Predicting longevity using metabolomics: a novel tool for precision lifestyle medicine?

A global perspective on the status of clinical metabolomics in laboratory medicine - a survey by the IFCC metabolomics working group

OBJECTIVES

Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation.

METHODS

A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed.

RESULTS

Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology.

CONCLUSIONS

Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease Among Low-Income Black and White Americans

BACKGROUND

Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

METHODS

In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.

RESULTS

Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (r=0.61) and inverse association with CHD (odds ratio, 0.57 [0.49-0.65]), robust to adjustment for LE8 score and across participants with different sociodemographic and health status ([odds ratios, 0.42-0.69]; all P<0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort (r=0.49; odds ratio, 0.57 [0.46-0.69]).

CONCLUSIONS

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

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.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease among Low-Income Black and White Americans

Background and Aims

Life's Essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

Methods

In a nested case-control study of coronary heart disease (CHD) among 598 Black and 596 White low-income Americans, we estimated LE8 score, conducted untargeted plasma metabolites profiling, and used elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. Mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 598 Chinese adults.

Results

Higher LE8 score was associated with lower CHD risk [standardized OR (95% CI)=0.61 (0.53-0.69)]. The identified MetaSig, consisting of 133 metabolites, showed strong correlation with LE8 score ( r =0.61) and inverse association with CHD risk [OR (95% CI)=0.57 (0.49-0.65)], robust to adjustment for LE8 score and across participants with different sociodemographic and health status (ORs: 0.42-0.69; all P <0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%) ( P <0.001). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort [ r =0.49; OR (95% CI)=0.57 (0.46-0.69)].

Conclusions

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective and comprehensive measure of LE8 score and its metabolic phenotype relevant to CHD prevention among diverse populations.

Applications of liquid chromatography-mass spectrometry based metabolomics in predictive and personalized medicine

Metabolomics is a fast-developing technique used in biomedical researches focusing on pathological mechanism illustration or novel biomarker development for diseases. The ability of simultaneously quantifying thousands of metabolites in samples makes metabolomics a promising technique in predictive or personalized medicine-oriented researches and applications. Liquid chromatography-mass spectrometry is the most widely employed analytical strategy for metabolomics. In this current mini-review, we provide a brief update on the recent developments and novel applications of LC-MS based metabolomics in the predictive and personalized medicine sector, such as early diagnosis, molecular phenotyping or prognostic evaluation. COVID-19 related metabolomic studies are also summarized. We also discuss the prospects of metabolomics in precision medicine-oriented researches, as well as critical issues that need to be addressed when employing metabolomic strategy in clinical applications.

Serum Metabolomic Profiling in Aging Mice Using Liquid Chromatography-Mass Spectrometry

BACKGROUND

The process of aging and metabolism are intricately linked, thus rendering the identification of reliable biomarkers related to metabolism crucial for delaying the aging process. However, research of reliable markers that reflect aging profiles based on machine learning is scarce.

METHODS

Serum samples were obtained from aged mice (18-month-old) and young mice (3-month-old). LC-MS was used to perform a comprehensive analysis of the serum metabolome and machine learning was used to screen potential aging-related biomarkers.

RESULTS

In total, aging mice were characterized by 54 different metabolites when compared to control mice with criteria: VIP ≥ 1, q-value < 0.05, and Fold-Change ≥ 1.2 or ≤0.83. These metabolites were mostly involved in fatty acid biosynthesis, cysteine and methionine metabolism, D-glutamine and D-glutamate metabolism, and the citrate cycle (TCA cycle). We merged the comprehensive analysis and four algorithms (LR, GNB, SVM, and RF) to screen aging-related biomarkers, leading to the recognition of oleic acid. In addition, five metabolites were identified as novel aging-related indicators, including oleic acid, citric acid, D-glutamine, trypophol, and L-methionine.

CONCLUSIONS

Changes in the metabolism of fatty acids and conjugates, organic acids, and amino acids were identified as metabolic dysregulation related to aging. This study revealed the metabolic profile of aging and provided insights into novel potential therapeutic targets for delaying the effects of aging.

Overweight, Obesity, and CVD Risk: a Focus on Visceral/Ectopic Fat

PURPOSE OF REVIEW

Despite its prevalence and well-documented impact on population health, obesity has not emerged as a strong independent risk factor for cardiovascular disease after control for intermediate risk factors. The purpose of this brief narrative review is to highlight results from imaging studies that have not only documented the remarkable heterogeneity of body fat topography but also the importance of visceral adiposity as a key body fat depot associated with cardiovascular disease risk and type 2 diabetes.

RECENT FINDINGS

Simple tools are also discussed in order to refine cardiometabolic risk assessment in persons with overweight/obesity. It is proposed that four lifestyle vital signs should be considered in clinical practice to improve discrimination of health risk in individuals with overweight/obesity: waist circumference as a simple marker of abdominal adiposity, cardiorespiratory fitness, overall diet quality, and level of reported physical activity. Heterogeneity of obesity is proposed as an example of a condition that would benefit from a precision lifestyle medicine approach.

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.

The Role of Selenoprotein Tissue Homeostasis in MetS Programming: Energy Balance and Cardiometabolic Implications

Selenium (Se) is an essential trace element mainly known for its antioxidant, anti-inflammatory, and anti-apoptotic properties, as it is part of the catalytic center of 25 different selenoproteins. Some of them are related to insulin resistance (IR) and metabolic syndrome (MetS) generation, modulating reactive oxygen species (ROS), and the energetic sensor AMP-activated protein kinase (AMPK); they can also regulate the nuclear transcription factor kappa-B (NF-kB), leading to changes in inflammation production. Selenoproteins are also necessary for the correct synthesis of insulin and thyroid hormones. They are also involved in endocrine central regulation of appetite and energy homeostasis, affecting growth and development. MetS, a complex metabolic disorder, can appear during gestation and lactation in mothers, leading to energetic and metabolic changes in their offspring that, according to the metabolic programming theory, will produce cardiovascular and metabolic diseases later in life. However, there is a gap concerning Se tissue levels and selenoproteins’ implications in MetS generation, which is even greater during MetS programming. This narrative review also provides an overview of the existing evidence, based on experimental research from our laboratory, which strengthens the fact that maternal MetS leads to changes in Se tissue deposits and antioxidant selenoproteins’ expression in their offspring. These changes contribute to alterations in tissues’ oxidative damage, inflammation, energy balance, and tissue function, mainly in the heart. Se imbalance also could modulate appetite and endocrine energy balance, affecting pups’ growth and development. MetS pups present a profile similar to that of diabetes type 1, which also appeared when dams were exposed to low-Se dietary supply. Maternal Se supplementation should be taken into account if, during gestation and/or lactation periods, there are suspicions of endocrine energy imbalance in the offspring, such as MetS. It could be an interesting therapy to induce heart reprogramming. However, more studies are necessary.

The Metabolic Signature of Cardiorespiratory Fitness: A Systematic Review

Background

Cardiorespiratory fitness (CRF) is a potent health marker, the improvement of which is associated with a reduced incidence of non-communicable diseases and all-cause mortality. Identifying metabolic signatures associated with CRF could reveal how CRF fosters human health and lead to the development of novel health-monitoring strategies.

Objective

This article systematically reviewed reported associations between CRF and metabolites measured in human tissues and body fluids.

Methods

PubMed, EMBASE, and Web of Science were searched from database inception to 3 June, 2021. Metabolomics studies reporting metabolites associated with CRF, measured by means of cardiopulmonary exercise test, were deemed eligible. Backward and forward citation tracking on eligible records were used to complement the results of database searching. Risk of bias at the study level was assessed using QUADOMICS.

Results

Twenty-two studies were included and 667 metabolites, measured in plasma (n = 619), serum (n = 18), skeletal muscle (n = 16), urine (n = 11), or sweat (n = 3), were identified. Lipids were the metabolites most commonly positively (n = 174) and negatively (n = 274) associated with CRF. Specific circulating glycerophospholipids (n = 85) and cholesterol esters (n = 17) were positively associated with CRF, while circulating glycerolipids (n = 152), glycerophospholipids (n = 42), acylcarnitines (n = 14), and ceramides (n = 12) were negatively associated with CRF. Interestingly, muscle acylcarnitines were positively correlated with CRF (n = 15).

Conclusions

Cardiorespiratory fitness was associated with circulating and muscle lipidome composition. Causality of the revealed associations at the molecular species level remains to be investigated further. Finally, included studies were heterogeneous in terms of participants’ characteristics and analytical and statistical approaches.

PROSPERO Registration Number

CRD42020214375.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40279-021-01590-y.

Cross-Species and Human Inter-Tissue Network Analysis of Genes Implicated in Longevity and Aging Reveal Strong Support for Nutrient Sensing

Intensive research efforts have been undertaken to slow human aging and therefore potentially delay the onset of age-related diseases. These efforts have generated an enormous amount of high-throughput data covering different levels in the physiologic hierarchy, e.g., genetic, epigenetic, transcriptomic, proteomic, and metabolomic, etc. We gathered 15 independent sources of information about genes potentially involved in human longevity and lifespan (N = 5836) and subjected them to various integrated analyses. Many of these genes were initially identified in non-human species, and we investigated their orthologs in three non-human species [i.e., mice (N = 967), fruit fly (N = 449), and worm (N = 411)] for further analysis. We characterized experimentally determined protein-protein interaction networks (PPIN) involving each species' genes from 9 known protein databases and studied the enriched biological pathways among the individually constructed PPINs. We observed three important signaling pathways: FoxO signaling, mTOR signaling, and autophagy to be common and highly enriched in all four species (p-value ≤ 0.001). Our study implies that the interaction of proteins involved in the mechanistic target of rapamycin (mTOR) signaling pathway is somewhat limited to each species or that a "rewiring" of specific networks has taken place over time. To corroborate our findings, we repeated our analysis in 43 different human tissues. We investigated conserved modules in various tissue-specific PPINs of the longevity-associated genes based upon their protein expression. This analysis also revealed mTOR signaling as shared biological processes across four different human tissue-specific PPINs for liver, heart, skeletal muscle, and adipose tissue. Further, we explored our results' translational potential by assessing the protein interactions with all the reported drugs and compounds that have been experimentally verified to promote longevity in the three-comparator species. We observed that the target proteins of the FDA-approved drug rapamycin (a known inhibitor of mTOR) were conserved across all four species. Drugs like melatonin and metformin exhibited shared targets with rapamycin in the human PPIN. The detailed information about the curated gene list, cross-species orthologs, PPIN, and pathways was assembled in an interactive data visualization portal using RStudio's Shiny framework (https://agingnetwork.shinyapps.io/frontiers/).

Metabolic View on Human Healthspan: A Lipidome-Wide Association Study

As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied ‘omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level.

Reversing Type 2 Diabetes: The Time for Lifestyle Medicine Has Come!

The IDF (International Diabetes Federation) Diabetes Atlas Committee has recently published the global estimates of diabetes prevalence for 2019 [...].

Perioperative Precision Medicine: Where Are We in 2020?

PURPOSE OF REVIEW

The present review examines how targeted approaches to care, based on individual variability in patient characteristics, could be applied in the perioperative setting. Such an approach would enhance individualized risk assessment and allow for targeted preventive and therapeutic decision-making in patients at increased risk for adverse perioperative events.

RECENT FINDINGS

Prior and current studies highlight valuable lessons on how future investigations attempting to link specific patient-related characteristics or treatment modalities with outcomes and adverse drug responses might be designed in the perioperative setting.

SUMMARY

Our review highlights the past, present, and future directions of perioperative precision medicine. Current evidence provides important lessons on how a specific patient and disease tailored approach can help perioperative physicians in delivering the most appropriate and safest perioperative care.

Obesity Phenotypes, Diabetes, and Cardiovascular Diseases

This review addresses the interplay between obesity, type 2 diabetes mellitus, and cardiovascular diseases. It is proposed that obesity, generally defined by an excess of body fat causing prejudice to health, can no longer be evaluated solely by the body mass index (expressed in kg/m²) because it represents a heterogeneous entity. For instance, several cardiometabolic imaging studies have shown that some individuals who have a normal weight or who are overweight are at high risk if they have an excess of visceral adipose tissue-a condition often accompanied by accumulation of fat in normally lean tissues (ectopic fat deposition in liver, heart, skeletal muscle, etc). On the other hand, individuals who are overweight or obese can nevertheless be at much lower risk than expected when faced with excess energy intake if they have the ability to expand their subcutaneous adipose tissue mass, particularly in the gluteal-femoral area. Hence, excessive amounts of visceral adipose tissue and of ectopic fat largely define the cardiovascular disease risk of overweight and moderate obesity. There is also a rapidly expanding subgroup of patients characterized by a high accumulation of body fat (severe obesity). Severe obesity is characterized by specific additional cardiovascular health issues that should receive attention. Because of the difficulties of normalizing body fat content in patients with severe obesity, more aggressive treatments have been studied in this subgroup of individuals such as obesity surgery, also referred to as metabolic surgery. On the basis of the above, we propose that we should refer to obesities rather than obesity.