Deep learning in systems medicine.

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Targeting the gut to prevent and counteract metabolic disorders and pathologies during aging.

Impairment of gut function is one of the explanatory mechanisms of health status decline in elderly population. These impairments involve a decline in gut digestive physiology, metabolism and immune status, and associated to that, changes in composition and function of the microbiota it harbors. Continuous deteriorations are generally associated with the development of systemic dysregulations and ultimately pathologies that can worsen the initial health status of individuals. All these alterations observed at the gut level can then constitute a wide range of potential targets for development of nutritional strategies that can impact gut tissue or associated microbiota pattern. This can be key, in a preventive manner, to limit gut functionality decline, or in a curative way to help maintaining optimum nutrients bioavailability in a context on increased requirements, as frequently observed in pathological situations. The aim of this review is to give an overview on the alterations that can occur in the gut during aging and lead to the development of altered function in other tissues and organs, ultimately leading to the development of pathologies. Subsequently is discussed how nutritional strategies that target gut tissue and gut microbiota can help to avoid or delay the occurrence of aging-related pathologies.

Mediterranean diet intervention alters the gut microbiome in older people reducing frailty and improving health status: the NU-AGE 1-year dietary intervention across five European countries.

OBJECTIVE: Ageing is accompanied by deterioration of multiple bodily functions and inflammation, which collectively contribute to frailty. We and others have shown that frailty co-varies with alterations in the gut microbiota in a manner accelerated by consumption of a restricted diversity diet. The Mediterranean diet (MedDiet) is associated with health. In the NU-AGE project, we investigated if a 1-year MedDiet intervention could alter the gut microbiota and reduce frailty. DESIGN: We profiled the gut microbiota in 612 non-frail or pre-frail subjects across five European countries (UK, France, Netherlands, Italy and Poland) before and after the administration of a 12-month long MedDiet intervention tailored to elderly subjects (NU-AGE diet). RESULTS: Adherence to the diet was associated with specific microbiome alterations. Taxa enriched by adherence to the diet were positively associated with several markers of lower frailty and improved cognitive function, and negatively associated with inflammatory markers including C-reactive protein and interleukin-17. Analysis of the inferred microbial metabolite profiles indicated that the diet-modulated microbiome change was associated with an increase in short/branch chained fatty acid production and lower production of secondary bile acids, p-cresols, ethanol and carbon dioxide. Microbiome ecosystem network analysis showed that the bacterial taxa that responded positively to the MedDiet intervention occupy keystone interaction positions, whereas frailty-associated taxa are peripheral in the networks. CONCLUSION: Collectively, our findings support the feasibility of improving the habitual diet to modulate the gut microbiota which in turn has the potential to promote healthier ageing.

Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data.

INTRODUCTION: Metabolomics is a powerful phenotyping tool in nutrition and health research, generating complex data that need dedicated treatments to enrich knowledge of biological systems. In particular, to investigate relations between environmental factors, phenotypes and metabolism, discriminant statistical analyses are generally performed separately on metabolomic datasets, complemented by associations with metadata. Another relevant strategy is to simultaneously analyse thematic data blocks by a multi-block partial least squares discriminant analysis (MBPLSDA) allowing determining the importance of variables and blocks in discriminating groups of subjects, taking into account data structure. OBJECTIVE: The present objective was to develop a full open-source standalone tool, allowing all steps of MBPLSDA for the joint analysis of metabolomic and epidemiological data. METHODS: This tool was based on the mbpls function of the ade4 R package, enriched with functionalities, including some dedicated to discriminant analysis. Provided indicators help to determine the optimal number of components, to check the MBPLSDA model validity, and to evaluate the variability of its parameters and predictions. RESULTS: To illustrate the potential of this tool, MBPLSDA was applied to a real case study involving metabolomics, nutritional and clinical data from a human cohort. The availability of different functionalities in a single R package allowed optimizing parameters for an efficient joint analysis of metabolomics and epidemiological data to obtain new insights into multidimensional phenotypes. CONCLUSION: In particular, we highlighted the impact of filtering the metabolomic variables beforehand, and the relevance of a MBPLSDA approach in comparison to a standard PLS discriminant analysis method.

Metabolic adaptations to HFHS overfeeding: how whole body and tissues postprandial metabolic flexibility adapt in Yucatan mini-pigs.

PURPOSE: In the present study, we aimed to metabolically characterize the postprandial adaptations of the major tissues involved in energy, lipids and amino acids metabolisms in mini-pigs. METHOD: Mini-pigs were fed on high-fat-high-sucrose (HFHS) diet for 2 months and several tissues explored for metabolic analyses. Further, the urine metabolome was followed over the time to picture the metabolic adaptations occurring at the whole body level following overfeeding. RESULTS: After 2 months of HFHS consumption, mini-pigs displayed an obese phenotype characterized by high circulating insulin, triglycerides and cholesterol levels. At the tissue level, a general (muscle, adipose tissue, intestine) reduction in the capacity to phosphorylate glucose was observed. This was also supported by the enhanced hepatic gluconeogenesis potential, despite the concomitant normoglycaemia, suggesting that the high circulating insulin levels would be enough to maintain glucose homoeostasis. The HFHS feeding also resulted in a reduced capacity of two other pathways: the de novo lipogenesis, and the branched-chain amino acids transamination. Finally, the follow-up of the urine metabolome over the time allowed determining breaking points in the metabolic trajectory of the animals. CONCLUSIONS: Several features confirmed the pertinence of the animal model, including increased body weight, adiposity and porcine obesity index. At the metabolic level, we observed a perturbed glucose and amino acid metabolism, known to be related to the onset of the obesity. The urine metabolome analyses revealed several metabolic pathways potentially involved in the obesity onset, including TCA (citrate, pantothenic acid), amino acids catabolism (cysteine, threonine, leucine).

Systems Metabolomics for Prediction of Metabolic Syndrome.

The evolution of human health is a continuum of transitions, involving multifaceted processes at multiple levels, and there is an urgent need for integrative biomarkers that can characterize and predict progression toward disease development. The objective of this work was to perform a systems metabolomics approach to predict metabolic syndrome (MetS) development. A case-control design was used within the French occupational GAZEL cohort (n = 112 males: discovery study; n = 94: replication/validation study). Our integrative strategy was to combine untargeted metabolomics with clinical, sociodemographic, and food habit parameters to describe early phenotypes and build multidimensional predictive models. Different models were built from the discriminant variables, and prediction performances were optimized either when reducing the number of metabolites used or when keeping the associated signature. We illustrated that a selected reduced metabolic profile was able to reveal subtle phenotypic differences 5 years before MetS occurrence. Moreover, resulting metabolomic markers, when combined with clinical characteristics, allowed improving the disease development prediction. The validation study showed that this predictive performance was specific to the MetS component. This work also demonstrates the interest of such an approach to discover subphenotypes that will need further characterization to be able to shift to molecular reclassification and targeting of MetS.

Time Course of Molecular and Metabolic Events in the Development of Insulin Resistance in Fructose-Fed Rats.

We aimed to determine the time-course of metabolic changes related to the early onset of insulin resistance (IR), trying to evidence breaking points preceding the appearance of the clinical IR phenotype. The model chosen was the fructose (FRU)-fed rat compared to controls fed with starch. We focused on the hepatic metabolism after 0, 5, 12, 30, or 45 days of FRU intake. The hepatic molecular metabolic changes followed indeed a multistep trajectory rather than a continuous progression. After 5 d of FRU feeding, we observed deep modifications in the hepatic metabolism, driven by the induction of lipogenic genes and important glycogen depletion. Thereafter, a steady-state period between days 12 and 30 was observed, characterized by a switch from carbohydrate to lipid utilization at the hepatic level and increased insulin levels aiming at alleviating lipid accumulation and hyperglycemia, respectively. The FRU-fed animals were only clinically IR at day 45 (altered homeostasis model assessment-estimated insulin resistance and muscle glucose transport). Furthermore, the urine metabolome revealed even earlier metabolic trajectory changes that precede the hepatic alterations. We identified several candidate metabolites linked to the tryptophan-nicotinamide metabolism and the installation of fasting hyperglycemia that suggest a role of this metabolic pathway on the development of the IR phenotype in the FRU-fed rats.

Non-enzymatic cyclic oxygenated metabolites of adrenic, docosahexaenoic, eicosapentaenoic and α-linolenic acids; bioactivities and potential use as biomarkers.

Cyclic oxygenated metabolites are formed in vivo through non-enzymatic free radical reaction of n-6 and n-3 polyunsaturated fatty acids (PUFAs) such as arachidonic (ARA C20:4 n-6), adrenic (AdA 22:4 n-6), α-linolenic (ALA 18:3 n-3), eicosapentaenoic (EPA 20:5 n-3) and docosahexaenoic (DHA 22:6 n-3) acids. These cyclic compounds are known as isoprostanes, neuroprostanes, dihomo-isoprostanes and phytoprostanes. Evidence has emerged for their use as biomarkers of oxidative stress and, more recently, the n-3PUFA-derived compounds have been shown to mediate bioactivities as secondary messengers. Accordingly, this review will focus on the cyclic oxygenated metabolites generated from AdA, ALA, EPA and DHA. This article is part of a Special Issue entitled "Oxygenated metabolism of PUFA: analysis and biological relevance".

Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study.

Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods.

Developmental programming of eNOS uncoupling and enhanced vascular oxidative stress in adult rats after transient neonatal oxygen exposure.

The authors have previously shown that neonatal hyperoxic stress leads to high blood pressure, impaired endothelium-mediated vasodilatation, and increased vascular production of superoxide anion by NAD(P)H oxidase in adulthood. However, it is unknown whether changes in nitric oxide (NO) production and/or bioinactivation prevail and whether NO synthase (NOS) is also a source of superoxide. The purpose of this study was to evaluate whether adult animals exposed to neonatal hyperoxic stress have impaired vascular NO production associated with NOS uncoupling participating to vascular superoxide production and vascular dysfunction. In adult male rats exposed to 80% oxygen from day 3 to 10 of life (H, n = 6) versus room air controls (CTRL, n = 6), vascular (aorta) NO production is decreased at baseline (CTRL: 21 ± 1 vs. H: 16 ± 2 4,5-diaminofluorescein diacetate fluorescence intensity arbitrary units; P < 0.05) and after carbachol stimulation (acetylcholine analog; CTRL: 26 ± 2 vs. H: 18±2; P < 0.05). Pretreatment with L-arginine (CTRL: 32 ± 4 vs. H: 31 ± 5) and L-sepiapterine [analog of key NOS cofactor tetrahydro-L-biopterin (BH4)] (CTRL: 30 ± 3 vs. H: 29 ± 3) normalizes NO production after carbachol. L-Sepiapterine also normalizes impaired vasodilatation to carbachol. Vascular endothelial NO synthase (eNOS) immunostaining is reduced, whereas total eNOS protein expression is increased in H (CTRL: 0.76 ± 0.08 vs. H: 1.76± 0.21; P < 0.01). The significantly higher superoxide generation (CTRL: 20 ± 2 vs. H: 28 ± 3 hydroethidine fluorescence intensity arbitrary units; P < 0.05) is prevented by pretreatment with the eNOS inhibitor N-nitro-L-arginine methyl ester (CTRL: 21 ± 4 vs. H: 22 ± 4). Taken together, the current data indicate a role for eNOS uncoupling in enhanced vascular superoxide, impaired endothelium-mediated vasodilatation, and decreased NO production in adult animals with programmed elevated blood pressure after a brief neonatal oxygen exposure.

Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics.

In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome-as in multiblock supervised modeling-and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively called "global" and "partial" effects, by percentages of explained variance in dedicated PLS regression models. These effects have been computed in two different path diagrams in a case study relative to metabolic syndrome, involving metabolomics and clinical data from an older men's cohort (NuAge). From the two effects associated with each path, the results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the metabolic syndrome exploration.

Hexapeptides from human milk prevent the induction of oxidative stress from parenteral nutrition in the newborn guinea pig.

INTRODUCTION: In preterm neonates, peroxides contaminating total parenteral nutrition (TPN) contribute to oxidative stress, which is suspected to be a strong inducer of hepatic complications related to prematurity. Recently, others reported that hexapeptides derived from human milk (HM) exerted free radical-scavenging activities in vitro. Therefore, the aim of this study was to assess the capacity of these hexapeptides to limit the generation of peroxides in TPN and to prevent TPN-induced hepatic oxidative stress. METHODS: At 3 d of life, guinea pigs were infused, through a catheter in jugular vein, with TPN containing or not peptide-A (YGYTGA) or peptide-B (ISELGW). Peroxide concentrations were measured in TPN solutions, whereas glutathione, glutathionyl-1,4-dihydroxynonenal (GS-HNE) and mRNA levels of interleukin-1 (IL-1) and tumor necrosis factor-α (TNFα) were determined in liver after 4 d of infusion. RESULTS: The addition of peptide-A to TPN allowed a reduction in peroxide contamination by half. In vivo, peptide-A or peptide-B corrected the hepatic oxidative status induced by TPN. Indeed, both peptides lowered the hepatic redox potential of glutathione and the level of GS-HNE, a marker of lipid peroxidation. As compared with animals infused with TPN without peptide, the hepatic mRNA levels of IL-1 and TNFα were lower in animals infused with TPN containing peptide-A or peptide-B. DISCUSSION: These results suggest that the addition of YGYTGA or ISELGW to TPN will reduce oxidative stress in newborns. The reduction in mRNA of two proinflammatory cytokines could be important for the incidence of hepatic complications related to TPN.

Increasing intake of long-chain n-3 PUFA enhances lipoperoxidation and modulates hepatic gene expression in a dose-dependent manner.

Long-chain (LC) n-3 PUFA have a broad range of biological properties that can be achieved at the gene expression level. This has been well described in liver, where LC n-3 PUFA modulate the expression of genes related to lipid metabolism. However, the complexity of biological pathway modulations and the nature of bioactive molecules are still under investigation. The present study aimed to investigate the dose-response effects of LC n-3 PUFA on the production of peroxidised metabolites, as potential bioactive molecules, and on global gene expression in liver. Hypercholesterolaemic rabbits received by daily oral administration (7 weeks) either oleic acid-rich oil or a mixture of oils providing 0.1, 0.5 or 1 % (groups 1, 2 and 3 respectively) of energy as DHA. Levels of specific peroxidised metabolites, namely 4-hydroxyhexenal (4-HHE)-protein adducts, issued from LC n-3 PUFA were measured by GC/MS/MS in liver in parallel to transcription profiling. The intake of LC n-3 PUFA increased, in a dose-dependent manner, the hepatic production of 4-HHE. At the highest dose, LC n-3 PUFA provoked an accumulation of TAG in liver, which can be directly linked to increased mRNA levels of lipoprotein hepatic receptors (LDL-receptor and VLDL-receptor). In groups 1 and 2, the mRNA levels of microsomal TAG transfer protein decreased, suggesting a possible new mechanism to reduce VLDL secretion. These modulations of genes related to lipoprotein metabolism were independent of PPARα signalling but were probably linked to the activation of the farnesol X receptor pathway by LC n-3 PUFA and/or their metabolites such as HHE.

Glucose-induced insulin secretion: nutritional prevention and novel avenues for therapy.

Insulin resistance, the most important pathophysiological feature in various prediabetic and diabetic states is partly related to impaired glucose-stimulated insulin secretion and insulin modulation of pancreatic beta cell with peripheral impaired insulin response. This chapter concentrates on aspects of potential new strategies in the treatment of the disease going from nutritional preventive approaches towards currently utilized drugs for treatment that target the pancreatic beta cells with potentiation of glucose-stimulated insulin secretion.

The biological relevance of direct antioxidant effects of polyphenols for cardiovascular health in humans is not established.

Human studies provide evidence for beneficial effects of polyphenol-rich foods on cardiovascular health. The antioxidant activity of polyphenols potentially explains these effects, but is the antioxidant activity a reliable predictor for these effects? An International Life Sciences Institute Europe working group addressed this question and explored the potential of antioxidant claims for polyphenols in relation to cardiovascular health by using the so-called Process for the Assessment of Scientific Support for Claims on Foods project criteria. In this process, analytical aspects of polyphenols, their occurrence in foods, dietary intake, and bioavailability were reviewed. Human studies on polyphenols and cardiovascular health were reviewed together with methods for biomarkers of oxidative damage and total antioxidant capacity (TAC). In retrospective studies, F2-isoprostanes and oxidized LDL, the most reliable biomarkers of lipid peroxidation, and measures for TAC showed the expected differences between cardiovascular disease patients and healthy controls, but prospective studies are lacking, and a causal relationship between these biomarkers and cardiovascular health could not be established. Therefore, the physiological relevance of a potential change in these biomarkers is unclear. We found limited evidence that some types of polyphenol-rich products modify these biomarkers in humans. A direct antioxidant effect of polyphenols in vivo is questionable, however, because concentrations in blood are low compared with other antioxidants and extensive metabolism following ingestion lowers their antioxidant activity. Therefore, the biological relevance of direct antioxidant effects of polyphenols for cardiovascular health could not be established. Overall, although some polyphenol-rich foods exert beneficial effects on some biomarkers of cardiovascular health, there is no evidence that this is caused by improvements in antioxidant function biomarkers (oxidative damage or antioxidant capacity).

Metaproteomics Approach and Pathway Modulation in Obesity and Diabetes: A Narrative Review.

Low-grade inflammatory diseases revealed metabolic perturbations that have been linked to various phenotypes, including gut microbiota dysbiosis. In the last decade, metaproteomics has been used to investigate protein composition profiles at specific steps and in specific healthy/pathologic conditions. We applied a rigorous protocol that relied on PRISMA guidelines and filtering criteria to obtain an exhaustive study selection that finally resulted in a group of 10 studies, based on metaproteomics and that aim at investigating obesity and diabetes. This batch of studies was used to discuss specific microbial and human metaproteome alterations and metabolic patterns in subjects affected by diabetes (T1D and T2D) and obesity. We provided the main up- and down-regulated protein patterns in the inspected pathologies. Despite the available results, the evident paucity of metaproteomic data is to be considered as a limiting factor in drawing objective considerations. To date, ad hoc prepared metaproteomic databases collecting pathologic data and related metadata, together with standardized analysis protocols, are required to increase our knowledge on these widespread pathologies.

Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly.

Aging is accompanied by physiological changes affecting body composition and functionality, including accumulation of fat mass at the expense of muscle mass, with effects upon morbidity and quality of life. The gut microbiome has recently emerged as a key environmental modifier of human health that can modulate healthy aging and possibly longevity. However, its associations with adiposity in old age are still poorly understood. Here we profiled the gut microbiota in a well-characterized cohort of 201 Italian elderly subjects from the NU-AGE study, by 16S rRNA amplicon sequencing. We then tested for association with body composition from dual-energy X-ray absorptiometry (DXA), with a focus on visceral and subcutaneous adipose tissue. Dietary patterns, serum metabolome and other health-related parameters were also assessed. This study identified distinct compositional structures of the elderly gut microbiota associated with DXA parameters, diet, metabolic profiles and cardio-metabolic risk factors.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men.

BACKGROUND: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. METHODS: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. FINDINGS: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). INTERPRETATION: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. FUNDING: The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.

An Early Stage Researcher's Primer on Systems Medicine Terminology.

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.

Metabolomic and Lipidomic Signatures of Metabolic Syndrome and its Physiological Components in Adults: A Systematic Review.

The aim of this work was to conduct a systematic review of human studies on metabolite/lipid biomarkers of metabolic syndrome (MetS) and its components, and provide recommendations for future studies. The search was performed in MEDLINE, EMBASE, EMB Review, CINHAL Complete, PubMed, and on grey literature, for population studies identifying MetS biomarkers from metabolomics/lipidomics. Extracted data included population, design, number of subjects, sex/gender, clinical characteristics and main outcome. Data were collected regarding biological samples, analytical methods, and statistics. Metabolites were compiled by biochemical families including listings of their significant modulations. Finally, results from the different studies were compared. The search yielded 31 eligible studies (2005-2019). A first category of articles identified prevalent and incident MetS biomarkers using mainly targeted metabolomics. Even though the population characteristics were quite homogeneous, results were difficult to compare in terms of modulated metabolites because of the lack of methodological standardization. A second category, focusing on MetS components, allowed comparing more than 300 metabolites, mainly associated with the glycemic component. Finally, this review included also publications studying type 2 diabetes as a whole set of metabolic risks, raising the interest of reporting metabolomics/lipidomics signatures to reflect the metabolic phenotypic spectrum in systems approaches.