Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes

COVID-19 and Comorbidities: What Has Been Unveiled by Metabolomics?

The COVID-19 pandemic has brought about diverse impacts on the global population. Individuals with comorbidities were more susceptible to the severe symptoms caused by the virus. Within the crisis scenario, metabolomics represents a potential area of science capable of providing relevant information for understanding the metabolic pathways associated with the intricate interaction between the viral disease and previous comorbidities. This work aims to provide a comprehensive description of the scientific production pertaining to metabolomics within the specific context of COVID-19 and comorbidities, while highlighting promising areas for exploration by those interested in the subject. In this review, we highlighted the studies of metabolomics that indicated a variety of metabolites associated with comorbidities and COVID-19. Furthermore, we observed that the understanding of the metabolic processes involved between comorbidities and COVID-19 is limited due to the urgent need to report disease outcomes in individuals with comorbidities. The overlap of two or more comorbidities associated with the severity of COVID-19 hinders the comprehension of the significance of each condition. Most identified studies are observational, with a restricted number of patients, due to challenges in sample collection amidst the emergent situation.

Metabolomic signatures associated with weight gain and psychosis spectrum diagnoses: A pilot study

Psychosis spectrum disorders (PSDs), as well as other severe mental illnesses where psychotic features may be present, like bipolar disorder, are associated with intrinsic metabolic abnormalities. Antipsychotics (APs), the cornerstone of treatment for PSDs, incur additional metabolic adversities including weight gain. Currently, major gaps exist in understanding psychosis illness biomarkers, as well as risk factors and mechanisms for AP-induced weight gain. Metabolomic profiles may identify biomarkers and provide insight into the mechanistic underpinnings of PSDs and antipsychotic-induced weight gain. In this 12-week prospective naturalistic study, we compared serum metabolomic profiles of 25 cases within approximately 1 week of starting an AP to 6 healthy controls at baseline to examine biomarkers of intrinsic metabolic dysfunction in PSDs. In 17 of the case participants with baseline and week 12 samples, we then examined changes in metabolomic profiles over 12 weeks of AP treatment to identify metabolites that may associate with AP-induced weight gain. In the cohort with pre-post data (n = 17), we also compared baseline metabolomes of participants who gained ≥5% baseline body weight to those who gained <5% to identify potential biomarkers of antipsychotic-induced weight gain. Minimally AP-exposed cases were distinguished from controls by six fatty acids when compared at baseline, namely reduced levels of palmitoleic acid, lauric acid, and heneicosylic acid, as well as elevated levels of behenic acid, arachidonic acid, and myristoleic acid (FDR < 0.05). Baseline levels of the fatty acid adrenic acid was increased in 11 individuals who experienced a clinically significant body weight gain (≥5%) following 12 weeks of AP exposure as compared to those who did not (FDR = 0.0408). Fatty acids may represent illness biomarkers of PSDs and early predictors of AP-induced weight gain. The findings may hold important clinical implications for early identification of individuals who could benefit from prevention strategies to reduce future cardiometabolic risk, and may lead to novel, targeted treatments to counteract metabolic dysfunction in PSDs.

Systematic metabolomic studies identified adult adiposity biomarkers with acetylglycine associated with fat loss in vivo

Obesity is associated with various adverse health outcomes. Body fat (BF) distribution is recognized as an important factor of negative health consequences of obesity. Although metabolomics studies, mainly focused on body mass index (BMI) and waist circumference, have explored the biological mechanisms involved in the development of obesity, these proxy composite measures are not accurate and cannot reflect BF distribution, and thus may hinder accurate assessment of metabolic alterations and differential risk of metabolic disorders among individuals presenting adiposity differently throughout the body. Thus, the exact relations between metabolites and BF remain to be elucidated. Here, we aim to examine the associations of metabolites and metabolic pathways with BF traits which reflect BF distribution. We performed systematic untargeted serum metabolite profiling and dual-energy X-ray absorptiometry (DXA) whole body fat scan for 517 Chinese women. We jointly analyzed DXA-derived four BF phenotypes to detect cross-phenotype metabolite associations and to prioritize important metabolomic factors. Topology-based pathway analysis was used to identify important BF-related biological processes. Finally, we explored the relationships of the identified BF-related candidate metabolites with BF traits in different sex and ethnicity through two independent cohorts. Acetylglycine, the top distinguished finding, was validated for its obesity resistance effect through in vivo studies of various diet-induced obese (DIO) mice. Eighteen metabolites and fourteen pathways were discovered to be associated with BF phenotypes. Six of the metabolites were validated in varying sex and ethnicity. The obesity-resistant effects of acetylglycine were observed to be highly robust and generalizable in both human and DIO mice. These findings demonstrate the importance of metabolites associated with BF distribution patterns and several biological pathways that may contribute to obesity and obesity-related disease etiology, prevention, and intervention. Acetylglycine is highlighted as a potential therapeutic candidate for preventing excessive adiposity in future studies.

Metabolome-Wide Associations of Gestational Weight Gain in Pregnant Women with Overweight and Obesity

Excessive gestational weight gain (GWG) is associated with adverse pregnancy outcomes. This metabolome-wide association study aimed to identify metabolomic markers for GWG. This longitudinal study included 39 Black and White pregnant women with a prepregnancy body mass index (BMI) of ≥ 25 kg/m2. Untargeted metabolomic profiling was performed using fasting plasma samples collected at baseline (mean: 12.1 weeks) and 32 weeks of gestation. The associations of metabolites at each time point and changes between the two time points with GWG were examined by linear and least absolute shrinkage and selection operator (LASSO) regression analyses. Pearson correlations between the identified metabolites and cardiometabolic biomarkers were examined. Of the 769 annotated metabolites, 88 metabolites at 32 weeks were individually associated with GWG, with four (phosphatidylcholine (PC) 34:4, triacylglycerol (TAG) 52:6, arachidonic acid, isoleucine) jointly associated with GWG (area under the receiver operating characteristic curve (AUC) for excessive GWG: 0.80, 95% CI: 0.67, 0.93). No correlations were observed between the 88 metabolites and insulin, C-peptide, and high-sensitivity C-reactive protein at 32 weeks. Twelve metabolites at baseline (AUC for excessive GWG: 0.80, 95% CI: 0.62, 0.99) and three metabolite changes (AUC for excessive GWG: 0.73, 95% CI: 0.44, 1.00) were jointly associated with GWG. We identified novel metabolites in the first and third trimesters associated with GWG, which may shed light on the pathophysiology of GWG.

Asiatic acid alleviates liver fibrosis via multiple signaling pathways based on integrated network pharmacology and lipidomics

Liver fibrosis is characterized by the abnormal deposition of the extracellular matrix with a severe inflammatory response and/or metabolic disorder. Asiatic acid (AA), a natural compound derived from Centella asiatica, exhibited potent anti-fibrosis effects. This investigation first confirmed the anti-fibrosis effects of AA in TGF-β-LX-2 cells and CCl₄-induced liver fibrosis mice, and then sought to elucidate a novel mechanism of action by integrating network pharmacology and lipidomics. Network pharmacology was used to find potential targets of AA, while lipidomics was used to identify differential metabolites between fibrosis and recovered cohorts. AA could suppress hepatic stellate cell activation in vitro and improve liver fibrosis in vivo. Network pharmacology unveiled the genes involved in pathways in cancer, peroxisome proliferators-activated receptors signaling pathway, and arachidonic acid metabolism pathway. Furthermore, five key genes were found in the both human and mouse databases, indicating that arachidonic acid metabolism was important. Changes in lyso-phosphocholine (22:5), prostaglandin F2α, and other related lipid metabolites also suggested the involvement of arachidonic acid metabolism the anti-fibrotic effect. In summary, our integrated strategies demonstrated that AA targeted multiple targets and impeded the progression of liver fibrosis by ameliorating arachidonic acid metabolism.

Metabotyping for Precision Nutrition and Weight Management: Hype or Hope?

PURPOSE OF REVIEW

Precision nutrition requires a solid understanding of the factors that determine individual responses to dietary treatment. We review the current state of knowledge in identifying human metabotypes - based on circulating biomarkers - that can predict weight loss or other relevant physiological outcomes in response to diet treatment.

RECENT FINDINGS

Not many studies have been conducted in this area and the ones identified here are heterogeneous in design and methodology, and therefore difficult to synthesize and draw conclusions. The basis of the creation of metabotypes varies widely, from using thresholds for a single metabolite to using complex algorithms to generate multi-component constructs that include metabolite and genetic information. Furthermore, available studies are a mix of hypothesis-driven and hypothesis-generating studies, and most of them lack experimental testing in human trials. Although this field of research is still in its infancy, precision-based dietary intervention strategies focusing on the metabotype group level hold promise for designing more effective dietary treatments for obesity.

Altered oxylipin levels in human vitreous indicate imbalance in pro-/anti-inflammatory homeostasis in proliferative diabetic retinopathy

Proliferative diabetic retinopathy (PDR) is an advanced stage of diabetic retinopathy (DR), characterized by retinal neovascularization. It is a progressive fundus disease and a severe complication of diabetes that causes vision impairment. Hyperglycemia-induced persistent low-grade inflammation is a crucial factor underlying the pathogenesis of DR-associated damage and contributing to the progression of PDR. Highly enriched polyunsaturated fatty acids (PUFAs) in the retina are precursors to oxidized metabolites, namely, oxylipins, which exert pro-inflammatory or anti-inflammatory (resolving) effects under different pathological conditions and have been implicated in diabetes. To evaluate differences in oxylipin levels in the vitreous obtained from PDR and non-diabetic subjects, we performed a targeted assessment of oxylipins. A total of 41 patients with PDR and 22 non-diabetic control subjects were enrolled in this study. Vitreous humor obtained during routinely scheduled vitrectomy underwent a targeted but unbiased screening for oxylipins using mass spectrometry-based lipidomics. We found 21 oxylipins showing statistically significant differences in their levels between PDR and non-diabetic subjects (p < 0.05). Lipoxygenase (LOX)- and cytochrome P450 (CYP)- derived oxylipins were the most affected, while cyclooxygenase (COX) oxylipins were affected to a lesser extent. When categorized by their precursor PUFAs, ±19,20-EpDPE, a CYP product of docosahexaenoic acid (DHA) and 12S-HETE, a LOX product of arachidonic acid (ARA), were increased by the largest magnitude. Moreover, of these 21 oxylipins, 7 were considered as potential biomarkers for discriminating PDR patients from the non-diabetic controls. Our results indicate that altered oxylipin levels in the vitreous implicate an underlying imbalanced inflammation-resolution homeostasis in PDR.

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.

Gestational diabetes mellitus is associated with the neonatal gut microbiota and metabolome

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic disease that occurs in pregnant women and increases the risk for the development of diabetes. The relationship between GDM and meconium microbiota and metabolome remains incompletely understood.

METHODS

Four hundred eighteen mothers (147 women with GDM and 271 normal pregnant women) and their neonates from the GDM Mother and Child Study were included in this study. Meconium microbiota were profiled by 16S rRNA gene sequencing. Meconium and maternal serum metabolome were examined by UPLC-QE.

RESULTS

Microbial communities in meconium were significantly altered in neonates from the GDM mothers. A reduction in alpha diversity was observed in neonates of GDM mothers. At the phylum level, the abundance of Firmicutes and Proteobacteria changed significantly in neonates of GDM mothers. Metabolomic analysis of meconium showed that metabolic pathways including taurine and hypotaurine metabolism, pyrimidine metabolism, beta-alanine metabolism, and bile acid biosynthesis were altered in GDM subjects. Several changed metabolites varying by the similar trend across the maternal serum and neonatal meconium were observed.

CONCLUSION

Altogether, these findings suggest that GDM could alter the serum metabolome and is associated with the neonatal meconium microbiota and metabolome, highlighting the importance of maternal factors on early-life metabolism.

Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.)

Oat (Avena sativa L.) seed is a rich resource of beneficial lipids, soluble fiber, protein, and antioxidants, and is considered a healthful food for humans. Little is known regarding the genetic controllers of variation for these compounds in oat seed. We characterized natural variation in the mature seed metabolome using untargeted metabolomics on 367 diverse lines and leveraged this information to improve prediction for seed quality traits. We used a latent factor approach to define unobserved variables that may drive covariance among metabolites. One hundred latent factors were identified, of which 21% were enriched for compounds associated with lipid metabolism. Through a combination of whole-genome regression and association mapping, we show that latent factors that generate covariance for many metabolites tend to have a complex genetic architecture. Nonetheless, we recovered significant associations for 23% of the latent factors. These associations were used to inform a multi-kernel genomic prediction model, which was used to predict seed lipid and protein traits in two independent studies. Predictions for 8 of the 12 traits were significantly improved compared to genomic best linear unbiased prediction when this prediction model was informed using associations from lipid-enriched factors. This study provides new insights into variation in the oat seed metabolome and provides genomic resources for breeders to improve selection for health-promoting seed quality traits. More broadly, we outline an approach to distill high-dimensional "omics" data to a set of biologically meaningful variables and translate inferences on these data into improved breeding decisions.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Discovery of Gut Bacteria Specific to Alzheimer's Associated Diseases is a Clue to Understanding Disease Etiology: Meta-Analysis of Population-Based Data on Human Gut Metagenomics and Metabolomics

Alzheimer's disease (AD)-associated sequence (ADAS) of cultured fecal bacteria was discovered in human gut targeted screening. This study provides important information to expand our current understanding of the structure/activity relationship of ADAS and putative inhibitors/activators that are potentially involved in ADAS appearance/disappearance. The NCBI database analysis revealed that ADAS presents at a large proportion in American Indian Oklahoman (C&A) with a high prevalence of obesity/diabetes and in colorectal cancer (CRC) patients from the US and China. An Oklahoman non-native group (NNI) showed no ADAS. Comparison of two large US populations reveals that ADAS is more frequent in individuals aged ≥66 and in females. Prevalence and levels of fecal metabolites are altered in the C&A and CRC groups versus controls. Biogenic amines (histamine, tryptamine, tyramine, phenylethylamine, cadaverine, putrescine, agmatine, spermidine) that present in food and are produced by gut microbiota are significantly higher in C&A (e.g., histamine/histidine 95-fold) versus NNI (histamine/histidine 16-fold). The majority of these bio-amines are cytotoxic at concentrations found in food. Inositol phosphate signaling implicated in AD is altered in C&A and CRC. Tryptamine stimulated accumulation of inositol phosphate. The seizure-eliciting tryptamine induced cytoplasmic vacuolization and vesiculation with cell fragmentation. Present additions of ADAS-carriers at different ages including infants led to an ADAS-comprising human sample size of 2,830 from 27 studies from four continents (North America, Australia, Asia, Europe). Levels of food-derived monoamine oxidase inhibitors and anti-bacterial compounds, the potential modulators of ADAS-bacteria growth and biogenic amine production, were altered in C&A versus NNI. ADAS is attributable to potentially modifiable risk factors of AD associated diseases.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

Plasma leptin level mirrors metabolome alterations in young adults

INTRODUCTION

Leptin is known to regulate pathways of energy metabolism, reproduction, and control appetite. Whether plasma leptin levels reflect changes in metabolites of these pathways is unknown.

OBJECTIVES

We aimed to find whether there is an association between leptin levels and levels of metabolites of energy and hormone metabolism.

METHODS

We performed an untargeted metabolomics analysis of plasma from 110 healthy adults (men: women = 1:1; aged 18-40 years), using liquid chromatography-tandem mass spectrometry. Blood samples were collected from all the study subjects in the fasting state. Clinical features and markers of obesity and Type 2 diabetes mellitus (T2DM) were assessed in all. The association between levels of metabolites and clinical and biochemical parameters was identified using the multivariable-adjusted linear regression model and PLS-DA analysis.

RESULTS

The leptin level was found to have a significant association with a substantial number of metabolites in women and men. Leptin level was positively associated with glycocholic acid and arachidic acid, metabolites related to energy metabolisms, pregnanediol-3-glucuronide, a metabolite of progesterone metabolism, and quercetin 3'-sulfate, a diet-derived metabolite. Leptin level was negatively associated with ponasteroside A and barringtogenol C levels. Leptin level was positively correlated with adiponectin and negatively with total calorie intake and levels of triglyceride and very-low-density lipoprotein. Leptin levels were associated with lipid and sex hormone metabolism in women, while metabolites involved in amino acid metabolism were correlated to leptin in men.

CONCLUSION

Our study indicates that leptin level reflects metabolome alterations and hence could be a useful marker to detect early changes in energy and hormone metabolisms.

Latent-period stool proteomic assay of multiple sclerosis model indicates protective capacity of host-expressed protease inhibitors

Diseases are often diagnosed once overt symptoms arise, ignoring the prior latent period when effective prevention may be possible. Experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis, exhibits such disease latency, but the molecular processes underlying this asymptomatic period remain poorly characterized. Gut microbes also influence EAE severity, yet their impact on the latent period remains unknown. Here, we show the latent period between immunization and EAE's overt symptom onset is characterized by distinct host responses as measured by stool proteomics. In particular, we found a transient increase in protease inhibitors that inversely correlated with disease severity. Vancomycin administration attenuated both EAE symptoms and protease inhibitor induction potentially by decreasing immune system reactivity, supporting a subset of the microbiota's role in modulating the host's latent period response. These results strengthen previous evidence of proteases and their inhibitors in EAE and highlight the utility stool-omics for revealing complex, dynamic biology.

Study on the Antihypertensive Mechanism of Astragalus membranaceus and Salvia miltiorrhiza Based on Intestinal Flora-Host Metabolism

Our previous studies have shown that the combination of Astragalus membranaceus and Salvia miltiorrhiza (HD) had a good antihypertensive effect, but its potential mechanism remained unclear. This study aimed to investigate the role of intestinal flora and serum metabolism induced by HD against hypertension. 16 spontaneous hypertensive rats (SHRs) were divided into HD group (5.9 g/kg) and model group (M) (normal saline), with eight Wistar-Kyoto (WKY) rats as control group (W) (normal saline). Rats were fed by gavage once a day for 28 days. The changes of intestinal flora and serum metabolism were analyzed by 16S rDNA sequencing and LC-MS/MS assay. HD decreased blood pressure steadily, improved the structure and composition of imbalance flora in SHRs, increased the abundance and diversity of flora, and decreased flora Firmicutes to Bacteroidetes (F/B) ratio. Rumen bacterium NK4A214, Clostridium sp. MC 40 increased remarkably in M group. Akkermansia, Akkermansia muciniphila, and Lactobacillus intestinalis increased significantly in HD group, which were functionally related to the significant increase of Lachnoclostridium, Faecalibaculum, and Lactobacillus reuteri in W group, which were all probiotics producing butyric acid, lactic acid, and regulating inflammation and other antihypertensive related factors. HD also changed the serum metabolic pattern of SHRs. 16 potential biomarkers related to inflammation, vasodilation, steroid hormones, oxidative stress, and etc. changed significantly, mainly enriched in arachidonic acid metabolism, tryptophan metabolism, steroid hormone biosynthesis, and glutathione metabolism. The correlation analysis demonstrated that the dominant genius and species in three groups were highly correlated with steroid hormone biosynthesis, arachidonic acid metabolism, tryptophan metabolism, and vitamin B6 metabolism. Our research indicated that HD had a good antihypertensive effect, which may be driven by the protective intestinal flora and beneficial metabolites induced by it, and the metabolites were closely related to the changes of intestinal flora. It provided new insights for the antihypertensive mechanism of HD.

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

INTRODUCTION

Obesity is a disorder characterized by a disproportionate increase in body weight in relation to height, mainly due to the accumulation of fat, and is considered a pandemic of the present century by many international health institutions. It is associated with several non-communicable chronic diseases, namely, metabolic syndrome, type 2 diabetes mellitus (T2DM), cardiovascular diseases (CVD), and cancer. Metabolomics is a useful tool to evaluate changes in metabolites due to being overweight and obesity at the body fluid and cellular levels and to ascertain metabolic changes in metabolically unhealthy overweight and obese individuals (MUHO) compared to metabolically healthy individuals (MHO).

OBJECTIVES

We aimed to conduct a systematic review (SR) of human studies focused on identifying metabolomic signatures in obese individuals and obesity-related metabolic alterations, such as inflammation or oxidative stress.

METHODS

We reviewed the literature to identify studies investigating the metabolomics profile of human obesity and that were published up to May 7th, 2019 in SCOPUS and PubMed through an SR. The quality of reporting was evaluated using an adapted of QUADOMICS.

RESULTS

Thirty-three articles were included and classified according to four types of approaches. (i) studying the metabolic signature of obesity, (ii) studying the differential responses of obese and non-obese subjects to dietary challenges (iii) studies that used metabolomics to predict weight loss and aimed to assess the effects of weight loss interventions on the metabolomics profiles of overweight or obese human subjects (iv) articles that studied the effects of specific dietary patterns or dietary compounds on obesity-related metabolic alterations in humans.

CONCLUSION

The present SR provides state-of-the-art information about the use of metabolomics as an approach to understanding the dynamics of metabolic processes involved in human obesity and emphasizes metabolic signatures related to obesity phenotypes.

The relationship between the effect of matured hop extract and physical activity on reducing body fat: re-analysis of data from a randomized, double-blind, placebo-controlled parallel group study

BACKGROUND

We recently reported that successive ingestion of matured hop extract (MHE), produced by oxidation of hops, results in a reduction of body fat in healthy overweight participants. A combined effect of MHE and physical activity on body fat has not been investigated. Thus, we re-analyzed data from the previous study to explore the relationship between the effect of MHE and walking as an index of physical activity.

METHODS

This analysis uses existing data from a randomized, double-blind, placebo-controlled parallel group study in which MHE (active) or placebo was given for 12 w to 200 healthy overweight Japanese, from May to December 2014. Correlation between the change in abdominal fat areas at 12 w and the number of steps taken per day was tested by Spearman's correlation coefficient test. The subjects were stratified using the average number of steps per day of Japanese into walking less and walking more subgroups (WL and WM, respectively) as follows: placebo (WL, n = 43; WM, n = 44) and active (WL, n = 49; WM, n = 42). Reductions in total, visceral, and subcutaneous fat area (TFA, VFA and SFA, respectively) were evaluated. The interaction effect between ingestion (active/placebo) and walking (WL/WM) was analyzed using two-way analysis of variance (ANOVA).

RESULTS

There was a significant negative correlation between the change in VFA and daily steps taken in the active group (r = - 0.208, P = 0.048). No significant correlation in TFA or SFA. Although the interaction effect in TFA was not significant, the main effect of ingestion was significant (P = 0.045). In contrast, the interaction effect in VFA was suggested to be synergistic (P = 0.055).

CONCLUSION

The results suggested that MHE ingestion combined with light intensity exercise would induce a greater reduction in VFA which would be beneficial for obese or overweight individuals in reducing obesity and obesity-related diseases.

TRIAL REGISTRATION

UMIN-CTR UMIN000014185 registered 6 June 2014.