males, and other compounds were elevated in females. Interestingly, the volcano plot also confirms the similar patterns of amino acids and derivatives higher in males. The age-based analysis suggested that metabolites may undergo substantial alterations during the 25-35-year age range, indicating a potential metabolic turning point associated with the age group. Moreover, a more distinct difference between the 25-35 and above 35 age groups compared to the below 25 and 25-35 age groups was observed, with the most significant compound decreased in the above 35 age groups.

CONCLUSION

These findings may contribute to the development of comprehensive metabolomics analyses with confounding factor-based adjustment and enhance the reliability and interpretability of future large-scale investigations.

Relation of the kynurenine pathway with normal age: A systematic review

BACKGROUND

The kynurenine pathway (KP) is gaining more attention as a common pathway involved in age-related conditions. However, which changes in the KP occur due to normal ageing is still largely unclear. The aim of this systematic review was to summarize the available evidence for associations of KP metabolites with age.

METHODS

We used an broad search strategy and included studies up to October 2023.

RESULTS

Out of 8795 hits, 55 studies were eligible for the systematic review. These studies suggest that blood levels of tryptophan decrease with age, while blood and cerebrospinal fluid levels of kynurenine and its ratio with tryptophan increase. Studies investigating associations between cerebrospinal fluid and blood levels of kynurenic acid and quinolinic acid with age reported either positive or non-significant findings. However, there is a large heterogeneity across studies. Additionally, most studies were cross-sectional, and only few studies investigated associations with other downstream kynurenines.

CONCLUSIONS

This systematic review suggests that levels of kynurenines are positively associated with age. Larger and prospective studies are needed that also investigate a more comprehensive panel of KP metabolites and changes during the life-course.

Past or Present; Which Exposures Predict Metabolomic Aging Better? The Doetinchem Cohort Study

People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36-75 of Round 4 (2003-2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987-1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R2 6.8 and 5.8, respectively) and women (R2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men and women.

Reliability of Time-Series Plasma Metabolome Data over 6 Years in a Large-Scale Cohort Study

Studies examining long-term longitudinal metabolomic data and their reliability in large-scale populations are limited. Therefore, we aimed to evaluate the reliability of repeated measurements of plasma metabolites in a prospective cohort setting and to explore intra-individual concentration changes at three time points over a 6-year period. The study participants included 2999 individuals (1317 men and 1682 women) from the Tsuruoka Metabolomics Cohort Study, who participated in all three surveys-at baseline, 3 years, and 6 years. In each survey, 94 plasma metabolites were quantified for each individual and quality control (QC) sample. The coefficients of variation of QC, intraclass correlation coefficients, and change rates of QC were calculated for each metabolite, and their reliability was classified into three categories: excellent, fair to good, and poor. Seventy-six percent (71/94) of metabolites were classified as fair to good or better. Of the 39 metabolites grouped as excellent, 29 (74%) in men and 26 (67%) in women showed significant intra-individual changes over 6 years. Overall, our study demonstrated a high degree of reliability for repeated metabolome measurements. Many highly reliable metabolites showed significant changes over the 6-year period, suggesting that repeated longitudinal metabolome measurements are useful for epidemiological studies.

Wide-scope targeted analysis of bioactive lipids in human plasma by LC/MS/MS

Quantitative information on blood metabolites can be used in developing advanced medical strategies such as early detection and prevention of disease. Monitoring bioactive lipids such as steroids, bile acids, and PUFA metabolites could be a valuable indicator of health status. However, a method for simultaneously measuring these bioactive lipids has not yet been developed. Here, we report a LC/MS/MS method that can simultaneously measure 144 bioactive lipids, including steroids, bile acids, and PUFA metabolites, from human plasma, and a sample preparation method for these targets. Protein removal by methanol precipitation and purification of bioactive lipids by solid-phase extraction improved the recovery of the targeted compounds in human plasma samples, demonstrating the importance of sample preparation methods for a wide range of bioactive lipid analyses. Using the developed method, we studied the plasma from healthy human volunteers and confirmed the presence of bioactive lipid molecules associated with sex differences and circadian rhythms. The developed method of bioactive lipid analysis can be applied to health monitoring and disease biomarker discovery in precision medicine.

Aging and age-related diseases with a focus on therapeutic potentials of young blood/plasma

Aging is accompanied by alterations in the body with time-related to decline of physiological integrity and functionality process, responsible for increasing diseases and vulnerability to death. Several ages associated with biomarkers were observed in red blood cells, and consequently plasma proteins have a critical rejuvenating role in the aging process and age-related disorders. Advanced age is a risk factor for a broad spectrum of diseases and disorders such as cardiovascular diseases, musculoskeletal disorders and liver, chronic kidney disease, neurodegenerative diseases, and cancer because of loss of regenerative capacity, correlated to reduced systemic factors and raise of pro-inflammatory cytokines. Most studies have shown that systemic factors in young blood/plasma can strongly protect against age-related diseases in various tissues by restoring autophagy, increasing neurogenesis, and reducing oxidative stress, inflammation, and apoptosis. Here, we focus on the current advances in using young plasma or blood to combat aging and age-related diseases and summarize the experimental and clinical evidence supporting this approach. Based on reports, young plasma or blood is new a therapeutic approach to aging and age-associated diseases.

The effect of lipid metabolism on age-associated cognitive decline: Lessons learned from model organisms and human

Lipids are required as integral building blocks of cells to support cellular structures and functions. The intricate mechanisms underpinning lipid homeostasis are essential for the health and maintenance of the central nervous system. Here we summarize the recent advances in dissecting the effect of lipid metabolism on cognitive function and its age-associated decline by reviewing relevant studies ranging from invertebrate model organisms to mammals including human.

Targeted metabolomics reveals plasma biomarkers and metabolic alterations of the aging process in healthy young and older adults

With the exponential growth in the older population in the coming years, many studies have aimed to further investigate potential biomarkers associated with the aging process and its incumbent morbidities. Age is the largest risk factor for chronic disease, likely due to younger individuals possessing more competent adaptive metabolic networks that result in overall health and homeostasis. With aging, physiological alterations occur throughout the metabolic system that contribute to functional decline. In this cross-sectional analysis, a targeted metabolomic approach was applied to investigate the plasma metabolome of young (21-40y; n = 75) and older adults (65y + ; n = 76). A corrected general linear model (GLM) was generated, with covariates of gender, BMI, and chronic condition score (CCS), to compare the metabolome of the two populations. Among the 109 targeted metabolites, those associated with impaired fatty acid metabolism in the older population were found to be most significant: palmitic acid (p < 0.001), 3-hexenedioic acid (p < 0.001), stearic acid (p = 0.005), and decanoylcarnitine (p = 0.036). Derivatives of amino acid metabolism, 1-methlyhistidine (p = 0.035) and methylhistamine (p = 0.027), were found to be increased in the younger population and several novel metabolites were identified, such as cadaverine (p = 0.034) and 4-ethylbenzoic acid (p = 0.029). Principal component analysis was conducted and highlighted a shift in the metabolome for both groups. Receiver operating characteristic analyses of partial least squares-discriminant analysis models showed the candidate markers to be more powerful indicators of age than chronic disease. Pathway and enrichment analyses uncovered several pathways and enzymes predicted to underlie the aging process, and an integrated hypothesis describing functional characteristics of the aging process was synthesized. Compared to older participants, the young group displayed greater abundance of metabolites related to lipid and nucleotide synthesis; older participants displayed decreased fatty acid oxidation and reduced tryptophan metabolism, relative to the young group. As a result, we offer a better understanding of the aging metabolome and potentially reveal new biomarkers and predicted mechanisms for future study.

Effect of biological sex on human circulating lipidome: An overview of the literature

Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.

Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study

BACKGROUND AND AIMS

Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV).

METHODS

From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition.

RESULTS

In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate.

CONCLUSIONS

Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.

Sebacic Acid as a Potential Age-Related Biomarker of Liver Aging: Evidence Linking Mice and Human

The aging process is complicated and involves diverse organ dysfunction; furthermore, the biomarkers that are able to reflect biological aging are eagerly sought after to monitor the system-wide decline associated with the aging process. To address this, we performed a metabolomics analysis using a longitudinal cohort study from Taiwan (N = 710) and established plasma metabolomic age using a machine learning algorithm. The resulting estimation of age acceleration among the older adults was found to be correlated with HOMA-insulin resistance. In addition, a sliding window analysis was used to investigate the undulating decrease in hexanoic and heptanoic acids that occurs among the older adults at different ages. A comparison of the metabolomic alterations associated with aging between humans and mice implied that ω-oxidation of medium-chain fatty acids was commonly dysregulated in older subjects. Among these fatty acids, sebacic acid, an ω-oxidation product produced by the liver, was significantly decreased in the plasma of both older humans and aged mice. Notably, an increase in the production and consumption of sebacic acid within the liver tissue of aged mice was observed, along with an elevation of pyruvate-to-lactate conversion. Taken together, our study reveals that sebacic acid and metabolites of ω-oxidation are the common aging biomarkers in both humans and mice. The further analysis suggests that sebacic acid may play an energetic role in supporting the production of acetyl-CoA during liver aging, and thus its alteration in plasma concentration potentially reflects the aging process.

Metabolomic epidemiology offers insights into disease aetiology

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

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.

The Association of Tryptophan and Its Metabolites With Incident Hip Fractures, Mortality, and Prevalent Frailty in Older Adults: The Cardiovascular Health Study

Amino acids are the building blocks of proteins, and sufficient protein intake is important for skeletal health. We utilized stored serum from the Cardiovascular Health Study in 1992-1993 to examine the relationship between levels of the essential amino acid tryptophan (trp) and its oxidized and nonoxidized metabolites to risk for incident hip fractures and mortality over 12 years of follow-up. We included 131 persons who sustained a hip fracture during this time period and 131 without a hip fracture over these same 12 years of follow-up; 58% female and 95% White. Weighted multivariable Cox hazards models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of incident hip fracture associated with a one standard deviation (SD) higher trp or its metabolites exposure. Relative risk regression was used to evaluate the cross-sectional association of trp and its metabolites with frailty. Higher serum levels of trp were significantly associated with lower risk of incident hip fractures (HR = 0.75 per SD of trp (95% CI 0.57-0.99) but were not significantly associated with mortality or frailty status by Freid's frailty index. There were no statistically significant associations between any of the oxidized or nonoxidized products of trp with incident hip fractures (p ≥ 0.64), mortality (p ≥ 0.20), or cross-sectional frailty status (p ≥ 0.13) after multiple testing adjustment. Randomized clinical trials examining whether increasing trp intake is beneficial for osteoporosis are needed. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

An epidemiological introduction to human metabolomic investigations

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Correlations between kynurenines in plasma and CSF, and their relation to markers of Alzheimer's disease pathology

INTRODUCTION

Altered levels of kynurenines in blood and cerebrospinal fluid (CSF) have been reported in Alzheimer's disease (AD). However, it is still largely unknown whether peripheral kynurenine concentrations resemble those found in CSF and how they relate to AD pathology. We therefore studied correlations between kynurenines in plasma and CSF and their associations with CSF amyloid-beta (Aβ1-42) and tau levels in patients from the memory clinic spanning the whole cognitive spectrum.

METHODS

The Biobank Alzheimer Center Limburg study is a prospective cohort study of consecutive patients referred to the memory clinic of the Alzheimer Center Limburg. Plasma and CSF concentrations of tryptophan (TRP), eight kynurenines and neopterin from 138 patients were determined by means of LC-MS/MS. Additionally, CSF Aβ1-42, total-tau (t-tau) and phosphorylated tau (p-tau) concentrations were determined using commercially available single-parameter ELISA methods. Partial correlations were used to analyze cross-sectional associations between kynurenines in plasma and CSF and their relation to AD related CSF-biomarkers adjusted for age, sex, educational level, and kidney function.

RESULTS

Moderate to strong correlations were observed between plasma and CSF levels for quinolinic acid (QA; r = 0.63), TRP (r = 0.47), anthranilic acid (r = 0.59), picolinic acid (r = 0.55), and the kynurenine (KYN)/TRP ratio (KTR; r = 0.55; all p < 0.0001), while other kynurenines correlated only weakly with their corresponding CSF values. No correlations were found between plasma and CSF levels of KA/QA. Several kynurenines were also weakly correlated with Aβ1-42, t-tau or p-tau. Plasma levels of KA/QA were negatively correlated with Aβ1-42 (r = -0.21, p < 0.05). Plasma levels of TRP were negatively correlated with t-tau (r = -0.19) and levels of KYN with p-tau (r = -0.18; both p < 0.05). CSF levels of KYN (r = 0.20, p < 0.05), KA (r = 0.23, p < 0.01), and KTR (r = 0.18, p < 0.05) were positively correlated with Aβ1-42. Finally, TRP and KYN were negatively (r = -0.22 and r = -0.18, respectively), and neopterin positively (r = 0.19) correlated with p-tau (all p < 0.05).

CONCLUSIONS

Plasma concentrations of TRP, KP metabolites, KTR, and neopterin all significantly correlated positively with their corresponding CSF concentrations, but many correlations were weak. Additionally, our results suggest a relation between higher kynurenine levels and lower AD pathology load. These results need verification in future studies and require more research into (shared) underlying mechanisms.

Tuberculosis is associated with sputum metabolome variations, irrespective of patient sex or HIV status: an untargeted GCxGC-TOFMS study

INTRODUCTION

Various studies have identified TB-induced metabolome variations. However, in most of these studies, a large degree of variation exists between individual patients.

OBJECTIVES

To identify differential metabolites for TB, independent of patients' sex or HIV status.

METHODS

Untargeted GCxGC/TOF-MS analyses were applied to the sputum of 31 TB + and 197 TB- individuals. Univariate statistics were used to identify metabolites which are significantly different between TB + and TB- individuals (a) irrespective of HIV status, and (b) with a HIV + status. Comparisons a and b were repeated for (i) all participants, (ii) males only and (iii) females only.

RESULTS

Twenty-one compounds were significantly different between the TB + and TB- individuals within the female subgroup (11% lipids; 10% carbohydrates; 1% amino acids, 5% other and 73% unannotated), and 6 within the male subgroup (20% lipids; 40% carbohydrates; 6% amino acids, 7% other and 27% unannotated). For the HIV + patients (TB + vs. TB-), a total of 125 compounds were significant within the female subgroup (16% lipids; 8% carbohydrates; 12% amino acids, 6% organic acids, 8% other and 50% unannotated), and 44 within the male subgroup (17% lipids; 2% carbohydrates; 14% amino acids related, 8% organic acids, 9% other and 50% unannotated). Only one annotated compound, 1-oleoyl lysophosphaditic acid, was consistently identified as a differential metabolite for TB, irrespective of sex or HIV status. The potential clinical application of this compound should be evaluated further.

CONCLUSIONS

Our findings highlight the importance of considering confounders in metabolomics studies in order to identify unambiguous disease biomarkers.

Exploring the Relationship between the Gut Microbiota and Ageing: A Possible Age Modulator

The gut microbiota (GM) has been the subject of intense research in recent years. Therefore, numerous factors affecting its composition have been thoroughly examined, and with them, their function and role in the individual's systems. The gut microbiota's taxonomical composition dramatically impacts older adults' health status. In this regard, it could either extend their life expectancy via the modulation of metabolic processes and the immune system or, in the case of dysbiosis, predispose them to age-related diseases, including bowel inflammatory and musculoskeletal diseases and metabolic and neurological disorders. In general, the microbiome of the elderly tends to present taxonomic and functional changes, which can function as a target to modulate the microbiota and improve the health of this population. The GM of centenarians is unique, with the faculty-promoting metabolic pathways capable of preventing and counteracting the different processes associated with age-related diseases. The molecular mechanisms by which the microbiota can exhibit anti-ageing properties are mainly based on anti-inflammatory and antioxidant actions. This review focuses on analysing the current knowledge of gut microbiota characteristics and modifiers, its relationship with ageing, and the GM-modulating approaches to increase life expectancy.

Human Metabolome Reference Database in a Biracial Cohort across the Adult Lifespan

As one of the OMICS in systems biology, metabolomics defines the metabolome and simultaneously quantifies numerous metabolites that are final or intermediate products and effectors of upstream biological processes. Metabolomics provides accurate information that helps determine the physiological steady state and biochemical changes during the aging process. To date, reference values of metabolites across the adult lifespan, especially among ethnicity groups, are lacking. The "normal" reference values according to age, sex, and race allow the characterization of whether an individual or a group deviates metabolically from normal aging, encompass a fundamental element in any study aimed at understanding mechanisms at the interface between aging and diseases. In this study, we established a metabolomics reference database from 20-100 years of age from a biracial sample of community-dwelling healthy men and women and examined metabolite associations with age, sex, and race. Reference values from well-selected healthy individuals can contribute to clinical decision-making processes of metabolic or related diseases.

SLC38A10 Deficiency in Mice Affects Plasma Levels of Threonine and Histidine in Males but Not in Females: A Preliminary Characterization Study of SLC38A10−/− Mice

Solute carriers belong to the biggest group of transporters in the human genome, but more knowledge is needed to fully understand their function and possible role as therapeutic targets. SLC38A10, a poorly characterized solute carrier, is preliminary characterized here. By using a knockout mouse model, we studied the biological effects of SLC38A10 deficiency in vivo. We performed a transcriptomic analysis of the whole brain and found seven differentially expressed genes in SLC38A10-deficient mice (Gm48159, Nr4a1, Tuba1c, Lrrc56, mt-Tp, Hbb-bt and Snord116/9). By measuring amino acids in plasma, we found lower levels of threonine and histidine in knockout males, whereas no amino acid levels were affected in females, suggesting that SLC38A10−/− might affect sexes differently. Using RT-qPCR, we investigated the effect of SLC38A10 deficiency on mRNA expression of other SLC38 members, Mtor and Rps6kb1 in the brain, liver, lung, muscle, and kidney, but no differences were found. Relative telomere length measurement was also taken, as a marker for cellular age, but no differences were found between the genotypes. We conclude that SLC38A10 might be important for keeping amino acid homeostasis in plasma, at least in males, but no major effects were seen on transcriptomic expression or telomere length in the whole brain.

Large-Scale metabolomics: Predicting biological age using 10,133 routine untargeted LC-MS measurements

Untargeted metabolomics is the study of all detectable small molecules, and in geroscience, metabolomics has shown great potential to describe the biological age-a complex trait impacted by many factors. Unfortunately, the sample sizes are often insufficient to achieve sufficient power and minimize potential biases caused by, for example, demographic factors. In this study, we present the analysis of biological age in ~10,000 toxicologic routine blood measurements. The untargeted screening samples obtained from ultra-high pressure liquid chromatography-quadruple time of flight mass spectrometry (UHPLC- QTOF) cover + 300 batches and + 30 months, lack pooled quality controls, lack controlled sample collection, and has previously only been used in small-scale studies. To overcome experimental effects, we developed and tested a custom neural network model and compared it with existing prediction methods. Overall, the neural network was able to predict the chronological age with an rmse of 5.88 years (r²  = 0.63) improving upon the 6.15 years achieved by existing normalization methods. We used the feature importance algorithm, Shapley Additive exPlanations (SHAP), to identify compounds related to the biological age. Most importantly, the model returned known aging markers such as kynurenine, indole-3-aldehyde, and acylcarnitines along with a potential novel aging marker, cyclo (leu-pro). Our results validate the association of tryptophan and acylcarnitine metabolism to aging in a highly uncontrolled large-s cale sample. Also, we have shown that by using robust computational methods it is possible to deploy large LC-MS datasets for metabolomics studies to reduce the risk of bias and empower aging studies.

Replication and mediation of the association between the metabolome and clinical markers of metabolic health in an adolescent cohort study

Metabolomics-derived metabolites (henceforth metabolites) may mediate the relationship between modifiable risk factors and clinical biomarkers of metabolic health (henceforth clinical biomarkers). We set out to study the associations of metabolites with clinical biomarkers and a potential mediation effect in a population of young adults. First, we conducted a systematic literature review searching for metabolites associated with 11 clinical biomarkers (inflammation markers, glucose, blood pressure or blood lipids). Second, we replicated the identified associations in a study population of n = 218 (88 males and 130 females, average age of 18 years) participants of the DONALD Study. Sex-stratified linear regression models adjusted for age and BMI and corrected for multiple testing were calculated. Third, we investigated our previously reported metabolites associated with anthropometric and dietary factors mediators in sex-stratified causal mediation analysis. For all steps, both urine and blood metabolites were considered. We found 41 metabolites in the literature associated with clinical biomarkers meeting our inclusion criteria. We were able to replicate an inverse association of betaine with CRP in women, between body mass index and C-reactive protein (CRP) and between body fat and leptin. There was no evidence of mediation by lifestyle-related metabolites after correction for multiple testing. We were only able to partially replicate previous findings in our age group and did not find evidence of mediation. The complex interactions between lifestyle factors, the metabolome, and clinical biomarkers warrant further investigation.

Metabolomics Profiling of Age-Associated Metabolites in Malay Population

Aging is a complex process characterized by progressive loss of functional abilities due to the accumulation of molecular damages. Metabolomics could offer novel insights into the predictors and mechanisms of aging. This cross-sectional study is aimed at identifying age-associated plasma metabolome in a Malay population. A total of 146 (90 females) healthy participants aged 28-69 were selected for the study. Untargeted metabolomics profiling was performed using liquid chromatography-tandem mass spectrometry. Association analysis was based on the general linear model. Gender-associated metabolites were adjusted for age, while age-associated metabolites were adjusted for gender or analyzed in a gender-stratified manner. Gender-associated metabolites such as 4-hydroxyphenyllactic acid, carnitine, cortisol, and testosterone sulfate showed higher levels in males than females. Deoxycholic acid and hippuric acid were among the metabolites with a positive association with age after being adjusted for gender, while 9(E),11(E)-conjugated linoleic acid, cortisol, and nicotinamide were negatively associated with age. In gender-stratified analysis, glutamine was one of the common metabolites that showed a direct association with age in both genders, while metabolites such as 11-deoxy prostaglandin F2β, guanosine monophosphate, and testosterone sulfate were inversely associated with age in males and females. This study reveals several age-associated metabolites in Malays that could reflect the changes in metabolisms during aging and may be used to discern the risk of geriatric syndromes and disorders later. Further studies are required to determine the interplay between these metabolites and environmental factors on the functional outcomes during aging.

Microbiota-associated mechanisms underlying sexual dimorphism in hypertension

Consistent research over the last 20 years has shown that there are clear sex differences in the pathogenesis of hypertension, the leading risk factor for the development of cardiovascular diseases. More recently, there is evidence in both humans and experimental animal models that causally implicates the gut microbiota in hypertension. It therefore follows that sex differences in the gut microbiota may mediate the extent of disease between sexes. This new field is rapidly changing and advancing, and the purpose of this review is to cover the most up-to-date evidence regarding the sexual dimorphism of the gut microbiota and its potential influence on the differential manifestation of hypertension in males versus females. Emphasis will be placed on the mechanisms thought to contribute to these sex differences in both the gut microbiota and hypertension, including sex steroid hormones, gut-derived metabolites, the immune system, and pregnancy.

Comparative plasma and urine metabolomics analysis of juvenile and adult canines

Background and aims

The metabolomic profile of a biofluid can be affected by age, and thus provides detailed information about the metabolic alterations in biological processes and reflects the in trinsic rule regulating the growth and developmental processes.

Methods

To systemically investigate the characteristics of multiple metabolic profiles associated with canine growth, we analyzed the metabolomics in the plasma and urine samples from 15 young and 15 adult beagle dogs via UHPLC-Q-TOFMS-based metabolomics. Blood routine and serum biochemical analyses were also performed on fasting blood samples.

Results

The metabolomics results showed remarkable differences in metabolite fingerprints both in plasma and urine between the young and adult groups. The most obvious age-related metabolite alterations include decreased serumlevels of oxoglutaric acid and essential amino acids and derivatives but increased levels of urine levels of O-acetylserine. These changes primarily involved in amino acid metabolism and bile secretion pathways. We also found that the levels of glutamine were consistently higher in both serum and urine of adults, while N-acetylhistamine and uracil concentrations were much lower in the adult group compared to younger ones.

Conclusion

Our study provides a whole metabolic profile of serum and urine characteristics of young and adult canines, identifying several metabolites that were significantly associated with age change, which provides theoretical support for the nutrition-related research and age-related homeostasis maintenance in dogs.

Differences in Metabolomic Profiles by Birthplace in Mexican-Origin Hispanic Men Who Participated in a Weight Loss Lifestyle Intervention

Birthplace, as a proxy for environmental exposures (e.g., diet), may influence metabolomic profiles and influence risk of cancer. This secondary analysis investigated metabolomic profile differences between foreign and U.S.-born Mexican-origin (MO) Hispanic men to shed light on potential mechanisms through which foreign- and U.S.-born individuals experience differences in cancer risk and risk factors. Plasma samples from MO Hispanic men (N = 42) who participated in a previous lifestyle intervention were collected pre-and post-intervention. Metabolomic profiles were characterized from samples using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-QTOF). Models were visualized using supervised orthogonal projections to latent structures-discriminant analysis (OPLS-DA). Progenesis QI was used for peak integration and metabolite identification. Plasma metabolomic profiles differed between foreign- and U.S.-born pre-intervention (R2 = .65) and post-intervention (R2 = .62). Metabolomic profiles differed pre- versus post-intervention (R2 = .35 and R2 = .65) for the foreign- and U.S.-born group, respectively. Both endogenous metabolites and dietary components characterized differences between foreign- and U.S.-born participants pre- and post-intervention. Plasma metabolomic profiles from MO Hispanic men differed by birthplace. These results advance our understanding of relevant exposures that may affect cancer risk among MO Hispanic men born abroad or in the United States.

Behavioral profiling of SLC38A10 knockout mice using the multivariate concentric square fieldTM test

Introduction

SLC38A10 is a gene that encodes the SLC38A10 protein, also known as SNAT10. The SLC38 family is evolutionary old, and SLC38A10 is one of the oldest members of the family. It is ubiquitously expressed, and its substrates are glutamine, glutamate, alanine, aspartate, and serine. However, little is known about its biological importance.

Methods

In the current study, an SLC38A10 knockout mouse was run in the multivariate concentric square field ^TM (MCSF) test. The MCSF test gives the mouse a choice of areas to explore; sheltered areas, elevated and illuminated areas, or open spaces, and a behavioral profile is obtained. The multivariate data obtained were analyzed (i) for each parameter, (ii) parameters grouped into functional categories, and (iii) with a principal component analysis.

Results

In the trend analysis, knockout mice had a decreased exploratory behavior compared to controls but did not show a distinct grouping in the principal component analysis.

Discussion

There was not a pronounced difference in the behavioral profile in SLC38A10 knockout mice compared to their wild-type controls, although subtle alterations in zones associated with exploratory behavior and risk assessment in female and male knockout mice, respectively, could be observed. These results imply that a loss of function of the SLC38A10 protein in mice does not drastically alter behavior in the MSCF test.

Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults

BACKGROUND

Quantification of metabolic changes over the human life course is essential to understanding ageing processes. Yet longitudinal metabolomics data are rare and long gaps between visits can introduce biases that mask true trends. We introduce new ways to process quantitative time-series population data and elucidate metabolic ageing trends in two large cohorts.

METHODS

Eligible participants included 1672 individuals from the Cardiovascular Risk in Young Finns Study and 3117 from the Northern Finland Birth Cohort 1966. Up to three time points (ages 24-49 years) were analysed by nuclear magnetic resonance metabolomics and clinical biochemistry (236 measures). Temporal trends were quantified as median change per decade. Sample quality was verified by consistency of shared biomarkers between metabolomics and clinical assays. Batch effects between visits were mitigated by a new algorithm introduced in this report. The results below satisfy multiple testing threshold of P < 0.0006.

RESULTS

Women gained more weight than men (+6.5% vs +5.0%) but showed milder metabolic changes overall. Temporal sex differences were observed for C-reactive protein (women +5.1%, men +21.1%), glycine (women +5.2%, men +1.9%) and phenylalanine (women +0.6%, men +3.5%). In 566 individuals with ≥+3% weight gain vs 561 with weight change ≤-3%, divergent patterns were observed for insulin (+24% vs -10%), very-low-density-lipoprotein triglycerides (+32% vs -6%), high-density-lipoprotein2 cholesterol (-6.5% vs +4.7%), isoleucine (+5.7% vs -6.0%) and C-reactive protein (+25% vs -22%).

CONCLUSION

We report absolute and proportional trends for 236 metabolic measures as new reference material for overall age-associated and specific weight-driven changes in real-world populations.

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.

Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies.

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.

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.

Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids

Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.

Exploring the association between habitual food intake and the urine and blood metabolome in adolescents and young adults: a cohort study

SCOPE

Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. We aimed to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults.

METHODS

The study population comprised 228 participants (94 male and 134 female) of the DONALD study. Dietary intake was assessed by yearly repeated 3d-food records. Habitual diet was estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, we quantified 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, we determined unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF).

RESULTS

We observed 6 metabolites in agreement between oPLS and RF in urine, 1 in females (vanillylmandelate to processed/ other meat) and 5 in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables). We observed no association in blood in agreement.

CONCLUSION

We observed a limited reflection of habitual food group intake by single metabolites in urine and not in blood. The explored biomarkers should be confirmed in additional studies. This article is protected by copyright. All rights reserved.

Cord blood metabolites and rapid postnatal growth as multiple mediators in the prenatal propensity to childhood overweight

BACKGROUND

The mechanisms underlying childhood overweight and obesity are poorly known. Here, we investigated the direct and indirect effects of different prenatal exposures on offspring rapid postnatal growth and overweight in childhood, mediated through cord blood metabolites. Additionally, rapid postnatal growth was considered a potential mediator on childhood overweight, alone and sequentially to each metabolite.

METHODS

Within four European birth-cohorts (N = 375 mother-child dyads), information on seven prenatal exposures (maternal education, pre-pregnancy BMI, weight gain and tobacco smoke during pregnancy, age at delivery, parity, and child gestational age), selected as obesogenic according to a-priori knowledge, was collected. Cord blood levels of 31 metabolites, associated with rapid postnatal growth and/or childhood overweight in a previous study, were measured via liquid-chromatography-quadrupole-time-of-flight-mass-spectrometry. Rapid growth at 12 months and childhood overweight (including obesity) between four and eight years were defined with reference to WHO growth charts. Single mediation analysis was performed using the imputation approach and multiple mediation analysis using the extended-imputation approach.

RESULTS

Single mediation suggested that the effect of maternal education, pregnancy weight gain, parity, and gestational age on rapid postnatal growth but not on childhood overweight was partly mediated by seven metabolites, including cholestenone, decenoylcarnitine(C10:1), phosphatidylcholine(C34:3), progesterone and three unidentified metabolites; and the effect of gestational age on childhood overweight was mainly mediated by rapid postnatal growth. Multiple mediation suggested that the effect of gestational age on childhood overweight was mainly mediated by rapid postnatal growth and that the mediating role of the metabolites was marginal.

CONCLUSION

Our findings provide evidence of the involvement of in utero metabolism in the propensity to rapid postnatal growth and of rapid postnatal growth in the propensity to childhood overweight. We did not find evidence supporting a mediating role of the studied metabolites alone between the studied prenatal exposures and the propensity to childhood overweight.

Dietary and serum tyrosine, white matter microstructure and inter-individual variability in executive functions in overweight adults: Relation to sex/gender and age

Tyrosine (tyr), the precursor of the neurotransmitter dopamine, is known to modulate cognitive functions including executive attention. Tyr supplementation is suggested to influence dopamine-modulated cognitive performance. However, results are inconclusive regarding the presence or strength and also the direction of the association between tyr and cognitive function. This pre-registered cross-sectional analysis investigates whether diet-associated serum tyr relates to executive attention performance, and whether this relationship is moderated by differences in white matter microstructure. 59 healthy, overweight, young to middle-aged adults (20 female, 28.3 ± 6.6 years, BMI: 27.3 ± 1.5 kg/m²) drawn from a longitudinal study reported dietary habits, donated blood and completed diffusion-weighted brain magnetic resonance imaging and the attention network test. Main analyses were performed using linear regressions and non-parametric voxel-wise inference testing. Confirmatory analyses did neither support an association between dietary and serum tyr nor a relationship between relative serum tyr/large neutral amino acids (LNAA) levels or white matter microstructure and executive attention performance. However, exploratory analyses revealed higher tyr intake, higher serum tyr and better executive attention performance in the male sex/gender group. In addition, older age was associated with higher dietary tyr intake and lower fractional anisotropy in a widespread cluster across the brain. Finally, a positive association between relative serum tyr/LNAA and executive attention performance was found in the male sex/gender group when accounting for age effects. Our analysis advances the field of dopamine-modulated cognitive functions by revealing sex/gender and age differences which might be diet-related. Longitudinal or intervention studies and larger sample sizes are needed to provide more reliable evidence for links between tyr and executive attention.

1H NMR-Based Metabolomics Reveals the Intrinsic Interaction of Age, Plasma Signature Metabolites, and Nutrient Intake in the Longevity Population in Guangxi, China

Health and longevity populations have distinct metabolic and nutrient intake profiles. However, the relationship between biomarkers of longevity-related metabolites and dietary nutrient intake profiles, as well as metabolic markers associated with longevity features, have not been fully elucidated. Therefore, ¹H nuclear magnetic resonance (¹H NMR)-based plasma metabolomics profiling was conducted in the present study to identify potential metabolites which can be used as specific markers for the evaluation of healthy aging. Plasma samples were obtained from centenarians and nonagenarians from the longevous region, and elderly participants aged 60–89 from the longevous region, as well as a low centenarian ratio region. The results showed that participants from longevous regions exhibited higher plasma levels of citrate, tyrosine, choline, carnitine, and valine, as well as lower contents of VLDL, lactate, alanine, N-acetyl glycoprotein (NAG), trimethylamine oxide (TMAO), α-glucose, β-glucose, and unsaturated lipids. The differential plasma metabolites were associated with an alteration in glycolysis/gluconeogenesis; aminoacyl-tRNA biosynthesis; alanine, aspartate, and glutamate metabolism; and phenylalanine, tyrosine, and tryptophan biosynthesis in participants from longevous regions. The signature metabolites were associated with higher dietary fiber intake, as well as lower energy and fat intake. The results of the present study demonstrate key longevity signature metabolites in plasma, and the dietary patterns identified provide a basis for further health and longevity research.

Heritability of Urinary Amines, Organic Acids, and Steroid Hormones in Children

Variation in metabolite levels reflects individual differences in genetic and environmental factors. Here, we investigated the role of these factors in urinary metabolomics data in children. We examined the effects of sex and age on 86 metabolites, as measured on three metabolomics platforms that target amines, organic acids, and steroid hormones. Next, we estimated their heritability in a twin cohort of 1300 twins (age range: 5.7–12.9 years). We observed associations between age and 50 metabolites and between sex and 21 metabolites. The monozygotic (MZ) and dizygotic (DZ) correlations for the urinary metabolites indicated a role for non-additive genetic factors for 50 amines, 13 organic acids, and 6 steroids. The average broad-sense heritability for these amines, organic acids, and steroids was 0.49 (range: 0.25–0.64), 0.50 (range: 0.33–0.62), and 0.64 (range: 0.43–0.81), respectively. For 6 amines, 7 organic acids, and 4 steroids the twin correlations indicated a role for shared environmental factors and the average narrow-sense heritability was 0.50 (range: 0.37–0.68), 0.50 (range; 0.23–0.61), and 0.47 (range: 0.32–0.70) for these amines, organic acids, and steroids. We conclude that urinary metabolites in children have substantial heritability, with similar estimates for amines and organic acids, and higher estimates for steroid hormones.