Identification of pathognomonic purine synthesis biomarkers by metabolomic profiling of adolescents with obesity and type 2 diabetes

Metabolomics Characterization of Disease Markers in Diabetes and Its Associated Pathologies

With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.

Circulating Metabolite Biomarkers of Glycemic Control in Youth-Onset Type 2 Diabetes

OBJECTIVE

We aimed to identify metabolites associated with loss of glycemic control in youth-onset type 2 diabetes.

RESEARCH DESIGN AND METHODS

We measured 480 metabolites in fasting plasma samples from the TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) study. Participants (N = 393; age 10-17 years) were randomly assigned to metformin, metformin plus rosiglitazone, or metformin plus lifestyle intervention. Additional metabolomic measurements after 36 months were obtained in 304 participants. Cox models were used to assess baseline metabolites, interaction of metabolites and treatment group, and change in metabolites (0-36 months), with loss of glycemic control adjusted for age, sex, race, treatment group, and BMI. Metabolite prediction models of glycemic failure were generated using elastic net regression and compared with clinical risk factors.

RESULTS

Loss of glycemic control (HbA1c ≥8% or insulin therapy) occurred in 179 of 393 participants (mean 12.4 months). Baseline levels of 33 metabolites were associated with loss of glycemic control (q < 0.05). Associations of hexose and xanthurenic acid with treatment failure differed by treatment randomization; youths with higher baseline levels of these two compounds had a lower risk of treatment failure with metformin alone. For three metabolites, changes from 0 to 36 months were associated with loss of glycemic control (q < 0.05). Changes in d-gluconic acid and 1,5-AG/1-deoxyglucose, but not baseline levels of measured metabolites, predicted treatment failure better than changes in HbA1c or measures of β-cell function.

CONCLUSIONS

Metabolomics provides insight into circulating small molecules associated with loss of glycemic control and may highlight metabolic pathways contributing to treatment failure in youth-onset diabetes.

Gluco-regulation & type 2 diabetes: entrenched misconceptions updated to new governing principles for gold standard management

Our understanding of type 2 diabetes (T2D) has evolved dramatically. Advances have upended entrenched dogmas pertaining to the onset and progression of T2D, beliefs that have prevailed from the early era of diabetes research-and continue to populate our medical textbooks and continuing medical education materials. This review article highlights key insights that lend new governing principles for gold standard management of T2D. From the historical context upon which old beliefs arose to new findings, this article outlines evidence and perspectives on beta cell function, the underlying defects in glucoregulation, the remediable nature of T2D, and, the rationale supporting the shift to complication-centric prescribing. Practical approaches translate this rectified understanding of T2D into strategies that fill gaps in current management practices of prediabetes through late type 2 diabetes.

Untargeted serum metabolic profiling of diabetes mellitus among Parkinson's disease patients

Type 2 diabetes mellitus (T2DM) is a common comorbidity among Parkinson's disease (PD) patients. Yet, little is known about dysregulated pathways that are unique in PD patients with T2DM. We applied high-resolution metabolomic profiling in serum samples of 636 PD and 253 non-PD participants recruited from Central California. We conducted an initial discovery metabolome-wide association and pathway enrichment analysis. After adjusting for multiple testing, in positive (or negative) ion mode, 30 (25) metabolic features were associated with T2DM in both PD and non-PD participants, 162 (108) only in PD participants, and 32 (7) only in non-PD participants. Pathway enrichment analysis identified 17 enriched pathways associated with T2DM in both the PD and non-PD participants, 26 pathways only in PD participants, and 5 pathways only in non-PD participants. Several amino acid, nucleic acids, and fatty acid metabolisms were associated with T2DM only in the PD patient group suggesting a possible link between PD and T2DM.

Comparative profiling of gut microbiota and metabolome in diet-induced obese and insulin-resistant C57BL/6J mice

Diet-based models are commonly used to investigate obesity and related disorders. We conducted a comparative profiling of three obesogenic diets HFD, high fat diet; HFHF, high fat high fructose diet; and HFCD, high fat choline deficient diet to assess their impact on the gut microbiome and metabolome. After 20 weeks, we analyzed the gut microbiota and metabolomes of liver, plasma, cecal, and fecal samples. Fecal and plasma bile acids (BAs) and fecal short-chain fatty acids (SCFAs) were also examined. Significant changes were observed in fecal and cecal metabolites, with increased Firmicutes and decreased Bacteroidetes in the HFD, HFHF, and HFCD-fed mice compared to chow and LFD (low fat diet)-fed mice. Most BAs were reduced in plasma and fecal samples of obese groups, except taurocholic acid, which increased in HFCD mice's plasma. SCFAs like acetate and butyrate significantly decreased in obesogenic diet groups, while propionic acid specifically decreased in the HFCD group. Pathway analysis revealed significant alterations in amino acid, carbohydrate metabolism, and nucleic acid biosynthesis pathways in obese mice. Surprisingly, even LFD-fed mice showed distinct changes in microbiome and metabolite profiles compared to the chow group. This study provides insights into gut microbiome dysbiosis and metabolite alterations induced by obesogenic and LFD diets in various tissues. These findings aid in selecting suitable diet models to study the role of the gut microbiome and metabolites in obesity and associated disorders, with potential implications for understanding similar pathologies in humans.

Prebiotics, Probiotics, and Synbiotics-A Research Hotspot for Pediatric Obesity

Childhood obesity is a major public health problem worldwide with an increasing prevalence, associated not only with metabolic syndrome, insulin resistance, hypertension, dyslipidemia, and non-alcoholic fatty liver disease (NAFLD), but also with psychosocial problems. Gut microbiota is a new factor in childhood obesity, which can modulate the blood lipopolysaccharide levels, the satiety, and fat distribution, and can ensure additional calories to the host. The aim of this review was to assess the differences and the impact of the gut microbial composition on several obesity-related complications such as metabolic syndrome, NAFLD, or insulin resistance. Early dysbiosis was proven to be associated with an increased predisposition to obesity. Depending on the predominant species, the gut microbiota might have either a positive or negative impact on the development of obesity. Prebiotics, probiotics, and synbiotics were suggested to have a positive effect on improving the gut microbiota and reducing cardio-metabolic risk factors. The results of clinical trials regarding probiotic, prebiotic, and synbiotic administration in children with metabolic syndrome, NAFLD, and insulin resistance are controversial. Some of them (Lactobacillus rhamnosus bv-77, Lactobacillus salivarius, and Bifidobacterium animalis) were proven to reduce the body mass index in obese children, and also improve the blood lipid content; others (Bifidobacterium bifidum, Bifidobacterium longum, Lactobacillus acidophilus, Lacticaseibacillus rhamnosus, Enterococcus faecium, and fructo-oligosaccharides) failed in proving any effect on lipid parameters and glucose metabolism. Further studies are necessary for understanding the mechanism of the gut microbiota in childhood obesity and for developing low-cost effective strategies for its management.

Multispecies probiotic affects fecal short-chain fatty acids in postmenopausal women with obesity: A post hoc analysis of a randomized, double-blind, placebo-controlled study

OBJECTIVES

Probiotics are known to regulate host metabolism. The aim of this study was to assess whether interventions with a multi-strain probiotic formula affect fecal short-chain fatty acids (SCFAs).

METHODS

The analysis was carried out in 56 obese, postmenopausal women randomized to three groups: probiotic dose 2.5 × 109 CFU/d (n = 18; lower probiotic dose [LPD]), 1 × 1010 CFU/d (n = 18; higher probiotic dose [HPD]), or placebo (n = 20).

RESULTS

An increase in three SCFA fecal concentrations in the HPD group was observed: acetic acid (C2; effect [E] = 1.72, SE = 0.73; 95% confidence interval [CI], 0.28-3.16; P = 0.019), butyric acid (C4; E = 0.98, SE = 0.46; 95% CI, 0.08-1.88; P = 0.033), and valeric acid (C5; E = 0.68, SE = 0.23; 95% CI, 0.23-1.12; P = 0.003). The mediation analysis showed that the decrease in uric acid under HPD may be transmitted through the elevation of C5 content. Multi-strain probiotic increases the SCFA content in the stool in a dose-dependent manner, which may diminish some cardiovascular risk factors because of a reduction in blood uric acid levels.

CONCLUSION

Assessing long-term health benefits requires further research, including assessment of blood SCFA concentrations and multiomic and mechanistic approaches.

Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis

Obesity in children and adolescents has increased globally. Increased body mass index (BMI) during adolescence carries significant long-term adverse health outcomes, including chronic diseases such as cardiovascular disease, stroke, diabetes, and cancer. Little is known about the metabolic consequences of changes in BMI in adolescents outside of typical clinical parameters. Here, we used untargeted metabolomics to assess changing BMI in male adolescents. Untargeted metabolomic profiling was performed on urine samples from 360 adolescents using UPLC-QTOF-MS. The study includes a baseline of 235 subjects in a discovery set and 125 subjects in a validation set. Of them, a follow-up of 81 subjects (1 year later) as a replication set was studied. Linear regression analysis models were used to estimate the associations of metabolic features with BMI z-score in the discovery and validation sets, after adjusting for age, race, and total energy intake (kcal) at false-discovery-rate correction (FDR) ≤ 0.1. We identified 221 and 16 significant metabolic features in the discovery and in the validation set, respectively. The metabolites associated with BMI z-score in validation sets are glycylproline, citrulline, 4-vinylsyringol, 3'-sialyllactose, estrone sulfate, carnosine, formiminoglutamic acid, 4-hydroxyproline, hydroxyprolyl-asparagine, 2-hexenoylcarnitine, L-glutamine, inosine, N-(2-Hydroxyphenyl) acetamide glucuronide, and galactosylhydroxylysine. Of those 16 features, 9 significant metabolic features were associated with a positive change in BMI in the replication set 1 year later. Histidine and arginine metabolism were the most affected metabolic pathways. Our findings suggest that obesity and its metabolic outcomes in the urine metabolome of children are linked to altered amino acids, lipid, and carbohydrate metabolism. These identified metabolites may serve as biomarkers and aid in the investigation of obesity's underlying pathological mechanisms. Whether these features are associated with the development of obesity, or a consequence of changing BMI, requires further study.

Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications-Review

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.

Metabolic Markers Associated with Progression of Type 2 Diabetes Induced by High-Fat Diet and Single Low Dose Streptozotocin in Rats

Science is still searching for readily available, cost-effective biomarkers to assess metabolic disorders occurring before the onset and during the development of type-2 diabetes (T2DM). The aim of the present study was to induce T2DM in rats through a high-fat diet, followed by a single administration of low dose streptozotocin (STZ), and make an assessment of the development of the disease. The rats were divided into two groups-experimental and control-and were monitored for a period of 10 days. Changes in anthropometric parameters, glucose, insulin, lipids, uric acid, advanced oxidation protein products (AOPP), as well as the histological changes in the liver and pancreas, were recorded. To assess insulin resistance, we used the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and beta cell function (HOMA-β) and visceral obesity-adiposity index (AI). The data demonstrate that the increasing values of glucose, HOMA-IR, AI, total cholesterol, triacylglycerols, low- and very-low-density lipoproteins are important markers of the pre-diabetic state. The stable hyperglycemia and increased levels of TC, TG, VLDL, LDL, uric acid and AOPP in experimental rats strongly suggest the development of T2DM. HOMA-IR, HOMA-β, AI, and uric acid are reliable criteria for T2DM in rats.

Adenylosuccinic Acid: An Orphan Drug with Untapped Potential

Adenylosuccinic acid (ASA) is an orphan drug that was once investigated for clinical application in Duchenne muscular dystrophy (DMD). Endogenous ASA participates in purine recycling and energy homeostasis but might also be crucial for averting inflammation and other forms of cellular stress during intense energy demand and maintaining tissue biomass and glucose disposal. This article documents the known biological functions of ASA and explores its potential application for the treatment of neuromuscular and other chronic diseases.

Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study

BACKGROUND

Type 2 diabetes (T2D) and coronary artery disease (CAD) both have known genetic determinants, but the mechanisms through which their associated genetic variants lead to disease onset remain poorly understood.

METHODS

We used large-scale metabolomics data in a two-sample reverse Mendelian randomization (MR) framework to estimate effects of genetic liability to T2D and CAD on 249 circulating metabolites in the UK Biobank (N = 118,466). We examined the potential for medication use to distort effect estimates by conducting age-stratified metabolite analyses.

FINDINGS

Using inverse variance weighted (IVW) models, higher genetic liability to T2D was estimated to decrease high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) (e.g.

, HDL-C

 -0.05 SD; 95% CI -0.07 to -0.03, per doubling of liability), whilst increasing all triglyceride groups and branched chain amino acids (BCAAs). IVW estimates for CAD liability suggested an effect on reducing HDL-C as well as raising very-low density lipoprotein cholesterol (VLDL-C) and LDL-C. In pleiotropy-robust models, T2D liability was still estimated to increase BCAAs, but several estimates for higher CAD liability reversed and supported decreased LDL-C and apolipoprotein-B. Estimated effects of CAD liability differed substantially by age for non-HDL-C traits, with higher CAD liability lowering LDL-C only at older ages when statin use was common.

INTERPRETATION

Overall, our results support largely distinct metabolic features of genetic liability to T2D and CAD, illustrating both challenges and opportunities for preventing these commonly co-occurring diseases.

FUNDING

Wellcome Trust [218495/Z/19/Z], UK MRC [MC_UU_00011/1; MC_UU_00011/4], the University of Bristol, Diabetes UK [17/0005587], World Cancer Research Fund [IIG_2019_2009].

Synergetic effects of concurrent chronic exposure to a mixture of OCPs and high-fat diets on type 2 diabetes and beneficial effects of caloric restriction in female zebrafish

This study aimed to investigate the relationship among chronic exposure to a low concentration of organochlorine pesticides (OCPs), high-fat diet (HFD)-induced obesity, and caloric restriction in type 2 diabetes (T2D). Thus, female zebrafish were divided into four groups and treated for 12 weeks as follows: (i) negative control, (ii) HFD (obesity) control, (iii) obesity + a mixture of OCPs (OP), and (iv) obesity + a mixture of OCPs + caloric restriction (OPR). We then assessed T2D-related effects via hematological analysis, histopathology, mitochondrial evaluation, and multiomics analyses. The OP group showed a significant increase in glucose levels, whereas the OPR group maintained glucose at nonsignificant levels. Multiomics analyses revealed that the exacerbated metabolic effects in the OP group were associated with molecular alterations in oxidative stress, inflammation, nucleotide metabolism, and glucose/lipid homeostasis. These alterations were histologically verified by the increased numbers of hypertrophic adipocytes and inflammatory cells observed. Caloric restriction activated pathways related to antioxidant response, mitochondrial fatty acid oxidation, and energy metabolism in zebrafish, leading to preserved glucose homeostasis. In conclusion, this study identified molecular mechanisms underlying the synergistic effect of concurrent exposure to a mixture of OCPs and HFD as well as shed light on the beneficial effect of regular caloric restriction in T2D development.

Childhood Obesity and the Cryptic Language of the Microbiota: Metabolomics’ Upgrading

The growing obesity epidemic in childhood is increasingly concerning for the related physical and psychological consequences, with a significant impact on health care costs in both the short and the long term. Nonetheless, the scientific community has not yet completely clarified the complex metabolic mechanisms underlying body weight alterations. In only a small percentage of cases, obesity is the result of endocrine, monogenic, or syndromic causes, while in much more cases, lifestyle plays a crucial role in obesity development. In this context, the pediatric age appears to be of considerable importance as prevention strategies together with early intervention can represent important therapeutic tools not only to counteract the comorbidities that increasingly affect children but also to hinder the persistence of obesity in adulthood. Although evidence in the literature supporting the alteration of the microbiota as a critical factor in the etiology of obesity is abundant, it is not yet fully defined and understood. However, increasingly clear evidence is emerging regarding the existence of differentiated metabolic profiles in obese children, with characteristic metabolites. The identification of specific pathology-related biomarkers and the elucidation of the altered metabolic pathways would therefore be desirable in order to clarify aspects that are still poorly understood, such as the consequences of the interaction between the host, the diet, and the microbiota. In fact, metabolomics can characterize the biological behavior of a specific individual in response to external stimuli, offering not only an eventual effective screening and prevention strategy but also the possibility of evaluating adherence and response to dietary intervention.

Analysis of correlations between gut microbiota, stool short chain fatty acids, calprotectin and cardiometabolic risk factors in postmenopausal women with obesity: a cross-sectional study

BACKGROUND

Microbiota and its metabolites are known to regulate host metabolism. In cross-sectional study conducted in postmenopausal women we aimed to assess whether the microbiota, its metabolites and gut barrier integrity marker are correlated with cardiometabolic risk factors and if microbiota is different between obese and non-obese subjects.

METHODS

We analysed the faecal microbiota of 56 obese, postmenopausal women by means of 16S rRNA analysis. Stool short chain fatty acids, calprotectin and anthropometric, physiological and biochemical parameters were correlates to microbiome analyses.

RESULTS

Alpha-diversity was inversely correlated with lipopolysaccharide (Rho = - 0.43, FDR P (Q) = 0.004). Bray-Curtis distance based RDA revealed that visceral fat and waist circumference had a significant impact on metabolic potential (P = 0.003). Plasma glucose was positively correlated with the Coriobacteriaceae (Rho = 0.48, Q = 0.004) and its higher taxonomic ranks, up to phylum (Actinobacteria, Rho = 0.46, Q = 0.004). At the metabolic level, the strongest correlation was observed for the visceral fat (Q < 0.15), especially with the DENOVOPURINE2-PWY, PWY-841 and PWY0-162 pathways. Bacterial abundance was correlated with SCFAs, thus some microbiota-glucose relationships may be mediated by propionate, as indicated by the significant average causal mediation effect (ACME): Lachnospiraceae (ACME 1.25, 95%CI (0.10, 2.97), Firmicutes (ACME 1.28, 95%CI (0.23, 3.83)) and Tenericutes (ACME - 0.39, 95%CI (- 0.87, - 0.03)). There were significant differences in the distribution of phyla between this study and Qiita database (P < 0.0001).

CONCLUSIONS

Microbiota composition and metabolic potential are associated with some CMRF and fecal SCFAs concentration in obese postmenopausal women. There is no unequivocal relationship between fecal SCFAs and the marker of intestinal barrier integrity and CMRF. Further studies with appropriately matched control groups are warranted to look for causality between SCFAs and CMRF.

Profile of gut microbiota and serum metabolites associated with metabolic syndrome in a remote island most afflicted by obesity in Japan

Numerous studies have revealed distinct differences in the profiles of gut microbiota between non-obese and obese individuals. To date, however, little is known if any disparities in the community of gut microbiota exist between metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) subjects. We therefore aimed to comprehensively characterize the gut microbiota and circulating metabolites in serum from both MHO and MUO residing in the remote island, Kumejima, where the prevalence of obesity is one of the highest in Japan, and explored possible correlations between the gut microbiota profile and markers of metabolic syndrome. Results revealed that MUO showed significantly higher levels of genera such as g_Succinivibrio, g_Granulicatella, g_Brachyspira, g_Oribacterium and g_Atopobium in comparison to MHO. Moreover, abundance of g_Succinivibrio, g_Brachyspira and g_Atopobium were positively correlated with value of fasting insulin, HOMA-R, circulating triglycerides, diastolic blood pressure, BMI, body weight, waist circumference and HbA1c. In addition, MUO compared to MHO showed an imbalance of serum metabolites, with a significant elevation in 2-oxoisovaleric acid, pyruvic acid, 2-hydroxybutyric acid, and creatine. Our data highlight unmet needs in precision approaches for the treatment of obesity, targeting the gut microbiota profile and serum metabolites in a distinct population affected by obesity.

Amino Acid-Related Metabolic Signature in Obese Children and Adolescents

The growing interest in metabolomics has spread to the search for suitable predictive biomarkers for complications related to the emerging issue of pediatric obesity and its related cardiovascular risk and metabolic alteration. Indeed, several studies have investigated the association between metabolic disorders and amino acids, in particular branched-chain amino acids (BCAAs). We have performed a revision of the literature to assess the role of BCAAs in children and adolescents' metabolism, focusing on the molecular pathways involved. We searched on Pubmed/Medline, including articles published until February 2022. The results have shown that plasmatic levels of BCAAs are impaired already in obese children and adolescents. The relationship between BCAAs, obesity and the related metabolic disorders is explained on one side by the activation of the mTORC1 complex-that may promote insulin resistance-and on the other, by the accumulation of toxic metabolites, which may lead to mitochondrial dysfunction, stress kinase activation and damage of pancreatic cells. These compounds may help in the precocious identification of many complications of pediatric obesity. However, further studies are still needed to better assess if BCAAs may be used to screen these conditions and if any other metabolomic compound may be useful to achieve this goal.

A systematic review of metabolomic studies of childhood obesity: State of the evidence for metabolic determinants and consequences

Childhood obesity has become a global epidemic and carries significant long-term consequences to physical and mental health. Metabolomics, the global profiling of small molecules or metabolites, may reveal the mechanisms of development of childhood obesity and clarify links between obesity and metabolic disease. A systematic review of metabolomic studies of childhood obesity was conducted, following Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, searching across Scopus, Ovid, Web of Science and PubMed databases for articles published from January 1, 2005 to July 8, 2020, retrieving 1271 different records and retaining 41 articles for qualitative synthesis. Study quality was assessed using a modified Newcastle-Ottawa Scale. Thirty-three studies were conducted on blood, six on urine, three on umbilical cord blood, and one on saliva. Thirty studies were primarily cross-sectional, five studies were primarily longitudinal, and seven studies examined effects of weight-loss following a life-style intervention. A consistent metabolic profile of childhood obesity was observed including amino acids (particularly branched chain and aromatic), carnitines, lipids, and steroids. Although the use of metabolomics in childhood obesity research is still developing, the identified metabolites have provided additional insight into the pathogenesis of many obesity-related diseases. Further longitudinal research is needed into the role of metabolic profiles and child obesity risk.

Omics era in type 2 diabetes: From childhood to adulthood

Parallel to the dramatic rise of pediatric obesity, estimates reported an increased prevalence of type 2 diabetes (T2D) already in childhood. The close relationship between obesity and T2D in children is mainly sustained by insulin resistance (IR). In addition, the cardiometabolic burden of T2D including nonalcoholic fatty liver disease, cardiovascular disease and metabolic syndrome is also strictly related to IR. Although T2D pathophysiology has been largely studied in an attempt to improve therapeutic options, molecular mechanisms are still not fully elucidated. In this perspective, omics approaches (including lipidomics, metabolomics, proteomics and metagenomics) are providing the most attractive therapeutic options for T2D. In particular, distinct both lipids and metabolites are emerging as potential therapeutic tools. Of note, among lipid classes, the pathogenic role of ceramides in T2D context has been supported by several data. Thus, selective changes of ceramides expression might represent innovative therapeutic strategies for T2D treatment. More, distinct metabolomics pathways have been also found to be associated with higher T2D risk, by providing novel potential T2D biomarkers. Taken together, omics data are responsible for the expanding knowledge of T2D pathophysiology, by providing novel insights to improve therapeutic strategies for this tangled disease. We aimed to summarize the most recent evidence in the intriguing field of the omics approaches in T2D both in adults and children.

Perturbation of serum metabolome in relation to type 2 diabetes mellitus and urinary levels of phthalate metabolites and bisphenols

BACKGROUND

Emerging evidence has proved the associations between exposure to phthalates (PAEs) and bisphenols and type 2 diabetes mellitus (T2DM), but the underlying mechanisms for these associations are poorly understood. Metabolomics is a powerful tool to identify differential metabolites and metabolic pathways related to diseases and chemical exposure, which may reveal underlying mechanisms. However, little is known about the roles of metabolism in the associations for PAE and bisphenol exposure with T2DM.

OBJECTIVES

The purpose of the study was to investigate the roles of metabolism in the associations for exposure to PAEs and bisphenols with T2DM.

METHODS

In this study, 60 T2DM cases and 60 controls, who were matched in age, sex, and body mass index (BMI), were selected from the total study population in our previous studies. Fasting blood and spot urine samples of the volunteers were used for non-targeted metabolomics analysis and determination of phthalate metabolites (mPAEs) and bisphenols, respectively. The associations of urinary mPAEs and bisphenols with screened metabolic biomarkers in metabolomics analysis were analyzed using multiple linear regression models.

RESULTS

Based on non-targeted metabolomics, 19 serum metabolic biomarkers were screened between T2DM cases and controls, mostly related to galactose metabolism, amino acid metabolism, and pyrimidine metabolism. More than half of mPAEs were mostly positively associated with up-regulated metabolic biomarkers and negatively associated with down-regulated biomarkers. Different from PAEs, no evident results suggested the roles of metabolism in the associations between bisphenol exposure and T2DM.

CONCLUSIONS

Combined with the positive associations between most urinary mPAEs and T2DM in our previous study, our findings indicated that PAE exposure may contribute to T2DM risk through disturbing galactose metabolism, amino acid metabolism (especially arginine biosynthesis and alanine, aspartate and glutamate metabolism), and pyrimidine metabolism.

Common Genetic Aberrations Associated with Metabolic Interferences in Human Type-2 Diabetes and Acute Myeloid Leukemia: A Bioinformatics Approach

Type-2 diabetes mellitus (T2D) is a chronic metabolic disorder, associated with an increased risk of developing solid tumors and hematological malignancies, including acute myeloid leukemia (AML). However, the genetic background underlying this predisposition remains elusive. We herein aimed at the exploration of the genetic variants, related transcriptomic changes and disturbances in metabolic pathways shared by T2D and AML, utilizing bioinformatics tools and repositories, as well as publicly available clinical datasets. Our approach revealed that rs11709077 and rs1801282, on PPARG, rs11108094 on USP44, rs6685701 on RPS6KA1 and rs7929543 on AC118942.1 comprise common SNPs susceptible to the two diseases and, together with 64 other co-inherited proxy SNPs, may affect the expression patterns of metabolic genes, such as USP44, METAP2, PPARG, TIMP4 and RPS6KA1, in adipose tissue, skeletal muscle, liver, pancreas and whole blood. Most importantly, a set of 86 AML/T2D common susceptibility genes was found to be significantly associated with metabolic cellular processes, including purine, pyrimidine, and choline metabolism, as well as insulin, AMPK, mTOR and PI₃K signaling. Moreover, it was revealed that the whole blood of AML patients exhibits deregulated expression of certain T2D-related genes. Our findings support the existence of common metabolic perturbations in AML and T2D that may account for the increased risk for AML in T2D patients. Future studies may focus on the elucidation of these pathogenetic mechanisms in AML/T2D patients, as well as on the assessment of certain susceptibility variants and genes as potential biomarkers for AML development in the setting of T2D. Detection of shared therapeutic molecular targets may enforce the need for repurposing metabolic drugs in the therapeutic management of AML.

Non-targeted Serum Metabolomics Identifies Candidate Biomarkers Panels Associated with Nonalcoholic Fatty Liver Disease: A Pilot Study in Russian Male Patients

Aims:

The aim of the present study was to explore changes in the serum metabolome of patients with NAFLD relative to healthy controls to identify biomarkers associated with steatosis or Non-Alcoholic Steatohepatitis (NASH).

Background:

The serum metabolome reflects changes at the organismal level. This is especially important in Non-Alcoholic Liver Disease (NAFLD), where changes in hormones, cytokines, enzymes and other metabolic alterations can affect the liver, as well as adipose tissue, skeletal muscle and other systems.

Objective:

The objectives were to conduct non-targeted serum metabolomics, data processing, and identification of candidate biomarkers, as well as panels and assessment of their prognostic value.

Materials and Methods:

Non-targeted metabolomic analysis of blood serum samples from 21 male patients with NAFLD (simple steatosis or NASH) and seven male Control group was performed using gas chromatography-mass spectrometry.

Results:

A total of 319 serum metabolites were detected in NAFLD and Control groups, several of which differed significantly between groups. The most discriminating biomarkers were 3-hydroxybutyric acid, 2-hydroxybutyric acid, 2,3-dihydroxybutyric acid, arabitol and 3-methyl-2-oxovaleric acid. Using a panel of three, four or more markers could distinguish patients with NAFLD from controls, and patients with NASH from those with simple steatosis.

Conclusion:

We identified candidate biomarkers for simple steatosis and NASH. Since NAFLD is a multifactorial disease, it is preferable to use a marker panel rather than individual metabolites. Markers may not only result from dysregulation of metabolic pathways in patients with NAFLD, they may also reflect adaptive responses to disease, including functional changes in the intestinal microbiota.