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

Initial military training modulates serum fatty acid and amino acid metabolites

Initial military training (IMT) results in increased fat‐free mass (FFM) and decreased fat mass (FM). The underlying metabolic adaptations facilitating changes in body composition during IMT are unknown. The objective of this study was to assess changes in body composition and the serum metabolome during 22‐week US Army IMT. Fifty‐four volunteers (mean ± SD; 22 ± 3 year; 24.6 ± 3.7 kg/m²) completed this longitudinal study. Body composition measurements (InBody 770) and blood samples were collected under fasting, rested conditions PRE and POST IMT. Global metabolite profiling was performed to identify metabolites involved in energy, carbohydrate, lipid, and protein metabolism (Metabolon, Inc.). There was no change in body mass (POST‐PRE; 0.4 ± 5.1 kg, p = 0.59), while FM decreased (−1.7 ± 3.5 kg, p < 0.01), and FFM increased (2.1 ± 2.8 kg, p < 0.01) POST compared to PRE IMT. Of 677 identified metabolites, 340 differed at POST compared to PRE (p < 0.05, Q < 0.10). The majority of these metabolites were related to fatty acid (73%) and amino acid (26%) metabolism. Increases were detected in 41% of branched‐chain amino acid metabolites, 53% of histidine metabolites, and 35% of urea cycle metabolites. Decreases were detected in 93% of long‐chain fatty acid metabolites, while 58% of primary bile acid metabolites increased. Increases in amino acid metabolites suggest higher rates of protein turnover, while changes in fatty acid metabolites indicate increased fat oxidation, which likely contribute changes in body composition during IMT. Overall, changes in metabolomics profiles provide insight into metabolic adaptions underlying changes in body composition during IMT.

Metabolomic signatures after bariatric surgery - a systematic review

Metabolomics emerged as an important tool to gain insights on how the body responds to therapeutic interventions. Bariatric surgery is the most effective treatment for severe obesity and obesity-related co-morbidities. Our aim was to conduct a systematic review of the available data on metabolomics profiles that characterize patients submitted to different bariatric surgery procedures, which could be useful to predict clinical outcomes including weight loss and type 2 diabetes remission. For that, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA guidelines were followed. Data from forty-seven original study reports addressing metabolomics profiles induced by bariatric surgery that met eligibility criteria were compiled and summarized. Amino acids, lipids, energy-related and gut microbiota-related were the metabolite classes most influenced by bariatric surgery. Among these, higher pre-operative levels of specific lipids including phospholipids, long-chain fatty acids and bile acids were associated with post-operative T2D remission. As conclusion, metabolite profiling could become a useful tool to predict long term response to different bariatric surgery procedures, allowing more personalized interventions and improved healthcare resources allocation.

A multivariant recall-by-genotype study of the metabolomic signature of BMI

OBJECTIVE

This study estimated the effect of BMI on circulating metabolites in young adults using a recall-by-genotype study design.

METHODS

A recall-by-genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low versus high genetic liability for higher BMI defined by a genetic risk score (GRS). Regression analyses were performed to investigate associations between BMI GRS group and relative abundance of 973 metabolites.

RESULTS

After correction for multiple testing, 29 metabolites were associated with BMI GRS group. Bilirubin was among the most strongly associated metabolites, with reduced levels measured in individuals in the high-BMI GRS group (β = -0.32, 95% CI: -0.46 to -0.18, Benjamini-Hochberg adjusted p = 0.005). This study observed associations between BMI GRS group and the levels of several potentially diet-related metabolites, including hippurate, which had lower mean abundance in individuals in the high-BMI GRS group (β = -0.29, 95% CI: -0.44 to -0.15, Benjamini-Hochberg adjusted p = 0.008).

CONCLUSIONS

Together with existing literature, these results suggest that a genetic predisposition to higher BMI captures differences in metabolism leading to adiposity gain. In the absence of prospective data, separating these effects from the downstream consequences of weight gain is challenging.

Sex Dimorphism in the Metabolome of Metabolic Syndrome in Morbidly Obese Individuals

Adult morbid obesity is defined as abnormal or excessive fat accumulation, mostly resulting from a long-term unhealthy lifestyle. Between 10% and 30% of people with obesity exhibit low cardiometabolic risk. The metabolic syndrome has been suggested as an indicator of obesity-related metabolic dysregulation. Although the prevalence of obesity does not seem to be sex-related and metabolic syndrome occurs at all ages, in the last few years, sex-specific differences in the pathophysiology, diagnosis, and treatment of metabolic syndrome have received attention. The aim of this study was to determine the prevalence of metabolic syndrome and its components in different sex and age groups in people with metabolic unhealthy obesity and to compare them with people with metabolic healthy obesity. We analyzed the metabolome in 1350 well-phenotyped morbidly obese individuals and showed that there is a strong sex-dependent association of metabolic syndrome with circulating metabolites. Importantly, we demonstrated that metabolic dysregulation in women and men with severe obesity and metabolic syndrome is age-dependent. The metabolic profiles from our study showed age-dependent sex differences in the impact of MetS which are consistent with the cardiometabolic characterization. Although there is common ground for MetS in the metabolome of severe obesity, men older than 54 are affected in a more extensive and intensive manner. These findings strongly argue for more studies aimed at unraveling the mechanisms that underlie this sex-specific metabolic dysregulation in severe obesity. Moreover, these findings suggest that women and men might benefit from differential sex and age specific interventions to prevent the adverse cardiometabolic effects of severe obesity.

Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes

Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.

Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups.

Metabolic Profiling of Obesity With and Without the Metabolic Syndrome: A Multisample Evaluation

CONTEXT

There is a dispute whether obesity without major metabolic derangements may represent a benign condition or not.

OBJECTIVE

We aimed to compare the plasma metabolome in obese subjects without metabolic syndrome (MetS) with normal-weight subjects without MetS and with obese subjects with MetS.

METHODS

This was a cross-sectional study at 2 academic centers in Sweden. Individuals from 3 population-based samples (EpiHealth, n = 2342, SCAPIS-Uppsala, n = 4985, and SCAPIS-Malmö, n = 3978) were divided into groups according to their body mass index (BMI) and presence/absence of MetS (National Cholesterol Education Program [NCEP]/consensus criteria). In total, 791 annotated endogenous metabolites were measured by ultra-performance liquid chromatography-tandem mass spectrometry.

RESULTS

We observed major differences in metabolite profiles (427 metabolites) between obese (BMI ≥ 30 kg/m2) and normal-weight (BMI < 25 kg/m2) subjects without MetS after adjustment for major lifestyle factors. Pathway enrichment analysis highlighted branch-chained and aromatic amino acid synthesis/metabolism, aminoacyl-tRNA biosynthesis, and sphingolipid metabolism. The same pathways, and similar metabolites, were also highlighted when obese subjects with and without MetS were compared despite adjustment for BMI and waist circumference, or when the metabolites were related to BMI and number of MetS components in a continuous fashion. Similar metabolites and pathways were also related to insulin sensitivity (Matsuda index) in a separate study (POEM, n = 501).

CONCLUSION

Our data suggest a graded derangement of the circulating metabolite profile from lean to obese to MetS, in particular for metabolites involved in amino acid synthesis/metabolism and sphingolipid metabolism. Insulin resistance is a plausible mediator of this gradual metabolic deterioration.

Longitudinal associations of pre-pregnancy BMI and gestational weight gain with maternal urinary metabolites: an NYU CHES study

Background/Objectives:

Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The objective of this study was to explore associations of pre-pregnancy body mass index (pBMI) and GWG with longitudinally measured maternal urinary metabolites throughout pregnancy.

Subjects/Methods:

Among 652 participants in the New York University Children’s Health and Environment Study, a longitudinal pregnancy cohort, targeted metabolomics were measured in serially collected urine samples throughout pregnancy. Metabolites were measured at median 10 (T1), 21 (T2), and 29 (T3) weeks gestation using the Biocrates AbsoluteIDQ® p180 Urine Extension kit. Acylcarnitine, amino acid, biogenic amine, phosphatidylcholine, lysophosphatidylcholine, sphingolipid, and sugar levels were quantified. Pregnant people 18 years or older, without type 1 or 2 diabetes and with singleton live births and valid pBMI and metabolomics data were included. GWG and pBMI were calculated using weight and height data obtained from electronic health records. Linear mixed effects models with interactions with time were fit to determine the gestational age-specific associations of categorical pBMI and continuous interval-specific GWG with urinary metabolites. All analyses were corrected for false discovery rate.

Results:

Participants with obesity had lower long-chain acylcarnitine levels throughout pregnancy and lower phosphatidylcholine and glucogenic amino acids and higher phenylethylamine concentrations in T2 and T3 compared with participants with normal/underweight pBMI. GWG was associated with taurine in T2 and T3 and C5 acylcarnitine species, C5:1, C5-DC, and C5-M-DC, in T2.

Conclusions:

pBMI and GWG were associated with the metabolic environment of pregnant individuals, particularly in relation to mid-pregnancy. These results highlight the importance of both preconception and prenatal maternal health.

Serum metabolite profiling yields insights into health promoting effect of A. muciniphila in human volunteers with a metabolic syndrome

Reduction of A. muciniphila relative abundance in the gut microbiota is a widely accepted signature associated with obesity-related metabolic disorders. Using untargeted metabolomics profiling of fasting plasma, our study aimed at identifying metabolic signatures associated with beneficial properties of alive and pasteurized A. muciniphila when administrated to a cohort of insulin-resistant individuals with metabolic syndrome. Our data highlighted either shared or specific alterations in the metabolome according to the form of A. muciniphila administered with respect to a control group. Common responses encompassed modulation of amino acid metabolism, characterized by reduced levels of arginine and alanine, alongside several intermediates of tyrosine, phenylalanine, tryptophan, and glutathione metabolism. The global increase in levels of acylcarnitines together with specific modulation of acetoacetate also suggested induction of ketogenesis through enhanced β-oxidation. Moreover, our data pinpointed some metabolites of interest considering their emergence as substantial compounds pertaining to health and diseases in the more recent literature.

Obesity definition, diagnosis, bias, standard operating procedures (SOPs), and telehealth: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022

Background

The Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) regarding definition, diagnosis, bias, standard operating procedures (SOPs) and telehealth is intended to provide clinicians an overview of obesity medicine and provide basic organizational tools towards establishing, directing, managing, and maintaining an obesity medical practice.

Methods

This CPS is based upon published scientific citations, clinical perspectives of OMA authors, and peer review by Obesity Medicine Association leadership.

Results

OMA has defined obesity as: "A chronic, progressive, relapsing, and treatable multi-factorial, neurobehavioral disease, wherein an increase in body fat promotes adipose tissue dysfunction and abnormal fat mass physical forces, resulting in adverse metabolic, biomechanical, and psychosocial health consequences." While body mass index may be sufficiently diagnostic for populations and many patients, accurate diagnosis of adiposity in an individual may require anthropometric assessments beyond body weight alone (e.g., waist circumference, percent body fat, and android/visceral fat). Obesity complications can be categorized as "sick fat disease" (adiposopathy) and/or "fat mass disease." Obesity complications predominantly of fat mass origins include sleep apnea and orthopedic conditions. Obesity complications due to adiposopathic endocrinopathies and/or immunopathies include cardiovascular disease, cancer, elevated blood sugar, elevated blood pressure, dyslipidemia, fatty liver, and alterations in sex hormones in both males (i.e., hypogonadism) and females (i.e., polycystic ovary syndrome). Obesity treatment begins with proactive steps to avoid weight bias, including patient-appropriate language, office equipment, and supplies. To help manage obesity and its complications, this CPS provides a practical template for an obesity medicine practice, creation of standard operating procedures, and incorporation of the OMA "ADAPT" method in telehealth (Assessment, Diagnosis, Advice, Prognosis, and Treatment).

Conclusions

The OMA CPS regarding "Obesity Definition, Diagnosis, Bias, Standard Operating Procedures (SOPs), and Telehealth" is one in a series of OMA CPSs designed to assist clinicians care for patients with the disease of obesity.

Metabolic syndrome and cardiovascular diseases: Going beyond traditional risk factors

Metabolic syndrome (MS) is a chronic non-infective syndrome characterised clinically by a set of vascular risk factors that include insulin resistance, hypertension, abdominal obesity, impaired glucose metabolism, and dyslipidaemia. These risk factors are due to a pro-inflammatory state, oxidative stress, haemodynamic dysfunction, and ischaemia, which overlap in 'dysmetabolic' patients. This review aimed to evaluate the relationship between the traditional components of MS with cardiovascular disease (CVD), inflammation, and oxidative stress. MEDLINE-PubMed, EMBASE, and Cochrane databases were searched. Chronic low-grade inflammatory states and metaflammation are often accompanied by metabolic changes directly related to CVD incidence, such as diabetes mellitus, hypertension, and obesity. Moreover, the metaflammation is characterised by an increase in the serum concentration of pro-inflammatory cytokines, mainly interleukin-1 β (IL-1β), IL-6, and tumour necrosis factor-α (TNF-α), originating from the chronically inflamed adipose tissue and associated with oxidative stress. The increase of reactive oxygen species overloads the antioxidant systems causing post-translational alterations of proteins, lipids, and DNA leading to oxidative stress. Hyperglycaemia contributes to the increase in oxidative stress and the production of advanced glycosylation end products (AGEs) which are related to cellular and molecular dysfunction. Oxidative stress and inflammation are associated with cellular senescence and CVD. CVD should not be seen only as being triggered by classical MS risk factors. Atherosclerosis is a multifactorial pathological process with several triggering and aetiopathogenic mechanisms. Its medium and long-term repercussions, however, invariably constitute a significant cause of morbidity and mortality. Implementing preventive and therapeutic measures against oxy-reductive imbalances and metaflammation states has unquestionable potential for favourable clinical outcomes in cardiovascular medicine.

Acute aerobic exercise reveals FAHFAs distinguish the metabolomes of overweight and normal weight runners

Background

Responses of the metabolome to acute aerobic exercise may predict maximum oxygen consumption (VO₂max) and longer-term outcomes, including the development of diabetes and its complications.

Methods

Serum samples were collected from overweight/obese trained (OWT) and normal-weight trained (NWT) runners prior to and immediately after a supervised 90-minute treadmill run at 60% VO₂max (NWT = 14, OWT = 11) in a cross-sectional study. We applied a liquid chromatography high-resolution–mass spectrometry–based untargeted metabolomics platform to evaluate the effect of acute aerobic exercise on the serum metabolome.

Results

NWT and OWT metabolic profiles shared increased circulating acylcarnitines and free fatty acids (FFAs) with exercise, while intermediates of adenine metabolism, inosine, and hypoxanthine were strongly correlated with body fat percentage and VO₂max. Untargeted metabolomics-guided follow-up quantitative lipidomic analysis revealed that baseline levels of fatty acid esters of hydroxy fatty acids (FAHFAs) were generally diminished in the OWT group. FAHFAs negatively correlated with visceral fat mass and HOMA-IR. Strikingly, a 4-fold decrease in FAHFAs was provoked by acute aerobic running in NWT participants, an effect that negatively correlated with circulating IL-6; these effects were not observed in the OWT group. Machine learning models based on a preexercise metabolite profile that included FAHFAs, FFAs, and adenine intermediates predicted VO₂max.

Conclusion

These findings in overweight human participants and healthy controls indicate that exercise-provoked changes in FAHFAs distinguish normal-weight from overweight participants and could predict VO₂max. These results support the notion that FAHFAs could modulate the inflammatory response, fuel utilization, and insulin resistance.

Trial registration

ClinicalTrials.gov, NCT02150889.

Funding

NIH DK091538, AG069781, DK098203, TR000114, UL1TR002494.

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.

Transcriptome signature changes in the liver of a migratory passerine

The liver plays a principal role in avian migration. Here, we characterised the liver transcriptome of a long-distance migrant, the Northern Wheatear (Oenanthe oenanthe), sampled at different migratory stages, looking for molecular processes linked with adaptations to migration. The analysis of the differentially expressed genes suggested changes in the periods of the circadian rhythm, variation in the proportion of cells in G1/S cell-cycle stages and the putative polyploidization of this cell population. This may explain the dramatic increment in the liver's metabolic capacities towards migration. Additionally, genes involved in anti-oxidative stress, detoxification and innate immune responses, lipid metabolism, inflammation and angiogenesis were regulated. Lipophagy and lipid catabolism were active at all migratory stages and increased towards the fattening and fat periods, explaining the relevance of lipolysis in controlling steatosis and maintaining liver health. Our study clears the way for future functional studies regarding long-distance avian migration.

Effect of General Adiposity and Central Body Fat Distribution on the Circulating Metabolome: A Multicohort Nontargeted Metabolomics Observational and Mendelian Randomization Study

Obesity is associated with adverse health outcomes, but the metabolic effects have not yet been fully elucidated. We aimed to investigate the association between adiposity and circulating metabolites and to address causality with Mendelian randomization (MR). Metabolomics data were generated with nontargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry in plasma and serum from three population-based Swedish cohorts: ULSAM (N = 1,135), PIVUS (N = 970), and TwinGene (N = 2,059). We assessed associations of general adiposity measured as BMI and central body fat distribution measured as waist-to-hip ratio adjusted for BMI (WHRadjBMI) with 210 annotated metabolites. We used MR analysis to assess causal effects. Lastly, we attempted to replicate the MR findings in the KORA and TwinsUK cohorts (N = 7,373), the CHARGE Consortium (N = 8,631), the Framingham Heart Study (N = 2,076), and the DIRECT Consortium (N = 3,029). BMI was associated with 77 metabolites, while WHRadjBMI was associated with 11 and 3 metabolites in women and men, respectively. The MR analyses in the Swedish cohorts suggested a causal association (P value <0.05) of increased general adiposity and reduced levels of arachidonic acid, dodecanedioic acid, and lysophosphatidylcholine (P-16:0) as well as with increased creatine levels. The results of the replication effort provided support for a causal association of adiposity with reduced levels of arachidonic acid (P value = 0.03). Adiposity is associated with variation of large parts of the circulating metabolome; however, further investigation of causality is required in well-powered cohorts.

Integrative Lipidomics and Metabolomics for System-Level Understanding of the Metabolic Syndrome in Long-Term Treated HIV-Infected Individuals

People living with HIV (PLWH) require life-long anti-retroviral treatment and often present with comorbidities such as metabolic syndrome (MetS). Systematic lipidomic characterization and its association with the metabolism are currently missing. We included 100 PLWH with MetS and 100 without MetS from the Copenhagen Comorbidity in HIV Infection (COCOMO) cohort to examine whether and how lipidome profiles are associated with MetS in PLWH. We combined several standard biostatistical, machine learning, and network analysis techniques to investigate the lipidome systematically and comprehensively and its association with clinical parameters. Additionally, we generated weighted lipid-metabolite networks to understand the relationship between lipidomic profiles with those metabolites associated with MetS in PLWH. The lipidomic dataset consisted of 917 lipid species including 602 glycerolipids, 228 glycerophospholipids, 61 sphingolipids, and 26 steroids. With a consensus approach using four different statistical and machine learning methods, we observed 13 differentially abundant lipids between PLWH without MetS and PLWH with MetS, which mainly belongs to diacylglyceride (DAG, n = 2) and triacylglyceride (TAG, n = 11). The comprehensive network integration of the lipidomics and metabolomics data suggested interactions between specific glycerolipids' structural composition patterns and key metabolites involved in glutamate metabolism. Further integration of the clinical data with metabolomics and lipidomics resulted in the association of visceral adipose tissue (VAT) and exposure to earlier generations of antiretroviral therapy (ART). Our integrative omics data indicated disruption of glutamate and fatty acid metabolism, suggesting their involvement in the pathogenesis of PLWH with MetS. Alterations in the lipid homeostasis and glutaminolysis need clinical interventions to prevent accelerated aging in PLWH with MetS.

Untargeted Metabolomics Analysis of the Serum Metabolic Signature of Childhood Obesity

Obesity rates among children are growing rapidly worldwide, placing massive pressure on healthcare systems. Untargeted metabolomics can expand our understanding of the pathogenesis of obesity and elucidate mechanisms related to its symptoms. However, the metabolic signatures of obesity in children have not been thoroughly investigated. Herein, we explored metabolites associated with obesity development in childhood. Untargeted metabolomic profiling was performed on fasting serum samples from 27 obese Caucasian children and adolescents and 15 sex- and age-matched normal-weight children. Three metabolomic assays were combined and yielded 726 unique identified metabolites: gas chromatography–mass spectrometry (GC–MS), hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC–MS/MS), and lipidomics. Univariate and multivariate analyses showed clear discrimination between the untargeted metabolomes of obese and normal-weight children, with 162 significantly differentially expressed metabolites between groups. Children with obesity had higher concentrations of branch-chained amino acids and various lipid metabolites, including phosphatidylcholines, cholesteryl esters, triglycerides. Thus, an early manifestation of obesity pathogenesis and its metabolic consequences in the serum metabolome are correlated with altered lipid metabolism. Obesity metabolite patterns in the adult population were very similar to the metabolic signature of childhood obesity. Identified metabolites could be potential biomarkers and used to study obesity pathomechanisms.

Profound Perturbation in the Metabolome of a Canine Obesity and Metabolic Disorder Model

Canine models are increasingly being used in metabolic studies due to their physiological similarity with humans. The present study aimed to identify changes in metabolic pathways and biomarkers with potential clinical utility in a canine model of obesity and metabolic disorders induced by a high-fat diet (HFD). Eighteen male beagles were included in this study, 9 of which were fed a HFD for 24 weeks, and the remaining 9 were fed normal chow (NC) during the same period. Plasma and urine samples were collected at weeks 12 and 24 for untargeted metabolomic analysis. Dogs fed a HFD showed a gradual body weight increase during the feeding period and had hyperlipidemia, increased leukocyte counts, and impaired insulin sensitivity at week 24. Plasma and urine metabonomics analysis displayed clear separations between the HFD-fed and NC-fed dogs. A total of 263 plasma metabolites varied between the two groups, including stearidonic acid, linolenic acid, carnitine, long-chain ceramide, 3-methylxanthine, and theophylline, which are mainly engaged in fatty acid metabolism, sphingolipid metabolism, and caffeine metabolism. A total of 132 urine metabolites related to HFD-induced obesity and metabolic disorders were identified, including 3-methylxanthine, theophylline, pyridoxal 5'-phosphate, and harmine, which participate in pathways such as caffeine metabolism and vitamin digestion and absorption. Eight metabolites with increased abundance (e.g., 3-methylxanthine, theophylline, and harmine) and 4 metabolites with decreased abundance (e.g., trigonelline) in both the plasma and urine of the HFD-fed dogs were identified. In conclusion, the metabolomic analysis revealed molecular events underlying a canine HFD model and identified several metabolites as potential targets for the prevention and treatment of obesity-related metabolic disorders.

Maternal Body Mass Index, Early-Pregnancy Metabolite Profile, and Birthweight

CONTEXT

Maternal prepregnancy body mass index (BMI) has a strong influence on gestational metabolism, but detailed metabolic alterations are unknown.

OBJECTIVE

First, to examine the associations of maternal prepregnancy BMI with maternal early-pregnancy metabolite alterations. Second, to identify an early-pregnancy metabolite profile associated with birthweight in women with a higher prepregnancy BMI that improved prediction of birthweight compared to glucose and lipid concentrations.

DESIGN, SETTING, AND PARTICIPANTS

Prepregnancy BMI was obtained in a subgroup of 682 Dutch pregnant women from the Generation R prospective cohort study.

MAIN OUTCOME MEASURES

Maternal nonfasting targeted amino acids, nonesterified fatty acid, phospholipid, and carnitine concentrations measured in blood serum at mean gestational age of 12.8 weeks. Birthweight was obtained from medical records.

RESULTS

A higher prepregnancy BMI was associated with 72 altered amino acids, nonesterified fatty acid, phospholipid and carnitine concentrations, and 6 metabolite ratios reflecting Krebs cycle, inflammatory, oxidative stress, and lipid metabolic processes (P-values < 0.05). Using penalized regression models, a metabolite profile was selected including 15 metabolites and 4 metabolite ratios based on its association with birthweight in addition to prepregnancy BMI. The adjusted R2 of birthweight was 6.1% for prepregnancy BMI alone, 6.2% after addition of glucose and lipid concentrations, and 12.9% after addition of the metabolite profile.

CONCLUSIONS

A higher maternal prepregnancy BMI was associated with altered maternal early-pregnancy amino acids, nonesterified fatty acids, phospholipids, and carnitines. Using these metabolites, we identified a maternal metabolite profile that improved prediction of birthweight in women with a higher prepregnancy BMI compared to glucose and lipid concentrations.

A systematic review of metabolomic studies of childhood obesity: State of the evidence for metabolic determinants and consequences

Childhood obesity has become a global epidemic and carries significant long-term consequences to physical and mental health. Metabolomics, the global profiling of small molecules or metabolites, may reveal the mechanisms of development of childhood obesity and clarify links between obesity and metabolic disease. A systematic review of metabolomic studies of childhood obesity was conducted, following Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, searching across Scopus, Ovid, Web of Science and PubMed databases for articles published from January 1, 2005 to July 8, 2020, retrieving 1271 different records and retaining 41 articles for qualitative synthesis. Study quality was assessed using a modified Newcastle-Ottawa Scale. Thirty-three studies were conducted on blood, six on urine, three on umbilical cord blood, and one on saliva. Thirty studies were primarily cross-sectional, five studies were primarily longitudinal, and seven studies examined effects of weight-loss following a life-style intervention. A consistent metabolic profile of childhood obesity was observed including amino acids (particularly branched chain and aromatic), carnitines, lipids, and steroids. Although the use of metabolomics in childhood obesity research is still developing, the identified metabolites have provided additional insight into the pathogenesis of many obesity-related diseases. Further longitudinal research is needed into the role of metabolic profiles and child obesity risk.

De Novo Glycine Synthesis Is Reduced in Adults With Morbid Obesity and Increases Following Bariatric Surgery

BACKGROUND

Glycine is a dietary non-essential amino acid that is low in obesity and increases following bariatric surgery. However, the exact mechanism responsible remains unclear and it is unknown whether hypoglycinemia is a cause or consequence of insulin resistance.

OBJECTIVE

Using multiple isotopically labeled tracers, we aimed to determine the underlying kinetic changes responsible for hypoglycinemia in obesity by: 1) Comparing glycine kinetics between participants with morbid obesity (BMI ≥ 32.5 kg/m²) to those with healthy weight (BMI < 25 kg/m²), and 2) Comparing glycine kinetic changes in participants with morbid obesity after bariatric surgery.

METHODS

[1,2-¹³C₂] glycine, [2,3,3-²H₃] serine, and [²H₅] phenylalanine were infused to compare the glycine kinetic parameters between 21 participants with morbid obesity and 21 controls with healthy weight. Participants with morbid obesity then underwent bariatric surgery and 17 were re-studied 6 months later. Data were analyzed by non-parametric methods and presented as median (interquartile range).

RESULTS

Compared to controls, participants with morbid obesity had significantly lower plasma glycine concentrations at 163 (153-171) vs. 201 (172-227) µmol/L and significantly reduced de novo glycine synthesis rate at 86.2 (64.5-111) vs.124 (103-159) µmol·kg LBM^-1·h¹, p < 0.001. Following surgery, body weight and insulin resistance decreased and this was accompanied by significant increases in plasma glycine concentration to 210 (191-243) µmol/L as well as the de novo glycine synthesis rate to 127 (98.3-133) µmol·kg LBM^-1·h^-1, p < 0.001 vs. baseline.

CONCLUSION

Hypoglycinemia in participants with morbid obesity was associated with impaired de novo glycine synthesis. The increase in plasma glycine concentration and de novo glycine synthesis plus the marked improvement in insulin resistance after bariatric surgery suggest that hypoglycinemia may be secondary to impaired glycine synthesis because of obesity-induced insulin resistance.

CLINICAL TRIAL REGISTRATION

[https://tinyurl.com/6wfj7yss], identifier [NCT04660513].

Metabolomic Signatures for the Effects of Weight Loss Interventions on Severe Obesity in Children and Adolescents

Childhood obesity has increased worldwide, and many clinical and public interventions have attempted to reduce morbidity. We aimed to determine the metabolomic signatures associated with weight control interventions in children with obesity. Forty children from the “Intervention for Children and Adolescent Obesity via Activity and Nutrition (ICAAN)” cohort were selected according to intervention responses. Based on changes in body mass index z-scores, 20 were responders and the remaining non-responders. Their serum metabolites were quantitatively analyzed using capillary electrophoresis time-of-flight mass spectrometry at baseline and after 6 and 18 months of intervention. After 18 months of intervention, the metabolite cluster changes in the responders and non-responders showed a difference on the heatmap, but significant metabolites were not clear. However, regardless of the responses, 13 and 49 metabolites were significant in the group of children with obesity intervention at 6 months and 18 months post-intervention compared to baseline. In addition, the top five metabolic pathways (D-glutamine and D-glutamate metabolism; arginine biosynthesis; alanine, aspartate, and glutamate metabolism; TCA cycle (tricarboxylic acid cycle); valine, leucine, and isoleucine biosynthesis) including several amino acids in the metabolites of obese children after 18 months were significantly changed. Our study showed significantly different metabolomic profiles based on time post obesity-related intervention. Through this study, we can better understand and predict childhood obesity through metabolite analysis and monitoring.

Pyrroloquinoline quinone attenuated benzyl butyl phthalate induced metabolic aberration and a hepatic metabolomic analysis

Benzyl butyl phthalate (BBP) has recently been implicated as an obesogen. Our recent study demonstrated that BBP can exacerbate high fat diet (HFD) induced diabesity in male mice. Here, we explored if pyrroloquinoline quinone (PQQ), a natural antioxidant andphytochemical, can attenuate metabolic aberrations induced by HFD or HFD-BBPcombination. C57Bl/6 male and female mice were fed either a chow diet (CD) or HFD with or without BBP (3 mg/kg body weight/day)and/or PQQ (20 mg/kg/day)for 16 weeks. The mice's body and tissue weight, fasting blood glucose, glucose and insulin tolerance test, and liver metabolites level weremeasured. In HFD-fed male mice, PQQ significantly attenuated the increased body weight, liver weight, fasting blood glucose, and insulin intolerance under BBP exposure.Even though female mice did show some reversal of metabolic characteristics by PQQ, the response was not similar nor consistent with the male population. Amongthe 14 hepatic metabolites that were significantly altered by HFD compared to CD, only three major metabolites (acetyl-L-carnitine, DL-stachytine, and propionylcarnitine) were decreased. These three were shown to have more reduction under BBP exposure in the presence of HFD whereas with addition of PQQ, these metabolites were restored. Pathway analysis and literature search revealed that these metabolites were negatively associated with obesity and were involved in several pathways including beta-oxidation, oxidative stress, and mitochondrial function. Overall,this finding indicated the potential use of PQQ to restore thewide range of aberrant metabolic effectinduced by an obesogen in the presence of a western diet.

Prediction of Healthy Pregnancy Outcomes in Women with Overweight and Obesity: The Role of Maternal Early-Pregnancy Metabolites

Women with obesity receive intensified antenatal care due to their increased risk of pregnancy complications, even though not all of these women develop complications. We developed a model based on maternal characteristics for prediction of healthy pregnancy outcomes in women with obesity or who are overweight. We assessed whether early-pregnancy metabolites improved prediction. In a population-based cohort study among a subsample of 1180 Dutch pregnant women with obesity or who are overweight, we developed a prediction model using 32 maternal socio-demographic, lifestyle, physical and pregnancy-related characteristics. We determined early-pregnancy amino acids, nonesterifed fatty acids, phospholipids and carnitines in blood serum using liquid chromatography-tandem mass spectrometry. A healthy pregnancy outcome was the absence of fetal death, gestational hypertension, preeclampsia, gestational diabetes, caesarian section, preterm birth, large-for-gestational-age at birth, macrosomia, postpartum weight retention and offspring overweight/obesity at 5 years. Maternal age, relationship status, parity, early-pregnancy body mass index, mid-pregnancy gestational weight gain, systolic blood pressure and estimated fetal weight were selected into the model using backward selection (area under the receiver operating characteristic curve: 0.65 (95% confidence interval 0.61 to 0.68)). Early-pregnancy metabolites did not improve model performance. Thus, in women with obesity or who are overweight, maternal characteristics can moderately predict a healthy pregnancy outcome. Maternal early-pregnancy metabolites have no incremental value in the prediction of a healthy pregnancy outcome.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Lipidomic and Metabolomic Signature of Progression of Chronic Kidney Disease in Patients with Severe Obesity

Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study would justify the use of comprehensive mass spectrometry-based lipidomics to measure other lipids aside from conventional lipid profiles and to validate possible early markers of risk of CKD in patients with severe obesity.

Metabolomic Signature of Patients With Narcolepsy

BACKGROUND AND OBJECTIVE

Narcolepsy type 1 (NT1) is an orphan brain disorder caused by the irreversible destruction of orexin neurons. Metabolic disturbances are common in patients with NT1 who have a body mass index (BMI) 10-20% higher than the general population, with one third being obese (BMI>30 kg/m²). Besides the destruction of orexin neurons in NT1, the metabolic alterations in obese and non-obese patients with narcolepsy type 1 remain unknown. The aim of the study was to identify possible differences in plasma metabolic profiles between patients with NT1 and controls as a function of their BMI status.

METHODS

We used a targeted liquid chromatography-mass spectrometry metabolomics approach to measure 141 circulating, low molecular weight metabolites in drug-free fasted plasma samples from 117 NT1 patients (including 41 obese subjects) compared with 116 BMI-matched controls (including 57 obese subjects).

RESULTS

Common metabolites driving the difference between NT1 and controls, irrespective of BMI, were identified, namely sarcosine, glutamate, nonaylcarnitine (C9), 5 long chain lysophosphatidylcholine acyls, one sphingolipid, 12 phosphatidylcholine diacyls and 11 phosphatidylcholine acyl-akyls, all showing increased concentrations in NT1. Metabolite concentrations significantly affected by NT1 (n = 42) and BMI category (n = 40) showed little overlap (n = 5). Quantitative enrichment analysis revealed common metabolic pathways that were implicated in the NT1/control differences, in both normal BMI and obese comparisons, namely glycine and serine, arachidonic acid, and tryptophan metabolisms. The metabolites driving these differences were glutamate, sarcosine and ornithine (glycine and serine metabolism), glutamate and PC aa C34:4 (arachidonic acid metabolism) and glutamate, serotonin and tryptophan (tryptophan metabolism). Linear metabolite-endophenotype regression analyses highlight that as part of the NT1 metabolic phenotype, most of the relationships between the sleep parameters (i.e. slow wave sleep duration, sleep latency and periodic leg movement) and metabolite concentrations seen in the controls were lost.

DISCUSSION

These results represented the most comprehensive metabolic profiling of patients with NT1 as a function of BMI and propose some metabolic diagnostic biomarkers for NT1, namely glutamate, sarcosine, serotonin, tryptophan, nonaylcarnitine and some phosphatidylcholines. The metabolic pathways identified offer, if confirmed, possible targets for treatment of obesity in NT1.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that a distinct metabolic profile can differentiate patients with Narcolepsy Type 1 from patients without the disorder.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

Background

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

Methods

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

Findings

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

Interpretation

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Paediatric obesity: a systematic review and pathway mapping of metabolic alterations underlying early disease processes

BACKGROUND

The alarming trend of paediatric obesity deserves our greatest awareness to hinder the early onset of metabolic complications impacting growth and functionality. Presently, insight into molecular mechanisms of childhood obesity and associated metabolic comorbidities is limited. This systematic review aimed at scrutinising what has been reported on putative metabolites distinctive for metabolic abnormalities manifesting at young age by searching three literature databases (Web of Science, Pubmed and EMBASE) during the last 6 years (January 2015-January 2021). Global metabolomic profiling of paediatric obesity was performed (multiple biological matrices: blood, urine, saliva and adipose tissue) to enable overarching pathway analysis and network mapping. Among 2792 screened Q1 articles, 40 met the eligibility criteria and were included to build a database on metabolite markers involved in the spectrum of childhood obesity. Differential alterations in multiple pathways linked to lipid, carbohydrate and amino acid metabolisms were observed. High levels of lactate, pyruvate, alanine and acetate marked a pronounced shift towards hypoxic conditions in children with obesity, and, together with distinct alterations in lipid metabolism, pointed towards dysbiosis and immunometabolism occurring early in life. Additionally, aberrant levels of several amino acids, most notably belonging to tryptophan metabolism including the kynurenine pathway and its relation to histidine, phenylalanine and purine metabolism were displayed. Moreover, branched-chain amino acids were linked to lipid, carbohydrate, amino acid and microbial metabolism, inferring a key role in obesity-associated insulin resistance.

CONCLUSIONS

This systematic review revealed that the main metabolites at the crossroad of dysregulated metabolic pathways underlying childhood obesity could be tracked down to one central disturbance, i.e. impending insulin resistance for which reference values and standardised measures still are lacking. In essence, glycolytic metabolism was evinced as driving energy source, coupled to impaired Krebs cycle flux and ß-oxidation. Applying metabolomics enabled to retrieve distinct metabolite alterations in childhood obesity(-related insulin resistance) and associated pathways at early age and thus could provide a timely indication of risk by elucidating early-stage biomarkers as hallmarks of future metabolically unhealthy phenotypes.

Metabolomic alteration induced by psychotropic drugs: Short-term metabolite profile as a predictor of weight gain evolution

Psychotropic drugs can induce strong metabolic adverse effects, potentially increasing morbidity and/or mortality of patients. Metabolomic profiling, by studying the levels of numerous metabolic intermediates and products in the blood, allows a more detailed examination of metabolism dysfunctions. We aimed to identify blood metabolomic markers associated with weight gain in psychiatric patients. Sixty-two patients starting a treatment known to induce weight gain were recruited. Two hundred and six selected metabolites implicated in various pathways were analyzed in plasma, at baseline and after 1 month of treatment. Additionally, 15 metabolites of the kynurenine pathway were quantified. This latter analysis was repeated in a confirmatory cohort of 24 patients. Among the 206 metabolites, a plasma metabolomic fingerprint after 1 month of treatment embedded 19 compounds from different chemical classes (amino acids, acylcarnitines, carboxylic acids, catecholamines, nucleosides, pyridine, and tetrapyrrole) potentially involved in metabolic disruption and inflammation processes. The predictive potential of such early metabolite changes on 3 months of weight evolution was then explored using a linear mixed-effects model. Of these 19 metabolites, short-term modifications of kynurenine, hexanoylcarnitine, and biliverdin, as well as kynurenine/tryptophan ratio at 1 month, were associated with 3 months weight evolution. Alterations of the kynurenine pathway were confirmed by quantification, in both exploratory and confirmatory cohorts. Our metabolomic study suggests a specific metabolic dysregulation after 1 month of treatment with psychotropic drugs known to induce weight gain. The identified metabolomic signature could contribute in the future to the prediction of weight gain in patients treated with psychotropic drugs.

Aqueous Metabolite Trends for the Progression of Nonalcoholic Fatty Liver Disease in Female Bariatric Surgery Patients by Targeted 1H-NMR Metabolomics

Determining biomarkers and better characterizing the biochemical progression of nonalcoholic fatty liver disease (NAFLD) remains a clinical challenge. A targeted ¹H-NMR study of serum, combined with clinical variables, detected and localized biomarkers to stages of NAFLD in morbidly obese females. Pre-surgery serum samples from 100 middle-aged, morbidly obese female subjects, grouped on gold-standard liver wedge biopsies (non-NAFLD; steatosis; and fibrosis) were collected, extracted, and analyzed in aqueous (D₂O) buffer (¹H, 600 MHz). Profiled concentrations were subjected to exploratory statistical analysis. Metabolites varying significantly between the non-NAFLD and steatosis groups included the ketone bodies 3-hydroxybutyrate (↓; p = 0.035) and acetone (↓; p = 0.012), and also alanine (↑; p = 0.004) and a putative pyruvate signal (↑; p = 0.003). In contrast, the steatosis and fibrosis groups were characterized by 2-hydroxyisovalerate (↑; p = 0.023), betaine (↓; p = 0.008), hypoxanthine (↓; p = 0.003), taurine (↓; p = 0.001), 2-hydroxybutyrate (↑; p = 0.045), 3-hydroxyisobutyrate (↑; p = 0.046), and increasing medium chain fatty acids. Exploratory classification models with and without clinical variables exhibited overall success rates ca. 75–85%. In the study conditions, inhibition of fatty acid oxidation and disruption of the hepatic urea cycle are supported as early features of NAFLD that continue in fibrosis. In fibrosis, markers support inflammation, hepatocyte damage, and decreased liver function. Complementarity of NMR concentrations and clinical information in classification models is shown. A broader hypothesis that standard-of-care sera can yield metabolomic information is supported.

The Relation Between Adult Weight Gain, Adipocyte Volume, and the Metabolic Profile at Middle Age

CONTEXT

Weight gain during adulthood increases cardiometabolic disease risk, possibly through adipocyte hypertrophy.

OBJECTIVE

We aimed to study the specific metabolomic profile of adult weight gain, and to examine its association with adipocyte volume.

METHODS

Nuclear magnetic resonance-based metabolomics were measured in the Netherlands Epidemiology of Obesity (NEO) study (n = 6347, discovery) and Oxford Biobank (n = 6317, replication). Adult weight gain was calculated as the absolute difference between body mass index (BMI) at middle age and recalled BMI at age 20 years. We performed linear regression analyses with both exposures BMI at age 20 years and weight gain, and separately with BMI at middle age in relation to 149 serum metabolomic measures, adjusted for age, sex, and multiple testing. Additionally, subcutaneous abdominal adipocyte biopsies were collected in a subset of the Oxford Biobank (n = 114) to estimate adipocyte volume.

RESULTS

Mean (SD) weight gain was 4.5 (3.7) kg/m2 in the NEO study and 3.6 (3.7) kg/m2 in the Oxford Biobank. Weight gain, and not BMI at age 20 nor middle age, was associated with concentrations of 7 metabolomic measures after successful replication, which included polyunsaturated fatty acids, small to medium low-density lipoproteins, and total intermediate-density lipoprotein. One SD weight gain was associated with 386 μm3 (95% CI, 143-629) higher median adipocyte volume. Adipocyte volume was associated with lipoprotein particles specific for adult weight gain.

CONCLUSION

Adult weight gain is associated with specific metabolomic alterations of which the higher lipoprotein concentrations were likely contributed by larger adipocyte volumes, presumably linking weight gain to cardiometabolic disease.

A predictive regression model of the obesity-related inflammatory status based on gut microbiota composition

BACKGROUND AND AIM

Fecal microbiome disturbances are linked to different human diseases. In the case of obesity, gut microbiota seems to play a role in the development of low-grade inflammation. The purpose of the present study was to identify specific bacterial families and genera associated with an increased obesity-related inflammatory status, which would allow to build a regression model for the prediction of the inflammatory status of obese and overweight subjects based on fecal microorganisms.

METHODS

A total of 361 volunteers from the Obekit trial (65 normal-weight, 110 overweight, and 186 obese) were classified according to four variables: waist/hip ratio (≥0.86 for women and ≥1.00 for men), leptin/adiponectin ratio (LAR, ≥3.0 for women and ≥1.4 for men), and plasma C-reactive protein (≥2 mg/L) and TNF levels (≥0.85 pg/mL). An inflammation score was designed to classify individuals in low (those subjects who did exceed the threshold value in 0 or 1 variable) or high inflammatory index (those subjects who did exceed the threshold value in 2 or more variables). Fecal 16 S rRNA sequencing was performed for all participants, and differential abundance analyses for family and genera were performed using the MicrobiomeAnalyst web-based platform.

RESULTS

Methanobacteriaceae, Christensenellaceae, Coriobacteriaceae, Bifidobacteriaceae, Catabacteriaceae, and Dehalobacteriaceae families, and Methanobrevibacter, Eggerthella, Gemmiger, Anaerostipes, and Collinsella genera were significantly overrepresented in subjects with low inflammatory index. Conversely, Carnobacteriaceae, Veillonellaceae, Pasteurellaceae, Prevotellaceae and Enterobacteriaceae families, and Granulicatella, Veillonella, Haemophilus, Dialister Parabacteroides, Prevotella, Shigella, and Allisonella genera were more abundant in subjects with a high inflammatory index. A regression model adjusted by BMI, sex, and age and including the families Coriobacteriaceae and Prevotellaceae and the genus Veillonella was developed.

CONCLUSION

A microbiota-based regression model was able to predict the obesity-related inflammatory status (area under the ROC curve = 0.8570 ± 0.0092 Harrell's optimism-correction) and could be useful in the precision management of inflammobesity.

Branched-Chain Amino Acids and Risk of Breast Cancer

Background

Circulating branched-chain amino acid (BCAA) levels reflect metabolic health and dietary intake. However, associations with breast cancer are unclear.

Methods

We evaluated circulating BCAA levels and breast cancer risk within the Nurses’ Health Study (NHS) and NHSII (1997 cases and 1997 controls). A total of 592 NHS women donated 2 blood samples 10 years apart. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer risk in multivariable logistic regression models. We conducted an external validation in 1765 cases in the Women’s Health Study (WHS). All statistical tests were 2-sided.

Results

Among NHSII participants (predominantly premenopausal at blood collection), elevated circulating BCAA levels were associated with lower breast cancer risk (eg, isoleucine highest vs lowest quartile, multivariable OR = 0.86, 95% CI = 0.65 to 1.13, P_trend = .20), with statistically significant linear trends among fasting samples (eg, isoleucine OR = 0.74, 95% CI = 0.53 to 1.05, P_trend = .05). In contrast, among postmenopausal women, proximate measures (<10 years from blood draw) were associated with increased breast cancer risk (eg, isoleucine OR = 1.63, 95% CI = 1.12 to 2.39, P_trend = .01), with stronger associations among fasting samples (OR = 1.73, 95% CI = 1.15 to 2.61, P_trend = .01). Distant measures (10-20 years since blood draw) were not associated with risk. In the WHS, a positive association was observed for distant measures of leucine among postmenopausal women (OR = 1.23, 95% CI = 0.96 to 1.58, P_trend = .04).

Conclusions

No statistically significant associations between BCAA levels and breast cancer risk were consistent across NHS and WHS or NHSII and WHS. Elevated circulating BCAA levels were associated with lower breast cancer risk among predominantly premenopausal NHSII women and higher risk among postmenopausal women in NHS but not in the WHS. Additional studies are needed to understand this complex relationship.

MD, Eckel-Passow J, Acosta A. Precision Medicine for Obesity

Obesity is a multifactorial disease with a variable and underwhelming weight loss response to current treatment approaches. Precision medicine proposes a new paradigm to improve disease classification based on the premise of human heterogeneity, with the ultimate goal of maximizing treatment effectiveness, tolerability, and safety. Recent advances in high-throughput biochemical assays have contributed to the partial characterization of obesity's pathophysiology, as well as to the understanding of the role that intrinsic and environmental factors, and their interaction, play in its development and progression. These data have led to the development of biological markers that either are being or will be incorporated into strategies to develop personalized lines of treatment for obesity. There are currently many ongoing initiatives aimed at this; however, much needs to be resolved before precision obesity medicine becomes common practice. This review aims to provide a perspective on the currently available data of high-throughput technologies to treat obesity.

Immunometabolic signatures predict risk of progression to sepsis in COVID-19

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986-0.995), with sensitivity of 0.978 (0.963-0.992) and specificity of 0.920 (0.890-0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952-0.977), with sensitivity of 0.993(0.984-1.000) and specificity of 0.851 (0.815-0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800-0.858), with sensitivity of 0.738 (0.695-0.781) and specificity of 0.781 (0.735-0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788-0.874), with sensitivity of 0.765 (0.697-0.832) and specificity of 0.817 (0.770-0.865).

A novel strategy for D-psicose and lipase co-production using a co-culture system of engineered Bacillus subtilis and Escherichia coli and bioprocess analysis using metabolomics

To develop an economically feasible fermentation process, this study designed a novel bioprocess based on the co-culture of engineered Bacillus subtilis and Escherichia coli for the co-production of extracellular D-psicose and intracellular lipase. After optimizing the co-culture bioprocess, 11.70 g/L of D-psicose along with 16.03 U/mg of lipase was obtained; the glucose and fructose were completely utilized. Hence, the conversion rate of D-psicose reached 69.54%. Compared with mono-culture, lipase activity increased by 58.24%, and D-psicose production increased by 7.08%. In addition, the co-culture bioprocess was explored through metabolomics analysis, which included 168 carboxylic acids and derivatives, 70 organooxygen compounds, 34 diazines, 32 pyridines and derivatives, 30 benzene and substituted derivatives, and other compounds. It also could be found that the relative abundance of differential metabolites in the co-culture system was significantly higher than that in the mono-culture system. Pathway analysis revealed that, tryptophan metabolism and β-alanine metabolism had the highest correlation and played an important role in the co-culture system; among them, tryptophan metabolism regulates protein synthesis and β-alanine metabolism, which is related to the formation of metabolic by-products. These results confirm that the co-cultivation of B. subtilis and E. coli can provide a novel idea for D-psicose and lipase biorefinery, and are beneficial for the discovery of valuable secondary metabolites such as turanose and morusin.

The snapshot of metabolic health in evaluating micronutrient status, the risk of infection and clinical outcome of COVID-19

COVID-19 has re-established the significance of analyzing the organism through a metabolic perspective to uncover the dynamic interconnections within the biological systems. The role of micronutrient status and metabolic health emerge as pivotal in COVID-19 pathogenesis and the immune system's response. Metabolic disruption, proceeding from modifiable factors, has been proposed as a significant risk factor accounting for infection susceptibility, disease severity and risk for post-COVID complications. Metabolomics, the comprehensive study and quantification of intermediates and products of metabolism, is a rapidly evolving field and a novel tool in biomarker discovery. In this article, we propose that leveraging insulin resistance biomarkers along with biomarkers of micronutrient deficiencies, will allow for a diagnostic window and provide functional therapeutic targets. Specifically, metabolomics can be applied as: a. At-home test to assess the risk of infection and propose nutritional support, b. A screening tool for high-risk COVID-19 patients to develop serious illness during hospital admission and prioritize medical support, c(i). A tool to match nutritional support with specific nutrient requirements for mildly ill patients to reduce the risk for hospitalization, and c(ii). for critically ill patients to reduce recovery time and risk of post-COVID complications, d. At-home test to monitor metabolic health and reduce post-COVID symptomatology. Metabolic rewiring offers potential virtues towards disease prevention, dissection of high-risk patients, taking actionable therapeutic measures, as well as shielding against post-COVID syndrome.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

Untargeted metabolomics and transcriptomics identified glutathione metabolism disturbance and PCS and TMAO as potential biomarkers for ER stress in lung

Endoplasmic reticulum (ER) stress is a cellular state that results from the overload of unfolded/misfolded protein in the ER that, if not resolved properly, can lead to cell death. Both acute lung infections and chronic lung diseases have been found related to ER stress. Yet no study has been presented integrating metabolomic and transcriptomic data from total lung in interpreting the pathogenic state of ER stress. Total mouse lungs were used to perform LC-MS and RNA sequencing in relevance to ER stress. Untargeted metabolomics revealed 16 metabolites of aberrant levels with statistical significance while transcriptomics revealed 1593 genes abnormally expressed. Enrichment results demonstrated the injury ER stress inflicted upon lung through the alteration of multiple critical pathways involving energy expenditure, signal transduction, and redox homeostasis. Ultimately, we have presented p-cresol sulfate (PCS) and trimethylamine N-oxide (TMAO) as two potential ER stress biomarkers. Glutathione metabolism stood out in both omics as a notably altered pathway that believed to take important roles in maintaining the redox homeostasis in the cells critical for the development and relief of ER stress, in consistence with the existing reports.

Advantages of Studying the Metabolome in Response to Mixed-Macronutrient Challenges and Suggestions for Future Research Designs

Evaluating the postprandial response to a dietary challenge containing all macronutrients-carbohydrates, lipids, and protein-may provide stronger insights of metabolic health than a fasted measurement. Metabolomic profiling deepens the understanding of the homeostatic and adaptive response to a dietary challenge by classifying multiple metabolic pathways and biomarkers. A total of 26 articles were identified that measure the human blood metabolome or lipidome response to a mixed-macronutrient challenge. Most studies were cross-sectional, exploring the baseline and postprandial response to the dietary challenge. Large variations in study designs were reported, including the macronutrient and caloric composition of the challenge and the delivery of the challenge as a liquid shake or a solid meal. Most studies utilized a targeted metabolomics platform, assessing only a particular metabolic pathway, however, several studies utilized global metabolomics and lipidomics assays demonstrating the expansive postprandial response of the metabolome. The postprandial response of individual amino acids was largely dependent on the amino acid composition of the test meal, with the exception of alanine and proline, 2 nonessential amino acids. Long-chain fatty acids and unsaturated long-chain acylcarnitines rapidly decreased in response to the dietary challenges, representing the switch from fat to carbohydrate oxidation. Studies were reviewed that assessed the metabolome response in the context of obesity and metabolic diseases, providing insight on how weight status and disease influence the ability to cope with a nutrient load and return to homeostasis. Results demonstrate that the flexibility to respond to a substrate load is influenced by obesity and metabolic disease and flexibility alterations will be evident in downstream metabolites of fat, carbohydrate, and protein metabolism. In response, we propose suggestions for standardization between studies with the potential of creating a study exploring the postprandial response to a multitude of challenges with a variety of macronutrients.

A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk

The dietary shift from animal protein (AP) to plant protein (PP) sources is encouraged for both environmental and health reasons. For instance, PPs are associated with lower cardiovascular and diabetes risks compared with APs, although the underlying mechanisms mostly remain unknown. Metabolomics is a valuable tool for globally and mechanistically characterizing the impact of AP and PP intake, given its unique ability to provide integrated signatures and specific biomarkers of metabolic effects through a comprehensive snapshot of metabolic status. This scoping review is aimed at gathering and analyzing the available metabolomics data associated with PP- and AP-rich diets, and discusses the metabolic effects underlying these metabolomics signatures and their potential implication for cardiometabolic health. We selected 24 human studies comparing the urine, plasma, or serum metabolomes associated with diets with contrasted AP and PP intakes. Among the 439 metabolites reported in those studies as able to discriminate AP- and PP-rich diets, 46 were considered to provide a robust level of evidence, according to a scoring system, especially amino acids (AAs) and AA-related products. Branched-chain amino acids, aromatic amino acids (AAAs), glutamate, short-chain acylcarnitines, and trimethylamine-N-oxide, which are known to be related to an increased cardiometabolic risk, were associated with AP-rich diets, whereas glycine (rather related to a reduced risk) was associated with PP-rich diets. Tricarboxylic acid (TCA) cycle intermediates and products from gut microbiota AAA degradation were also often reported, but the direction of their associations differed across studies. Overall, AP- and PP-rich diets result in different metabolomics signatures, with several metabolites being plausible candidates to explain some of their differential associations with cardiometabolic risk. Additional studies specifically focusing on protein type, with rigorous intake control, are needed to better characterize the associated metabolic phenotypes and understand how they could mediate differential AP and PP effects on cardiometabolic risk.

Distinct metabolite profiles of adiposity indices and their relationships with habitual diet in young adults

BACKGROUND AND AIMS

Obesity is characterized as overall or regional adiposity accumulation. However, the metabolic status underlying fat accumulation was not well understood. We sought to identify metabolite profiles based on their correlations with body mass index (BMI), body fat percentage (BFP), waist circumference (WC), and visceral adiposity index (VAI) in young Chinese adults (19-37 years old), and their associations with dietary consumption were also explored.

METHODS AND RESULTS

A total of 86 plasma samples were analyzed using untargeted lipidomics and metabolomics approaches. Metabolite profiles of adiposity indices were identified using random forest modelling. Ridge regression was used to generate metabolite scores. Overall, 30, 46, 30, and 20 metabolites correlated with BMI, BFP, WC, and VAI, respectively, which resulted in metabolite scores for each index. Top three enriched categories of the identified metabolites were glycerophospholipids, glycerolipids, and sphingolipids, with some specific metabolites (such as phosphatidylserine (37:2), phatidylethanolamine (42:4), and ceramide (40:0)) exclusively associated with overall adiposity, and some other metabolites exclusively associated with abdominal adiposity indices, e.g., triradylglycerol (45:0, 52:4, and 35:0) and diacylglycerol (38:4, 36:3, and 36:5). Moreover, metabolite scores were negatively associated with the intake of food rich in protein or fiber, while they were positively associated with food rich in carbohydrate, with similar results for adiposity indices.

CONCLUSION

We observed unique metabolite profiles of regional or overall fat deposition in young adults. Glycerophospholipids, glycerolipids, or sphingolipids may be involved in the regulation of adiposity accumulation, affected by dietary exposures.

Circulating Plasma Metabolites and Cognitive Function in a Puerto Rican Cohort

BACKGROUND

Minorities, including mainland Puerto Ricans, are impacted disproportionally by Alzheimer's disease (AD), dementia, and cognitive decline. Studying blood metabolomics in this population has the potential to probe the biological underpinnings of this health disparity.

OBJECTIVE

We performed a comprehensive analysis of circulating plasma metabolites in relation to cognitive function in 736 participants from the Boston Puerto Rican Health Study (BPRHS) who underwent untargeted mass-spectrometry based metabolomics analysis and had undergone a battery of in-person cognitive testing at baseline.

METHODS

After relevant exclusions, 621 metabolites were examined. We used multivariable regression, adjusted for age, sex, education, apolipoprotein E genotype, smoking, and Mediterranean dietary pattern, to identify metabolites related to global cognitive function in our cohort. LASSO machine learning was used in a complementary analysis to identify metabolites that could discriminate good from poor extremes of cognition. We also conducted sensitivity analyses: restricted to participants without diabetes, and to participants with good adherence to Mediterranean diet.

RESULTS

Of 621 metabolites, FDR corrected (p < 0.05) multivariable linear regression identified 3 metabolites positively, and 10 negatively, associated with cognitive function in the BPRHS. In a combination of FDR-corrected linear regression, logistic regression regularized via LASSO, and sensitivity analyses restricted to participants without diabetes, and with good adherence to the Mediterranean diet, β-cryptoxanthin plasma concentration was consistently associated with better cognitive function and N-acetylisoleucine and tyramine O-sulfate concentrations were consistently associated with worse cognitive function.

CONCLUSION

This untargeted metabolomics study identified potential biomarkers for cognitive function in a cohort of Puerto Rican older adults.

Activation of AMP-Activated Protein Kinase-Sirtuin 1 Pathway Contributes to Salvianolic Acid A-Induced Browning of White Adipose Tissue in High-Fat Diet Fed Male Mice

Background: Salvianolic acid A (Sal A), a natural polyphenolic compound extracted from Radix Salvia miltiorrhiza (Danshen), exhibits exceptional pharmacological activities against cardiovascular diseases. While a few studies have reported anti-obesity properties of Sal A, the underlying mechanisms are largely unknown. Given the prevalence of obesity and promising potential of browning of white adipose tissue to combat obesity, recent research has focused on herbal ingredients that may promote browning and increase energy expenditure.

Purpose: The present study was designed to investigate the protective antiobesity mechanisms of Sal A, in part through white adipose browning.

Methods: Both high-fat diet (HFD)-induced obese (DIO) male mice model and fully differentiated C3H10T1/2 adipocytes from mouse embryo fibroblasts were employed in this study. Sal A (20 and 40 mg/kg) was administrated to DIO mice by intraperitoneal injection for 13-weeks. Molecular mechanisms mediating effects of Sal A were evaluated.

Resluts: Sal A treatment significantly attenuated HFD-induced weight gain and lipid accumulation in epididymal fat pad. Uncoupling protein 1 (UCP-1), a specialized thermogenic protein and marker for white adipocyte browning, was significantly induced by Sal A treatment in both white adipose tissues and cultured adipocytes. Further mechanistic investigations revealed that Sal A robustly reversed HFD-decreased AMP-activated protein kinase (AMPK) phosphorylation and sirtuin 1 (SIRT1) expression in mice. Genetically silencing either AMPK or SIRT1 using siRNA abolished UCP-1 upregulation by Sal A. AMPK silencing significantly blocked Sal A-increased SIRT1 expression, while SIRT1 silencing did not affect Sal A-upregulated phosphorylated-AMPK. These findings indicate that AMPK was involved in Sal A-increased SIRT1.

Conclusion: Sal A increases white adipose tissue browning in HFD-fed male mice and in cultured adipocytes. Thus, Sal is a potential natural therapeutic compound for treating and/or preventing obesity.

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.

Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND

The mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study.

METHODS

Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants.

RESULTS

After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR1-sd 1.50, 95% CI 1.30-1.74), WC (OR1-sd 1.46, 95% CI 1.27-1.69), and WHR (OR1-sd 1.54, 95% CI 1.33-1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR1-sd: 1.26, 95% CI 1.07-1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06-0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05-0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32-0.87, p = 0.01).

CONCLUSIONS

Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss.

Stool metabolome-microbiota evaluation among children and adolescents with obesity, overweight, and normal-weight using 1H NMR and 16S rRNA gene profiling

Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using ¹H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

Plasma Metabolomic Profiling in 1391 Subjects with Overweight and Obesity from the SPHERE Study

Overweight and obesity have high prevalence worldwide and assessing the metabolomic profile is a useful approach to study their related metabolic processes. In this study, we assessed the metabolomic profile of 1391 subjects affected by overweight and obesity, enrolled in the frame of the SPHERE study, using a validated LC-MS/MS targeted metabolomic approach determining a total of 188 endogenous metabolites. Multivariable censored linear regression Tobit models, correcting for age, sex, and smoking habits, showed that 83 metabolites were significantly influenced by body mass index (BMI). Among compounds with the highest association, aromatic and branched chain amino acids (in particular tyrosine, valine, isoleucine, and phenylalanine) increased with the increment of BMI, while some glycerophospholipids decreased, in particular some lysophosphatidylcholines (as lysoPC a C18:2) and several acylalkylphosphatidylcholines (as PC ae C36:2, PC ae C34:3, PC ae C34:2, and PC ae C40:6). The results of this investigation show that several endogenous metabolites are influenced by BMI, confirming the evidence with the strength of a large number of subjects, highlighting differences among subjects with different classes of obesity and showing unreported associations between BMI and different phosphatidylcholines.

Precision Medicine and Obesity

The highly variable response to obesity therapies justifies the search for treatment strategies that are best suited to individual patients to enhance their effectiveness and tolerability via precision medicine. Precision medicine development in recent years has been driven by the emergence of powerful methods to characterize patients ("omic" assays). Current available information has revealed that there are numerous intermediary processes that contribute to obesity and have provided a framework for partially comprehending the mechanisms behind the heterogeneity of obesity and its clinical consequences. Some of these processes have or are currently being targeted to individualize obesity therapy with some success.