The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis

Branched-chain amino acid supplementation drives dynamic changes in gut microbiota without impairing glucose and lipid homeostasis at the different stages of insulin resistance in mice on a high-fat diet

OBJECTIVE

The potential role of dietary branched-chain amino acids on circulating branched-chain amino acid levels and their relationship with metabolic health are complex, and the literature is inconsistent. We aimed to explore the dynamic effects of branched-chain amino acid supplementation on glucose and lipid homeostasis at different stages of insulin resistance in high-fat diet-fed mice.

METHODS

Male C57BL/6J mice were fed with a normal chow diet, high-fat diet, or high-fat diet supplemented with 100% branched-chain amino acids for 12 or 24 wk. Metabolic parameters and gut microbiota profiling were performed at these two time points.

RESULTS

High-fat diet feeding caused varying degrees of branched-chain amino acid metabolic disorders in two different stages of insulin resistance. Supplementing with branched-chain amino acids further exacerbated branched-chain amino acid accumulation in the early stage of insulin resistance (12 wk), while adding branched-chain amino acids did not further elevate branched-chain amino acid levels in the hyperglycemia and hyperinsulinemia stage (24 wk). Compared with the high-fat diet group, branched-chain amino acid supplementation did not affect body weight; liver total cholesterol and triacylglycerol levels; and serum glucose, insulin, total cholesterol, triacylglycerol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol levels as well as glucose tolerance at these two time points but triggered dynamic changes in the gut bacterial diversity and gut microbiota composition and abundance, especially in the genus associated with obesity and related metabolic disorders.

CONCLUSION

Dietary branched-chain amino acid supplementation drives dynamic changes in circulating branched-chain amino acid levels and gut microbiome without subsequent effects on glucose and lipid homeostasis in high-fat diet-induced obese mice within the parameters of our study.

Correlation between newborn weight and serum BCAAs in pregnant women with diabetes

BACKGROUND

Branched-chain amino acids (BCAAs), including leucine, isoleucine, and valine, are essential amino acids for mammals. Maternal BCAAs during pregnancy have been associated with newborn development. Meanwhile, BCAAs have been tightly linked with insulin resistance and diabetes in recent years. Diabetes in pregnancy is a common metabolic disorder. The current study aims to assess the circulating BCAA levels in pregnant women with diabetes and their relationship with neonatal development.

METHODS

The serum concentrations of BCAAs and their corresponding branched-chain α-keto acids (BCKAs) catabolites in 33 pregnant women with normal glucose tolerance, 16 pregnant women with type 2 diabetes before pregnancy (PDGM), and 15 pregnant women with gestational diabetes mellitus (GDM) were determined using a liquid chromatography system coupled to a mass spectrometer. The data were tested for normal distribution and homogeneity of variance before statistical analysis. Correlations were computed with the Pearson correlation coefficient.

RESULTS

The maternal serum BCAAs and BCKAs levels during late pregnancy were higher in women with PGDM than those in healthy women. Meanwhile, the circulating BCAAs and BCKAs showed no significant changes in women with GDM compared with those in healthy pregnant women. Furthermore, the circulating BCAA and BCKA levels in women with PGDM were positively correlated with the weight of the newborn. The circulating leucine level in women with GDM was positively correlated with the weight of the newborn. BCAA and BCKA levels in healthy pregnant women showed no correlation with newborn weight.

CONCLUSIONS

The serum BCAAs in pregnant women with diabetes, which was elevated in PGDM but not GDM, were positively correlated with newborn weight. These findings highlight potential approaches for early identification of high-risk individuals and interventions to reduce the risk of adverse pregnancy outcomes.

1H-NMR-based metabolomics reveals the preventive effect of Enteromorpha prolifera polysaccharides on diabetes in Zucker diabetic fatty rats

The primary objective of this investigation was to explore the beneficial impacts of Enteromorpha prolifera polysaccharide (EP) on dysglycemia in Zucker diabetic fatty (ZDF) rats, while also shedding light on its potential mechanism using 1H-NMR-based metabolomics. The results demonstrated a noteworthy reduction in fasting blood glucose (FBG, 46.3%), fasting insulin (50.17%), glycosylated hemoglobin A1c (HbA1c, 44.1%), and homeostatic model assessment of insulin resistance (HOMA-IR, 59.75%) following EP administration, while the insulin sensitivity index (ISI, 19.6%) and homeostatic model assessment of β-cell function (HOMA-β, 2.5-fold) were significantly increased. These findings indicate that EP enhances β-cell function, increases insulin sensitivity, and improves insulin resistance caused by diabetes. Moreover, EP significantly reduced serum lipid levels, suggesting improvement of dyslipidemia. Through the analysis of serum metabolomics, 17 metabolites were found to be altered in diabetic rats, 14 of which were upregulated and 3 of which were downregulated. Notably, the administration of EP successfully reversed the abnormal levels of 9 out of the 17 metabolites. Pathway analysis further revealed that EP treatment partially restored metabolic dysfunction, with notable effects observed in valine, leucine, and isoleucine metabolism; aminoacyl-transfer RNA (tRNA) biosynthesis; and ketone body metabolism. These findings collectively indicate the potential therapeutic efficacy of EP in preventing glycemic abnormalities and improving insulin resistance. Thus, EP holds promise as a valuable treatment option for individuals with diabetes.

Analyzing Immune Cell Infiltration and Copper Metabolism in Diabetic Foot Ulcers

Background

Diabetes impairs wound healing, notably in diabetic foot ulcers (DFU). Stress, marked by the accumulation of lipoylated mitochondrial enzymes and the depletion of Fe-S cluster proteins, triggers cuproptosis-a distinct form of cell death. The involvement of copper in the pathophysiology of DFU has been recognized, and currently, a copper-based therapeutic strategy is emerging as a viable option for enhancing ulcer healing. This study investigates genes linked to copper metabolism in DFU, aiming to uncover potential targets for therapeutic intervention.

Methods

Two diabetic wound Gene Expression Omnibus (GEO) datasets were analyzed to study immune cell dysregulation in diabetic wounds. Differentially expressed genes related to copper metabolism were identified and analyzed using machine learning methods. Gene ontology, pathway enrichment, and immune infiltration analyses were performed using DFU samples. The expression of identified genes was validated using qRT-PCR and single-cell RNA sequencing.

Results

Ten genes associated with copper metabolism were identified. Among these, SLC31A1 and ADNP were found to be significantly differentially expressed in DFU. Notably, SLC31A1 exhibited higher expression in macrophages, whereas ADNP was found to be highly expressed in fibroblasts and chondrocytes.

Conclusion

The study indicates a close link between copper metabolism, the infiltration of immune cells, and DFU. It proposes that copper metabolism could influence the progression of DFU through the activation of immune responses. These observations offer fresh perspectives on the underlying mechanisms of DFU and identify potential targets for therapeutic intervention.

New Mediators in the Crosstalk between Different Adipose Tissues

Adipose tissue is a multifunctional organ that regulates many physiological processes such as energy homeostasis, nutrition, the regulation of insulin sensitivity, body temperature, and immune response. In this review, we highlight the relevance of the different mediators that control adipose tissue activity through a systematic review of the main players present in white and brown adipose tissues. Among them, inflammatory mediators secreted by the adipose tissue, such as classical adipokines and more recent ones, elements of the immune system infiltrated into the adipose tissue (certain cell types and interleukins), as well as the role of intestinal microbiota and derived metabolites, have been reviewed. Furthermore, anti-obesity mediators that promote the activation of beige adipose tissue, e.g., myokines, thyroid hormones, amino acids, and both long and micro RNAs, are exhaustively examined. Finally, we also analyze therapeutic strategies based on those mediators that have been described to date. In conclusion, novel regulators of obesity, such as microRNAs or microbiota, are being characterized and are promising tools to treat obesity in the future.

Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics.

MATERIALS AND METHODS

The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules.

RESULTS

Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively.

CONCLUSION

We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.

Molecular mechanisms of metabolic dysregulation in diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM), one of the most serious complications of diabetes mellitus, has become recognized as a cardiometabolic disease. In normoxic conditions, the majority of the ATP production (>95%) required for heart beating comes from mitochondrial oxidative phosphorylation of fatty acids (FAs) and glucose, with the remaining portion coming from a variety of sources, including fructose, lactate, ketone bodies (KB) and branched chain amino acids (BCAA). Increased FA intake and decreased utilization of glucose and lactic acid were observed in the diabetic hearts of animal models and diabetic patients. Moreover, the polyol pathway is activated, and fructose metabolism is enhanced. The use of ketones as energy sources in human diabetic hearts also increases significantly. Furthermore, elevated BCAA levels and impaired BCAA metabolism were observed in the hearts of diabetic mice and patients. The shift in energy substrate preference in diabetic hearts results in increased oxygen consumption and impaired oxidative phosphorylation, leading to diabetic cardiomyopathy. However, the precise mechanisms by which impaired myocardial metabolic alterations result in diabetes mellitus cardiac disease are not fully understood. Therefore, this review focuses on the molecular mechanisms involved in alterations of myocardial energy metabolism. It not only adds more molecular targets for the diagnosis and treatment, but also provides an experimental foundation for screening novel therapeutic agents for diabetic cardiomyopathy.

Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men

BACKGROUND

Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.

METHODS

We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.

FINDINGS

After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).

INTERPRETATION

This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.

FUNDING

National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].

Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors

BACKGROUND

The lack of specific predictors for type-2 diabetes mellitus (T2DM) severely impacts early intervention/prevention efforts. Elevated branched-chain amino acids (BCAAs: Isoleucine, leucine, valine) and aromatic amino acids (AAAs: Tyrosine, tryptophan, phenylalanine)) show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical studies. However, improvement is needed to support its clinical utility.

AIM

To evaluate the effects of body mass index (BMI) and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body weight.

METHODS

Ninety-seven new-onset T2DM patients (< 12 mo) differing in BMI [normal weight (NW), n = 33, BMI = 22.23 ± 1.60; overweight, n = 42, BMI = 25.9 ± 1.07; obesity (OB), n = 22, BMI = 31.23 ± 2.31] from the First People's Hospital of Yunnan Province, Kunming, China, were studied. One-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/AAAs.

RESULTS

Fasting serum AAAs, BCAAs, glutamate, and alanine were greater and high-density lipoprotein (HDL) was lower (P < 0.05, each) in OB-T2DM patients than in NW-T2DM patients, especially in male OB-T2DM patients. Arginine, histidine, leucine, methionine, and lysine were greater in male patients than in female patients. Moreover, histidine, alanine, glutamate, lysine, valine, methionine, leucine, isoleucine, tyrosine, phenylalanine, and tryptophan were significantly correlated with abdominal adiposity, body weight and BMI, whereas isoleucine, leucine and phenylalanine were negatively correlated with HDL.

CONCLUSION

Heterogeneously elevated amino acids, especially BCAAs/AAAs, across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM development. The higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals, whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW individuals. This potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to be used as the T2DM predictor.

Gut microbial changes associated with obesity in youth with type 1 diabetes

Obesity is increasingly prevalent in type 1 diabetes (T1D) and is associated with management problems and higher risk for diabetes complications. Gut microbiome changes have been described separately in each of T1D and obesity, however, it is unknown to what extent gut microbiome changes are seen when obesity and T1D concomitantly occur.

OBJECTIVE

To describe the gut microbiome and microbial metabolite changes associated with obesity in T1D. We hypothesized significant gut microbial and metabolite differences between T1D youth who are lean (BMI: 5-<85%) vs. those with obesity (BMI: ≥95%).

METHODS

We analyzed stool samples for gut microbial (using metagenomic shotgun sequencing) and short-chain fatty acid (SCFA) metabolite differences in lean (n=27) and obese (n=21) T1D youth. The mean±SD age was 15.3±2.2yrs, A1c 7.8±1.3%, diabetes duration 5.1±4.4yrs, 42.0% females, and 94.0% were White. Linear discriminant analysis (LDA) effect size (LEfSe) was used to identify taxa that best discriminated between the BMI groups.

RESULTS

Bacterial community composition showed differences in species type (β-diversity) by BMI group (p=0.013). At the genus level, there was a higher ratio of Prevotella to Bacteroides in the obese group (p=0.0058). LEfSe analysis showed a differential distribution of significantly abundant taxa in either the lean or obese groups, including increased relative abundance of Prevotella copri , among other taxa in the obese group. Functional profiling showed that pathways associated with decreased insulin sensitivity were upregulated in the obese group. Stool SCFAs (acetate, propionate and butyrate) were higher in the obese compared to the lean group (p<0.05 for all).

CONCLUSIONS

Our findings identify gut microbiome, microbial metabolite and functional pathways differences associated with obesity in T1D. These findings could be helpful in identifying gut microbiome targeted therapies to manage obesity in T1D.

The association between dietary amino acid profile and the risk of type 2 diabetes: Ravansar non-communicable disease cohort study

BACKGROUND

Type 2 diabetes (T2D) is one of the most common chronic diseases and the main risk factors for T2D consist of a combination of lifestyle, unhealthy diet, and genetic factors. Amino acids are considered to be a major component of dietary sources for many of the associations between dietary protein and chronic disease. Therefore, this study amied to determine the association between dietary amino acid intakes and the incidence of T2D.

METHODS

The present nested case-control study was conducted using data from the Ravansar Non-Communicable Disease (RaNCD) Cohort Study. The information required for this study was collected from individuals who participated in the Adult Cohort Study from the start of the study until September 2023. Over a 6-year follow-up period, data from 113 new T2D cases were available. Four controls were then randomly selected for each case using density sampling. Cases and controls were matched for sex and age at the interview. Food frequency questionnaire (FFQ) was used to collect data related to all amino acids including tryptophan, threonine, isoleucine, leucine, lysine, methionine, cysteine, phenylalanine, tyrosine, valine, arginine, histidine, alanine, aspartic acid, glutamic acid, glycine, proline, and serine were also extracted. Binary logistic regression was used to estimate the crude and adjusted odds ratio for the risk of T2D.

RESULTS

Using the univariable model, a significant association was found between T2D risk and branched-chain, alkaline, sulfuric, and essential amino acids in the fourth quartile. Accordingly, individuals in the fourth quartile had a 1.81- to 1.87-fold higher risk of developing new T2D than individuals in the lowest quartile (P<0.05). After adjustment for several variables, the risk of developing a new T2D was 2.70 (95% CI: 1.16-6.31), 2.68 (95% CI: 1.16-6.21), 2.98 (95% CI: 1.27-6.96), 2.45 (95% CI: 1.02-5.90), and 2.66 (95% CI: 1.13-6.25) times higher, for individuals in the fourth quartile of branched-chain, alkaline, sulfuric, alcoholic, and essential amino acids compared with those in the lowest quartile, respectively.

CONCLUSIONS

The results showed that the risk of developing a new T2D was higher for individuals in the fourth quartile of branched-chain amino acids, alkaline, sulfate, and essential amino acids than in the lower quartile.

Metabolite profiles of diabetes mellitus and response to intervention in anti-hyperglycemic drugs

Type 2 diabetes mellitus (T2DM) has become a major health problem, threatening the quality of life of nearly 500 million patients worldwide. As a typical multifactorial metabolic disease, T2DM involves the changes and interactions of various metabolic pathways such as carbohydrates, amino acid, and lipids. It has been suggested that metabolites are not only the endpoints of upstream biochemical processes, but also play a critical role as regulators of disease progression. For example, excess free fatty acids can lead to reduced glucose utilization in skeletal muscle and induce insulin resistance; metabolism disorder of branched-chain amino acids contributes to the accumulation of toxic metabolic intermediates, and promotes the dysfunction of β-cell mitochondria, stress signal transduction, and apoptosis. In this paper, we discuss the role of metabolites in the pathogenesis of T2DM and their potential as biomarkers. Finally, we list the effects of anti-hyperglycemic drugs on serum/plasma metabolic profiles.

Causality Investigation between Gut Microbiota, Derived Metabolites, and Obstructive Sleep Apnea: A Bidirectional Mendelian Randomization Study

Various studies have highlighted the important associations between obstructive sleep apnea (OSA) and gut microbiota and related metabolites. Nevertheless, the establishment of causal relationships between these associations remains to be determined. Multiple mendelian randomization (MR) analyses were performed to genetically predict the causative impact of 196 gut microbiota and 83 metabolites on OSA. Two-sample MR was used to assess the potential association, and causality was evaluated using inverse variance weighted (IVW), MR-Egger, and weighted median (WM) methods. Multivariable MR (MVMR) was employed to ascertain the causal independence between gut microbiota and the metabolites linked to OSA. Additionally, Cochran's Q test, the MR Egger intercept test and the MR Steiger test were used for the sensitivity analyses. The analysis of the 196 gut microbiota revealed that genus_Ruminococcaceae (UCG009) (PIVW = 0.010) and genus_Subdoligranulum (PIVW = 0.041) were associated with an increased risk of OSA onset. Conversely, Family_Ruminococcaceae (PIVW = 0.030), genus_Coprococcus2 (PWM = 0.025), genus_Eggerthella (PIVW = 0.011), and genus_Eubacterium (xylanophilum_group) (PIVW = 0.001) were negatively related to the risk of OSA. Among the 83 metabolites evaluated, 3-dehydrocarnitine, epiandrosterone sulfate, and leucine were determined to be potential independent risk factors associated with OSA. Moreover, the reverse MR analysis demonstrated a suggestive association between OSA exposure and six microbiota taxa. This study offers compelling evidence regarding the potential beneficial or detrimental causative impact of the gut microbiota and its associated metabolites on OSA risk, thereby providing new insights into the mechanisms of gut microbiome-mediated OSA development.

Depiction of Branched-Chain Amino Acids (BCAAs) in Diabetes with a Focus on Diabetic Microvascular Complications

Type 2 diabetes mellitus (T2DM) still holds the title as one of the most debilitating chronic diseases with rising prevalence and incidence, including its complications such as retinal, renal, and peripheral nerve disease. In order to develop novel molecules for diagnosis and treatment, a deep understanding of the complex molecular pathways is imperative. Currently, the existing agents for T2DM treatment target only blood glucose levels. Over the past decades, specific building blocks of proteins-branched-chain amino acids (BCAAs) including leucine, isoleucine, and valine-have gained attention because they are linked with insulin resistance, pre-diabetes, and diabetes development. In this review, we discuss the hypothetical link between BCAA metabolism, insulin resistance, T2DM, and its microvascular complications including diabetic retinopathy and diabetic nephropathy. Further research on these amino acids and their derivates may eventually pave the way to novel biomarkers or therapeutic concepts for the treatment of diabetes and its accompanied complications.

Plasma metabolomic response to high-carbohydrate meals of differing glycaemic load in overweight women

BACKGROUND

Metabolomic dysregulation following a meal in overweight individuals with the Metabolic Syndrome (MetS) involves multiple pathways of nutrient storage and oxidation.

OBJECTIVE

The aim of the current study was to perform an acute cross-over intervention to examine the interactive actions of meal glycaemic load (GL) on the dynamic responses of the plasma metabolome in overweight females.

METHODS

Postmenopausal women [63 ± 1.23y; Healthy (n = 20) and MetS (n = 20)] ingested two differing high-carbohydrate test meals (73 g carbohydrate; 51% energy) composed of either low glycemic index (LGI) or high (HGI) foods in a randomised sequence. Plasma metabolome was analysed using liquid chromatography-mass spectrometry (LC-MS).

RESULTS

In the overweight women with MetS, there were suppressed postprandial responses for several amino acids (AAs), including phenylalanine, leucine, valine, and tryptophan, p < 0.05), irrespective of the meal type. Meal GL exerted a limited impact on the overall metabolomic response, although the postprandial levels of alanine were higher with the low GL meal and uric acid was greater following the high GL meal (p < 0.05).

CONCLUSIONS

MetS participants exhibited reduced differences in the concentrations of a small set of AAs and a limited group of metabolites implicated in energy metabolism following the meals. However, the manipulation of meal GL had minimal impact on the postprandial metabolome. This study suggests that the GL of a meal is not a major determinant of postprandial response, with a greater impact exerted by the metabolic health of the individual. Trial registration Australia New Zealand Clinical Trials Registry: ACTRN12615001108505 (21/10/2015).

Insulin Resistance and Impaired Branched-Chain Amino Acid Metabolism in Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) is complicated and involves multiple contributing factors. Mounting evidence supports the concept that AD is an age-related metabolic neurodegenerative disease mediated in part by brain insulin resistance, and sharing similar metabolic dysfunctions and brain pathological characteristics that occur in type 2 diabetes mellitus (T2DM) and other insulin resistance disorders. Brain insulin signal pathway is a major regulator of branched-chain amino acid (BCAA) metabolism. In the past several years, impaired BCAA metabolism has been described in several insulin resistant states such as obesity, T2DM and cardiovascular disease. Disrupted BCAA metabolism leading to elevation in circulating BCAAs and related metabolites is an early metabolic phenotype of insulin resistance and correlated with future onset of T2DM. Brain is a major site for BCAA metabolism. BCAAs play pivotal roles in normal brain function, especially in signal transduction, nitrogen homeostasis, and neurotransmitter cycling. Evidence from animal models and patients support the involvement of BCAA dysmetabolism in neurodegenerative diseases including Huntington's disease, Parkinson's disease, and maple syrup urine disease. More recently, growing studies have revealed altered BCAA metabolism in AD, but the relationship between them is poorly understood. This review is focused on the recent findings regarding BCAA metabolism and its role in AD. Moreover, we will explore how impaired BCAA metabolism influences brain function and participates in the pathogenesis of AD.

Cardiovascular risk of metabolically healthy obesity in two european populations: Prevention potential from a metabolomic study

BACKGROUND

A new definition of metabolically healthy obesity (MHO) has recently been proposed to stratify the heterogeneous mortality risk of obesity. Metabolomic profiling provides clues to metabolic alterations beyond clinical definition. We aimed to evaluate the association between MHO and cardiovascular events and assess its metabolomic pattern.

METHODS

This prospective study included Europeans from two population-based studies, the FLEMENGHO and the Hortega study. A total of 2339 participants with follow-up were analyzed, including 2218 with metabolomic profiling. Metabolic health was developed from the third National Health and Nutrition Examination Survey and the UK biobank cohorts and defined as systolic blood pressure < 130 mmHg, no antihypertensive drugs, waist-to-hip ratio < 0.95 for women or 1.03 for men, and the absence of diabetes. BMI categories included normal weight, overweight, and obesity (BMI < 25, 25-30, ≥ 30 kg/m²). Participants were classified into six subgroups according to BMI category and metabolic healthy status. Outcomes were fatal and nonfatal composited cardiovascular events.

RESULTS

Of 2339 participants, the mean age was 51 years, 1161 (49.6%) were women, 434 (18.6%) had obesity, 117 (5.0%) were classified as MHO, and both cohorts had similar characteristics. Over a median of 9.2-year (3.7-13.0) follow-up, 245 cardiovascular events occurred. Compared to those with metabolically healthy normal weight, individuals with metabolic unhealthy status had a higher risk of cardiovascular events, regardless of BMI category (adjusted HR: 3.30 [95% CI: 1.73-6.28] for normal weight, 2.50 [95% CI: 1.34-4.66] for overweight, and 3.42 [95% CI: 1.81-6.44] for obesity), whereas those with MHO were not at increased risk of cardiovascular events (HR: 1.11 [95% CI: 0.36-3.45]). Factor analysis identified a metabolomic factor mainly associated with glucose regulation, which was associated with cardiovascular events (HR: 1.22 [95% CI: 1.10-1.36]). Individuals with MHO tended to present a higher metabolomic factor score than those with metabolically healthy normal weight (0.175 vs. -0.057, P = 0.019), and the score was comparable to metabolically unhealthy obesity (0.175 vs. -0.080, P = 0.91).

CONCLUSIONS

Individuals with MHO may not present higher short-term cardiovascular risk but tend to have a metabolomic pattern associated with higher cardiovascular risk, emphasizing a need for early intervention.

MetaboVariation: Exploring Individual Variation in Metabolite Levels

To date, most metabolomics biomarker research has focused on identifying disease biomarkers. However, there is a need for biomarkers of early metabolic dysfunction to identify individuals who would benefit from lifestyle interventions. Concomitantly, there is a need to develop strategies to analyse metabolomics data at an individual level. We propose "MetaboVariation", a method that models repeated measurements on individuals to explore fluctuations in metabolite levels at an individual level. MetaboVariation employs a Bayesian generalised linear model to flag individuals with intra-individual variations in their metabolite levels across multiple measurements. MetaboVariation models repeated metabolite levels as a function of explanatory variables while accounting for intra-individual variation. The posterior predictive distribution of metabolite levels at the individual level is available, and is used to flag individuals with observed metabolite levels outside the 95% highest posterior density prediction interval at a given time point. MetaboVariation was applied to a dataset containing metabolite levels for 20 metabolites, measured once every four months, in 164 individuals. A total of 28% of individuals with intra-individual variations in three or more metabolites were flagged. An R package for MetaboVariation was developed with an embedded R Shiny web application. To summarize, MetaboVariation has made considerable progress in developing strategies for analysing metabolomics data at the individual level, thus paving the way toward personalised healthcare.

Decreased Hyocholic Acid and Lysophosphatidylcholine Induce Elevated Blood Glucose in a Transgenic Porcine Model of Metabolic Disease

(1) Background: This work aims to investigate the metabolomic changes in PIGinH11 pigs and investigate differential compounds as potential therapeutic targets for metabolic diseases. (2) Methods: PIGinH11 pigs were established with a CRISPR/Cas9 system. PNPLA3^I148M, hIAPP, and GIPR^dn were knocked in the H11 locus of the pig genome. The differential metabolites between and within groups were compared at baseline and two months after high-fat-high-sucrose diet induction. (3) Results: 72.02% of the 815 detected metabolites were affected by the transgenic effect. Significantly increased metabolites included isoleucine, tyrosine, methionine, oxoglutaric acid, acylcarnitine, glucose, sphinganines, ceramides, and phosphatidylserines, while fatty acids and conjugates, phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins were decreased. Lower expression of GPAT3 and higher expression of PNPLA3^I148M decreased the synthesis of diacylglycerol and phosphatidylcholines. Accumulated ceramides that block Akt signaling and decrease hyocholic acid and lysophosphatidylcholines might be the main reason for increased blood glucose in PIGinH11 pigs, which was consistent with metabolomic changes in patients. (4) Conclusions: Through serum metabolomics and lipidomics studies, significant changes in obesity and diabetes-related biomarkers were detected in PIGinH11 pigs. Excessive fatty acids β-oxidation interfered with glucose and amino acids catabolism and reduced phosphatidylcholines. Decreased hyocholic acid, lysophosphatidylcholine, and increased ceramides exacerbated insulin resistance and elevated blood glucose. Phosphatidylserines were also increased, which might promote chronic inflammation by activating macrophages.