Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies

The Pediatric Obesity Microbiome and Metabolism Study (POMMS): Methods, Baseline Data, and Early Insights

OBJECTIVE

The purpose of this study was to establish a biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification.

METHODS

A total of 223 adolescents aged 10 to 18 years with BMI ≥95th percentile were enrolled, along with 71 healthy weight participants. Clinical data, fasting serum, and fecal samples were collected at repeated intervals over 6 months. Herein, the study design, data collection methods, and interim analysis-including targeted serum metabolite measurements and fecal 16S ribosomal RNA gene amplicon sequencing among adolescents with obesity (n = 27) and healthy weight controls (n = 27)-are presented.

RESULTS

Adolescents with obesity have higher serum alanine aminotransferase, C-reactive protein, and glycated hemoglobin, and they have lower high-density lipoprotein cholesterol when compared with healthy weight controls. Metabolomics revealed differences in branched-chain amino acid-related metabolites. Also observed was a differential abundance of specific microbial taxa and lower species diversity among adolescents with obesity when compared with the healthy weight group.

CONCLUSIONS

The Pediatric Metabolism and Microbiome Study (POMMS) biorepository is available as a shared resource. Early findings suggest evidence of a metabolic signature of obesity unique to adolescents, along with confirmation of previously reported findings that describe metabolic and microbiome markers of obesity.

Obesity-Related Changes in Human Plasma Lipidome Determined by the Lipidyzer Platform

Obesity is an increasing public health concern both in the developed and developing countries. Previous studies have demonstrated that considerable alterations in lipid metabolism and consequently marked changes in lipid profile are associated with the onset and progression of obesity-related complications. To characterize the full spectrum of obesity-induced changes in lipid metabolism, direct infusion tandem mass spectrometry analysis is the most promising approach. To better understand which of the many lipid species are the most strongly associated with obesity, the aim of our work was to measure and profile plasma lipids in normal (n = 57), overweight (n = 31), and obese (n = 48) individuals randomly selected from samples of Hungarian general and Roma populations by using the targeted quantitative lipidomics platform, the Lipidyzer. Principal component and stepwise regression analyses were used to identify the most significant clusters and species of lipids by increasing body mass index (BMI). From the 18 clusters identified four key lipid species (PE P-16:0/20:3, TG 20:4_33:1, TG 22:6_36:4, TG 18:3_33:0) showed a strong significant positive and three others (Hex-Cer 18:1;O2/22:0, LPC 18:2, PC 18:1_18:1) significant negative association with BMI. Compared to individual lipid species alone, the lipid species ratio (LSR) we introduced showed an extremely strong, at least 9 orders of magnitude stronger, association with BMI. The LSR can be used as a sensitive and predictive indicator to monitor obesity-related alterations in human plasma and control the effectiveness of treatment of obesity associated non-communicable diseases.

Obesity Connected Metabolic Changes in Type 2 Diabetic Patients Treated With Metformin

Metformin is widely used in the treatment of Type 2 Diabetes Mellitus (T2DM). However, it is known to have beneficial effects in many other conditions, including obesity and cancer. In this study, we aimed to investigate the metabolic effect of metformin in T2DM and its impact on obesity. A mass spectrometry (MS)-based metabolomics approach was used to analyze samples from two cohorts, including healthy lean and obese control, and lean as well as obese T2DM patients on metformin regimen in the last 6 months. The results show a clear group separation and sample clustering between the study groups due to both T2DM and metformin administration. Seventy-one metabolites were dysregulated in diabetic obese patients (30 up-regulated and 41 down-regulated), and their levels were unchanged with metformin administration. However, 30 metabolites were dysregulated (21 were up-regulated and 9 were down-regulated) and then restored to obese control levels by metformin administration in obese diabetic patients. Furthermore, in obese diabetic patients, the level of 10 metabolites was dysregulated only after metformin administration. Most of these dysregulated metabolites were dipeptides, aliphatic amino acids, nucleic acid derivatives, and urea cycle components. The metabolic pattern of 62 metabolites was persistent, and their levels were affected by neither T2DM nor metformin in obesity. Interestingly, 9 metabolites were significantly dysregulated between lean and obese cohorts due to T2DM and metformin regardless of the obesity status. These include arginine, citrulline, guanidoacetic acid, proline, alanine, taurine, 5-hydroxyindoleacetic acid, and 5-hydroxymethyluracil. Understanding the metabolic alterations taking place upon metformin treatment would shed light on possible molecular targets of metformin, especially in conditions like T2DM and obesity.

Maternal and Cord Blood Metabolite Associations with Gestational Weight Gain and Pregnancy Health Outcomes

Pre-pregnancy obesity and excessive gestational weight gain (GWG) are risk factors for future maternal and childhood obesity. Maternal obesity is potentially communicated to the fetus in part by the metabolome, altering the child's metabolic program in early development. Fasting maternal blood samples from 37 singleton pregnancies at 25-28 weeks of gestation were obtained from mothers with pre-pregnancy body mass indexes (BMIs) between 18 and 40 kg/m². Various health measures including GWG, diet, and physical activity were also assessed. At term (37-42 weeks), a venous umbilical cord sample was obtained. Serum metabolomic profiles were measured using nuclear magnetic resonance spectroscopy as well as a gut and metabolic hormone panel. Maternal and cord serum metabolites were tested for associations with pre-pregnancy BMI, GWG, health outcomes, and gut and metabolic hormones. While cord blood metabolites showed no significant correlation to maternal obesity status or other measured health outcomes, maternal serum metabolites showed distinct profiles for lean, overweight, and obese women. Additionally, four serum metabolites, namely, glutamate, lysine, pyruvate, and valine, allowed prediction of excessive GWG when pre-pregnancy BMI was controlled. Metabolic biomarkers predictive of GWG are reported and, if validated, could aid in the guidance of prenatal weight management plans as the majority of pregnancy weight gain occurs in the third trimester.

Metabolically healthy obesity is associated with longitudinal changes in high-density lipoprotein cholesterol in Chinese adults

PURPOSE

Whether metabolically healthy obesity (MHO) is associated with longitudinal changes in high-density lipoprotein cholesterol (HDL-C) remains unclear.

METHODS

MHO was defined as participants with overweight and obesity (BMI ≥ 24.0 kg/m², n = 2921), free of history of metabolic diseases, and without abnormalities of blood pressure, fasting blood glucose, hemoglobin A1c, lipid profile, carotid artery and liver ultrasonographic findings at baseline. Metabolically healthy normal weight (MHN) was defined as participants with normal weight (BMI < 24.0 kg/m², n = 9578) and without above-mentioned abnormalities. HDL-C, fasting blood glucose, hemoglobin A1c, and blood pressure were assessed annually. Glucose abnormality was considered if either FBG ≥ 5.6 mmol/L or HbA1c ≥ 5.7%; while, high blood pressure (HBP) was considered if either systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 80 mmHg during 5 years of follow-up.

RESULTS

Compared with the MHN group, the adjusted mean difference in HDL-C change rate was - 0.005 mmol/L per year [95% confidence interval (CI) - 0.007, - 0.003] for MHO after adjustment for a series of potential confounders. Furthermore, transiting to abnormality of blood glucose, but not high blood pressure, was associated with lower cumulative average of HDL-C in MHN group, compared with those remained in metabolically healthy status.

CONCLUSIONS

MHO and transiting from metabolically healthy to abnormality of blood glucose were associated with HDL-C in Chinese adults.

LEVEL OF EVIDENCE

III, cohort study.

Serum Metabolic Profiles of Chinese Women With Perimenopausal Obesity Explored by the Untargeted Metabolomics Approach

By far, no study has focused on observing the metabolomic profiles in perimenopause-related obesity. This study attempted to identify the metabolic characteristics of subjects with perimenopause obesity (PO). Thirty-nine perimenopausal Chinese women, 21 with PO and 18 without obesity (PN), were recruited in this study. A conventional ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry (UHPLC-QTOF/MS) followed by principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used as untargeted metabolomics approaches to explore the serum metabolic profiles. Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst were used to identify the related metabolic pathways. A total of 46 differential metabolites, along with seven metabolic pathways relevant to PO were identified, which belonged to lipid, amino acids, carbohydrates, and organic acids. As for amino acids, we found a significant increase in l-arginine and d-ornithine in the positive ion (POS) mode and l-leucine, l-valine, l-tyrosine, and N-acetyl-l-tyrosine in the negative ion (NEG) mode and a significant decrease in l-proline in the POS mode of the PO group. We also found phosphatidylcholine (PC) (16:0/16:0), palmitic acid, and myristic acid, which are associated with the significant upregulation of lipid metabolism. Moreover, the serum indole lactic acid and indoleacetic acid were upregulated in the NEG mode. With respect to the metabolic pathways, the d-arginine and d-ornithine metabolisms and the arginine and proline metabolism pathways in POS mode were the most dominant PO-related pathways. The changes of metabolisms of lipid, amino acids, and indoleacetic acid provided a pathophysiological scenario for Chinese women with PO. We believe that the findings of this study are helpful for clinicians to take measures to prevent the women with PO from developing severe incurable obesity-related complications, such as cardiovascular disease and stroke.

Metabolomic Signature Between Metabolically Healthy Overweight/Obese and Metabolically Unhealthy Overweight/Obese: A Systematic Review

The clinical manifestations of overweight/obesity are heterogeneous and complex. In contrast to metabolically unhealthy overweight/obese (MUO), a particular sub-group of obese patients who are considered as metabolically healthy overweight/obese (MHO), display favorable metabolic profiles characterized by high levels of insulin sensitivity, normal blood pressure, as well as favorable lipid, inflammation, hormone, liver enzyme, and immune profiles. While only a few available studies focused on the metabolic files underlying the obese phenotypes, the current review aimed to perform a systematic review of available studies focusing on describing the metabolomic signature between MUO and MHO. We did the systematic search for literature on MEDLINE (PubMed), the Cochrane Library, EMBASE, and searched for the references of relevant manuscripts from inception to 29 May 2020. After critical selection, 20 studies were eligible for this systematic review and evaluated by using QUADOMICS for quality assessment. Eventually, 12 of 20 studies were classified as "high quality". Branched-chain amino acids (isoleucine, leucine, and valine), aromatic amino acids (phenylalanine and tyrosine), lipids (palmitic acid, palmitoleic acid, oleic acid, eicosapentaenoic acid, and docosahexaenoic acid), and acylcarnitines (propionyl carnitine) levels might be elevated in MUO. The current results suggested that MHO showed a favorable trend in the overall metabolic signature. More longitudinal studies are needed to elaborate deeply on the metabolic pathway and the relationship between metabolic patterns and the occurrence of the disease.

Intergenerational Metabolomic Analysis of Mothers with a History of Gestational Diabetes Mellitus and Their Offspring

Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson's correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman's correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.

In Situ Mass Spectrometry Diagnostics of Impaired Glucose Tolerance Using Label-Free Metabolomic Signature

In metabolomics, mass spectrometry is used to detect a large number of low-molecular substances in a single analysis. Such a capacity could have direct application in disease diagnostics. However, it is challenging because of the analysis complexity, and the search for a way to simplify it while maintaining the diagnostic capability is an urgent task. It has been proposed to use the metabolomic signature without complex data processing (mass peak detection, alignment, normalization, and identification of substances, as well as any complex statistical analysis) to make the analysis more simple and rapid.

METHODS

A label-free approach was implemented in the metabolomic signature, which makes the measurement of the actual or conditional concentrations unnecessary, uses only mass peak relations, and minimizes mass spectra processing. The approach was tested on the diagnosis of impaired glucose tolerance (IGT).

RESULTS

The label-free metabolic signature demonstrated a diagnostic accuracy for IGT equal to 88% (specificity 85%, sensitivity 90%, and area under receiver operating characteristic curve (AUC) of 0.91), which is considered to be a good quality for diagnostics.

CONCLUSIONS

It is possible to compile label-free signatures for diseases that allow for diagnosing the disease in situ, i.e., right at the mass spectrometer without complex data processing. This achievement makes all mass spectrometers potentially versatile diagnostic devices and accelerates the introduction of metabolomics into medicine.

Higher donor body mass index is associated with increased hemolysis of red blood cells at 42-days of storage: A retrospective analysis of routine quality control data

BACKGROUND

For reasons unclear, some stored red blood cells (RBCs) have low hemolysis, while others have high hemolysis, which impacts quality consistency. To identify variables that influence hemolysis, routine quality control (QC) data for 42-days-stored RBCs with corresponding donor information were analyzed.

STUDY DESIGN AND METHODS

RBC QC and donor data were obtained from a national blood supplier. Regression models and analyses were performed on total cohort stratified by donor sex and by high hemolysis (≥90th percentile) vs control (<90th percentile) samples, including matching.

RESULTS

Data included 1734 leukoreduced RBCs (822 female, 912 male), processed by buffy coat-poor or whole blood filtration methods. Male RBCs had larger volume, hemoglobin content, and higher hemolysis than female RBCs (median hemolysis, 0.24% vs 0.21%; all P < .0001). Multivariable regression identified increased body mass index (BMI) and RBC variables were associated with higher hemolysis (P < .0001), along with older female age and buffy coat-poor processing method (P < .002). Logistic regression models comparing the high and control hemolysis subsets, matched for RBC component variables and processing method, identified overweight-obese BMI (>27 kg/m² ) in males remained the single donor-related variable associated with higher hemolysis (P < .0001); odds ratio, 3 (95% confidence interval [CI], 1.3-6.7), increasing to 4 (95% CI, 1.8-8.6) for obese males (BMI > 30 kg/m² ). Female donor obesity and older age trended toward higher hemolysis.

CONCLUSION

Donor BMI, sex, and female age influence the level of hemolysis of 42-days-stored RBCs. Other factors, not identified in this study, also influence the level of hemolysis.

Use of Metabolomic Profiling to Understand Variability in Adiposity Changes Following an Intentional Weight Loss Intervention in Older Adults

Inter-individual response to dietary interventions remains a major challenge to successful weight loss among older adults. This study applied metabolomics technology to identify small molecule signatures associated with a loss of fat mass and overall weight in a cohort of older adults on a nutritionally complete, high-protein diet. A total of 102 unique metabolites were measured using liquid chromatography-mass spectrometry (LC-MS) for 38 adults aged 65-80 years randomized to dietary intervention and 36 controls. Metabolite values were analyzed in both baseline plasma samples and samples collected following the six-month dietary intervention to consider both metabolites that could predict the response to diet and those that changed in response to diet or weight loss.Eight metabolites changed over the intervention at a nominally significant level: D-pantothenic acid, L-methionine, nicotinate, aniline, melatonin, deoxycarnitine, 6-deoxy-L-galactose, and 10-hydroxydecanoate. Within the intervention group, there was broad variation in the achieved weight-loss and dual-energy x-ray absorptiometry (DXA)-defined changes in total fat and visceral adipose tissue (VAT) mass. Change in the VAT mass was significantly associated with the baseline abundance of α-aminoadipate (p = 0.0007) and an additional mass spectrometry peak that may represent D-fructose, myo-inositol, mannose, α-D-glucose, allose, D-galactose, D-tagatose, or L-sorbose (p = 0.0001). This hypothesis-generating study reflects the potential of metabolomic biomarkers for the development of personalized dietary interventions.

Impact of Extreme Obesity and Diet-Induced Weight Loss on the Fecal Metabolome and Gut Microbiota

SCOPE

A limited number of human studies have characterized fecal microbiota and metabolome in extreme obesity and after diet-induced weight loss.

METHODS AND RESULTS

Fecal samples from normal-weight and extremely obese adults and from obese participants before and after moderate diet-induced weight loss are evaluated for their interaction with the intestinal adenocarcinoma cell line HT29 using an impedance-based in vitro model, which reveals variations in the interaction between the gut microbiota and host linked to obesity status. Microbiota composition, short chain fatty acids, and other intestinal metabolites are further analyzed to assess the interplay among diet, gut microbiota, and host in extreme obesity. Microbiota profiles are distinct between normal-weight and obese participants and are accompanied by fecal signatures in the metabolism of biliary compounds and catecholamines. Moderate diet-induced weight loss promotes shifts in the gut microbiota, and the primary fecal metabolomics features are associated with diet and the gut-liver and gut-brain axes.

CONCLUSIONS

Analyses of the fecal microbiota and metabolome enable assessment of the impact of diet on gut microbiota composition and activity, supporting the potential use of certain fecal metabolites or members of the gut microbiota as biomarkers for the efficacy of weight loss in extreme obesity.

Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, genome-scale models (GEMs) are focused upon as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to metabolism, transcription, and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. A variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics are reviewed. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. The authors find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, continued synthesis of valuable knowledge, through the integration of omic data with GEMs, are expected.

Omics Biomarkers in Obesity: Novel Etiological Insights and Targets for Precision Prevention

PURPOSE OF REVIEW

Omics-based technologies were suggested to provide an advanced understanding of obesity etiology and its metabolic consequences. This review highlights the recent developments in "omics"-based research aimed to identify obesity-related biomarkers.

RECENT FINDINGS

Recent advances in obesity and metabolism research increasingly rely on new technologies to identify mechanisms in the development of obesity using various "omics" platforms. Genetic and epigenetic biomarkers that translate into changes in transcriptome, proteome, and metabolome could serve as targets for obesity prevention. Despite a number of promising candidate biomarkers, there is an increased demand for larger prospective cohort studies to validate findings and determine biomarker reproducibility before they can find applications in primary care and public health. "Omics" biomarkers have advanced our knowledge on the etiology of obesity and its links with chronic diseases. They bring substantial promise in identifying effective public health strategies that pave the way towards patient stratification and precision prevention.

Validation and Application of a Derivatization-Free RP-HPLC-DAD Method for the Determination of Low Molecular Weight Salivary Metabolites

Saliva is an interesting, non-conventional, valuable diagnostic fluid. It can be collected using standardized sampling device; thus, its sampling is easy and non-invasive, it contains a variety of organic metabolites that reflect blood composition. The aim of this study was to validate a user-friendly method for the simultaneous determination of low molecular weight metabolites in saliva. We have optimized and validated a high throughput, direct, low-cost reversed phase liquid chromatographic method with diode array detection method without any pre- or post-column derivatization. We indexed salivary biomolecules in 35 whole non-stimulated saliva samples collected in 8 individuals in different days, including organic acids and amino acids and other carbonyl compounds. Among these, 16 whole saliva samples were collected by a single individual over three weeks before, during and after treatment with antibiotic in order to investigate the dynamics of metabolites. The concentrations of the metabolites were compared with the literature data. The multianalyte method here proposed requires a minimal sample handling and it is cost-effectiveness as it makes possible to analyze a high number of samples with basic instrumentation. The identification and quantitation of salivary metabolites may allow the definition of potential biomarkers for non-invasive "personal monitoring" during drug treatments, work out, or life habits over time.

Associations of BMI and Body Fat with Urine Metabolome in Adolescents Are Sex-Specific: A Cross-Sectional Study

Epidemiologic studies examining the relationship between body composition and the urine metabolome may improve our understanding of the role of metabolic dysregulation in body composition-related health conditions. Previous studies, mostly in adult populations, have focused on a single measure of body composition, body mass index (BMI), and sex-specific associations are rarely explored. We investigate sex-specific associations of two measures of body composition—BMI and body fat (BF)—with the urine metabolome in adolescents. In 369 participants (age 16–18, 49% female) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, we examined sex-specific associations of these two measures of body composition, BMI and BF, and 1407 (467 unknown) 24 h urine metabolites analyzed by untargeted metabolomics cross-sectionally. Missing metabolites were imputed. We related metabolites (dependent variable) to BMI and BF (independent variable) separately using linear regression. The models were additionally adjusted for covariates. We found 10 metabolites associated with both BMI and BF. We additionally found 11 metabolites associated with only BF, and nine with only BMI. None of these associations was in females. We observed a strong sexual dimorphism in the relationship between body composition and the urine metabolome.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.

Leptin-Mediated Changes in the Human Metabolome

CONTEXT

While severe obesity due to congenital leptin deficiency is rare, studies in patients before and after treatment with leptin can provide unique insights into the role that leptin plays in metabolic and endocrine function.

OBJECTIVE

The aim of this study was to characterize changes in peripheral metabolism in people with congenital leptin deficiency undergoing leptin replacement therapy, and to investigate the extent to which these changes are explained by reduced caloric intake.

DESIGN

Ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) was used to measure 661 metabolites in 6 severely obese people with congenital leptin deficiency before, and within 1 month after, treatment with recombinant leptin. Data were analyzed using unsupervised and hypothesis-driven computational approaches and compared with data from a study of acute caloric restriction in healthy volunteers.

RESULTS

Leptin replacement was associated with class-wide increased levels of fatty acids and acylcarnitines and decreased phospholipids, consistent with enhanced lipolysis and fatty acid oxidation. Primary and secondary bile acids increased after leptin treatment. Comparable changes were observed after acute caloric restriction. Branched-chain amino acids and steroid metabolites decreased after leptin, but not after acute caloric restriction. Individuals with severe obesity due to leptin deficiency and other genetic obesity syndromes shared a metabolomic signature associated with increased BMI.

CONCLUSION

Leptin replacement was associated with changes in lipolysis and substrate utilization that were consistent with negative energy balance. However, leptin's effects on branched-chain amino acids and steroid metabolites were independent of reduced caloric intake and require further exploration.

Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

Hepatic fat is a stronger correlate of key clinical and molecular abnormalities than visceral and abdominal subcutaneous fat in youth

INTRODUCTION

Body fat distribution is strongly associated with cardiometabolic disease (CMD), but the relative importance of hepatic fat as an underlying driver remains unclear. Here, we applied a systems biology approach to compare the clinical and molecular subnetworks that correlate with hepatic fat, visceral fat, and abdominal subcutaneous fat distribution.

RESEARCH DESIGN AND METHODS

This was a cross-sectional sub-study of 283 children/adolescents (7-19 years) from the Yale Pediatric NAFLD Cohort. Untargeted, high-resolution metabolomics (HRM) was performed on plasma and combined with existing clinical variables including hepatic and abdominal fat measured by MRI. Integrative network analysis was coupled with pathway enrichment analysis and multivariable linear regression (MLR) to examine which metabolites and clinical variables associated with each fat depot.

RESULTS

The data divided into four communities of correlated variables (|r|>0.15, p<0.05) after integrative network analysis. In the largest community, hepatic fat was associated with eight clinical biomarkers, including measures of insulin resistance and dyslipidemia, and 878 metabolite features that were enriched predominantly in amino acid (AA) and lipid pathways in pathway enrichment analysis (p<0.05). Key metabolites associated with hepatic fat included branched-chain AAs (valine and isoleucine/leucine), aromatic AAs (tyrosine and tryptophan), serine, glycine, alanine, and pyruvate, as well as several acylcarnitines and glycerophospholipids (all q<0.05 in MLR adjusted for covariates). The other communities detected in integrative network analysis consisted of abdominal visceral, superficial subcutaneous, and deep subcutaneous fats, but no clinical variables, fewer metabolite features (280, 312, and 74, respectively), and limited findings in pathway analysis.

CONCLUSIONS

These data-driven findings show a stronger association of hepatic fat with key CMD risk factors compared with abdominal fats. The molecular network identified using HRM that associated with hepatic fat provides insight into potential mechanisms underlying the hepatic fat-insulin resistance interface in youth.

Quality Assessment of Online Information on Body Contouring Surgery in Postbariatric Patient

BACKGROUND

Nowadays, we have to face the fact that the Web represents one of the most important sources of information for patients. Postbariatric patients in particular are usually very motivated, and they are enthusiastic users of the Web as a source of information on the different types of surgery they could undergo after their weight loss in order to reshape and remodel their body thus regaining physical and functional wellness and dignity. The aim of the study was to assess information on the four most commonly performed postbariatric procedures worldwide, tummy tuck, breast, arm and thigh lift, with the same scale.

METHODS

Google and Yahoo have been probed for the keywords "Post bariatric Mastopexy OR breast lift" and "Post bariatric abdominoplasty OR tummy tuck" and "Post bariatric brachioplasty OR arm lift" and "post bariatric thigh lift". The first 50 hits were included, and the quality of information was evaluated with the expanded EQIP scale.

RESULTS

There was a critical lack of information about qualitative risks and side-effect description, treatment of potential complications, alert signs for the patient and precautions that the patient may take. Moreover, there was poor information about the sequence of the medical procedure, quantitative benefits and risks and quality of life issues after the procedure, and often, there were no other sources of information.

CONCLUSIONS

Due to the poor and not reliable information offered by the Web, health professionals should seek for a good communication practice with their patients.

LEVEL OF EVIDENCE V

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

Mapping Metabolite and ICD-10 Associations

The search for novel metabolic biomarkers is intense but has had limited practical outcomes for medicine. Part of the problem is that we lack knowledge of how different comorbidities influence biomarkers’ performance. In this study, 49 metabolites were measured by targeted LC/MS protocols in the serum of 1011 volunteers. Their performance as potential biomarkers was evaluated by the area under the curve of receiver operator characteristics (AUC-ROC) for 105 diagnosis codes or code groups from the 10th revision of the international classification of diseases (ICD-10). Additionally, the interferences between diagnosis codes were investigated. The highest AUC-ROC values for individual metabolites and ICD-10 code combinations reached a moderate (0.7) range. Most metabolites that were found to be potential markers remained so independently of the control group composition or comorbidities. The precise value of the AUC-ROC, however, could vary depending on the comorbidities. Moreover, networks of metabolite and disease associations were built in order to map diseases, which may interfere with metabolic biomarker research on other diseases.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved the treatment of RA, patients often inquire about dietary interventions to improve RA symptoms, as they perceive pain and/or swelling after the consumption or avoidance of certain foods. There is evidence that some foods have pro- or anti-inflammatory effects mediated by diet-related metabolites. In addition, recent literature has shown a link between diet-related metabolites and microbiome changes, since the gut microbiome is involved in the metabolism of some dietary ingredients. But diet and the gut microbiome are not the only factors linked to circulating pro- and anti-inflammatory metabolites. Other factors including smoking, associated comorbidities, and therapeutic drugs might also modify the circulating metabolomic profile and play a role in RA pathogenesis. This article summarizes what is known about circulating pro- and anti-inflammatory metabolites in RA. It also emphasizes factors that might be involved in their circulating concentrations and diet-related metabolites with a beneficial effect in RA.

A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R Study

INTRODUCTION

Adverse exposures in early life may predispose children to cardio-metabolic disease in later life. Metabolomics may serve as a valuable tool to disentangle the metabolic adaptations and mechanisms that potentially underlie these associations.

OBJECTIVES

To describe the acquisition, processing and structure of the metabolomics data available in a population-based prospective cohort from early pregnancy onwards and to examine the relationships between metabolite profiles of pregnant women and their children at birth and in childhood.

METHODS

In a subset of 994 mothers-child pairs from a prospective population-based cohort study among pregnant women and their children from Rotterdam, the Netherlands, we used LC-MS/MS to determine concentrations of amino acids, non-esterified fatty acids, phospholipids and carnitines in blood serum collected in early pregnancy, at birth (cord blood), and at child's age 10 years.

RESULTS

Concentrations of diacyl-phosphatidylcholines, acyl-alkyl-phosphatidylcholines, alkyl-lysophosphatidylcholines and sphingomyelines were the highest in early pregnancy, concentrations of amino acids and non-esterified fatty acids were the highest at birth and concentrations of alkyl-lysophosphatidylcholines, free carnitine and acyl-carnitines were the highest at age 10 years. Correlations of individual metabolites between pregnant women and their children at birth and at the age of 10 years were low (range between r = - 0.10 and r = 0.35).

CONCLUSION

Our results suggest that unique metabolic profiles are present among pregnant women, newborns and school aged children, with limited intergenerational correlations between metabolite profiles. These data will form a valuable resource to address the early metabolic origins of cardio-metabolic disease.

Effects of resveratrol and its derivative pterostilbene on brown adipose tissue thermogenic activation and on white adipose tissue browning process

The main function of brown adipose tissue (BAT) is thermogenesis, a process mediated by uncoupling protein 1 (UCP1), which is located in the inner mitochondrial membrane and acts uncoupling oxidative phosphorylation from ATP production, thereby dissipating energy as heat. White adipose tissue can also express UCP1 positive cells due to a process known as browning. This phenomenon could also increase the thermogenic effect in the classical brown adipose depots. BAT thermogenesis depends, among other factors on both, nutritional conditions and food availability. Indeed, some studies have found that BAT recruitment and function are enhanced by some food components. The present study focuses on the effects of resveratrol and pterostilbene, two phenolic compounds belonging to the stilbene group, on BAT thermogenic activation and white adipose tissue browning process. The reported studies, carried out in cell cultures and animal models, show that both resveratrol and pterostilbene induce thermogenic capacity in interscapular BAT by increasing mitochondriogenesis, as well as enhancing fatty acid oxidation and glucose disposal. In addition, resveratrol seems to promote browning by activating peroxisome proliferator-activated receptor (PPAR), while the lack of changes in mitochondrial biogenesis suggests that probably the browning process occurs by direct resveratrol-mediated upregulation of ucp1 mRNA expression.

Metabolic signature of obesity-associated insulin resistance and type 2 diabetes

Background

Obesity is associated with an increased risk of insulin resistance and type 2 diabetes mellitus (T2DM). However, some obese individuals maintain their insulin sensitivity and exhibit a lower risk of associated comorbidities. The underlying metabolic pathways differentiating obese insulin sensitive (OIS) and obese insulin resistant (OIR) individuals remain unclear.

Methods

In this study, 107 subjects underwent untargeted metabolomics of serum samples using the Metabolon platform. Thirty-two subjects were lean controls whilst 75 subjects were obese including 20 OIS, 41 OIR, and 14 T2DM individuals.

Results

Our results showed that phospholipid metabolites including choline, glycerophosphoethanolamine and glycerophosphorylcholine were significantly altered from OIS when compared with OIR and T2DM individuals. Furthermore, our data confirmed changes in metabolic markers of liver disease, vascular disease and T2DM, such as 3-hydroxymyristate, dimethylarginine and 1,5-anhydroglucitol, respectively.

Conclusion

This pilot data has identified phospholipid metabolites as potential novel biomarkers of obesity-associated insulin sensitivity and confirmed the association of known metabolites with increased risk of obesity-associated insulin resistance, with possible diagnostic and therapeutic applications. Further studies are warranted to confirm these associations in prospective cohorts and to investigate their functionality.

Alterations Of Glycerophospholipid And Fatty Acyl Metabolism In Multiple Brain Regions Of Schizophrenia Microbiota Recipient Mice

BACKGROUND

Schizophrenia is a debilitating psychiatric disorder characterized by molecular and anatomical abnormalities of multiple brain regions. Our recent study showed that dysbiosis of the gut microbiota contributes to the onset of schizophrenia-relevant behaviors, but the underlying mechanisms remain largely unknown.

PURPOSE

This study aimed to investigate how gut microbiota shapes metabolic signatures in multiple brain regions of schizophrenia microbiota recipient mice.

METHODS

Gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) were used to compare the metabolic signatures in the cortex, cerebellum and striatum of schizophrenia microbiota and healthy microbiota recipient mice. Enrichment analysis was further conducted to uncover the crucial metabolic pathways related to schizophrenia-relevant behaviors.

RESULTS

We found that the metabolic phenotypes of these three regions were substantially different in schizophrenia microbiota recipient mice from those in healthy microbiota recipient mice. In total, we identified 499 differential metabolites that could discriminate the two groups in the three brain regions. These differential metabolites were mainly involved in glycerophospholipid and fatty acyl metabolism. Moreover, we found four of fatty acyl metabolites that were consistently altered in the three brain regions.

CONCLUSION

Taken together, our study suggests that alterations of glycerophospholipid and fatty acyl metabolism are implicated in the onset of schizophrenia-relevant behaviors, which may provide a new understanding of the etiology of schizophrenia.