Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants

Urpí-Sardà, Mireia; Almanza-Aguilera, Enrique; Llorach, Rafaël; Vázquez-Fresno, Rosa; Estruch, Ramón; Corella, Dolores; Sorlí, José V.; Carmona, Francesc; Sánchez-Plà, Álex; Salas‐Salvadó, Jordi; Andrés‐Lacueva, Cristina

doi:10.1016/j.diabet.2018.02.006

Cited by 61 publications

(41 citation statements)

References 40 publications

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“…The findings relating to the urea cycle metabolites was consistent with the results of a separate study which discovered that patients with T2DM had increased plasma levels of arginine, and decreased levels of ornithine [277]. Furthermore, metabolite profiling has revealed significant differences in the levels of certain urinary metabolites such as alanine, betaine, formic acid, and trigonelline, between diabetic and non-diabetic individuals [278]. Investigating the metabolic pathways that involve these metabolites may provide new insights into the pathophysiology of diabetes and the involvement of these metabolites.…”

Section: Metabolite Profilingsupporting

confidence: 82%

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants

2019

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Type 2 Diabetes Mellitus has reached epidemic proportions as a result of over-nutrition and increasingly sedentary lifestyles. Current therapies, although effective, are not without limitations. These limitations, the alarming increase in the prevalence of diabetes, and the soaring cost of managing diabetes and its complications underscores an urgent need for safer, more efficient and affordable alternative treatments. Over 1200 plant species are reported in ethnomedicine for treating diabetes and these represents an important and promising source for the identification of novel antidiabetic compounds. Evaluating medicinal plants for desirable bioactivity goes hand-in-hand with methods in analytical biochemistry for separating and identifying lead compounds. This review aims to provide a comprehensive summary of current methods used in antidiabetic plant research to form a useful resource for researchers beginning in the field. The review summarises the current understanding of blood glucose regulation and the general mechanisms of action of current antidiabetic medications, and combines knowledge on common experimental approaches for screening plant extracts for antidiabetic activity and currently available analytical methods and technologies for the separation and identification of bioactive natural products. Common in vivo animal models, in vitro models, in silico methods and biochemical assays used for testing the antidiabetic effects of plants are discussed with a particular emphasis on in vitro methods such as cell-based bioassays for screening insulin secretagogues and insulinomimetics. Enzyme inhibition assays and molecular docking are also highlighted. The role of metabolomics, metabolite profiling, and dereplication of data for the high-throughput discovery of novel antidiabetic agents is reviewed. Finally, this review also summarises sample preparation techniques such as liquid–liquid extraction, solid phase extraction, and supercritical fluid extraction, and the critical function of nuclear magnetic resonance and high resolution liquid chromatography–mass spectrometry for the dereplication, putative identification and structure elucidation of natural compounds from evidence-based medicinal plants.

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Section: Metabolite Profilingsupporting

confidence: 82%

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants

2019

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“…The recent study reported several alterations of CHD and DB in metabolic pathway, including cAMP signaling pathway (28) , glycolysis/gluconeogenesis and pyruvate metabolism (29) , which keep consistent with our results (Fig. 1).…”

Section: Discussionsupporting

confidence: 93%

Metabolomic differences and interactions between coronary heart disease and diabetes mellitus: Pathogenesis understanding and auxiliary diagnosis

Liu¹,

Guo²,

Taguchi³

et al. 2020

Preprint

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Background: Comprehensive understanding of plasma metabotype of diabetes (DB), coronary heart disease (CHD) and especially diabetes with coronary heart disease (CHDDB) has kept lacking. The metabolic fingerprints of CHD, DB and CHDDB were investigated to reveal their pathogenic mechanisms and interactions and identify their specific biomarkers.Methods: The plasma metabolomic differences and links of 15 DB, 15 CHD and 30 CHDDB patients and 15 matched healthy controls were investigated by NMR-based strategy. The univariate and multivariate statistical analyses-based pattern recognition was combined with network analysis to determine disease specific biomarkers and understand the corresponding pathogenic pathways.Results: A total of 17 metabolites related to the development of disease were identified by comparative metabolomic analysis, and 6 of them were shared by the three diseases. The metabolites involved in amino acid synthesis (valine, alanine, leucine, isoleucine, and N-acetyl-glycoprotein) were positively associated with CHD and CHDDB (Odds Ratios (OR) >1); The trimethylamine oxide, glycerol, lactose, indoleacetate and scyllo-inositol are closely related to the development of DB to CHDDB (OR>1), and indoleactate (OR: 1.06, 95% confidence interval (CI): 1.01-1.12) and lactose (OR: 2.46, 95% CI: 1.67-3.25) are particularly prominent in CHDDB. The three different multi-biomarker signatures could serve to distinguish between CHDDB, DB, and CHD. All diseases demonstrated the disturbed glycolysis/gluconeogenesis and amino acid biosynthesis pathway. Furthermore, inositol phosphate metabolism, tryptophan metabolism and microbiota metabolism play a major role in the development of CHDDB from DB.Conclusions: The disease-specific multi-biomarkers provide promising capability in auxiliary diagnosis of DB-related disease and follow-up of disease progression and treatment. The comparative metabolomics strategy of multi-diseases offers a comprehensive perspective in disease-specific markers and pathogenic pathways.

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“…Type 1 diabetes risk is traditionally associated with autoimmunity, and lysophosphatidylcholine (18:0/0:0), BCAA, and glutamic acid are increased along with decreased glutamine and methionine levels before and after seroconversion with autoantibodies ( 23 , 24 ). Type 2 diabetes risk is associated with insulin resistance ( 25 ) and with elevated amino acids isoleucine, leucine, valine, tyrosine, and phenylalanine and decreased asparagine, glycine, and glutamine levels ( 25 , 26 ). Although this study only included participants with type 1 diabetes, given the contemporary changes in the phenotypes of patients with type 1 diabetes and that insulin resistance may be present in some participants, we stratified our cohorts based on highest daily insulin requirements and found no differences between these subgroups.…”

Section: Discussionmentioning

confidence: 99%

Impaired Amino Acid and TCA Metabolism and Cardiovascular Autonomic Neuropathy Progression in Type 1 Diabetes

et al. 2019

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While diabetes is characterized by hyperglycemia, nutrient metabolic pathways like amino acid and tricarboxylic acid (TCA) cycle are also profoundly perturbed. As glycemic control alone does not prevent complications, we hypothesized that these metabolic disruptions are responsible for the development and progression of diabetic cardiovascular autonomic neuropathy (CAN). We performed standardized cardiovascular autonomic reflex tests and targeted fasting plasma metabolomic analysis of amino acids and TCA cycle intermediates in subjects with type 1 diabetes and healthy control subjects followed for 3 years. Forty-seven participants with type 1 diabetes (60% female and mean 6 SD age 35 6 13 years, diabetes duration 13 6 7 years, and HbA 1c 7.9 6 1.2%) had lower fumarate levels and higher threonine, serine, proline, asparagine, aspartic acid, phenylalanine, tyrosine, and histidine levels compared with 10 age-matched healthy control subjects. Higher baseline fumarate levels and lower baseline amino acid levelsasparagine and glutamine-correlate with CAN (lower baseline SD of normal R-R interval [SDNN]). Baseline glutamine and ornithine levels also associated with the progression of CAN (lower SDNN at 3 years) and change in SDNN, respectively, after adjustment for baseline HbA 1c , blood glucose, BMI, cholesterol, urine microalbumin-tocreatinine ratio, estimated glomerular filtration rate, and years of diabetes. Therefore, significant changes in the anaplerotic flux into the TCA cycle could be the critical defect underlying CAN progression.

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Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants

Cited by 61 publications

References 40 publications

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants

Metabolomic differences and interactions between coronary heart disease and diabetes mellitus: Pathogenesis understanding and auxiliary diagnosis

Impaired Amino Acid and TCA Metabolism and Cardiovascular Autonomic Neuropathy Progression in Type 1 Diabetes

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