Association between insulin resistance and plasma amino acid profile in non-diabetic Japanese subjects

Unlocking the Potential: Amino Acids' Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus

Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.

Aromatic Amino Acids and Their Interactions with Gut Microbiota-Related Metabolites for Risk of Gestational Diabetes: A Prospective Nested Case-Control Study in a Chinese Cohort

INTRODUCTION

The aim of this study was to explore associations of aromatic amino acids (AAA) in early pregnancy with gestational diabetes mellitus (GDM), and whether high AAA and gut microbiota-related metabolites had interactive effects on GDM risk.

METHODS

We conducted a 1:1 case-control study (n = 486) nested in a prospective cohort of pregnant women from 2010 to 2012. According to the International Association of Diabetes and Pregnancy Study Group's criteria, 243 women were diagnosed with GDM. Binary conditional logistic regression was performed to examine associations of AAA with GDM risk. Interactions between AAA and gut microbiota-related metabolites for GDM were examined using additive interaction measures.

RESULTS

High phenylalanine and tryptophan were associated with increased GDM risk (OR: 1.72, 95% CI: 1.07-2.78 and 1.66, 1.02-2.71). The presence of high trimethylamine (TMA) markedly increased the OR of high phenylalanine alone up to 7.95 (2.79-22.71), while the presence of low glycoursodeoxycholic acid (GUDCA) markedly increased the OR of high tryptophan alone up to 22.88 (5.28-99.26), both with significant additive interactions. Furthermore, high lysophosphatidylcholines (LPC18:0) mediated both interactive effects.

CONCLUSIONS

High phenylalanine may have an additive interaction with high TMA, while high tryptophan may have an additive interaction with low GUDCA toward increased risk of GDM, both being mediated via LPC18:0.

Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications

Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.

Molecular characterization of variants in mitochondrial DNA encoded genes using next generation sequencing analysis and mitochondrial dysfunction in women with PCOS

Emerging studies indicates mitochondrial dysfunction and involvement of mitochondrial DNA (mtDNA) variants in the pathogenesis of polycystic ovary syndrome (PCOS). Cumulative effect of mtDNA rare variants are now gaining considerable interest apart from common variants in the pathogenesis of complex diseases. Rare variants may modify the effect of polymorphism or in combination with the common variants may affect the risk of disease. With the evolution of high throughput sequencing techniques, which can be utilized to identify common as well as rare variants along with heteroplasmy levels, comprehensive characterization of the mtDNA variants is possible. Till date, few studies reported common mtDNA variants using traditional sequencing techniques but rare variants in mtDNA encoding genes remain unexplored in women with PCOS. These mtDNA variants may be responsible for mitochondrial dysfunction and may contribute in PCOS pathogenesis. In this study we determined mtDNA copy number, a biomarker of mitochondrial dysfunction and first time analysed variants in mtDNA encoded genes in women with PCOS using mitochondrial Next Generation sequencing (NGS) approach and compared allele frequency from mitochondrial 1000 genome dataset. Variant annotation and prioritization was done using highly automated pipeline, MToolBox that excludes reads mapped from nuclear mitochondrial DNA sequences (NumtS) to identify unique mtDNA reads. The present study identified significant reduction in mtDNA copy number in women with PCOS compared to non-PCOS women. A total of unique 214 prioritized common to rare variants were identified in mtDNA encoded genes, 183 variants in OXPHOS complexes, 14 variants in MT-tRNA and 17 variants in MT-rRNA genes that may be involved in mitochondrial dysfunction in PCOS. Numerous variants were heteroplasmic, pathogenic in nature and occurred in evolutionary conserved region. Heteroplasmic variants were more frequently occurred in MT-CO3 gene. Non-synonymous variants were more than synonymous variants and mainly occurred in OXPHOS complex I and IV. Few variants were found to be associated with diseases in MITOMAP database. The study provides a better understanding towards pathogenesis of PCOS from novel aspects focusing on mitochondrial genetic defects as underlying cause for contributing mitochondrial dysfunction in women with PCOS.

Metabolomic profiles in night shift workers: A cross-sectional study on hospital female nurses

Background and aim

Shift work, especially including night shifts, has been found associated with several diseases, including obesity, diabetes, cancers, and cardiovascular, mental, gastrointestinal and sleep disorders. Metabolomics (an omics-based methodology) may shed light on early biological alterations underlying these associations. We thus aimed to evaluate the effect of night shift work (NSW) on serum metabolites in a sample of hospital female nurses.

Methods

We recruited 46 nurses currently working in NSW in Milan (Italy), matched to 51 colleagues not employed in night shifts. Participants filled in a questionnaire on demographics, lifestyle habits, personal and family health history and work, and donated a blood sample. The metabolome was evaluated through a validated targeted approach measuring 188 metabolites. Only metabolites with at least 50% observations above the detection limit were considered, after standardization and log-transformation. Associations between each metabolite and NSW were assessed applying Tobit regression models and Random Forest, a machine-learning algorithm.

Results

When comparing current vs. never night shifters, we observed lower levels of 21 glycerophospholipids and 6 sphingolipids, and higher levels of serotonin (+171.0%, 95%CI: 49.1-392.7), aspartic acid (+155.8%, 95%CI: 40.8-364.7), and taurine (+182.1%, 95%CI: 67.6-374.9). The latter was higher in former vs. never night shifters too (+208.8%, 95%CI: 69.2-463.3). Tobit regression comparing ever (i.e., current + former) and never night shifters returned similar results. Years worked in night shifts did not seem to affect metabolite levels. The Random-Forest algorithm confirmed taurine and aspartic acid among the most important variables in discriminating current vs. never night shifters.

Conclusions

This study, although based on a small sample size, shows altered levels of some metabolites in night shift workers. If confirmed, our results may shed light on early biological alterations that might be related to adverse health effects of NSW.

AMINO ACIDS METABOLOMIC SIGNATURE OF BLOOD PRESSURE VARIABILITY In Type 2 Diabetes

Context

Accumulating data supports the key role of disrupted amino acids (AAs) metabolism in diabetes. Conflicting data regarding the relevance of serum AAs in diabetes and hypertension suggest that their relationship needs further investigation.

Objective

To investigate serum AAs as biomarkers of increased BP variability evaluated during 24-hour ambulatory BP monitoring in the presence of type 2 diabetes.

Design

Cross-sectional.

Subjects and Methods

We analyzed serum AAs using targeted metabolomics (ultrahigh-performance liquid chromatography/mass spectrometry) in patients with type 2 diabetes (n=80). BP variability was assessed using 24-hour ambulatory BP monitoring. Participants were divided into two groups based on the 24-hour diastolic BP variability median value.

Results

Aspartic acid, isoleucine, leucine, and phenylalanine were significantly lower, while glutamine was significantly higher in the group with higher diastolic BP variability (p-value <0.05 and variable importance in the projection >1). Corresponding pathways identified as disrupted in patients with diabetes and a higher 24-hour diastolic BP variability were phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and alanine, aspartate, and glutamate metabolism (pathway impact value >0).

Conclusions

We identified specific changes in serum AAs and target AAs pathways in relation to increased 24-hour diastolic BP variability in patients with type 2 diabetes.

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.

Associations of serum amino acids with insulin resistance among people with and without overweight or obesity: A prospective study in Japan

BACKGROUND & AIMS

Limited evidence exists regarding the prospective associations between amino acids and insulin resistance. In addition, amino acids have been suggested to promote insulin resistance with the requirement of obesity in animal studies, but the interaction between amino acids and obesity on the development of insulin resistance has not been examined in epidemiological studies. We aimed to investigate the differences in the prospective associations of serum amino acids with insulin resistance among adults with and without overweight or obesity.

METHODS

Fasting serum concentrations of 25 amino acids were quantified in 1131 non-diabetic Japanese workers aged 22-71 years at baseline. The homeostasis model assessment of insulin resistance (HOMA-IR) was estimated at baseline and the 3-year follow-up. Generalized linear models were used to assess the associations between amino acids at baseline and HOMA-IR at follow-up with adjustment for potential confounding factors. A Bonferroni-corrected threshold of p = 0.001 was considered significant for multiple tests.

RESULTS

The associations for the following amino acids with HOMA-IR at the 3-year follow-up significantly varied by obesity status: isoleucine, valine, tyrosine, alanine, and methionine (all p for interaction <0.05). Higher concentrations of serum isoleucine, valine, tyrosine, and alanine (per 1SD) were significantly associated with higher HOMA-IR levels in overweight/obese participants (multivariable-adjusted β coefficients ranging from 0.09 to 0.12; all p < 0.001), but no association was observed in the underweight/normal-weight participants. The associations for serum methionine were direct among overweight/obese participants, but inverse among underweight/normal-weight participants (all p < 0.001).

CONCLUSIONS

This study demonstrated the prospective associations of different individual serum amino acids with insulin resistance, with most pronounced associations being for overweight/obese adults. Our findings support the possibility of heterogeneous effects of individual amino acids, as well as their interplay with obesity in the progression of insulin resistance.

Plasma Amino Acid Concentrations in Patients with Alcohol and/or Cocaine Use Disorders and Their Association with Psychiatric Comorbidity and Sex

(1) Background: Co-occurrence of mental and substance use disorders (SUD) is prevalent, but complicates their clinical courses, and specific biomarkers are required. Amino acids are altered in primary mental disorders; however, little is known about SUD and psychiatric comorbidity. Because most psychiatric disorders and biomarkers show sex differences, we investigated amino acids in men and women with alcohol and/or cocaine use disorders (AUD and/or CUD) and psychiatric comorbidity. (2) Methods: A cross-sectional study was conducted in 295 participants, who were divided into four groups (AUD, n = 60; CUD, n = 41; AUD + CUD, n = 64; and control, n = 130). Participants were clinically assessed, and plasma amino acid concentrations were analyzed in relation to sex, diagnosis of SUD and psychiatric comorbidity (3) Results: In the total sample, there were sex differences, and women showed lower Iso, Leu, Gln and Glu than men. While patients with CUD and AUD + CUD had higher Glu, Gly, Orn and Ser than controls, patients with AUD showed no differences. In SUD, patients with psychiatric comorbidity had lower Orn and higher Ala than non-comorbid patients in the AUD group. (4) Conclusions: There was a dysregulation of plasma amino acids in abstinent patients with SUD. However, our results suggest the importance of considering the clinical characteristics and sex in the validity of amino acids as potential biomarkers for SUD.

Positive association of branched-chain amino acids with triglyceride and glycated haemoglobin in Indian patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

Over the past few years, branched-chain amino acids (BCAAs) are increasingly being linked to insulin resistance and type 2 diabetes mellitus (T2DM), but their relevance for metabolic dyslipidaemia in T2DM is unclear. This study aims to determine the plasma and urinary BCAAs and their association with insulin resistance, lipid profile and glycated haemoglobin in patients with T2DM among Indian adults.

METHODS

In this analytical cross-sectional study, a total of eighty subjects were recruited, 40 T2DM cases and 40 healthy controls. Blood samples collected were subjected to fasting blood sugar (FBS), lipid profile, HbA1c, insulin and BCAAs analysis and urine samples were assessed for BCAAs. All associations were assessed using Spearman Rank Correlation.

RESULTS

The plasma levels of BCAAs were significantly higher (p < 0.05) in subjects with T2DM than in control subjects. Spearman Rank Correlation analyses revealed a non-significant (p = 0.21) but positive association between BCAAs and homeostasis model assessment of insulin resistance (HOMA-IR) in patients with T2DM (Rho: 0.27). Among lipid profile parameters, only triglycerides had a significant positive correlation to plasma BCAAs in cases (Rho: 0.5971) but not in control subjects. Findings also revealed a significant positive (p < 0.05) association between plasma BCAAs and HbA1c in patients with T2DM (Rho: 0.5325). Urinary BCAAs levels had a non-significant increase in T2DM subjects and did not show any significant correlation with other parameters assessed.

CONCLUSION

Elevated levels of plasma BCAAs are positively associated with triglyceride and HbA1c. They could serve as an effective marker for the assessment of metabolic dyslipidaemia in subjects with T2DM. Further, large scale studies are needed for confirmation of the same.

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.

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.

Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort

In a Chinese prospective cohort, 500 patients with new-onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discover the metabolite changes before T2D onset and the related diabetogenic loci. A serum metabolomics analysis reveals that 81 metabolites changed significantly before T2D onset. Based on binary logistic regression, eight metabolites are defined as a biomarker panel for T2D prediction. Pipecolinic acid, carnitine C14:0, epinephrine and phosphatidylethanolamine 34:2 are first found associated with future T2D. The addition of the biomarker panel to the clinical markers (BMI, triglycerides, and fasting glucose) significantly improves the predictive ability in the discovery and validation sets, respectively. By associating metabolomics with genomics, a significant correlation (p < 5.0 × 10-8) between eicosatetraenoic acid and the FADS1 (rs174559) gene is observed, and suggestive correlations (p < 5.0 × 10-6) between pipecolinic acid and CHRM3 (rs535514), and leucine/isoleucine and WWOX (rs72487966) are discovered. Elevated leucine/isoleucine levels increased the risk of T2D. In conclusion, multiple metabolic dysregulations are observed to occur before T2D onset, and the new biomarker panel can help to predict T2D risk.

Markers of branched-chain amino acid catabolism are not affected by exercise training in pregnant women with obesity

Despite the role of branched-chain amino acids (BCAAs) in physiological processes such as nutrient signaling and protein synthesis, there is ongoing debate about the link between circulating BCAAs and insulin resistance (IR) in various populations. In healthy women, IR mildly increases during pregnancy, whereas both BCAAs and markers of BCAA catabolism decrease, indicating that fetal growth is being prioritized. Exercise reduces IR in nonpregnant adults, but less is known about the effect of exercise during pregnancy in women with obesity on IR and BCAA breakdown. The aim of this study was to determine the effect of a moderate-intensity exercise intervention during pregnancy on maternal circulating BCAAs and markers of BCAA catabolism [short-chain acylcarnitines (ACs)], and their associations with IR. Healthy obese [n = 80, means ± SD; body mass index (BMI): 36.9 ± 5.7 kg/m²] pregnant women were randomized into an exercise (n = 40, aerobic/resistance 3×/wk, ∼13th gestation week until birth) or a nonexercise control (n = 40) group. Blood was collected at 12.2 ± 0.5 and 36.0 ± 0.4 gestation weeks and analyzed for BCAA-derived acylcarnitine concentrations as markers of BCAA breakdown toward oxidative pathways, and glucose and insulin concentrations [updated homeostatic model assessment of IR (HOMA2-IR)]. After adjusting for HOMA2-IR, there were no interaction effects of group by time. In addition, there was a main positive effect of time on HOMA2-IR (12 wk: 2.3 ± 0.2, 36 wk: 3.0 ± 0.2, P = 0.003). A moderate-intensity exercise intervention during pregnancy in women with obesity was not associated with changes in BCAA-derived ACs versus standard of care. The decrease in BCAA-derived ACs throughout gestation could not be explained by IR.NEW & NOTEWORTHY This research showed an increase in insulin resistance (IR) and decrease in branched-chain amino acid catabolism throughout gestation in women with obesity, and addition of a moderate exercise intervention (known to attenuate IR in nonpregnant populations) did not alter these shifts. Findings provide support for metabolic safety of exercise during pregnancy.

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.

Metabolic dysfunction in pregnancy: Fingerprinting the maternal metabolome using proton nuclear magnetic resonance spectroscopy

Aims

Maternal metabolic disorders place the mother at risk for negative pregnancy outcomes with potentially long-term health impacts for the child. Metabolic syndrome, a cluster of features associated with increased risk of metabolic disorders, such as cardiovascular disease, diabetes and stroke, affects roughly one in five Canadians. Metabolomics is a relatively new technique that may be a useful tool to identify women at risk of metabolic disorders. This study set out to characterize urinary metabolic biomarkers of pregnant women with obesity and of pregnant women who later developed gestational diabetes mellitus (pre-GDM), compared to controls.

Methods and Materials

Second trimester urine samples were collected through the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort and examined with 1H nuclear magnetic resonance (NMR) spectroscopy. Multivariate analysis was used to examine group differences, and machine learning feature selection tools identified the metabolites contributing to separation.

Results

Obesity and pre-GDM metabolomes were distinct from controls and from each other. In each comparison, the glycine, serine and threonine pathways were the most impacted. Pantothenate, formic acid and glycine were downregulated by obesity, while formic acid, dimethylamine and galactose were downregulated in pre-GDM. The three most impacted metabolites for the comparison of obesity versus pre-GDM groups were upregulated creatine/caffeine, downregulated sarcosine/dimethylamine and upregulated maltose/sucrose in individuals who later developed GDM.

Conclusion

These findings suggest a role for urinary metabolomics in the prediction of GDM and metabolic marker identification for potential diagnostics and prognostics in women at risk.

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 and aromatic amino acids and cardiometabolic risk in Black African and Asian Indian populations

INTRODUCTION

Studies have shown that systemic levels of branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) are elevated in cardiometabolic diseases (CMDs) in populations resident in high income countries. However, little is known about the association of BCAAs and AAAs with metabolic syndrome and its components in Asian Indian (AI) and Black African (BA) populations.

OBJECTIVE

The aim of this study was to describe the association of BCAAs and AAAs with the metabolic syndrome, its individual components and insulin resistance in AI and BA populations.

METHODS

Serum samples collected from AI (n = 349) and BA (n = 369) subjects were used to measure levels of BCAAs and AAAs by ultra-pressure liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Anthropometric, demographic and cardiometabolic variables were measured in all subjects.

RESULTS

The sum of BCAAs and AAAs was higher in AIs compared to BAs. The BCAAs and AAAs were positively associated with insulin resistance, metabolic syndrome and its individual components. This was particularly the case for AI subjects, in unadjusted regression models. However, these associations were non-significant after adjusting for co-variates, particularly visceral adipose tissue (VAT). Triglyceride levels were significantly associated with valine and leucine levels in BAs even after adjustment for co-variates. Lastly, we found that fasting circulatory BCAA and AAA levels are strongly correlated with VAT in both populations.

CONCLUSION

This study identified specific associations of serum valine and leucine levels with triglycerides in BAs. The association of amino acids with CMDs was observed in AIs, but was found to be the result of confounding by VAT. Further studies are required to determine whether BCAAs and AAAs are aetiological factors in CMDs and how VAT modulates their serum levels.

Exploring mechanistic links between extracellular branched-chain amino acids and muscle insulin resistance: an in vitro approach

Branched-chain amino acids (BCAAs) are essential for critical metabolic processes; however, recent studies have associated elevated plasma BCAA levels with increased risk of insulin resistance. Using skeletal muscle cells, we aimed to determine whether continued exposure of high extracellular BCAA would result in impaired insulin signaling and whether the compound sodium phenylbutyrate (PB), which induces BCAA metabolism, would lower extracellular BCAA, thereby alleviating their potentially inhibitory effects on insulin-mediated signaling. Prolonged exposure of elevated BCAA to cells resulted in impaired insulin receptor substrate 1/AKT signaling and insulin-stimulated glycogen synthesis. PB significantly reduced media BCAA and branched-chain keto acid concentrations and increased phosphorylation of AKT [+2.0 ± 0.1-fold; P < 0.001 versus without (-)PB] and AS160 (+3.2 ± 0.2-fold; P < 0.001 versus -PB); however, insulin-stimulated glycogen synthesis was further reduced upon PB treatment. Continued exposure of high BCAA resulted in impaired intracellular insulin signaling and glycogen synthesis, and while forcing BCAA catabolism using PB resulted in increases in proteins important for regulating glucose uptake, PB did not prevent the impairments in glycogen synthesis with BCAA exposure.

Altered Metabolome of Lipids and Amino Acids Species: A Source of Early Signature Biomarkers of T2DM

Diabetes mellitus, a disease of modern civilization, is considered the major mainstay of mortalities around the globe. A great number of biochemical changes have been proposed to occur at metabolic levels between perturbed glucose, amino acid, and lipid metabolism to finally diagnoe diabetes mellitus. This window period, which varies from person to person, provides us with a unique opportunity for early detection, delaying, deferral and even prevention of diabetes. The early detection of hyperglycemia and dyslipidemia is based upon the detection and identification of biomarkers originating from perturbed glucose, amino acid, and lipid metabolism. The emerging “OMICS” technologies, such as metabolomics coupled with statistical and bioinformatics tools, proved to be quite useful to study changes in physiological and biochemical processes at the metabolic level prior to an eventual diagnosis of DM. Approximately 300–400 such metabolites have been reported in the literature and are considered as predicting or risk factor-reporting metabolic biomarkers for this metabolic disorder. Most of these metabolites belong to major classes of lipids, amino acids and glucose. Therefore, this review represents a snapshot of these perturbed plasma/serum/urinary metabolic biomarkers showing a significant correlation with the future onset of diabetes and providing a foundation for novel early diagnosis and monitoring the progress of metabolic syndrome at early symptomatic stages. As most metabolites also find their origin from gut microflora, metabolism and composition of gut microflora also vary between healthy and diabetic persons, so we also summarize the early changes in the gut microbiome which can be used for the early diagnosis of diabetes.

Divergent Changes in Serum Branched-Chain Amino Acid Concentrations and Estimates of Insulin Resistance throughout Gestation in Healthy Women

BACKGROUND

Branched-chain amino acid (BCAA) concentrations in the blood have been correlated with insulin resistance, but this relation throughout gestation (period in which insulin resistance typically increases) is unclear.

OBJECTIVE

The objective of this study was to determine the associations between changes in BCAA concentrations and estimates of insulin resistance throughout gestation.

METHODS

Serum BCAA (Leu, Ile, Val) concentrations and insulin resistance/sensitivity [i.e., homeostatic model assessment-2 of insulin resistance (HOMA2-IR), estimated metabolic clearance rate (MCR) of glucose, and estimated first- and second-phase insulin responses] were assessed at early (EP; 8.5 ± 0.2 wk) and/or late (LP; 29.2 ± 0.8 wk) pregnancy in 53 healthy women from the Glowing cohort. Adjusted Spearman correlations were used to evaluate the association between BCAA and insulin resistance/sensitivity measures at EP and LP, adjusted for body fat percentage and gestational weight gain (GWG). A multiple linear regression analysis was used to assess the association between changes in HOMA2-IR and BCAAs throughout gestation. Groups were made post hoc based on the mean percentage change (10% decrease) in Leu throughout gestation, creating a group with a ≥10% decrease in LeuLP-EP (BELOW) and a <10% decrease in LeuLP-EP (ABOVE), and Student's t tests were performed to assess differences between groups.

RESULTS

Leu and Ile concentrations positively correlated with HOMA2-IR at both time points, but these relations at EP disappeared/weakened when adjusted for body fat percentage. From EP to LP, the change in Leu (LeuLP-EP) was negatively associated with the change in HOMA2-IR (HOMA2-IRLP-EP) (β = -0.037, P = 0.006). MCR was lower in the BELOW group compared with the ABOVE group, whereas there was no difference in HOMA2-IR between groups.

CONCLUSIONS

In this pregnancy cohort, BCAA concentrations decreased throughout gestation, whereas the mean insulin resistance did not change. These data do not support a connection between changes in blood BCAA concentrations and estimates of insulin resistance in pregnant women. This trial is registered at clinicaltrials.gov as NCT01131117.

Identification of Variants in Mitochondrial D-Loop and OriL Region and Analysis of Mitochondrial DNA Copy Number in Women with Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a multifactorial disorder characterized by irregular menstrual problems, hyperandrogenism, and presence of polycystic ovaries. Till date, molecular mechanism underlying PCOS remains elusive. Recently mitochondrial displacement loop (D-loop) variants have been identified to be novel players in the pathogenesis of PCOS. At present, rare variants, besides common variants, are also the focus of research as it is believed to make essential contribution to the risk of complex diseases. However, rare and low hetroplasmic variants in mitochondrial D-loop are still not investigated in PCOS women. Furthermore, variants in light-strand origin of DNA replication (OriL) of mitochondrial DNA (mtDNA) have not been explored in PCOS. Hence, in this study, we investigated rare to common mitochondrial D-loop and OriL region variants obtained using mtDNA next-generation sequencing in women with PCOS. Furthermore, we also assessed mtDNA copy number, a biomarker of mitochondrial dysfunction (MD) in women with PCOS, as the variants in mtDNA are known to be associated with low mtDNA copy number in PCOS women. A total of 67 D-loop variants including 6 novel variants were identified in 30 PCOS women. Among 67 variants, 29 variants were reported in PCOS women. A single variant, 5746A was found in OriL region in two PCOS women. Both transition and transversion variants were found but transition variants occur at very high frequency compared with transversions (82.35% vs. 17.64%, respectively). As transition variants in mtDNA are known to arise because of polymerase γ errors, occurrence of high transition rates indicates that most mutation arises because of defect in replication errors that causes mtDNA damage leading to MD. Furthermore, mtDNA copy number was found to be low in women with PCOS compared with healthy control women suggesting that MD may be the contributing factor in the pathogenesis of PCOS.

Adverse Outcomes in Obese Cardiac Surgery Patients Correlates With Altered Branched-Chain Amino Acid Catabolism in Adipose Tissue and Heart

Background: Predicting relapses of post-operative complications in obese patients who undergo cardiac surgery is significantly complicated by persistent metabolic maladaptation associated with obesity. Despite studies supporting the linkages of increased systemic branched-chain amino acids (BCAAs) driving the pathogenesis of obesity, metabolome wide studies have either supported or challenged association of circulating BCAAs with cardiovascular diseases (CVDs). Objective: We interrogated whether BCAA catabolic changes precipitated by obesity in the heart and adipose tissue can be reliable prognosticators of adverse outcomes following cardiac surgery. Our study specifically clarified the correlation between BCAA catabolizing enzymes, cellular BCAAs and branched-chain keto acids (BCKAs) with the severity of cardiometabolic outcomes in obese patients pre and post cardiac surgery. Methods: Male and female patients of ages between 44 and 75 were stratified across different body mass index (BMI) (non-obese = 17, pre-obese = 19, obese class I = 14, class II = 17, class III = 12) and blood, atrial appendage (AA), and subcutaneous adipose tissue (SAT) collected during cardiac surgery. Plasma and intracellular BCAAs and BC ketoacids (BCKAs), tissue mRNA and protein expression and activity of BCAA catabolizing enzymes were assessed and correlated with clinical parameters. Results: Intramyocellular, but not systemic, BCAAs increased with BMI in cardiac surgery patients. In SAT, from class III obese patients, mRNA and protein expression of BCAA catabolic enzymes and BCKA dehydrogenase (BCKDH) enzyme activity was decreased. Within AA, a concomitant increase in mRNA levels of BCAA metabolizing enzymes was observed, independent of changes in BCKDH protein expression or activity. BMI, indices of tissue dysfunction and duration of hospital stay following surgery correlated with BCAA metabolizing enzyme expression and metabolite levels in AA and SAT. Conclusion: This study proposes that in a setting of obesity, dysregulated BCAA catabolism could be an effective surrogate to determine cardiac surgery outcomes and plausibly predict premature re-hospitalization.

The Emerging role of Branch Chain Amino Acids in the Prediction of Diabetes: A Brief Review

Diabetes is a chronic condition; those with diabetes are at high risk of developing diabetes complications. One important approach to tackle the diabetes burden is to screen for undiagnosed diabetes and to identify factors that lead to the risk of developing diabetes in the future. The earlier identification of individuals at risk of developing diabetes is crucial for delaying or preventing the onset of type 2 diabetes. Numerous studies have demonstrated that circulating concentrations of branch chain amino acids (BCAAs) predict the risk for developing diabetes; thus, contributing to the recent resurgence of interest in these common analytes. The present review aimed to address the recent findings regarding BCAAs and their role in insulin resistance and diabetes. Recent studies demonstrate that BCAAs are strongly associated with a number of pathological mechanisms causing insulin resistance and type 2 diabetes. The research findings related to BCAA signaling pathways and metabolism broaden our understanding of this topic. However, it remains unclear how increased levels of BCAAs will assist in the prediction of future insulin resistance or type 2 diabetes. Future research needs to determine whether BCAAs are a causative factor for insulin resistance and type 2 diabetes, or just a biomarker of impaired insulin action.

Plasma metabolites associated with homeostatic model assessment of insulin resistance: metabolite-model design and external validation

Different plasma metabolites have been related to insulin resistance (IR). However, there is a lack of metabolite models predicting IR with external validation. The aim of this study is to identify a multi-metabolite model associated to the homeostatic model assessment (HOMA)-IR values. We performed a cross-sectional metabolomics analysis of samples collected from overweight and obese subjects from two independent studies. The training step was performed in 236 subjects from the SATIN study and validated in 102 subjects from the GLYNDIET study. Plasma metabolomics profile was analyzed using three different approaches: GC/quadrupole-TOF, LC/quadrupole-TOF, and nuclear magnetic resonance (NMR). Associations between metabolites and HOMA-IR were assessed using elastic net regression analysis with a leave-one-out cross validation (CV) and 100 CV runs. HOMA-IR was analyzed both as linear and categorical (median or lower versus higher than the median). Receiver operating characteristic curves were constructed based on metabolites’ weighted models. A set of 30 metabolites discriminating extremes of HOMA-IR were consistently selected. These metabolites comprised some amino acids, lipid species and different organic acids. The area under the curve (AUC) for the discrimination between HOMA-IR extreme categories was 0.82 (95% CI: 0.74–0.90), based on the multi-metabolite model weighted with the regression coefficients of metabolites in the validation dataset. We identified a set of metabolites discriminating between extremes of HOMA-IR and able to predict HOMA-IR with high accuracy.

Creatinine, total cysteine and uric acid are associated with serum retinol in patients with cardiovascular disease

Purpose

We hypothesized that biomarkers and dietary factors related to cardiovascular disease risk were associated with serum retinol and evaluated these potential associations in patients with suspected coronary artery disease (CAD).

Methods

We used cross-sectional data from 4116 patients hospitalised for suspected CAD. Dietary data were obtained from a subgroup of 1962 patients using a food frequency questionnaire. Potential biomarkers and dietary factors were explored using linear regression modelling adjusted for age and sex. Regression coefficients and corresponding confidence intervals (CI) are given as  % change in serum retinol per unit change in the predictors. Analyses were performed in the total population and in strata of serum retinol tertiles.

Results

In age- and sex-adjusted models, serum creatinine (standardized β: 0.38, 95% CI [0.35, 0.42]), plasma total cysteine (0.26, [0.23, 0.29]), serum uric acid (0.30, [0.26, 0.33]) and plasma neopterin (0.22, [0.18, 0.25]) were positively associated, whereas plasma serine (− 0.15, [− 0.18, − 0.12]) and serum C-reactive protein (− 0.15, [− 0.18, − 0.12]) were inversely associated with serum retinol. When we included the significant biomarkers in a multivariate model, the model explained 33% of the variability (R² = 0.33) in serum retinol. The results were similar in the lower and upper tertiles of serum retinol. Weak or no associations were observed for dietary factors.

Conclusions

In patients with suspected CAD, concentrations of creatinine, cysteine and uric acid were positively associated with serum retinol. Future studies should assess whether retinol concentrations are influenced by metabolic alterations in patients at risk of cardiovascular disease.

Plasma metabolites predict both insulin resistance and incident type 2 diabetes: a metabolomics approach within the Prevención con Dieta Mediterránea (PREDIMED) study

BACKGROUND

Insulin resistance is a complex metabolic disorder and is often associated with type 2 diabetes (T2D).

OBJECTIVES

The aim of this study was to test whether baseline metabolites can additionally improve the prediction of insulin resistance beyond classical risk factors. Furthermore, we examined whether a multimetabolite model predicting insulin resistance in nondiabetics can also predict incident T2D.

METHODS

We used a case-cohort study nested within the Prevención con Dieta Mediterránea (PREDIMED) trial in subsets of 700, 500, and 256 participants without T2D at baseline and 1 and 3 y. Fasting plasma metabolites were semiquantitatively profiled with liquid chromatography-tandem mass spectrometry. We assessed associations between metabolite concentrations and the homeostasis model of insulin resistance (HOMA-IR) through the use of elastic net regression analysis. We subsequently examined associations between the baseline HOMA-IR-related multimetabolite model and T2D incidence through the use of weighted Cox proportional hazard models.

RESULTS

We identified a set of baseline metabolites associated with HOMA-IR. One-year changes in metabolites were also significantly associated with HOMA-IR. The area under the curve was significantly greater for the model containing the classical risk factors and metabolites together compared with classical risk factors alone at baseline [0.81 (95% CI: 0.79, 0.84) compared with 0.69 (95% CI: 0.66, 0.73)] and during a 1-y period [0.69 (95% CI: 0.66, 0.72) compared with 0.57 (95% CI: 0.53, 0.62)]. The variance in HOMA-IR explained by the combination of metabolites and classical risk factors was also higher in all time periods. The estimated HRs for incident T2D in the multimetabolite score (model 3) predicting high HOMA-IR (median value or higher) or HOMA-IR (continuous) at baseline were 2.00 (95% CI: 1.58, 2.55) and 2.24 (95% CI: 1.72, 2.90), respectively, after adjustment for T2D risk factors.

CONCLUSIONS

The multimetabolite model identified in our study notably improved the predictive ability for HOMA-IR beyond classical risk factors and significantly predicted the risk of T2D.

Plasma metabolites and lipids predict insulin sensitivity improvement in obese, nondiabetic individuals after a 2-phase dietary intervention

Background

Weight loss in obese individuals aims to reduce the risk of type 2 diabetes by improving glycemic control. Yet, significant intersubject variability is observed and the outcomes remain poorly predictable.

Objective

The aim of the study was to predict whether an individual will show improvements in insulin sensitivity above or below the median population change at 6 mo after a low-calorie-diet (LCD) intervention.

Design

With the use of plasma lipidomics and metabolomics for 433 subjects from the Diet, Obesity, and Genes (DiOGenes) Study, we attempted to predict good or poor Matsuda index improvements 6 mo after an 8-wk LCD intervention (800 kcal/d). Three independent analysis groups were defined: "training" (n = 119) for model construction, "testing" (n = 162) for model comparison, and "validation" (n = 152) to validate the final model.

Results

Initial modeling with baseline clinical variables (body mass index, Matsuda index, total lipid concentrations, sex, age) showed limited performance [area under the curve (AUC) on the "testing dataset" = 0.69; 95% CI: 0.61, 0.77]. Significantly better performance was achieved with an omics model based on 27 variables (AUC = 0.77; 95% CI: 0.70, 0.85; P = 0.0297). This model could be greatly simplified while keeping the same performance. The simplified model relied on baseline Matsuda index, proline, and phosphatidylcholine 0-34:1. It successfully replicated on the validation set (AUC = 0.75; 95% CI: 0.67, 0.83) with the following characteristics: specificity = 0.73, sensitivity = 0.68, negative predictive value = 0.60, and positive predictive value = 0.80. Marginally lower performance was obtained when replacing the Matsuda index with homeostasis model assessment of insulin resistance (AUC = 0.72; 95% CI: 0.64, 0.80; P = 0.08).

Conclusions

Our study proposes a model to predict insulin sensitivity improvements, 6 mo after LCD completion in a large population of overweight or obese nondiabetic subjects. It relies on baseline information from 3 variables, accessible from blood samples. This model may help clinicians assessing the large variability in dietary interventions and predict outcomes before an intervention. This trial was registered at www.clinicaltrials.gov as NCT00390637.

Amino acid profiles of young adults differ by sex, body mass index and insulin resistance

BACKGROUND AND AIMS

An increase in plasma branched-chain amino acids is associated with a higher risk of developing type 2 diabetes and cardiovascular diseases. However, little is known about the basal plasma amino acid concentrations in young adults. Our aim was to determine the plasma amino acid profiles of young adults and to evaluate how these profiles were modified by sex, body mass index (BMI) and insulin resistance (IR).

METHODS AND RESULTS

We performed a transversal study with 608 Mexican young adults aged 19.9 ± 2.4 years who were applicants to the Universidad Autónoma de San Luis Potosí. The subjects underwent a physical examination and provided a clinical history and a blood sample for biochemical, hormonal and amino acid analyses. The women had higher levels of arginine, aspartate and serine and lower levels of α-aminoadipic acid, cysteine, isoleucine, leucine, methionine, proline, tryptophan, tyrosine, urea and valine than the men. The obese subjects had higher levels of alanine, aspartate, cysteine, ornithine, phenylalanine, proline and tyrosine and lower levels of glycine, ornithine and serine than the normal weight subjects. Subjects with IR (defined as HOMA > 2.5) had higher levels of arginine, alanine, aspartate, isoleucine, leucine, phenylalanine, proline, tyrosine, taurine and valine than the subjects without IR. Furthermore, we identified two main groups in the subjects with obesity and/or IR; one group was composed of amino acids that positively correlated with the clinical, biochemical and hormonal parameters, whereas the second group exhibited negative correlations.

CONCLUSION

This study demonstrates that young adults with obesity or IR have altered amino acid profiles characterized by an increase in alanine, aspartate, proline and tyrosine and a decrease in glycine.

Evidence of a liver-alpha cell axis in humans: hepatic insulin resistance attenuates relationship between fasting plasma glucagon and glucagonotropic amino acids

AIMS/HYPOTHESIS

The secretion of glucagon is controlled by blood glucose and inappropriate secretion of glucagon contributes to hyperglycaemia in diabetes. Besides its role in glucose regulation, glucagon regulates amino acid metabolism in hepatocytes by increasing ureagenesis. Disruption of this mechanism causes hyperaminoacidaemia, which in turn increases glucagon secretion. We hypothesised that hepatic insulin resistance (secondary to hepatic steatosis) via defective glucagon signalling/glucagon resistance would lead to impaired ureagenesis and, hence, increased plasma concentrations of glucagonotropic amino acids and, subsequently, glucagon.

METHODS

To examine the association between glucagon and amino acids, and to explore whether this relationship was modified by hepatic insulin resistance, we studied a well-characterised cohort of 1408 individuals with normal and impaired glucose regulation. In this cohort, we have previously reported insulin resistance to be accompanied by increased plasma concentrations of glucagon. We now measure plasma levels of amino acids in the same cohort. HOMA-IR was calculated as a marker of hepatic insulin resistance.

RESULTS

Fasting levels of glucagonotropic amino acids and glucagon were significantly and inversely associated in linear regression models (persisting after adjustment for age, sex and BMI). Increasing levels of hepatic, but not peripheral insulin resistance (p > 0.166) attenuated the association between glucagon and circulating levels of alanine, glutamine and tyrosine, and was significantly associated with hyperaminoacidaemia and hyperglucagonaemia. A doubling of the calculated glucagon-alanine index was significantly associated with a 30% increase in hepatic insulin resistance, a 7% increase in plasma alanine aminotransferase levels, and a 14% increase in plasma γ-glutamyltransferase levels.

CONCLUSIONS/INTERPRETATION

This cross-sectional study supports the existence of a liver-alpha cell axis in humans: glucagon regulates plasma levels of amino acids, which in turn feedback to regulate the secretion of glucagon. With hepatic insulin resistance, reflecting hepatic steatosis, the feedback cycle is disrupted, leading to hyperaminoacidaemia and hyperglucagonaemia. The glucagon-alanine index is suggested as a relevant marker for hepatic glucagon signalling.

BCAA Metabolism and Insulin Sensitivity - Dysregulated by Metabolic Status?

Branched-chain amino acids (BCAAs) appear to influence several synthetic and catabolic cellular signaling cascades leading to altered phenotypes in mammals. BCAAs are most notably known to increase protein synthesis through modulating protein translation, explaining their appeal to resistance and endurance athletes for muscle hypertrophy, expedited recovery, and preservation of lean body mass. In addition to anabolic effects, BCAAs may increase mitochondrial content in skeletal muscle and adipocytes, possibly enhancing oxidative capacity. However, elevated circulating BCAA levels have been correlated with severity of insulin resistance. It is hypothesized that elevated circulating BCAAs observed in insulin resistance may result from dysregulated BCAA degradation. This review summarizes original reports that investigated the ability of BCAAs to alter glucose uptake in consequential cell types and experimental models. The review also discusses the interplay of BCAAs with other metabolic factors, and the role of excess lipid (and possibly energy excess) in the dysregulation of BCAA catabolism. Lastly, this article provides a working hypothesis of the mechanism(s) by which lipids may contribute to altered BCAA catabolism, which often accompanies metabolic disease.

Profiling of plasma metabolites in postmenopausal women with metabolic syndrome

Objective:

The aim of the study was to investigate the associations of amino acids and other polar metabolites with metabolic syndrome (MetS) in postmenopausal women in a lean Asian population.

Methods:

The participants were 1,422 female residents enrolled in a cohort study from April to August 2012. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III modified for Japanese women. Associations were examined between MetS and 78 metabolites assayed in fasting plasma samples using capillary electrophoresis-mass spectrometry. Replication analysis was performed to confirm the robustness of the results in a separate population created by random allocation.

Results:

Analysis was performed for 877 naturally postmenopausal women, including 594 in the original population and 283 in the replication population. The average age, body mass index, and levels of high- and low-density lipoprotein cholesterol of the entire population were 64.6 years, 23.0 kg/m², 72.1 mg/dL, and 126.1 mg/dL, respectively. There was no significant difference in low-density lipoprotein cholesterol levels between women with and without MetS. Thirteen metabolites were significantly related to MetS: multiple plasma amino acids were elevated in women with MetS, including branched-chain amino acids, alanine, glutamate, and proline; and alpha-aminoadipate, which is generated by lysine degradation, was also significantly increased.

Conclusions:

Our large-scale metabolomic profiling indicates that Japanese postmenopausal women with MetS have abnormal polar metabolites, suggesting altered catabolic pathways. These results may help to understand metabolic disturbance, including in persons with normal body mass index and relatively high levels of high-density lipoprotein cholesterol, and may have clinical utility based on further studies.

Hyperglucagonemia correlates with plasma levels of non-branched-chain amino acids in patients with liver disease independent of type 2 diabetes

Patients with type 2 diabetes (T2D) and patients with nonalcoholic fatty liver disease (NAFLD) frequently exhibit elevated plasma concentrations of glucagon (hyperglucagonemia). Hyperglucagonemia and α-cell hyperplasia may result from elevated levels of plasma amino acids when glucagon's action on hepatic amino acid metabolism is disrupted. We therefore measured plasma levels of glucagon and individual amino acids in patients with and without biopsy-verified NAFLD and with and without type T2D. Fasting levels of amino acids and glucagon in plasma were measured, using validated ELISAs and high-performance liquid chromatography, in obese, middle-aged individuals with I) normal glucose tolerance (NGT) and NAFLD, II) T2D and NAFLD, III) T2D without liver disease, and IV) NGT and no liver disease. Elevated levels of total amino acids were observed in participants with NAFLD and NGT compared with NGT controls (1,310 ± 235 µM vs. 937 ± 281 µM, P = 0.03) and in T2D and NAFLD compared with T2D without liver disease (1,354 ± 329 µM vs. 511 ± 235 µM, P < 0.0001). Particularly amino acids with known glucagonotropic effects (e.g., glutamine) were increased. Plasma levels of total amino acids correlated to plasma levels of glucagon also when adjusting for body mass index (BMI), glycated hemoglobin (Hb_A1c), and cholesterol levels (β = 0.013 ± 0.007, P = 0.024). Elevated plasma levels of total amino acids associate with hyperglucagonemia in NAFLD patients independently of glycemic control, BMI or cholesterol - supporting the potential importance of a "liver-α-cell axis" in which glucagon regulates hepatic amino acid metabolism. Fasting hyperglucagonemia as seen in T2D may therefore represent impaired hepatic glucagon action with increasing amino acids levels. NEW & NOTEWORTHY Hypersecretion of glucagon (hyperglucagonemia) has been suggested to be linked to type 2 diabetes. Here, we show that levels of amino acids correlate with levels of glucagon. Hyperglucagonemia may depend on hepatic steatosis rather than type 2 diabetes.

Amino acid profile and metabolic syndrome in a male Mediterranean population: A cross-sectional study

BACKGROUND AND AIMS

The metabolic syndrome (MetS) refers to a cluster of clinically relevant factors that increases the risk of cardiovascular diseases and all-cause mortality. Circulating levels of several amino acids and metabolites related to one-carbon metabolism have been associated with cardiometabolic risk factors and MetS. We aimed to identify the amino acid profile that is significantly associated with MetS among an all male Mediterranean population.

METHODS AND RESULTS

One hundred middle-aged men (54.6 ± 8.9 years) participated in a cross-sectional study carried out during 2011-2012. The International Diabetes Federation (IDF) criteria were used to define MetS. Fasting plasma levels of 20 common amino acids and 15 metabolites related to amino acid and one-carbon metabolism were measured using gas chromatography (GC-MS/MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). Principal components analysis was applied. Fifty-six participants fulfilled the IDF criteria for defining MetS. Five factors were extracted from the 35 measured metabolites. The branched-chain amino acids/aromatic amino acids (BCAA/AAA) related pattern and the glutamine/glycine/serine/asparagine (Gln/Gly/Ser/Asn) related pattern were significantly associated with MetS (odds ratio, 95% confidence interval; 6.41, 2.43-16.91, and 0.47, 0.23-0.96, respectively) after adjustment for age, current smoking status, physical activity level and medical treatment for hypertension, dyslipidaemia, type 2 diabetes mellitus. Further adjustment for liver function markers (i.e. glutamic oxaloacetic transaminase, glutamic pyruvic transaminase, and γ-glutamyltransferase), and plasma adiponectin levels did not significantly affect the associations.

CONCLUSION

The BCAA/AAA pattern was positively associated, while the Gln/Gly/Ser/Asn pattern was inversely associated with established cardiometabolic risk factors and MetS. Plasma adiponectin levels or markers of liver function did not significantly affect these associations.

Plasma-free amino acid profiles are predictors of cancer and diabetes development

Type 2 diabetes (T2D) and cancers are two major causes of morbidity and mortality worldwide. Nowadays, there is convincing evidence of positive associations between T2D and the incidence or prognosis of a wide spectrum of cancers, for example, breast, colon, liver and pancreas. Many observational studies suggest that certain medications used to treat hyperglycemia (or T2D) may affect cancer cells directly or indirectly. The potential mechanisms of the direct T2D cancer links have been hypothesized to be hyperinsulinemia, hyperglycemia and chronic inflammation; however, the metabolic pathways that lead to T2D and cancers still remain elusive. Plasma-free amino acid (PFAA) profiles have been highlighted in their associations with the risks of developing T2D and cancers in individuals with different ethnic groups and degree of obesity. The alterations of PFAAs might be predominately caused by the metabolic shift resulted from insulin resistance. The underlying mechanisms have not been fully elucidated, in particular whether the amino acids are contributing to these diseases development in a causal manner. This review addresses the molecular and clinical associations between PFAA alterations and both T2D and cancers, and interprets possible mechanisms involved. Revealing these interactions and mechanisms may improve our understanding of the complex pathogenesis of diabetes and cancers and improve their treatment strategies.

Insulin Resistance Is a Risk Factor for Silent Lacunar Infarction

Background and Purpose—

This study aims to investigate the association between insulin resistance (IR) and silent lacunar infarction (SLI) in healthy adults.

Methods—

We recruited 2326 healthy Korean adults who took health checkups, including a brain magnetic resonance imaging. SLI was defined as an infarction measuring 0.3 to 1.5 cm in diameter that was localized in the territory of perforating branches of cerebral arteries, as seen in the brain magnetic resonance imaging. The homeostasis model assessment–estimated insulin resistance index was used for IR estimation, and the cutoff value for its diagnosis for Koreans was 2.56.

Results—

The mean age of the study population was 56.2 years (range, 40–79 years), and 1279 subjects (55.0%) were male. The prevalence of SLI and IR was 8.1% and 18.1%, respectively. In multivariate logistic analysis, after adjusting for traditional SLI-associated risk factors, IR was positively associated with the prevalence of SLI (adjusted odds ratio, 1.69; 95% confidence interval, 1.16–2.46). The proportion of subjects with multiple SLI lesions (≥2) was also higher in the IR (+) group than that in the IR (−) group (4.3% versus 1.7%; P <0.001). In ordered logistic regression, IR was positively associated with an increase in SLI severity (adjusted odds ratio, 1.76; 95% confidence interval, 1.21–2.56).

Conclusions—

IR is an independent risk factor of SLI presence and its severity in Koreans. Whether improvement of IR might prevent SLI occurrence needs to be addressed by clinical trials.

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis

BACKGROUND

The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues.

METHODS

Our RSF approach was illustrated with data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, with concentrations of 127 serum metabolites as exposure variables and time to development of type 2 diabetes mellitus (T2D) as outcome variable. Out of this data set, Cox regression with a stepwise selection method was recently published. Replication of methodical comparison (RSF and Cox regression) was conducted in two independent cohorts. Finally, the R-code for implementing the metabolite selection procedure into the RSF-syntax is provided.

RESULTS

The application of the RSF approach in EPIC-Potsdam resulted in the identification of 16 incident T2D-associated metabolites which slightly improved prediction of T2D when used in addition to traditional T2D risk factors and also when used together with classical biomarkers. The identified metabolites partly agreed with previous findings using Cox regression, though RSF selected a higher number of highly correlated metabolites.

CONCLUSIONS

The RSF method appeared to be a promising approach for identification of disease-associated variables in complex data with time to event as outcome. The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data.

Dietary fibers influence the intestinal SCFAs and plasma metabolites profiling in growing pigs

Dietary fibers (DFs), widely used as food additives to replace fat, can benefit metabolic disorders.

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

Recent studies have shown the positive association between increased circulating BCAAs (valine, leucine, and isoleucine) and insulin resistance (IR) in obese or diabetic patients. However, results seem to be controversial in different races, diets, and distinct tissues. Our aims were to evaluate the relationship between BCAA and IR as well as later diabetes risk and explore the phenotypic and genetic factors influencing BCAA level based on available studies. We performed systematic review, searching MEDLINE, EMASE, ClinicalTrials.gov, the Cochrane Library, and Web of Science from inception to March 2016. After selection, 23 studies including 20,091 participants were included. Based on current evidence, we found that BCAA is a useful biomarker for early detection of IR and later diabetic risk. Factors influencing BCAA level can be divided into four parts: race, gender, dietary patterns, and gene variants. These factors might not only contribute to the elevated BCAA level but also show obvious associations with insulin resistance. Genes related to BCAA catabolism might serve as potential targets for the treatment of IR associated metabolic disorders. Moreover, these factors should be controlled properly during study design and data analysis. In the future, more large-scale studies with elaborate design addressing BCAA and IR are required.

Branched-chain amino acids as biomarkers in diabetes

PURPOSE OF REVIEW

Numerous human studies have consistently demonstrated that concentrations of branched-chain amino acids (BCAAs) in plasma and urine are associated with insulin resistance and have the quality to predict diabetes development. However, it is not known how altered BCAA levels link to insulin action and diabetes. This review addresses some recent findings in BCAA metabolism and discusses their role as reporter molecules of insulin sensitivity and diabetes and their possible contribution to disease progression.

RECENT FINDINGS

Changes in plasma and urine levels result mainly from altered metabolism in tissues and recent studies have thus focused on organ-specific changes in BCAA handling using animal models and human tissue samples. A decreased mitochondrial oxidation has been demonstrated in peripheral tissues and that was shown to be associated with an increased inflammatory tone and changes in adipokine levels (adiponectin and leptin). These changes appear already before insulin resistance is established. Key findings demonstrating the discordance between changes in BCAA and insulin resistance are derived from studies using insulin sensitizers and from data collected in patients undergoing Roux-en-Y bypass bariatric surgery. Intermediates derived from BCAA breakdown rather than BCAA itself were recently proposed to contribute to the development of insulin resistance and studies now explore the biomarker qualities of these metabolites.

SUMMARY

Understanding the mechanisms and putative causalities in the alterations in BCAA levels as found in obesity, metabolic syndrome and diabetes is crucial for any intervention options but also for the use of BCAA and derivatives as biomarkers in clinical routine.