A High Level of Circulating Valine Is a Biomarker for Type 2 Diabetes and Associated with the Hypoglycemic Effect of Sitagliptin

Identification of diagnostic biomarkers used in the diagnosis of cardiovascular diseases and diabetes mellitus: A systematic review of quantitative studies

AIMS

To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low- and middle-income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training.

MATERIALS AND METHODS

Papers were sourced from six databases: the British Nursing Index, Google Scholar, PubMed, Sage, Science Direct and Scopus. Articles published between January 2002 and January 2023 were systematically reviewed by three reviewers and appropriate search terms and inclusion/exclusion criteria were applied.

RESULTS

A total of 18 studies were yielded, as well as 234 diagnostic biomarkers (74 for CVD and 160 for DM). Primary biomarkers for the diagnosis of CVDs included growth differentiation factor 15 and neurogenic locus notch homologue protein 1 (Notch1). For the diagnosis of DM, alpha-2-macroglobulin, C-peptides, isoleucine, glucose, tyrosine, linoleic acid and valine were frequently reported across the included studies. Advanced analytical techniques, such as liquid chromatography mass spectrometry, enzyme-linked immunosorbent assays and vibrational spectroscopy, were also repeatedly reported in the included studies and were utilized in combination with traditional and alternative matrices such as fingernails, hair and saliva.

CONCLUSIONS

While advanced analytical techniques are expensive, laboratories in LMICs should carry out a cost-benefit analysis of their use. Alternatively, laboratories may want to explore emerging techniques such as infrared, Fourier transform-infrared and near-infrared spectroscopy, which allow sensitive noninvasive analysis.

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Insights into serum metabolic biomarkers for early detection of incident diabetic kidney disease in Chinese patients with type 2 diabetes by random forest

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD) worldwide. Early detection is critical for the risk stratification and early intervention of progressive DKD. Serum creatinine (sCr) and urine output are used to assess kidney function, but these markers are limited by their delayed changes following kidney pathology, and lacking of both sensitivity and accuracy. Hence, it is essential to illustrate potential diagnostic indicators to enhance the precise prediction of early DKD. A total of 194 Chinese individuals include 30 healthy participants (Stage 0) and 164 incidents with type 2 diabetes (T2D) spanning from DKD's Stage 1a to 4 were recruited and their serums were subjected for untargeted metabolomic analysis. Random forest (RF), a machine learning approach, together with univariate linear regression (ULR) and multivariate linear regression (MvLR) analysis were applied to characterize the features of untargeted metabolites of DKD patients and to identify candidate DKD biomarkers. Our results indicate that 2-(α-D-mannopyranosyl)-L-tryptophan (ADT), succinyladenosine (SAdo), pseudouridine and N,N,N-trimethyl-L-alanyl-L-proline betaine (L-L-TMAP) were associated with the development of DKD, in particular, the latter three that were significantly elevated in Stage 2-4 T2D incidents. Each of the four metabolites in combination with sCr achieves better performance than sCr alone with area under the receiver operating characteristic curve (AUC) of 0.81-0.91 in predicting DKD stages. An average of 3.9 years follow-up study of another cohort including 106 Stage 2-3 patients suggested that "urinary albumin-to-creatinine ratio (UACR) + ADT + SAdo" can be utilized for better prognosis evaluation of early DKD (average AUC = 0.9502) than UACR without sexual difference.

Predicting the onset of preeclampsia by longitudinal monitoring of metabolic changes throughout pregnancy with Raman spectroscopy

Preeclampsia is a life-threatening pregnancy disorder. Current clinical assays cannot predict the onset of preeclampsia until the late 2nd trimester, which often leads to poor maternal and neonatal outcomes. Here we show that Raman spectroscopy combined with machine learning in pregnant patient plasma enables rapid, highly sensitive maternal metabolome screening that predicts preeclampsia as early as the 1st trimester with >82% accuracy. We identified 12, 15 and 17 statistically significant metabolites in the 1st, 2nd and 3rd trimesters, respectively. Metabolic pathway analysis shows multiple pathways corresponding to amino acids, fatty acids, retinol, and sugars are enriched in the preeclamptic cohort relative to a healthy pregnancy. Leveraging Pearson's correlation analysis, we show for the first time with Raman Spectroscopy that metabolites are associated with several clinical factors, including patients' body mass index, gestational age at delivery, history of preeclampsia, and severity of preeclampsia. We also show that protein quantification alone of proinflammatory cytokines and clinically relevant angiogenic markers are inadequate in identifying at-risk patients. Our findings demonstrate that Raman spectroscopy is a powerful tool that may complement current clinical assays in early diagnosis and in the prognosis of the severity of preeclampsia to ultimately enable comprehensive prenatal care for all patients.

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.

Microbiota: A potential orchestrator of antidiabetic therapy

The gut microbiota, as a 'new organ' of humans, has been identified to affect many biological processes, including immunity, inflammatory response, gut-brain neural circuits, and energy metabolism. Profound dysbiosis of the gut microbiome could change the metabolic pattern, aggravate systemic inflammation and insulin resistance, and exacerbate metabolic disturbance and the progression of type 2 diabetes (T2D). The aim of this review is to focus on the potential roles and functional mechanisms of gut microbiota in the antidiabetic therapy. In general, antidiabetic drugs (α-glucosidase inhibitor, biguanides, incretin-based agents, and traditional Chinese medicine) induce the alteration of microbial diversity and composition, and the levels of bacterial component and derived metabolites, such as lipopolysaccharide (LPS), short chain fatty acids (SCFAs), bile acids and indoles. The altered microbial metabolites are involved in the regulation of gut barrier, inflammation response, insulin resistance and glucose homeostasis. Furthermore, we summarize the new strategies for antidiabetic treatment based on microbial regulation, such as pro/prebiotics administration and fecal microbiota transplantation, and discuss the need for more basic and clinical researches to evaluate the feasibility and efficacy of the new therapies for diabetes.

Amino Acid Profiles and Nutritional Evaluation of Fresh Sweet–Waxy Corn from Three Different Regions of China

This study conducted a comparative analysis of the amino acid compositions of Chinese Huangnuo 9 fresh sweet–waxy corn from three different provinces in China—Inner Mongolia, Jilin, and Heilongjiang Province. Moreover, we established a nutritive evaluation system based on amino acid profiles to evaluate, compare, and rank the fresh sweet–waxy corn planted in different regions. A total of 17 amino acids were quantified, and the amino acid composition of fresh sweet–waxy corn was analyzed and evaluated. The amino acid quality was determined by the amino acid pattern spectrum, chemical evaluations (including CS, AAS, EAAI, BV, U(a,u), NI, F, predict PER, and PDCAAS), flavor evaluation, amino acid matching degree evaluation, and the results of the factor analysis. The results showed that the protein content of fresh corn 1–1 from Inner Mongolia was the highest (40.26 ± 0.35 mg/g), but the factor analysis results, digestion, and absorption efficiency of fresh corn 1–2 were the best. The amino acid profile of fresh corn 1–1 was closest to each evaluation’s model spectrum. The results of the diversity evaluations in fresh corn 3–2 were the best, and fresh corn 3–3 had the most essential amino acid content. A total of 17 amino acids in fresh corn were divided into three principal component factor analyses: functional principal components (Leu, Pro, Glu, His, Ile, Ser, Met, Val, Tyr, Thr), regulatory principal components (Lys, Gly, Ala, Asp, Arg, Trp), and protection principal components (Phe). The scores of the three principal components and the comprehensive score in fresh corn 1–2 were all the highest, followed by 3–3 and 1–1. The amino acid nutritional values of fresh corn 1–2 were the highest in 12 samples.

Temporal profile of serum metabolites and inflammation following closed head injury in rats is associated with HPA axis hyperactivity

INTRODUCTION

Closed head injury (CHI) causes neurological disability along with systemic alterations that can activate neuro-endocrine response through hypothalamic-pituitary-adrenal (HPA) axis activation. A dysregulated HPA axis function can lead to relocation of energy substrates and alteration in metabolic pathways and inflammation at the systemic level.

OBJECTIVES

Assessment of time-dependent changes in serum metabolites and inflammation after both mild and moderate CHI. Along with this, serum corticosterone levels and hypothalamic microglial response were observed.

METHODS

Rats underwent mild and moderate weight-drop injury and their serum and hypothalamus were assessed at acute, sub-acute and chronic timepoints. Changes in serum metabolomics were determined using high resolution NMR spectroscopy. Serum inflammatory cytokine, corticosterone levels and hypothalamic microglia were assessed at all timepoints.

RESULTS

Metabolites including lactate, choline and branched chain amino acids were found as the classifiers that helped distinguish between control and injured rats during acute, sub-acute and chronic timepoints. While, increased αglucose: βglucose and TMAO: choline ratios after acute and sub-acute timepoints of mild injury differentiated from moderate injured rats. The injured rats also showed distinct inflammatory profile where IL-1β and TNF-α levels were upregulated in moderate injured rats while IL-10 levels were downregulated in mild injured rats. Furthermore, injury specific alterations in serum metabolic and immunologic profile were found to be associated with hyperactive HPA axis, with consistent increase in serum corticosterone concentration post injury. The hypothalamic microglia showed a characteristic activated de-ramified cellular morphology in both mild and moderate injured rats.

CONCLUSION

The study suggests that HPA axis hyperactivity along with hypothalamic microglial activation led to temporal changes in the systemic metabolism and inflammation. These time dependent changes in the metabolite profile of rats can further strengthen the knowledge of diagnostic markers and help distinguish injury related outcomes after TBI.

Improvement of substrate recognition in branched-chain aminoacyl-tRNA synthetases from Escherichia coli under conditions of pyrophosphate amplification

Isoleucyl-tRNA synthetase (IleRS), leucyl-tRNA synthetase (LeuRS), and valyl-tRNA synthetase (ValRS) are enzymes that have potential for the determination of l-isoleucine, l-leucine, and l-valine in food products and plasma. However, the disadvantages of these enzymes are their specificity and sensitivity. Here, we examined the substrate specificity of IleRS, LeuRS, and ValRS under various conditions of pyrophosphate amplification to improve their specificity and sensitivity. The amount of pyrophosphate produced in IleRS, LeuRS, and ValRS reactions was amplified after the addition of excess adenosine-5'-triphosphate and magnesium ions, and was approximately 9-, 8-, and 7-fold higher, respectively, for each of the initial l-amino acid substrates (50 μM). However, in addition to their target amino acids, IleRS, LeuRS, and ValRS also reacted with l-valine, l-lysine, and l-threonine, respectively. This substrate misrecognition was overcome by making the reaction pH more acidic and by increasing the magnesium ion concentration. The pyrophosphate amplification in IleRS, LeuRS, and ValRS reactions resulted in the production of p¹, p⁴-di (adenosine) 5'-tetraphosphate. We also observed a strong positive correlation (R = 0.99) between the amount of pyrophosphate produced and the initial concentration of l-amino acid with 5 and 50 μM l-isoleucine, l-leucine, and l-valine. Our results suggest that amino acid assays using IleRS, LeuRS, and ValRS are promising methods to accurately measure l-valine, l-isoleucine, and l-leucine in food products and plasma.

Mass Spectrometry-Based Metabolomic and Lipidomic Analysis of the Effect of High Fat/High Sugar Diet and GreenshellTM Mussel Feeding on Plasma of Ovariectomized Rats

This study aimed to examine the changes in lipid and metabolite profiles of ovariectomized (OVX) rats with diet-induced metabolic syndrome-associated osteoarthritis (MetOA) after supplementation with greenshell mussel (GSM) using an untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics approach. Ninety-six rats were fed with one of four diets: control, control supplemented with GSM + GSM, high fat/high sugar (HFHS), or high fat/high sugar enriched with GSM (HFHS + GSM). After 8 weeks on experimental diets, half of the rats in each group underwent OVX and the other half were sham operated. After being fed for an additional 28 weeks, blood samples were collected for the metabolomics analysis. Lipid and polar metabolites were extracted from plasma and analysed by LC-MS. We identified 29 lipid species from four lipid subclasses (phosphatidylcholine, lysophosphatidylcholine, diacylglycerol, and triacylglycerol) and a set of eight metabolites involved in amino acid metabolism (serine, threonine, lysine, valine, histidine, pipecolic acid, 3-methylcytidine, and cholic acid) as potential biomarkers for the effect of HFHS diet and GSM supplementation. GSM incorporation more specifically in the control diet generated significant alterations in the levels of several lipids and metabolites. Further studies are required to validate these findings that identify potential biomarkers to follow OA progression and to monitor the impact of GSM supplementation.

Branched chain amino acids-friend or foe in the control of energy substrate turnover and insulin sensitivity?

Branched chain amino acids (BCAA) and their derivatives are bioactive molecules with pleiotropic functions in the human body. Elevated fasting blood BCAA concentrations are considered as a metabolic hallmark of obesity, insulin resistance, dyslipidaemia, nonalcoholic fatty liver disease, type 2 diabetes and cardiovascular disease. However, since increased BCAA amount is observed both in metabolically healthy and obese subjects, a question whether BCAA are mechanistic drivers of insulin resistance and its morbidities or only markers of metabolic dysregulation, still remains open. The beneficial effects of BCAA on body weight and composition, aerobic capacity, insulin secretion and sensitivity demand high catabolic potential toward amino acids and/or adequate BCAA intake. On the opposite, BCAA-related inhibition of lipogenesis and lipolysis enhancement may preclude impairment in insulin sensitivity. Thereby, the following review addresses various strategies pertaining to the modulation of BCAA catabolism and the possible roles of BCAA in energy homeostasis. We also aim to elucidate mechanisms behind the heterogeneity of ramifications associated with BCAA modulation.

Autophagy Deficiency by Atg4B Loss Leads to Metabolomic Alterations in Mice

Autophagy is an essential protective mechanism that allows mammalian cells to cope with a variety of stressors and contributes to maintaining cellular and tissue homeostasis. Due to these crucial roles and also to the fact that autophagy malfunction has been described in a wide range of pathologies, an increasing number of in vivo studies involving animal models targeting autophagy genes have been developed. In mammals, total autophagy inactivation is lethal, and constitutive knockout models lacking effectors of this route are not viable, which has hindered so far the analysis of the consequences of a systemic autophagy decline. Here, we take advantage of atg4b^−/− mice, an autophagy-deficient model with only partial disruption of the process, to assess the effects of systemic reduction of autophagy on the metabolome. We describe for the first time the metabolic footprint of systemic autophagy decline, showing that impaired autophagy results in highly tissue-dependent alterations that are more accentuated in the skeletal muscle and plasma. These changes, which include changes in the levels of amino-acids, lipids, or nucleosides, sometimes resemble those that are frequently described in conditions like aging, obesity, or cardiac damage. We also discuss different hypotheses on how impaired autophagy may affect the metabolism of several tissues in mammals.

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.

Identification of serum predictors of n-acetyl-l-cysteine and isoproterenol induced remodelling in cardiac hypertrophy

Cardiac hypertrophy (CH), leading to cardiac failure is due to chronic metabolic alterations occurring during cellular stress. Besides the already known relationship between oxidative stress and CH, there are implications of reductive stress leading to CH. This study attempted to develop reductive stress-based CH rat model using n-acetyl-L-cysteine (NAC), a glutathione agonist that was compared with typical isoproterenol (ISO) induced CH model. The main objective was to identify serum metabolites that can serve as potent predictors for seven routine clinical and diagnostic parameters in CH: 3-hydroxybutyrate (3-HB), lactic acid (LA), urea, and ECG-CH parameters (QRS complex, R-amplitude, R-R interval, heart rate) that were hypothesized to underlie metabolic remodelling in this study. CH was assessed using electrocardiography, hypertrophic index and histopathological analysis (H&E stain) in both ventricles after 2 weeks. Gas chromatography mass spectroscopy analysis (GC-MS) identified unique metabolite finger-prints. Correlation and pattern analysis revealed strong relationships between specific metabolites and parameters (Pearson's score > 0.7) of this study. Multiple regression analysis (MRA) for the strongly related metabolites (independent variables) with each of the seven parameters (dependent variables) identified significant predictors for the latter namely fructose, valine, butanoic acid in NAC and cholesterol, erythrose, isoleucine in ISO models, with proline and succinic acid as common for both models. Metabolite set enrichment analysis (MSEA) of those significant predictors (p < 0.05) mapped butyrate metabolism as highly influential pathway in NAC, with arginine-proline metabolism and branched chain amino acid (BCAA) degradation as common pathways in both models, thus providing new insights towards initial metabolic remodeling in the pathogenesis of CH.

A Novel Dietary Intervention Reduces Circulatory Branched-Chain Amino Acids by 50%: A Pilot Study of Relevance for Obesity and Diabetes

Elevated circulating branched-chain amino acids (BCAAs; isoleucine, leucine, and valine) are associated with obesity and type 2 diabetes (T2D). Reducing circulatory BCAAs by dietary restriction was suggested to mitigate these risks in rodent models, but this is a challenging paradigm to deliver in humans. We aimed to design and assess the feasibility of a diet aimed at reducing circulating BCAA concentrations in humans, while maintaining energy balance and overall energy/protein intake. Twelve healthy individuals were assigned to either a 7-day BCAA-restricted diet or a 7-day control diet. Diets were iso-nitrogenous and iso-caloric, with only BCAA levels differing between the two. The BCAA-restricted diet significantly reduced circulating BCAA concentrations by ~50% i.e., baseline 437 ± 60 to 217 ± 40 µmol/L (p < 0.005). Individually, both valine (245 ± 33 to 105 ± 23 µmol/L; p < 0.0001), and leucine (130 ± 20 to 75 ± 13 µmol/L; p < 0.05), decreased significantly in response to the BCAA-restricted diet. The BCAA-restricted diet marginally lowered Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) levels: baseline 1.5 ± 0.2 to 1.0 ± 0.1; (p = 0.096). We successfully lowered circulating BCAAs by 50% while maintaining iso-nitrogenous, iso-caloric dietary intakes, and while meeting the recommended daily allowances (RDA) for protein requirements. The present pilot study represents a novel dietary means by which to reduce BCAA, and as such, provides a blueprint for a potential dietary therapeutic in obesity/diabetes.