The Relationship between Branched-Chain Amino Acid Related Metabolomic Signature and Insulin Resistance: A Systematic Review

Associations of childhood BMI, general and visceral fat mass with metabolite profiles at school-age

BACKGROUND

Childhood obesity increases metabolic disease risk. Underlying mechanisms remain unknown. We examined associations of body mass index (BMI), total body fat mass, and visceral fat mass with serum metabolites at school-age, and explored whether identified metabolites improved the identification of children at risk of a metabolically unhealthy phenotype.

METHODS

We performed a cross-sectional analysis among 497 children with a mean age of 9.8 (95% range 9.1, 10.6) years, participating in a population-based cohort study. We measured BMI, total body fat mass using DXA, and visceral fat mass using MRI. Serum concentrations of amino-acids, non-esterified-fatty-acids, phospholipids, and carnitines were determined using LC-MS/MS. Children were categorized as metabolically healthy or metabolically unhealthy, according to BMI, blood pressure, lipids, glucose, and insulin levels.

RESULTS

Higher BMI and total body fat mass were associated with altered concentrations of branched-chain amino-acids, essential amino-acids, and free carnitines. Higher BMI was also associated with higher concentrations of aromatic amino-acids and alkyl-lysophosphatidylcholines (FDR-corrected p-values < 0.05). The strongest associations were present for Lyso.PC.a.C14.0 and SM.a.C32.2 (FDR-corrected p-values < 0.01). Higher visceral fat mass was only associated with higher concentrations of 6 individual metabolites, particularly Lyso.PC.a.C14.0, PC.aa.C32.1, and SM.a.C32.2. We selected 15 metabolites that improved the prediction of a metabolically unhealthy phenotype, compared to BMI only (AUC: BMI: 0.59 [95% CI 0.47,0.71], BMI + Metabolites: 0.91 [95% CI 0.85,0.97]).

CONCLUSIONS

An adverse childhood body fat profile, characterized by higher BMI and total body fat mass, is associated with metabolic alterations, particularly in amino acids, phospholipids, and carnitines. Fewer associations were present for visceral fat mass. We identified a metabolite profile that improved the identification of impaired cardiometabolic health in children, compared to BMI only.

Branched-Chain and Aromatic Amino Acids, Type 2 Diabetes, and Cardiometabolic Risk Factors among Puerto Rican Adults

(1) Background: Branched-chain and aromatic amino acids (BCAAs/AAAs) have been considered as markers of type 2 diabetes (T2D); however, studies on associations between these metabolites and T2D and cardiometabolic traits in Hispanic populations are limited. The aim of this study was to examine the associations between baseline BCAAs (isoleucine, leucine, valine)/AAAs (phenylalanine, tyrosine) and prevalent and incident T2D, as well as baseline and longitudinal (2 year) changes in cardiometabolic traits (measures of glycemia, dyslipidemia, inflammation, and obesity) in two large cohorts of adults of Puerto Rican descent. (2) Methods: We included participants of the Boston Puerto Rican Health Study (BPRHS, n = 670) and San Juan Overweight Adult Longitudinal study (SOALS, n = 999) with available baseline metabolite and covariate data. T2D diagnosis was defined based on American Diabetes Association criteria. Multivariable logistic (for baseline T2D), Poisson (for incident T2D), and linear (for cardiometabolic traits) regression models were used; cohort-specific results were combined in the meta-analysis and adjusted for multiple comparisons. (3) Results: Higher baseline BCAAs were associated with higher odds of prevalent T2D (OR1SD BCAA score = 1.46, 95% CI: 1.34-1.59, p < 0.0001) and higher risk of incident T2D (IRR1SD BCAA score = 1.24, 95% CI: 1.13-1.37, p < 0.0001). In multivariable longitudinal analysis, higher leucine and valine concentrations were associated with 2-year increase in insulin (beta 1SD leucine = 0.37 mcU/mL, 95% CI: 0.11-0.63, p < 0.05; beta 1SD valine = 0.43 mcU/mL, 95% CI: 0.17-0.68, p < 0.01). Tyrosine was a significant predictor of incident T2D (IRR = 1.31, 95% CI: 1.09-1.58, p < 0.05), as well as 2 year increases in HOMA-IR (beta 1SD tyrosine = 0.13, 95% CI: 0.04-0.22, p < 0.05) and insulin concentrations (beta 1SD tyrosine = 0.37 mcU/mL, 95% CI: 0.12-0.61, p < 0.05). (4) Conclusions: Our results confirmed the associations between BCAAs and prevalent and incident T2D, as well as concurrent measures of glycemia, dyslipidemia, and obesity, previously reported in predominantly White and Asian populations. Baseline leucine, valine, and tyrosine were predictors of 2 year increases in insulin, whereas tyrosine was a significant predictor of deteriorating insulin resistance over time. Our study suggests that BCAAs and tyrosine could serve as early markers of future glycemic changes in Puerto Ricans.

Gut microbiome and metabolome alterations in traditional Chinese medicine damp-heat constitution following treatment with a Chinese patent medicine and lifestyle intervention

BACKGROUND

The gut microbiota is crucial in human health and diseases. Traditional Chinese Medicine Constitution (TCMC) divides people into those with a balanced constitution (Ping-he [PH]) and those with an unbalanced constitution. Dampness-heat constitution (Shi-re [SR]) is a common unbalanced constitution in the Chinese population and is susceptible to diseases. However, unbalanced constitutions can be regulated by Chinese medicine and lifestyle interventions in clinical practice. Ermiao Pill (EMP) is a Chinese medicine known for clearing heat and draining dampness and improving SR. However, the efficacy and mechanism of EMP are unclear.

HYPOTHESIS/PURPOSE

To determine alterations in the gut microbiota and metabolome in SR and any changes after EMP treatment combined with lifestyle intervention.

STUDY DESIGN

Randomized clinical trial.

METHODS

We enrolled 112 healthy SR individuals and evaluated the efficacy of EMP along with lifestyle interventions. We further assessed serum cytokine levels, serum and urinary metabolomes, and the gut microbiota by 16S rRNA gene sequencing analysis before and after the EMP and lifestyle interventions.

RESULTS

107 SR individuals (55 in the intervention group and 52 in the control group) completed the 1-month-intervention and 1-year-follow-up. The intervention group significantly improved their health status within 1 month, with a reduced SR symptom score, and the efficacy lasted to the 1-year follow-up. The control group needed a further 6 months to reduce the SR symptom score. The gut microbiota of PH individuals was more diverse and had significantly higher proportions of many bacterial species than the SR. Microbiota co-occurrence network analysis showed that SR enriches metabolites correlating with microbial community structure, consistent with traits of healthy SR-enriched microbiota.

CONCLUSION

EMP combined with lifestyle intervention produced health benefits in SR individuals. Our study indicates a pivotal role of gut microbiota and metabolome alterations in distinguishing between healthy SR and PH. Furthermore, the study reveals structural changes of gut microbiota and metabolites induced by EMP and lifestyle intervention. The treatment enriched the number of beneficial bacteria, such as Akkermansia muciniphila and Lactobacillus in the gut. Our findings provide a strong indication that several metabolite factors are associated with the gut microbiota. Moreover, the gut microbiome and metabolome might be powerful tools for TCMC diagnosis and personalized therapy.

Association between preoperative persistent hyperglycemia and postoperative delirium in geriatric hip fracture patients

BACKGROUND

The management of preoperative blood glucose levels in reducing the incidence of postoperative delirium (POD) remains controversial. This study aims to investigate the impact of preoperative persistent hyperglycemia on POD in geriatric patients with hip fractures.

METHODS

This retrospective cohort study analyzed medical records of patients who underwent hip fracture surgery at a tertiary medical institution between January 2013 and November 2023. Patients were categorized based on preoperative hyperglycemia (hyperglycemia defined as ≥ 6.1mmol/L), clinical classification of hyperglycemia, and percentile thresholds. Multivariate logistic regression and propensity score matching analysis (PSM) were employed to assess the association between different levels of preoperative glucose and POD. Subgroup analysis was conducted to explore potential interactions.

RESULTS

A total of 1440 patients were included in this study, with an incidence rate of POD at 19.1% (275/1440). Utilizing multiple logistic analysis, we found that patients with hyperglycemia had a 1.65-fold increased risk of experiencing POD compared to those with normal preoperative glucose levels (95% CI: 1.17-2.32). Moreover, a significant upward trend was discerned in both the strength of association and the predicted probability of POD with higher preoperative glucose levels. PSM did not alter this trend, even after meticulous adjustments for potential confounding factors. Additionally, when treating preoperative glucose levels as a continuous variable, we observed a 6% increase in the risk of POD (95% CI: 1-12%) with each 1mmol/L elevation in preoperative glucose levels.

CONCLUSIONS

There exists a clear linear dose-response relationship between preoperative blood glucose levels and the risk of POD. Higher preoperative hyperglycemia was associated with a greater risk of POD.

CLINICAL TRIAL NUMBER

NCT06473324.

Chronic treatment with glucagon-like peptide-1 and glucagon receptor co-agonist causes weight loss-independent improvements in hepatic steatosis in mice with diet-induced obesity

OBJECTIVES

Co-agonists at the glucagon-like peptide-1 and glucagon receptors (GLP1R/GCGR) show promise as treatments for metabolic dysfunction-associated steatotic liver disease (MASLD). Although most co-agonists to date have been heavily GLP1R-biased, glucagon directly acts on the liver to reduce fat content. The aims of this study were to investigate a GCGR-biased co-agonist as treatment for hepatic steatosis in mice.

METHODS

Mice with diet-induced obesity (DIO) were treated with Dicretin, a GLP1/GCGR co-agonist with high potency at the GCGR, Semaglutide (GLP1R monoagonist) or food restriction over 24 days, such that their weight loss was matched. Hepatic steatosis, glucose tolerance, hepatic transcriptomics, metabolomics and lipidomics at the end of the study were compared with Vehicle-treated mice.

RESULTS

Dicretin lead to superior reduction of hepatic lipid content when compared to Semaglutide or equivalent weight loss by calorie restriction. Markers of glucose tolerance and insulin resistance improved in all treatment groups. Hepatic transcriptomic and metabolomic profiling demonstrated many changes that were unique to Dicretin-treated mice. These include some known targets of glucagon signaling and others with as yet unclear physiological significance.

CONCLUSIONS

Our study supports the development of GCGR-biased GLP1/GCGR co-agonists for treatment of MASLD and related conditions.

Characterizing human postprandial metabolic response using multiway data analysis

INTRODUCTION

Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time.

OBJECTIVES

Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles.

METHODS

We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences.

RESULTS

Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state.

CONCLUSION

The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Time-resolved concentrations of serum amino acids, one-carbon metabolites and B-vitamin biomarkers during the postprandial and fasting state: the Postprandial Metabolism in Healthy Young Adults (PoMet) Study

Metabolomics has been utilised in epidemiological studies to investigate biomarkers of nutritional status and metabolism in relation to non-communicable diseases. However, little is known about the effect of prandial status on several biomarker concentrations. Therefore, the aim of this intervention study was to investigate the effect of a standardised breakfast meal followed by food abstinence for 24 h on serum concentrations of amino acids, one-carbon metabolites and B-vitamin biomarkers. Thirty-four healthy subjects (eighteen males and sixteen females) aged 20-30 years were served a breakfast meal (∼500 kcal) after which they consumed only water for 24 h. Blood samples were drawn before and at thirteen standardised timepoints after the meal. Circulating concentrations of most amino acids and metabolites linked to one-carbon metabolism peaked within the first 3 h after the meal. The branched-chain amino acids steadily increased from 6 or 8 hours after the meal, while proline decreased in the same period. Homocysteine and cysteine concentrations immediately decreased after the meal but steadily increased from 3 and 4 hours until 24 h. FMN and riboflavin fluctuated immediately after the meal but increased from 6 h, while folate increased immediately after the meal and remained elevated during the 24 h. Our findings indicate that accurate reporting of time since last meal is crucial when investigating concentrations of certain amino acids and one-carbon metabolites. Our results suggest a need for caution when interpretating studies, which utilise such biomarkers, but do not strictly control for time since the last meal.

PNPLA3 Genotype and Dietary Fat Modify Concentrations of Plasma and Fecal Short Chain Fatty Acids and Plasma Branched-Chain Amino Acids

The GG genotype of the Patatin-like phosphatase domain-containing 3 (PNPLA3), dietary fat, short-chain fatty acids (SCFA) and branched-chain amino acids (BCAA) are linked with non-alcoholic fatty liver disease. We studied the impact of the quality of dietary fat on plasma (p) and fecal (f) SCFA and p-BCAA in men homozygous for the PNPLA3 rs738409 variant (I148M). Eighty-eight randomly assigned men (age 67.8 ± 4.3 years, body mass index 27.1 ± 2.5 kg/m2) participated in a 12-week diet intervention. The recommended diet (RD) group followed the National and Nordic nutrition recommendations for fat intake. The average diet (AD) group followed the average fat intake in Finland. The intervention resulted in a decrease in total p-SCFAs and iso-butyric acid in the RD group (p = 0.041 and p = 0.002). Valeric acid (p-VA) increased in participants with the GG genotype regardless of the diet (RD, 3.6 ± 0.6 to 7.0 ± 0.6 µmol/g, p = 0.005 and AD, 3.8 ± 0.3 to 9.7 ± 8.5 µmol/g, p = 0.015). Also, genotype relation to p-VA was seen statistically significantly in the RD group (CC: 3.7 ± 0.4 to 4.2 ± 1.7 µmol/g and GG: 3.6 ± 0.6 to 7.0 ± 0.6 µmol/g, p = 0.0026 for time and p = 0.004 for time and genotype). P-VA, unlike any other SCFA, correlated positively with plasma gamma-glutamyl transferase (r = 0.240, p = 0.025). Total p-BCAAs concentration changed in the AD group comparing PNPLA3 CC and GG genotypes (CC: 612 ± 184 to 532 ± 149 µmol/g and GG: 587 ± 182 to 590 ± 130 µmol/g, p = 0.015 for time). Valine decreased in the RD group (p = 0.009), and leucine decreased in the AD group (p = 0.043). RD decreased total fecal SCFA, acetic acid (f-AA), and butyric acid (f-BA) in those with CC genotype (p = 0.006, 0.013 and 0.005, respectively). Our results suggest that the PNPLA3 genotype modifies the effect of dietary fat modification for p-VA, total f-SCFA, f-AA and f-BA, and total p-BCAA.

Metabolomic Changes in Rat Serum after Chronic Exposure to Glyphosate-Based Herbicide

Glyphosate-based herbicides (GBHs) have gained extensive popularity in recent decades. For many years, glyphosate has been regarded as harmless or minimally toxic to mammals due to the absence of its primary target, the shikimic acid pathway in humans. Nonetheless, mounting evidence suggests that glyphosate may cause adverse health effects in humans via other mechanisms. In this study, we described the metabolomic changes in the serum of experimental rats exposed to chronic GBH using the highly sensitive LC-MS/MS technique. We investigated the possible relationship between chronic exposure to GBH and neurological disorders. Our findings suggest that chronic exposure to GBH can alter spatial learning memory and the expression of some important metabolites that are linked to neurophysiological disorders in young rats, with the female rats showing higher susceptibility compared to the males. This indicates that female rats are more likely to show early symptoms of the disorder on exposure to chronic GBH compared to male rats. We observed that four important metabolites (paraxanthine, epinephrine, L-(+)-arginine, and D-arginine) showed significant changes and involvement in neurological changes as suggested by ingenuity pathway analysis. In conclusion, our results indicate that chronic exposure to GBH can increase the risk of developing neurological disorders.

Impaired glucose utilization in the brain of patients with delirium following hip fracture

Alterations in brain energy metabolism have long been proposed as one of several neurobiological processes contributing to delirium. This is supported by previous findings of altered CSF lactate and neuron-specific enolase concentrations and decreased glucose uptake on brain-PET in patients with delirium. Despite this, there are limited data on metabolic alterations found in CSF samples, and targeted metabolic profiling of CSF metabolites involved in energy metabolism has not been performed. The aim of the study was to investigate whether metabolites related to energy metabolism in the serum and CSF of patients with hip fracture are associated with delirium. The study cohort included 406 patients with a mean age of 81 years (standard deviation 10 years), acutely admitted to hospital for surgical repair of a hip fracture. Delirium was assessed daily until the fifth postoperative day. CSF was collected from all 406 participants at the onset of spinal anaesthesia, and serum samples were drawn concurrently from 213 participants. Glucose and lactate in CSF were measured using amperometry, whereas plasma glucose was measured in the clinical laboratory using enzymatic photometry. Serum and CSF concentrations of the branched-chain amino acids, 3-hydroxyisobutyric acid, acetoacetate and β-hydroxybutyrate were measured using gas chromatography-tandem mass spectrometry (GC-MS/MS). In total, 224 (55%) patients developed delirium pre- or postoperatively. Ketone body concentrations (acetoacetate, β-hydroxybutyrate) and branched-chain amino acids were significantly elevated in the CSF but not in serum among patients with delirium, despite no group differences in glucose concentrations. The level of 3-hydroxyisobutyric acid was significantly elevated in both CSF and serum. An elevation of CSF lactate during delirium was explained by age and comorbidity. Our data suggest that altered glucose utilization and a shift to ketone body metabolism occurs in the brain during delirium.

Bridging the Gap from Enterotypes to Personalized Dietary Recommendations: A Metabolomics Perspective on Microbiome Research

Advances in high-throughput DNA sequencing have propelled research into the human microbiome and its link to metabolic health. We explore microbiome analysis methods, specifically emphasizing metabolomics, how dietary choices impact the production of microbial metabolites, providing an overview of studies examining the connection between enterotypes and diet, and thus, improvement of personalized dietary recommendations. Acetate, propionate, and butyrate constitute more than 95% of the collective pool of short-chain fatty acids. Conflicting data on acetate's effects may result from its dynamic signaling, which can vary depending on physiological conditions and metabolic phenotypes. Human studies suggest that propionate has overall anti-obesity effects due to its well-documented chemistry, cellular signaling mechanisms, and various clinical benefits. Butyrate, similar to propionate, has the ability to reduce obesity by stimulating the release of appetite-suppressing hormones and promoting the synthesis of leptin. Tryptophan affects systemic hormone secretion, with indole stimulating the release of GLP-1, which impacts insulin secretion, appetite suppression, and gastric emptying. Bile acids, synthesized from cholesterol in the liver and subsequently modified by gut bacteria, play an essential role in the digestion and absorption of dietary fats and fat-soluble vitamins, but they also interact directly with intestinal microbiota and their metabolites. One study using statistical methods identified primarily two groupings of enterotypes Bacteroides and Ruminococcus. The Prevotella-dominated enterotype, P-type, in humans correlates with vegetarians, high-fiber and carbohydrate-rich diets, and traditional diets. Conversely, individuals who consume diets rich in animal fats and proteins, typical in Western-style diets, often exhibit the Bacteroides-dominated, B-type, enterotype. The P-type showcases efficient hydrolytic enzymes for plant fiber degradation but has limited lipid and protein fermentation capacity. Conversely, the B-type features specialized enzymes tailored for the degradation of animal-derived carbohydrates and proteins, showcasing an enhanced saccharolytic and proteolytic potential. Generally, models excel at predictions but often struggle to fully elucidate why certain substances yield varied responses. These studies provide valuable insights into the potential for personalized dietary recommendations based on enterotypes.

5-Aza-2'-deoxycytidine-mediated DNA hypomethylation with and without concurrent insulin resistance suppresses myotube mitochondrial capacity

Type 2 diabetes is characterized by elevated blood glucose and reduced insulin sensitivity in target tissues. Moreover, reduced mitochondrial metabolism and expressional profile of genes governing mitochondrial metabolism (such as peroxisome proliferator-activated receptor gamma coactivator 1-alpha [PGC-1α]) are also reduced during insulin resistance. Epigenetic regulation via DNA methylation of genes including PGC-1α may contribute to diminished mitochondrial capacity, while hypomethylation of PGC-1α (such as that invoked by exercise) has been associated with increased PGC-1α expression and favorable metabolic outcomes. The purpose of the present report is to characterize the effects of DNA hypomethylation on myotube metabolism and expression of several related metabolic targets. C2C12 myotubes were treated with 5-Aza-2'-deoxycytidine (5-Aza) for either 24 or 72 h both with and without hyperinsulinemic-induced insulin resistance. Mitochondrial and glycolytic metabolism were measured via oxygen consumption and extracellular acidification rate, respectively. Metabolic gene and protein expression were assessed via quantitative real time polymerase chain reaction and western blot analysis, respectively. Though expression of PGC-1α and other related targets remained unaltered, insulin resistance and 5-Aza treatment significantly reduced mitochondrial metabolism. Similarly, peak glycolytic metabolism was diminished by 5-Aza-treated cells, while basal glycolytic metabolism was unaltered. 5-Aza also reduced the expression of branched-chain amino acid (BCAA) catabolic components, however BCAA utilization was enhanced during insulin resistance with 5-Aza treatment. Together the present work provides proof-of-concept evidence of the potential role of DNA methylation in the regulation of mitochondrial metabolism and the potential interactions with insulin resistance in a model of skeletal muscle.

Exploratory analyses on the effect of time since last meal on concentrations of amino acids, lipids, one-carbon metabolites, and vitamins in the Hordaland Health Study

PURPOSE

Dietary intake may have pronounced effects on circulating biomarker concentrations. Therefore, the aim was to provide a descriptive overview of serum metabolite concentrations in relation to time since last meal, focusing on amino acids, lipids, one-carbon metabolites, and biomarkers of vitamin status.

METHODS

We used baseline data from the observational community-based Hordaland Health Study, including 2960 participants aged 46-49 years and 2874 participants aged 70-74 years. A single blood draw was taken from each participant, and time since last meal varied. Estimated marginal geometric mean metabolite concentrations were plotted as a function of time since last meal, up to 7 h, adjusted for age, sex, and BMI.

RESULTS

We observed a common pattern for nearly all amino acids and one-carbon metabolites with highest concentrations during the first 3 h after dietary intake. Homocysteine and cysteine were lowest the 1st hour after a meal, while no patterns were observed for glutamate and glutamic acid. The concentrations of phylloquinone and triglycerides were highest 1 h after dietary intake. Thiamine and thiamine monophosphate concentrations were highest, while flavin mononucleotide concentrations were lowest within the first 2 h after a meal. No clear patterns emerged for the other fat-soluble vitamins, blood lipids, or B-vitamin biomarkers.

CONCLUSION

Our findings suggest that distinguishing between "fasting" and "non-fasting" blood samples may be inadequate, and a more granular approach is warranted. This may have implications for how to account for dietary intake when blood sampling in both clinical and research settings.

Characterization and application of a lactate and branched chain amino acid metabolism related gene signature in a prognosis risk model for multiple myeloma

BACKGROUND

About 10% of hematologic malignancies are multiple myeloma (MM), an untreatable cancer. Although lactate and branched-chain amino acids (BCAA) are involved in supporting various tumor growth, it is unknown whether they have any bearing on MM prognosis.

METHODS

MM-related datasets (GSE4581, GSE136337, and TCGA-MM) were acquired from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Lactate and BCAA metabolism-related subtypes were acquired separately via the R package "ConsensusClusterPlus" in the GSE4281 dataset. The R package "limma" and Venn diagram were both employed to identify lactate-BCAA metabolism-related genes. Subsequently, a lactate-BCAA metabolism-related prognostic risk model for MM patients was constructed by univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. The gene set enrichment analysis (GSEA) and R package "clusterProfiler"were applied to explore the biological variations between two groups. Moreover, single-sample gene set enrichment analysis (ssGSEA), Microenvironment Cell Populations-counter (MCPcounte), and xCell techniques were applied to assess tumor microenvironment (TME) scores in MM. Finally, the drug's IC50 for treating MM was calculated using the "oncoPredict" package, and further drug identification was performed by molecular docking.

RESULTS

Cluster 1 demonstrated a worse prognosis than cluster 2 in both lactate metabolism-related subtypes and BCAA metabolism-related subtypes. 244 genes were determined to be involved in lactate-BCAA metabolism in MM. The prognostic risk model was constructed by CKS2 and LYZ selected from this group of genes for MM, then the prognostic risk model was also stable in external datasets. For the high-risk group, a total of 13 entries were enriched. 16 entries were enriched to the low-risk group. Immune scores, stromal scores, immune infiltrating cells (except Type 17 T helper cells in ssGSEA algorithm), and 168 drugs'IC50 were statistically different between two groups. Alkylating potentially serves as a new agent for MM treatment.

CONCLUSIONS

CKS2 and LYZ were identified as lactate-BCAA metabolism-related genes in MM, then a novel prognostic risk model was built by using them. In summary, this research may uncover novel characteristic genes signature for the treatment and prognostic of MM.

High doses of rosuvastatin induce impaired branched-chain amino acid catabolism and lead to insulin resistance

NEW FINDINGS

What is the central question of this study? Is there a risk of developing diabetes associated with statin treatment? What is the underlying mechanism of the increased incidence rate of new-onset diabetes in patients treated with rosuvastatin? What is the main finding and its importance? Rosuvastatin therapy reduced intraperitoneal glucose tolerance and changed the catabolism of branched-chain amino acid (BCAAs) in white adipose tissue and skeletal muscle. Protein phosphatase 2Cm knockdown completely abolished the effects of insulin and rosuvastatin on glucose absorption. This study provides mechanistic support for recent clinical data on rosuvastatin-related new-onset diabetes and underscores the logic for intervening in BCAA catabolism to prevent the harmful effects of rosuvastatin.

ABSTRACT

Accumulating evidence indicates that patients treated with rosuvastatin have an increased risk of developing new-onset diabetes. However, the underlying mechanism remains unclear. In this study, we administered rosuvastatin (10 mg/kg body weight) to male C57BL/6J mice for 12 weeks and found that oral rosuvastatin dramatically reduced intraperitoneal glucose tolerance. Rosuvastatin-treated mice showed considerably higher serum levels of branched-chain amino acids (BCAAs) than control mice. They also showed dramatically altered expression of BCAA catabolism-related enzymes in white adipose tissue and skeletal muscle, including downregulated mRNA expression of BCAT2 and protein phosphatase 2Cm (PP2Cm) and upregulated mRNA expression of branched-chain ketoacid dehydrogenase kinase (BCKDK). The levels of BCKD in the skeletal muscle were reduced in rosuvastatin-treated mice, which was associated with lower PP2Cm protein levels and increased BCKDK levels. We also investigated the effects of rosuvastatin and insulin administration on glucose metabolism and BCAA catabolism in C2C12 myoblasts. We observed that incubation with insulin enhanced glucose uptake and facilitated BCAA catabolism in C2C12 cells, which was accompanied by elevated Akt and glycogen synthase kinase 3 β (GSK3β) phosphorylation. These effects of insulin were prevented by co-incubation of the cells with 25 μM rosuvastatin. Moreover, the effects of insulin and rosuvastatin administration on glucose uptake and Akt and GSK3β signaling in C2C12 cells were abolished when PP2Cm was knocked down. Although the relevance of these data, obtained with high doses of rosuvastatin in mice, to therapeutic doses in humans remains to be elucidated, this study highlights a potential mechanism for the diabetogenic effects of rosuvastatin, and suggests that BCAA catabolism could be a pharmacological target for preventing the adverse effects of rosuvastatin.

Dietary Patterns Associated with Abnormal Glucose Tolerance following Gestational Diabetes Mellitus: The MyNutritype Study

Abnormal glucose tolerance (AGT), which includes type 2 diabetes and pre-diabetes, is highly prevalent in women post gestational diabetes mellitus (post-GDM). Dietary patterns have been associated with the risk of developing AGT in women post-GDM, but evidence in Asian populations is sparse. This study aimed to determine the association between a posteriori dietary patterns and AGT in women post-GDM. This cross-sectional study recruited 157 women post-GDM (mean age 34.8 years) from Seri Kembangan Health Clinic and Universiti Putra Malaysia. AGT was diagnosed according to the Malaysian Clinical Practice Guidelines using a 75 g 2 h oral glucose tolerance test or HbA1c. Food intake was assessed using the 2014 Malaysian Adult Nutrition Survey food frequency questionnaire. Five dietary patterns were derived using principal component analysis: 'Unhealthy', 'Fish-eggs-fruits-vegetables', 'Cereals-confectionaries', 'Legumes-dairy', and 'Meat-sugar-sweetened-beverages'. After adjusting for sociodemographic characteristics and total energy intake, the 'Cereals-confectionaries' dietary pattern was significantly associated with AGT (adjusted odds ratio 1.536, p = 0.049). Targeted lifestyle modification, including dietary intervention, for women post-GDM is warranted to reduce their risk of AGT and its complications.

PPARβ/δ Agonism with GW501516 Increases Myotube PGC-1α Content and Reduces BCAA Media Content Independent of Changes in BCAA Catabolic Enzyme Expression

Background

Type 2 diabetes is characterized by reduced insulin sensitivity, elevated blood metabolites, and reduced mitochondrial metabolism with reduced expression of genes governing metabolism such as peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α). PGC-1α regulates the expression of branched-chain amino acid (BCAA) metabolism, and thus, increased circulating BCAA in diabetics may be partially explained by reduced PGC-1α expression. PGC-1α functions in-part through interactions with peroxisome proliferator-activated receptor β/δ (PPARβ/δ). The present report examined the effects of the PPARβ/δ agonism on cell metabolism and related gene/protein expression of cultured myotubes, with a primary emphasis on determining the effects of GW on BCAA disposal and catabolic enzyme expression.

Methods

C2C12 myotubes were treated with GW501516 (GW) for up to 24 hours. Mitochondrial and glycolytic metabolism were measured via oxygen consumption and extracellular acidification rate, respectively. Metabolic gene and protein expression were assessed via quantitative real-time polymerase chain reaction (qRT-PCR) and western blot, respectively. Media BCAA content was assessed via liquid chromatography-mass spectrometry (LC/MS).

Results

GW significantly increased PGC-1α protein expression, mitochondrial content, and mitochondrial function. GW also significantly reduced BCAA content within culture media following 24-hour treatment; however, expression of BCAA catabolic enzymes/transporter was unchanged.

Conclusion

These data confirm the ability of GW to increase muscle PGC-1α content and decrease BCAA media content without affecting BCAA catabolic enzymes/transporter. These findings suggest heightened BCAA uptake (and possibly metabolism) may occur without substantial changes in the protein levels of related cell machinery.

Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response

AIMS/HYPOTHESIS

Although insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the probability of successful prevention and intervention. Moreover, treatment efficacy is affected by the genetics of the individual. We used gene expression profiles from a cross-sectional study to identify potential candidate genes for the prediction of diabetes risk and intervention response.

METHODS

Using a multivariate regression model, we linked gene expression profiles of human skeletal muscle and intermuscular adipose tissue (IMAT) to fasting glucose levels and glucose infusion rate. Based on the expression patterns of the top predictive genes, we characterised and compared individual gene expression with clinical classifications using k-nearest neighbour clustering. The predictive potential of the candidate genes identified was validated using muscle gene expression data from a longitudinal intervention study.

RESULTS

We found that genes with a strong association with clinical measures clustered into three distinct expression patterns. Their predictive values for insulin resistance varied substantially between skeletal muscle and IMAT. Moreover, we discovered that individual gene expression-based classifications may differ from classifications based predominantly on clinical variables, indicating that participant stratification may be imprecise if only clinical variables are used for classification. Of the 15 top candidate genes, ST3GAL2, AASS, ARF1 and the transcription factor SIN3A are novel candidates for predicting a refined diabetes risk and intervention response.

CONCLUSION/INTERPRETATION

Our results confirm that disease progression and successful intervention depend on individual gene expression states. We anticipate that our findings may lead to a better understanding and prediction of individual diabetes risk and may help to develop individualised intervention strategies.

Metabolic Signatures Elucidate the Effect of Body Mass Index on Type 2 Diabetes

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Systematic analysis of relationships between plasma branched-chain amino acid concentrations and cardiometabolic parameters: an association and Mendelian randomization study

BACKGROUND

Branched-chain amino acids (BCAAs; valine, leucine, and isoleucine) are essential amino acids that are associated with an increased risk of cardiometabolic diseases (CMD). However, there are still only limited insights into potential direct associations between BCAAs and a wide range of CMD parameters, especially those remaining after correcting for covariates and underlying causal relationships.

METHODS

To shed light on these relationships, we systematically characterized the associations between plasma BCAA concentrations and a large panel of 537 CMD parameters (including atherosclerosis-related parameters, fat distribution, plasma cytokine concentrations and cell counts, circulating concentrations of cardiovascular-related proteins and plasma metabolites) in 1400 individuals from the Dutch population cohort LifeLines DEEP and 294 overweight individuals from the 300OB cohort. After correcting for age, sex, and BMI, we assessed associations between individual BCAAs and CMD parameters. We further assessed the underlying causality using Mendelian randomization.

RESULTS

A total of 838 significant associations were detected for 409 CMD parameters. BCAAs showed both common and specific associations, with the most specific associations being detected for isoleucine. Further, we found that obesity status substantially affected the strength and direction of associations for valine, which cannot be corrected for using BMI as a covariate. Subsequent univariable Mendelian randomization (UVMR), after removing BMI-associated SNPs, identified seven significant causal relationships from four CMD traits to BCAA levels, mostly for diabetes-related parameters. However, no causal effects of BCAAs on CMD parameters were supported.

CONCLUSIONS

Our cross-sectional association study reports a large number of associations between BCAAs and CMD parameters. Our results highlight some specific associations for isoleucine, as well as obesity-specific effects for valine. MR-based causality analysis suggests that altered BCAA levels can be a consequence of diabetes and alteration in lipid metabolism. We found no MR evidence to support a causal role for BCAAs in CMD. These findings provide evidence to (re)evaluate the clinical importance of individual BCAAs in CMD diagnosis, prevention, and treatment.

Dietary Plant Protein Intake Can Reduce Maternal Insulin Resistance during Pregnancy

Evidence suggests that the source of dietary protein may have an impact on insulin resistance, but no studies have explored it in pregnant populations. In this study, we combined a population study and an animal experiment to explore this effect. The population study was conducted with data from NHANES. Multiple linear regression was used to observe the association of protein intake with outcomes, including fasting glucose (GLU), insulin (INS), and HOMA-IR. In the animal experiment, 36 pregnant SD rats in three groups were orally administered 100% animal protein, 50% animal protein and 50% plant protein, or 100% plant protein, respectively. The intervention continued throughout the whole pregnancy. On day 19.5, maternal plasma was collected after overnight fasting, and metabolomics was performed using UPLC-MS. We found plant protein intake was negatively correlated with INS and HOMA-IR in the whole population. During the third trimester, a similar correlation was also observed. The animal experiment also presented the same result. In metabolomic analysis, changes in various metabolites and related pathways including FoxO and mTOR signaling pathways were observed. In conclusion, we found a negative association between dietary plant protein intake and maternal insulin resistance during pregnancy. Changes in some active substances and related metabolic pathways may play an important role.

Plasma metabolomic profiling of dietary patterns associated with glucose metabolism status: The Maastricht Study

BACKGROUND

Glucose metabolism has been reported to be affected by dietary patterns, while the underlying mechanisms involved remain unclear. This study aimed to investigate the potential mediation role of circulating metabolites in relation to dietary patterns for prediabetes and type 2 diabetes.

METHODS

Data was derived from The Maastricht Study that comprised of 3441 participants (mean age of 60 years) with 28% type 2 diabetes patients by design. Dietary patterns were assessed using a validated food frequency questionnaire (FFQ), and the glucose metabolism status (GMS) was defined according to WHO guidelines. Both cross-sectional and prospective analyses were performed for the circulating metabolome to investigate their associations and mediations with responses to dietary patterns and GMS.

RESULTS

Among 226 eligible metabolite measures obtained from targeted metabolomics, 14 were identified to be associated and mediated with three dietary patterns (i.e. Mediterranean Diet (MED), Dietary Approaches to Stop Hypertension Diet (DASH), and Dutch Healthy Diet (DHD)) and overall GMS. Of these, the mediation effects of 5 metabolite measures were consistent for all three dietary patterns and GMS. Based on a 7-year follow-up, a decreased risk for apolipoprotein A1 (APOA1) and docosahexaenoic acid (DHA) (RR 0.60, 95% CI 0.55, 0.65; RR 0.89, 95% CI 0.83, 0.97, respectively) but an increased risk for ratio of ω-6 to ω-3 fatty acids (RR 1.29, 95% CI 1.05, 1.43) of type 2 diabetes were observed from prediabetes, while APOA1 showed a decreased risk of type 2 diabetes from normal glucose metabolism (NGM; RR 0.82, 95% CI 0.75, 0.89).

CONCLUSIONS

In summary, this study suggests that adherence to a healthy dietary pattern (i.e. MED, DASH, or DHD) could affect the GMS through circulating metabolites, which provides novel insights into understanding the biological mechanisms of diet on glucose metabolism and leads to facilitating prevention strategy for type 2 diabetes.

The Beneficial Effect of Cinnamon and Red Capsicum Intake on Postprandial Changes in Plasma Metabolites Evoked by a High-Carbohydrate Meal in Men with Overweight/Obesity

The relationship of high-carbohydrate (HC) meal intake to metabolic syndrome is still not fully explained. Metabolomics has the potential to indicate metabolic pathways altered by HC meals, which may improve our knowledge regarding the mechanisms by which HC meals may contribute to metabolic syndrome development. The fasting and postprandial metabolic response to HC or normo-carbohydrate (NC) meals with/without cinnamon + capsicum intake was evaluated using untargeted metabolomics and compared between normal-weight (NW) and overweight/obese (OW/OB) healthy men. Healthy male participants (age-matched) were divided into two groups (12 subjects per group). One was composed of men with normal weight (NW) and the other of men with overweight/obesity (OW/OB). On separate visits (with 2-3 week intervals), the participants received standardized HC or NC meals (89% or 45% carbohydrates, respectively). Fasting (0 min) and postprandial (30, 60, 120, 180 min) blood were collected for untargeted plasma metabolomics. Based on each metabolic feature's intensity change in time, the area under the curve (AUC) was calculated. Obtained AUCs were analyzed using multivariate statistics. Several metabolic pathways were found dysregulated after an HC meal in people from the OW/OB group but not the NW group. The consumption of HC meals by people with overweight/obesity led to a substantial increase in AUC, mainly for metabolites belonging to phospholipids and fatty acid amides. The opposite was observed for selected sphingolipids. The intake of cinnamon and capsicum normalized the concentration of selected altered metabolites induced by the intake of HC meals. A HC meal may induce an unfavourable postprandial metabolic response in individuals with overweight/obesity, and such persons should avoid HC meals.

Association of Metabolic Signatures with Nonalcoholic Fatty Liver Disease in Pediatric Population

Several adult omics studies have been conducted to understand the pathophysiology of nonalcoholic fatty liver disease (NAFLD). However, the histological features of children are different from those of adults, and the onset and progression of pediatric NAFLD are not fully understood. In this study, we aimed to evaluate the metabolome profile and metabolic pathway changes associated with pediatric NAFLD to elucidate its pathophysiology and to develop machine learning-based NAFLD diagnostic models. We analyzed the metabolic profiles of healthy control, lean NAFLD, overweight control, and overweight NAFLD groups of children and adolescent participants (N = 165) by assessing plasma samples. Additionally, we constructed diagnostic models by applying three machine learning methods (ElasticNet, random forest, and XGBoost) and multiple logistic regression by using NAFLD-specific metabolic features, genetic variants, and clinical data. We identified 18 NAFLD-specific metabolic features and metabolic changes in lipid, glutathione-related amino acid, and branched-chain amino acid metabolism by comparing the control and NAFLD groups in the overweight pediatric population. Additionally, we successfully developed and cross-validated diagnostic models that showed excellent diagnostic performance (ElasticNet and random forest model: area under the receiver operating characteristic curve, 0.95). Metabolome changes in the plasma of pediatric patients with NAFLD are associated with the pathophysiology of the disease and can be utilized as a less-invasive approach to diagnosing the disease.

Targeted Metabolomics Revealed a Sex-Dependent Signature for Metabolic Syndrome in the Mexican Population

Metabolic syndrome (MetS) is a group of several metabolic conditions predisposing to chronic diseases. Individuals diagnosed with MetS are physiologically heterogeneous, with significant sex-specific differences. Therefore, we aimed to investigate the potential sex-specific serum modifications of amino acids and acylcarnitines (ACs) and their relationship with MetS in the Mexican population. This study included 602 participants from the Health Workers Cohort Study. Forty serum metabolites were analyzed using a targeted metabolomics approach. Multivariate regression models were used to test associations of clinical and biochemical parameters with metabolomic profiles. Our findings showed a serum amino acid signature (citrulline and glycine) and medium-chain ACs (AC14:1, AC10, and AC18:10H) associated with MetS. Glycine and AC10 were specific metabolites representative of discrimination according to sex-dependent MetS. In addition, we found that glycine and short-chain ACs (AC2, AC3, and AC8:1) are associated with age-dependent MetS. We also reported a significant correlation between body fat and metabolites associated with sex-age-dependent MetS. In conclusion, the metabolic profile varies by MetS status, and these differences are sex-age-dependent in the Mexican population.

The mechanism of branched-chain amino acid transferases in different diseases: Research progress and future prospects

It is well known that the enzyme catalyzes the first step of branched-chain amino acid (BCAA) catabolism is branched-chain amino transferase (BCAT), which is involved in the synthesis and degradation of leucine, isoleucine and valine. There are two main subtypes of human branched chain amino transferase (hBCAT), including cytoplasmic BCAT (BCAT1) and mitochondrial BCAT (BCAT2). In recent years, the role of BCAT in tumors has attracted the attention of scientists, and there have been continuous research reports that BCAT plays a role in the tumor, Alzheimer’s disease, myeloid leukaemia and other diseases. It plays a significant role in the growth and development of diseases, and new discoveries about this gene in some diseases are made every year. BCAT usually promotes cancer proliferation and invasion by activating the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin pathway and activating Wnt/β-catenin signal transduction. This article reviews the role and mechanism of BCAT in different diseases, as well as the recent biomedical research progress. This review aims to make a comprehensive summary of the role and mechanism of BCAT in different diseases and to provide new research ideas for the treatment, prognosis and prevention of certain diseases.

Metabolic signatures of insulin resistance in non-diabetic individuals

BACKGROUND

Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance.

METHODS

The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18-75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI).

RESULTS

People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR.

CONCLUSIONS

In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations.

Branched Chain Amino Acids Promote ATP Production Via Translocation of Glucose Transporters

Purpose

We have previously shown that maintenance of ATP levels is a promising strategy for preventing neuronal cell death, and that branched chain amino acids (BCAAs) enhanced cellular ATP levels in cultured cells and antagonized cell death. BCAAs attenuated photoreceptor degeneration and retinal ganglion cell death in rodent models of retinal degeneration or glaucoma. This study aimed to elucidate the mechanisms through which BCAAs enhance ATP production.

Methods

Intracellular ATP concentration was measured in HeLa cells under glycolysis and citric acid cycle inhibited conditions. Next, glucose uptake was quantified in HeLa cells and in 661W retinal photoreceptor-derived cells under glycolysis inhibition, endoplasmic reticulum stress, and glucose transporters (GLUTs) inhibited conditions, by measuring the fluorescence of fluorescently labeled deoxy-glucose analog using flow cytometry. Then, the intracellular behavior of GLUT1 and GLUT3 were observed in HeLa or 661W cells transfected with enhanced green fluorescent protein-GLUTs.

Results

BCAAs recovered intracellular ATP levels during glycolysis inhibition and during citric acid cycle inhibition. BCAAs significantly increased glucose uptake and recovered decreased glucose uptake induced by endoplasmic reticulum stress or glycolysis inhibition. However, BCAAs were unable to increase intracellular ATP levels or glucose uptake when GLUTs were inhibited. Fluorescence microscopy revealed that supplementation of BCAAs enhanced the translocation of GLUTs proteins to the plasma membrane over time.

Conclusions

BCAAs increase ATP production by promoting glucose uptake through promotion of glucose transporters translocation to the plasma membrane. These results may help expand the clinical application of BCAAs in retinal neurodegenerative diseases, such as glaucoma and retinal degeneration.

Effects of Hydroxy-Alpha-Sanshool on Intestinal Metabolism in Insulin-Resistant Mice

To explore the hydroxy-alpha-sanshool (HAS) effects on the intestinal metabolites of insulin-resistant mice, the blank group (BG), model group (MG), and HAS dose group (DG) were designed. The insulin resistance (IR) model was induced through streptozotocin (STZ) combined with a high-fat and high-sugar diet. Based on the availability of the model, the HAS dose was given by gavage for 28 days. The determination of cecum and key serum indexes was made, including the contents of insulin (INS), triglycerides (TG), total cholesterol (TC), glycosylated serum protein (GSP), and glycosylated hemoglobin (GHb). The changes in gut microbiota and metabolites in cecal contents were detected by 16S rRNA gene amplicon sequencing and UPLC/HRMS technology, respectively. The results that the levels of GSP, GHb, TG, and TC were significantly increased; this was not the case for INS; or for the changes in the gut microbiota and metabolites in MG. However, the intervention of HAS effectively reversed these changes, for instance, it decreased levels of GSP, GHb, TG, TC, and alterations of metabolite composition for linoleic acid and tyrosine metabolism and recovered trends of declining species diversity and richness of the gut microbiota in MG. It was indicated that HAS alleviated IR by regulating the gut microbiota and metabolites and affecting lipid and amino acid metabolism pathways.

Dietary intake of branched-chain amino acids in relation to the risk of breast cancer

BACKGROUND

Given that, studies on the association of dietary intake of branched-chain amino acids (BCAAs) with risk of cancers, especially breast cancer, are limited, we aimed to examine the association between dietary intake of BCAAs and risk of breast cancer.

METHODS

This case-control study was performed on Iranian women aged ≥ 30 years from July 2013 to July 2015. Overall 1050 women including 350 patients and 700 controls were included. Breast cancer was diagnosed by physical examination, mammography and pathological confirmation. We assessed dietary intakes using the validated 106-item Willett-format semi-quantitative dish-based food frequency questionnaire. The total intake of valine, leucine, and isoleucine from all food items in the questionnaire was used to calculate BCAAs intake. To estimate odds ratios (ORs) and 95% confidence intervals (95% CI), we used logistic regression analysis.

RESULTS

After controlling for potential confounders, we found that women in the highest quartile of BCAAs had lower odds of breast cancer compared with the first quartile (OR: 0.50; 95% CI 0.34-0.72). When we stratified the analysis based on menopausal status, a significant inverse association between BCAAs intake and odds of postmenopausal breast cancer was observed (OR: 0.22; 95% CI 0.13-0.39), although this significant relationship was not found in premenopausal breast cancer (OR: 2.57; 95% CI 0.51-12.73). Also, this significant association was also observed for valine, leucine, and isoleucine separately.

CONCLUSION

We found that higher dietary intake of BCAAs was significantly associated with a reduced risk of postmenopausal breast cancer.

Novel Plasma Metabolomic Markers Associated with Diabetes Progression in Older Puerto Ricans

We assessed longitudinal associations between plasma metabolites, their network-derived clusters, and type 2 diabetes (T2D) progression in Puerto Rican adults, a high-risk Hispanic subgroup with established health disparities. We used data from 1221 participants free of T2D and aged 40–75 years at baseline in the Boston Puerto Rican Health and San Juan Overweight Adult Longitudinal Studies. We used multivariable Poisson regression models to examine associations between baseline concentrations of metabolites and incident T2D and prediabetes. Cohort-specific estimates were combined using inverse-variance weighted fixed-effects meta-analyses. A cluster of 13 metabolites of branched chain amino acids (BCAA), and aromatic amino acid metabolism (pooled IRR = 1.87, 95% CI: 1.28; 2.73), and a cell membrane component metabolite cluster (pooled IRR = 1.54, 95% CI: 1.04; 2.27) were associated with a higher risk of incident T2D. When the metabolites were tested individually, in combined analysis, 5 metabolites involved in BCAA metabolism were associated with incident T2D. These findings highlight potential prognostic biomarkers to identify Puerto Rican adults who may be at high risk for diabetes. Future studies should examine whether diet and lifestyle can modify the associations between these metabolites and progression to T2D.

Shenqi compound ameliorates type-2 diabetes mellitus by modulating the gut microbiota and metabolites

The gut microbiota (GM) and metabolites are important factors in mediating the development of type-2 diabetes mellitus (T2DM). An imbalance in the gut microbiota and metabolites can disrupt the function of the intestinal barrier, cause changes in the permeability of the intestinal mucosa and promote the immune inflammatory response, thereby aggravating the fluctuation of blood glucose level and promoting the occurrence and development of the chronic complications of DM. Manipulating the GM and metabolites is a promising therapeutic intervention and is being studied extensively. Shenqi compound (SQC) is a traditional Chinese medicine formulation, which has been widely used to improve T2DM. Studies have demonstrated that SQC can reduce glycemic variability, alleviate the inflammatory response, etc. However, its underlying mechanism remains unknown. Therefore, in this experiment, We administered SQC to Goto-Kakizaki (GK) rats and evaluated its effect on blood glucose homeostasis and the intestinal mucosal barrier. We identified the profiles of the GM and metabolites with the aid of 16S rDNA gene sequencing and non-target metabolomics analysis. It showed that SQC intervention could reduce glycemic variability, regulate serum levels of glucagon and insulin, and improve injury to the intestinal mucosal barrier of GK rats. In the gut, the ratio of bacteria of the phyla Bacteroidetes/Firmicutes could be improved after SQC intervention. SQC also regulated the relative abundance of Prevotellaceae, Butyricimonas, Bacteroides, Blautia, Roseburia, Lactobacillus, and Rothia. We found out that expression of 40 metabolites was significantly improved after SQC intervention. Further analyses of metabolic pathways indicated that the therapeutic effect of SQC might be related predominantly to its ability to improve gluconeogenesis/glycolysis, amino acid metabolism, lipid metabolism, citrate cycle, and butanoate metabolism. These results suggest that SQC may exert a beneficial role in T2DM by modulating the GM and metabolites in different pathways.

Age, Sex, Body Mass Index, Diet and Menopause Related Metabolites in a Large Homogeneous Alpine Cohort

Metabolomics in human serum samples provide a snapshot of the current metabolic state of an individuum. Metabolite concentrations are influenced by both genetic and environmental factors. Concentrations of certain metabolites can further depend on age, sex, menopause, and diet of study participants. A better understanding of these relationships is pivotal for the planning of metabolomics studies involving human subjects and interpretation of their results. We generated one of the largest single-site targeted metabolomics data sets consisting of 175 quantified metabolites in 6872 study participants. We identified metabolites significantly associated with age, sex, body mass index, diet, and menopausal status. While most of our results agree with previous large-scale studies, we also found novel associations including serotonin as a sex and BMI-related metabolite and sarcosine and C2 carnitine showing significantly higher concentrations in post-menopausal women. Finally, we observed strong associations between higher consumption of food items and certain metabolites, mostly phosphatidylcholines and lysophosphatidylcholines. Most, and the strongest, relationships were found for habitual meat intake while no significant relationships were found for most fruits, vegetables, and grain products. Summarizing, our results reconfirm findings from previous population-based studies on an independent cohort. Together, these findings will ultimately enable the consolidation of sets of metabolites which are related to age, sex, BMI, and menopause as well as to participants’ diet.

Branched-chain amino acids at supraphysiological but not physiological levels reduce myotube insulin sensitivity

AIMS

Branched-chain amino acids (BCAA) are often emphasized in the diets of avid exercisers, yet population data demonstrates a correlation between circulating BCAA and insulin resistance. However, it is unclear if BCAA independently promote insulin resistance in otherwise healthy cells. The purpose of this study is to examine the effect of a BCAA mixture on muscle insulin signaling in vitro in both insulin resistant and sensitive cells.

MATERIALS AND METHODS

C2C12 myotubes were treated with a BCAA mixture containing leucine:isoleucine:valine at a ratio of 2:1:1 at 0.2, 2, or 20 mM (based on leucine content) for either 30 min, 1 day, or 6 days. Western blot was used to assess insulin sensitivity of cells treated with BCAA both with and without concurrent insulin resistance, and, with and without insulin stimulation.

RESULTS

BCAA treatment for 1 day significantly reduced basal, but not insulin-stimulated pAkt expression. BCAA treatment for 6 days resulted in significantly reduced basal insulin signaling in healthy cells and insulin-stimulated insulin signaling in insulin resistant (but not insulin sensitive) cells.

CONCLUSION

Similar to previous observations demonstrating BCAA may correlate with insulin resistance during metabolically stressed conditions, we demonstrate excessively high BCAA exposure can negatively influence basal insulin signaling, as well as insulin sensitivity in insulin resistant myotubes. However, given the intentionally high concentrations of BCAA used in this study, the extent to which these observations translate to in vivo models is unclear and warrants further investigation.

AICAR stimulates mitochondrial biogenesis and BCAA catabolic enzyme expression in C2C12 myotubes

Type 2 diabetes is characterized by reduced insulin sensitivity, elevated blood metabolites, and reduced mitochondrial metabolism. Insulin resistant populations often exhibit reduced expression of genes governing mitochondrial metabolism such as peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α). Interestingly, PGC-1α regulates the expression of branched-chain amino acid (BCAA) metabolism, and thus, the consistently observed increased circulating levels of BCAA in diabetics may be partially explained by reduced PGC-1α expression. Conversely, PGC-1α upregulation appears to increase BCAA catabolism. PGC-1α activity is regulated by 5'-AMP-activated protein kinase (AMPK), however, only limited experimental data exists on the effect of AMPK activation in the regulation of BCAA catabolism. The present report examined the effects of the commonly used AMPK activator 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) on the metabolism and expression of several related targets (including BCAA catabolic enzymes) of cultured myotubes. C2C12 myotubes were treated with AICAR at 1 mM for up to 24 h. Mitochondrial and glycolytic metabolism were measured via oxygen consumption and extracellular acidification rate, respectively. Metabolic gene and protein expression were assessed via qRT-PCR and western blot, respectively. AICAR treatment significantly increased mitochondrial content and peak mitochondrial capacity. AICAR treatment also increased AMPK activation and mRNA expression of several regulators of mitochondrial biogenesis but reduced glycolytic metabolism and mRNA expression of several glycolytic enzymes. Interestingly, branched-chain alpha-keto acid dehydrogenase a (BCKDHa) protein was significantly increased following AICAR-treatment suggesting increased overall BCAA catabolic capacity in AICAR-treated cells. Together, these experiments demonstrate AICAR/AMPK activation can upregulate BCAA catabolic machinery in a model of skeletal muscle.

6:2 Cl-PFESA has the potential to cause liver damage and induce lipid metabolism disorders in female mice through the action of PPAR-γ

6:2 Cl-PFESA is a polyfluoroalkyl ether with high environmental persistence that has been confirmed to have significant adverse effects on animals. In this study, 6-week-old female C57BL/6 mice were exposed to 0, 1, 3 and 10 μg/L 6:2 Cl-PFESA for 10 weeks to estimate the hepatotoxicity of 6:2 Cl-PFESA and explore its underlying molecular mechanism. The results indicated that 6:2 Cl-PFESA preferentially bioaccumulated in the liver and induced hepatic cytoplasmic vacuolation and hepatomegaly in mice. In addition, serum metabolic profiling showed that 6:2 Cl-PFESA exposure caused an abnormal increase in amino acids and an abnormal decrease in acyl-carnitine, which interfered with fatty acid transport and increased the risk of metabolic diseases. Further experiments showed that 6:2 Cl-PFESA formed more hydrogen bonds with PPAR-γ than PFOS, Rosi and GW9662, and the binding affinity of 6:2 Cl-PFESA toward PPAR-γ was the highest among the ligands. 6:2 Cl-PFESA promoted the differentiation of 3T3-L1 cells by increasing PPAR-γ expression. Therefore, our results showed that 6:2 Cl-PFESA has the potential to induce liver damage and dysfunction in female mice, and this effect was achieved through PPAR-γ. This study is the first to reveal the hepatic toxicity of 6:2 Cl-PFESA in female mammals and provides new insights for subsequent in-depth research.

Comparing the effects of palmitate, insulin, and palmitate-insulin co-treatment on myotube metabolism and insulin resistance

Previous studies have shown various metabolic stressors such as saturated fatty acids (SFA) and excess insulin promote insulin resistance in metabolically meaningful cell types (such as skeletal muscle). Additionally, these stressors have been linked with suppressed mitochondrial metabolism, which is also a common characteristic of skeletal muscle of diabetics. This study characterized the individual and combined effects of excess lipid and excess insulin on myotube metabolism and related metabolic gene and protein expression. C2C12 myotubes were treated with either 500 μM palmitate (PAM), 100 nM insulin (IR), or both (PAM-IR). qRT-PCR and western blot were used to measure metabolic gene and protein expression, respectively. Oxygen consumption was used to measure mitochondrial metabolism. Glycolytic metabolism and insulin-mediated glucose uptake were measured via extracellular acidification rate. Cellular lipid and mitochondrial content were measured using Nile Red and NAO staining, respectively. IR and PAM-IR treatments led to reductions in p-Akt expression. IR treatment reduced insulin mediated glucose metabolism while PAM and PAM-IR treatment showed increases with concurrent reductions in mitochondrial metabolism. All three treatments showed suppression in mitochondrial metabolism. PAM and PAM-IR also showed increases in glycolytic metabolism. While PAM and PAM-IR significantly increased lipid content, expression of inflammatory and lipogenic proteins were unaltered. Lastly, PAM-IR reduced BCAT2 protein expression, a regulator of BCAA metabolism. Both stressors independently reduced insulin signaling, mitochondrial function, and cell metabolism, however, only PAM-IR co-treatment significantly reduced the expression of regulators of metabolism not seen with individual stressors, suggesting an additive effect of stressors on metabolic programming.

Antidiabetic Effect of Noodles Containing Fermented Lettuce Extracts

The aim of the current study was to examine the antidiabetic effect of noodle containing fermented lettuce extract (FLE) on diabetic mice as a pre-clinical study. The γ-aminobutyric acid (GABA) content, antioxidant capacity, and total polyphenol content of the FLE noodles were analyzed and compared with those of standard noodles. In addition, oral glucose and sucrose tolerance, and fasting blood glucose tests were performed using a high-fat diet/streptozotocin-mediated diabetic mouse model. Serum metabolite profiling of mice feed standard or FLE noodles was performed using gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) to understand the mechanism changes induced by the FLE noodles. The GABA content, total polyphenols, and antioxidant activity were high in FLE noodles compared with those in the standard noodles. In vivo experiments also showed that mice fed FLE noodles had lower blood glucose levels and insulin resistance than those fed standard noodles. Moreover, glycolysis, purine metabolism, and amino acid metabolism were altered by FLE as determined by GC-TOF-MS-based metabolomics. These results demonstrate that FLE noodles possess significant antidiabetic activity, suggesting the applicability of fermented lettuce extract as a potential food additive for diabetic food products.

Decreased Abundance of Akkermansia muciniphila Leads to the Impairment of Insulin Secretion and Glucose Homeostasis in Lean Type 2 Diabetes

Although obesity occurs in most of the patients with type 2 diabetes (T2D), a fraction of patients with T2D are underweight or have normal weight. Several studies have linked the gut microbiome to obesity and T2D, but the role of gut microbiota in lean individuals with T2D having unique clinical characteristics remains unclear. A metagenomic and targeted metabolomic analysis is conducted in 182 lean and abdominally obese individuals with and without newly diagnosed T2D. The abundance of Akkermansia muciniphila (A. muciniphila) significantly decreases in lean individuals with T2D than without T2D, but not in the comparison of obese individuals with and without T2D. Its abundance correlates inversely with serum 3β-chenodeoxycholic acid (βCDCA) levels and positively with insulin secretion and fibroblast growth factor 15/19 (FGF15/19) concentrations. The supplementation with A. muciniphila is sufficient to protect mice against high sucrose-induced impairment of glucose intolerance by decreasing βCDCA and increasing insulin secretion and FGF15/19. Furthermore, βCDCA inhibits insulin secretion and FGF15/19 expression. These findings suggest that decreased abundance of A. muciniphila is linked to the impairment of insulin secretion and glucose homeostasis in lean T2D, paving the way for new therapeutic options for the prevention or treatment of diabetes.

Amino Acid-Induced Impairment of Insulin Signaling and Involvement of G-Protein Coupling Receptor

Amino acids are needed for general bodily function and well-being. Despite their importance, augmentation in their serum concentration is closely related to metabolic disorder, insulin resistance (IR), or worse, diabetes mellitus. Essential amino acids such as the branched-chain amino acids (BCAAs) have been heavily studied as a plausible biomarker or even a cause of IR. Although there is a long list of benefits, in subjects with abnormal amino acids profiles, some amino acids are correlated with a higher risk of IR. Metabolic dysfunction, upregulation of the mammalian target of the rapamycin (mTOR) pathway, the gut microbiome, 3-hydroxyisobutyrate, inflammation, and the collusion of G-protein coupled receptors (GPCRs) are among the indicators and causes of metabolic disorders generating from amino acids that contribute to IR and the onset of type 2 diabetes mellitus (T2DM). This review summarizes the current understanding of the true involvement of amino acids with IR. Additionally, the involvement of GPCRs in IR will be further discussed in this review.

Chronically elevated branched chain amino acid levels are pro-arrhythmic

Aims

Cardiac arrhythmias comprise a major health and economic burden and are associated with significant morbidity and mortality, including cardiac failure, stroke, and sudden cardiac death (SCD). Development of efficient preventive and therapeutic strategies is hampered by incomplete knowledge of disease mechanisms and pathways. Our aim is to identify novel mechanisms underlying cardiac arrhythmia and SCD using an unbiased approach.

Methods and results

We employed a phenotype-driven N-ethyl-N-nitrosourea mutagenesis screen and identified a mouse line with a high incidence of sudden death at young age (6–9 weeks) in the absence of prior symptoms. Affected mice were found to be homozygous for the nonsense mutation Bcat2^{p.Q300*/p.Q300*} in the Bcat2 gene encoding branched chain amino acid transaminase 2. At the age of 4–5 weeks, Bcat2^{p.Q300*/p.Q300*} mice displayed drastic increase of plasma levels of branch chain amino acids (BCAAs—leucine, isoleucine, valine) due to the incomplete catabolism of BCAAs, in addition to inducible arrhythmias ex vivo as well as cardiac conduction and repolarization disturbances. In line with these findings, plasma BCAA levels were positively correlated to electrocardiogram indices of conduction and repolarization in the German community-based KORA F4 Study. Isolated cardiomyocytes from Bcat2^{p.Q300*/p.Q300*} mice revealed action potential (AP) prolongation, pro-arrhythmic events (early and late afterdepolarizations, triggered APs), and dysregulated calcium homeostasis. Incubation of human pluripotent stem cell-derived cardiomyocytes with elevated concentration of BCAAs induced similar calcium dysregulation and pro-arrhythmic events which were prevented by rapamycin, demonstrating the crucial involvement of mTOR pathway activation.

Conclusions

Our findings identify for the first time a causative link between elevated BCAAs and arrhythmia, which has implications for arrhythmogenesis in conditions associated with BCAA metabolism dysregulation such as diabetes, metabolic syndrome, and heart failure.

Childhood overeating is associated with adverse cardiometabolic and inflammatory profiles in adolescence

Childhood eating behaviour contributes to the rise of obesity and related noncommunicable disease worldwide. However, we lack a deep understanding of biochemical alterations that can arise from aberrant eating behaviour. In this study, we prospectively associate longitudinal trajectories of childhood overeating, undereating, and fussy eating with metabolic markers at age 16 years to explore adolescent metabolic alterations related to specific eating patterns in the first 10 years of life. Data are from the Avon Longitudinal Study of Parents and Children (n = 3104). We measure 158 metabolic markers with a high-throughput (1H) NMR metabolomics platform. Increasing childhood overeating is prospectively associated with an adverse cardiometabolic profile (i.e., hyperlipidemia, hypercholesterolemia, hyperlipoproteinemia) in adolescence; whereas undereating and fussy eating are associated with lower concentrations of the amino acids glutamine and valine, suggesting a potential lack of micronutrients. Here, we show associations between early behavioural indicators of eating and metabolic markers.

The Differential Metabolic Profiles Between Deltamethrin-Resistant and -Susceptible Strains of Aedes albopictus (Diptera: Culicidae) by 1H-NMR

Metabolomics can indicate the physiological and biochemical responses of mosquitoes to different stimulants, including insecticides, which allow them to adapt to different inhospitable environments. Though metabolic differences between insecticide-resistant and -susceptible strains have been established for other mosquito species, such as Anopheles and Culex, it is yet to be done for Aedes albopictus (Skuse). In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis performed on Ae. albopictus deltamethrin-resistant and -susceptible strains showed significant differences in amino acid, organic acid, and sugar metabolism. Concentrations of neutral amino acids and sugars tended to be lower in the deltamethrin-resistant strain than in the deltamethrin-suceptible strain, but the concentration of basic and acidic amino acids and organic acids increased. All these changes might accommodate biochemical and physiological needs in deltamethrin-resistant mosquitoes, such as enzyme synthesis and detoxification. This was further confirmed by the predictable draft metabolic map. This is the first report using NMR spectroscopy to investigate the metabolic differences between deltamethrin-resistant and -susceptible strains of Ae. albopictus. To a certain degree, this demonstrates how Ae. albopictus develop insecticide resistance by metabolic reprograming to survive under the insecticide pressure.

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.

Untargeted metabolomics as a diagnostic tool in NAFLD: discrimination of steatosis, steatohepatitis and cirrhosis

INTRODUCTION

Non-Alcoholic Fatty Liver Disease encompasses a spectrum of diseases ranging from simple steatosis to steatohepatitis (or NASH), up to cirrhosis and hepatocellular carcinoma (HCC). The challenge is to recognize the more severe and/or progressive pathology. A reliable non-invasive method does not exist. Untargeted metabolomics is a novel method to discover biomarkers and give insights on diseases pathophysiology.

OBJECTIVES

We applied metabolomics to understand if simple steatosis, steatohepatitis and cirrhosis in NAFLD patients have peculiar metabolites profiles that can differentiate them among each-others and from controls.

METHODS

Metabolomics signatures were obtained from 307 subjects from two separated enrollments. The first collected samples from 69 controls and 144 patients (78 steatosis, 23 NASH, 15 NASH-cirrhosis, 8 HCV-cirrhosis, 20 cryptogenic cirrhosis). The second, used as validation-set, enrolled 44 controls and 50 patients (34 steatosis, 10 NASH and 6 NASH-cirrhosis).The "Partial-Least-Square Discriminant-Analysis"(PLS-DA) was used to reveal class separation in metabolomics profiles between patients and controls and among each class of patients, and to reveal the metabolites contributing to class differentiation.

RESULTS

Several metabolites were selected as relevant, in particular:Glycocholic acid, Taurocholic acid, Phenylalanine, branched-chain amino-acids increased at the increase of the severity of the disease from steatosis to NASH, NASH-cirrhosis, while glutathione decreased (p < 0.001 for each). Moreover, an ensemble machine learning (EML) model was built (comprehending 10 different mathematical models) to verify diagnostic performance, showing an accuracy > 80% in NAFLD clinical stages prediction.

CONCLUSIONS

Metabolomics profiles of NAFLD patients could be a useful tool to non-invasively diagnose NAFLD and discriminate among the various stages of the disease, giving insights into its pathophysiology.

Metabolic Syndrome and Its Components Are Associated With Altered Amino Acid Profile in Chinese Han Population

OBJECTIVE

Recent studies have found that the levels of plasma amino acids, such as branched-chain amino acids and aromatic amino acids, were associated with visceral obesity, insulin resistance, future development of diabetes and cardiovascular diseases. However, few studies have involved a Chinese Han population. This study aimed to examine the association between amino acid profile and metabolic syndrome (MetS) and its components in the Chinese Han population.

METHODS

This is a cross-sectional study, which enrolled a cohort of 473 participants from a community. We employed the isotope internal standard method to determine the plasma concentrations of 28 amino acids using high-performance liquid chromatography-tandem mass spectrometry (LC/MS). Participants were divided into MetS (n = 72) and non-MetS groups (n = 401) to analyze the association between amino acids and MetS and its components.

RESULTS

The prevalence of MetS was 15.2% according to the criteria. Plasma concentrations of isoleucine (Ile), leucine (Leu), valine (Val), tyrosine (Tyr), tryptophan (Trp), phenylalanine (Phe), glutamic acid (Glu), aspartic acid (Asp), alanine (Ala), histidine (His), methionine (Met), asparagine (Asn), and proline (Pro) were significantly higher in the MetS group than those in the non-MetS group (P < 0.05), but taurine (Tau) was significantly lower (P < 0.05). When MetS components were increased, the concentrations of these 13 amino acids significantly increased (P < 0.05), but Tau concentration was significantly decreased (P < 0.05). We extracted the amino acid profile by principal component analysis (PCA), PC1 and PC2, which extracted from the 14 amino acids, were significantly associated with MetS (odds ratio, 95% confidence interval: 1.723, 1.325-2.085 and 1.325, 1.043-1.684, respectively). A total of 260 non-MetS participants were followed up effectively, and 42 participants developed new-onset MetS within 5 years. We found that the amino acid profile of PC1 was linked to the occurrence of future MetS. Decreased Tau was correlated with the future development of MetS.

CONCLUSION

Participants with MetS exhibit an abnormal amino acid profile, and its components gradually increase when these amino acids are altered. Amino acid PCA profile can be employed for assessing and monitoring MetS risk. Finally, decreased Tau may be linked to the future development of MetS.

Obesity Increases the Severity and Mortality of Influenza and COVID-19: A Systematic Review and Meta-Analysis

Since December 2019, COVID-19 has aroused global attention. Studies show the link between obesity and severe outcome of influenza and COVID-19. Thus, we aimed to compare the impacts of obesity on the severity and mortality of influenza and COVID-19 by performing a meta-analysis. A systematic search was performed in MEDLINE, EMASE, ClinicalTrials.gov, and Web of Science from January 2009 to July 2020. The protocol was registered onto PROSPERO (CRD42020201461). After selection, 46 studies were included in this meta-analysis. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were analyzed. We found obesity was a risk factor for the severity and mortality of influenza (ORsevere outcome = 1.56, CI: 1.28-1.90; ORmortality = 1.99, CI: 1.15-3.46). For COVID-19, obesity was a significant risk factor only for severe outcome (OR = 2.07, CI: 1.53-2.81) but not for mortality (OR = 1.57, CI: 0.85-2.90). Compared with obesity, morbid obesity was linked with a higher risk for the severity and mortality of both influenza (OR = 1.40, CI: 1.10-1.79) and COVID-19 (OR = 3.76, CI: 2.67-5.28). Thus, obesity should be recommended as a risk factor for the prognosis assessment of COVID-19. Special monitoring and earlier treatment should be implemented in patients with obesity and COVID-19.

Distinctive Metabolomics Patterns Associated With Insulin Resistance and Type 2 Diabetes Mellitus

Obesity is associated with an increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) which is a multi-factorial disease associated with a dysregulated metabolism and can be prevented in pre-diabetic individuals with impaired glucose tolerance. A metabolomic approach emphasizing metabolic pathways is critical to our understanding of this heterogeneous disease. This study aimed to characterize the serum metabolomic fingerprint and multi-metabolite signatures associated with IR and T2DM. Here, we have used untargeted high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) to identify candidate biomarkers of IR and T2DM in sera from 30 adults of normal weight, 26 obese adults, and 16 adults newly diagnosed with T2DM. Among the 3633 peak pairs detected, 62% were either identified or matched. A group of 78 metabolites were up-regulated and 111 metabolites were down-regulated comparing obese to lean group while 459 metabolites were up-regulated and 166 metabolites were down-regulated comparing T2DM to obese groups. Several metabolites were identified as IR potential biomarkers, including amino acids (Asn, Gln, and His), methionine (Met) sulfoxide, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, serotonin, L-2-amino-3-oxobutanoic acid, and 4,6-dihydroxyquinoline. T2DM was associated with dysregulation of 42 metabolites, including amino acids, amino acids metabolites, and dipeptides. In conclusion, these pilot data have identified IR and T2DM metabolomics panels as potential novel biomarkers of IR and identified metabolites associated with T2DM, with possible diagnostic and therapeutic applications. Further studies to confirm these associations in prospective cohorts are warranted.

Branched chain amino acids, aging and age-related health

Branched chain amino acids (BCAA: leucine, valine, isoleucine) have key physiological roles in the regulation of protein synthesis, metabolism, food intake and aging. Many studies report apparently inconsistent conclusions about the relationships between blood levels of BCAAs or dietary manipulation of BCAAs with age-related changes in body composition, sarcopenia, obesity, insulin and glucose metabolism, and aging biology itself. These divergent results can be resolved by consideration of the role of BCAAs as signalling molecules and the bidirectional mechanistic relationship between BCAAs and some aging phenotypes. The effects of BCAAs are also influenced by the background nutritional composition such as macronutrient ratios and imbalance with other amino acids. Understanding the interaction between BCAAs and other components of the diet may provide new opportunities for influencing age-related outcomes through manipulation of dietary BCAAs together with titration of macronutrient ratios and other amino acids.

Equivalent change enrichment analysis: assessing equivalent and inverse change in biological pathways between diverse experiments

Background

In silico functional genomics have become a driving force in the way we interpret and use gene expression data, enabling researchers to understand which biological pathways are likely to be affected by the treatments or conditions being studied. There are many approaches to functional genomics, but a number of popular methods determine if a set of modified genes has a higher than expected overlap with genes known to function as part of a pathway (functional enrichment testing). Recently, researchers have started to apply such analyses in a new way: to ask if the data they are collecting show similar disruptions to biological functions compared to reference data. Examples include studying whether similar pathways are perturbed in smokers vs. users of e-cigarettes, or whether a new mouse model of schizophrenia is justified, based on its similarity in cytokine expression to a previously published model. However, there is a dearth of robust statistical methods for testing hypotheses related to these questions and most researchers resort to ad hoc approaches. The goal of this work is to develop a statistical approach to identifying gene pathways that are equivalently (or inversely) changed across two experimental conditions.

Results

We developed Equivalent Change Enrichment Analysis (ECEA). This is a new type of gene enrichment analysis based on a statistic that we call the equivalent change index (ECI). An ECI of 1 represents a gene that was over or under-expressed (compared to control) to the same degree across two experiments. Using this statistic, we present an approach to identifying pathways that are changed in similar or opposing ways across experiments. We compare our approach to current methods on simulated data and show that ECEA is able to recover pathways exhibiting such changes even when they exhibit complex patterns of regulation, which other approaches are unable to do. On biological data, our approach recovered pathways that appear directly connected to the condition being studied.

Conclusions

ECEA provides a new way to perform gene enrichment analysis that allows researchers to compare their data to existing datasets and determine if a treatment will cause similar or opposing genomic perturbations.