Plasma metabolites of lipid metabolism associate with diabetic polyneuropathy in a cohort with screen-tested type 2 diabetes: ADDITION-Denmark
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
DISEASE(S): Obesity
PROVIDER: ST001411 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:ObjectiveThe global rise in type 2 diabetes is associated with a concomitant increase in diabetic complications. Diabetic polyneuropathy is the most frequent type 2 diabetes complication and is associated with poor outcomes. The metabolic syndrome has emerged as a major risk factor for diabetic polyneuropathy; however, the metabolites associated with the metabolic syndrome that correlate with diabetic polyneuropathy are unknown.MethodsWe conducted a global metabolomics analysis on plasma samples from a subcohort of participants from the Danish arm of Anglo-Danish-Dutch study of Intensive Treatment of Diabetes in Primary Care (ADDITION-Denmark) with and without diabetic polyneuropathy versus lean control participants.ResultsCompared to lean controls, type 2 diabetes participants had significantly higher HbA1c (p = 0.0028), BMI (p = 0.0004), and waist circumference (p = 0.0001), but lower total cholesterol (p = 0.0001). Out of 991 total metabolites, we identified 15 plasma metabolites that differed in type 2 diabetes participants by diabetic polyneuropathy status, including metabolites belonging to energy, lipid, and xenobiotic pathways, among others. Additionally, these metabolites correlated with alterations in plasma lipid metabolites in type 2 diabetes participants based on neuropathy status. Further evaluating all plasma lipid metabolites identified a shift in abundance, chain length, and saturation of free fatty acids in type 2 diabetes participants. Importantly, the presence of diabetic polyneuropathy impacted the abundance of plasma complex lipids, including acylcarnitines and sphingolipids.InterpretationOur explorative study suggests that diabetic polyneuropathy in type 2 diabetes is associated with novel alterations in plasma metabolites related to lipid metabolism.
| S-EPMC8164865 | biostudies-literature
Project description:BACKGROUND:Existing evidence for the prospective association of vitamin D status with type 2 diabetes (T2D) is focused almost exclusively on circulating total 25-hydroxyvitamin D [25(OH)D] without distinction between its subtypes: nonepimeric and epimeric 25(OH)D3 stereoisomers, and 25(OH)D2, the minor component of 25(OH)D. We aimed to investigate the prospective associations of circulating levels of the sum and each of these three metabolites with incident T2D. METHODS:This analysis in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study for T2D included 9671 incident T2D cases and 13,562 subcohort members. Plasma vitamin D metabolites were quantified by liquid chromatography-mass spectrometry. We used a multivariable Prentice-weighted Cox regression to estimate hazard ratios (HRs) of T2D for each metabolite. Analyses were performed separately within country, and estimates were combined across countries using random-effects meta-analysis. RESULTS:The mean concentrations (SD) of total 25(OH)D, nonepimeric 25(OH)D3, epimeric 25(OH)D3, and 25(OH)D2 were 41.1 (17.2), 40.7 (17.3), 2.13 (1.31), and 8.16 (6.52) nmol/L, respectively. Plasma total 25(OH)D and nonepimeric 25(OH)D3 were inversely associated with incident T2D [multivariable-adjusted HR per 1 SD = 0.81 (95% CI, 0.77, 0.86) for both variables], whereas epimeric 25(OH)D3 was positively associated [per 1 SD HR = 1.16 (1.09, 1.25)]. There was no statistically significant association with T2D for 25(OH)D2 [per 1 SD HR = 0.94 (0.76, 1.18)]. CONCLUSIONS:Plasma nonepimeric 25(OH)D3 was inversely associated with incident T2D, consistent with it being the major metabolite contributing to total 25(OH)D. The positive association of the epimeric form of 25(OH)D3 with incident T2D provides novel information to assess the biological relevance of vitamin D epimerization and vitamin D subtypes in diabetes etiology.
| S-EPMC6397435 | biostudies-other
Project description:Aims/hypothesisEmerging evidence suggests that in addition to hyperglycaemia, dyslipidaemia could represent a contributing pathogenetic factor to diabetic neuropathy, while obesity and insulin resistance play a role in the development of diabetic cardiac autonomic neuropathy (CAN) characterised by reduced heart rate variability (HRV), particularly in type 2 diabetes. We hypothesised that distinct lipid metabolites are associated with diminished HRV in recent-onset type 2 diabetes rather than type 1 diabetes.MethodsWe analysed 127 plasma lipid metabolites (11 acylcarnitines, 39 NEFA, 12 sphingomyelins (SMs), 56 phosphatidylcholines and nine lysophosphatidylcholines) using MS in participants from the German Diabetes Study baseline cohort recently diagnosed with type 1 (n = 100) and type 2 diabetes (n = 206). Four time-domain HRV indices (number of normal-to-normal (NN) intervals >50 ms divided by the number of all NN intervals [pNN50]; root mean square of successive differences [RMSSD]; SD of NN intervals [SDNN]; and SD of differences between adjacent NN intervals) and three frequency-domain HRV indices (very-low-frequency [VLF], low-frequency [LF] and high-frequency [HF] power spectrum) were computed from NN intervals recorded during a 3 h hyperinsulinaemic-euglycaemic clamp at baseline and in subsets of participants with type 1 (n = 60) and type 2 diabetes (n = 95) after 5 years.ResultsIn participants with type 2 diabetes, after Bonferroni correction and rigorous adjustment, SDNN was inversely associated with higher levels of diacyl-phosphatidylcholine (PCaa) C32:0, PCaa C34:1, acyl-alkyl-phosphatidylcholine (PCae) C36:0, SM C16:0 and SM C16:1. SD of differences between NN intervals was inversely associated with PCaa C32:0, PCaa C34:1, PCaa C34:2, PCae C36:0 and SM C16:1, and RMSSD with PCae C36:0. For VLF power, inverse associations were found with PCaa C30:0, PCaa C32:0, PCaa C32:1, PCaa C34:2 and SM C16:1, and for LF power inverse associations were found with PCaa C32:0 and SM C16:1 (r = -0.242 to r = -0.349; p ≤ 0.0005 for all correlations). In contrast, no associations of lipid metabolites with measures of cardiac autonomic function were noted in participants recently diagnosed with type 1 diabetes. After 5 years, HRV declined due to ageing rather than diabetes, whereby prediction analyses for lipid metabolites were hampered.Conclusions/interpretationHigher plasma levels of specific lipid metabolites are closely linked to cardiac autonomic dysfunction in recent-onset type 2 diabetes but not type 1 diabetes, suggesting a role for perturbed lipid metabolism in the early development of CAN in type 2 diabetes. Graphical abstract.
| S-EPMC7801358 | biostudies-literature
Project description:The prospero homeobox 1 (PROX1) gene may show pleiotropic effects on metabolism. We evaluated postprandial metabolic alterations dependently on the rs340874 genotypes, and 28 non-diabetic men were divided into two groups: high-risk (HR)-genotype (CC-genotype carriers, n = 12, 35.3 ± 9.5 years old) and low-risk (LR)-genotype (allele T carriers, n = 16, 36.3 ± 7.0 years old). Subjects participated in two meal-challenge-tests with high-carbohydrate (HC, carbohydrates 89%) and normo-carbohydrate (NC, carbohydrates 45%) meal intake. Fasting and 30, 60, 120, and 180 min after meal intake plasma samples were fingerprinted by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). In HR-genotype men, the area under the curve (AUC) of acetylcarnitine levels was higher after the HC-meal [+92%, variable importance in the projection (VIP) = 2.88] and the NC-meal (+55%, VIP = 2.00) intake. After the NC-meal, the HR-risk genotype carriers presented lower AUCs of oxidized fatty acids (-81-66%, VIP = 1.43-3.16) and higher linoleic acid (+80%, VIP = 2.29), while after the HC-meal, they presented lower AUCs of ornithine (-45%, VIP = 1.83), sphingosine (-48%, VIP = 2.78), linoleamide (-45%, VIP = 1.51), and several lysophospholipids (-40-56%, VIP = 1.72-2.16). Moreover, lower AUC (-59%, VIP = 2.43) of taurocholate after the HC-meal and higher (+70%, VIP = 1.42) glycodeoxycholate levels after the NC-meal were observed. Our results revealed differences in postprandial metabolites from inflammatory and oxidative stress pathways, bile acids signaling, and lipid metabolism in PROX1 HR-genotype men. Further investigations of diet-genes interactions by which PROX1 may promote T2DM development are needed.
| S-EPMC6520869 | biostudies-literature
Project description:BackgroundEpidemiologic studies have reported a modest inverse association between dairy consumption and the risk of type 2 diabetes (T2D). Whether plasma metabolite profiles associated with dairy consumption reflect this relationship remains unknown.ObjectivesWe aimed to identify the plasma metabolites associated with total and specific dairy consumption, and to evaluate the association between the identified multi-metabolite profiles and T2D.MethodsThe discovery population included 1833 participants from the Prevención con Dieta Mediterránea (PREDIMED) trial. The confirmatory cohorts included 1522 PREDIMED participants at year 1 of the trial and 4932 participants from the Nurses' Health Studies (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-Up Study US-based cohorts. Dairy consumption was assessed using validated FFQs. Plasma metabolites (n = 385) were profiled using LC-MS. We identified the dairy-related metabolite profiles using elastic net regularized regressions with a 10-fold cross-validation procedure. We evaluated the associations between the metabolite profiles and incident T2D in the discovery and the confirmatory cohorts.ResultsTotal dairy intake was associated with 38 metabolites. C14:0 sphingomyelin (positive coefficient), C34:0 phosphatidylethanolamine (positive coefficient), and γ-butyrobetaine (negative coefficient) were associated in a directionally similar fashion with total and specific (milk, yogurt, cheese) dairy consumption. The Pearson correlation coefficients between self-reported total dairy intake and predicted total dairy intake based on the corresponding multi-metabolite profile were 0.37 (95% CI, 0.33-0.40) in the discovery cohort and 0.16 (95% CI, 0.13-0.19) in the US confirmatory cohort. After adjusting for T2D risk factors, a higher total dairy intake-related metabolite profile score was associated with a lower T2D risk [HR per 1 SD; discovery cohort: 0.76 (95% CI, 0.63-0.90); US confirmatory cohort: 0.88 (95% CI, 0.78-0.99)].ConclusionsTotal dairy intake was associated with 38 metabolites, including 3 consistently associated with dairy subtypes (C14:0 sphingomyelin, C34:0 phosphatidylethanolamine, γ-butyrobetaine). A score based on the 38 identified metabolites showed an inverse association with T2D risk in Spanish and US populations.
| S-EPMC8246603 | biostudies-literature
Project description:Humans with the metabolic syndrome and type 2 diabetes have an altered gut microbiome. Emerging evidence indicates that it is not only the microorganisms and their structural components, but also their metabolites that influences the host and contributes to the development of the metabolic syndrome and type 2 diabetes. Here, we discuss some of the mechanisms underlying how microbial metabolites are recognised by the host or are further processed endogenously in the context of type 2 diabetes. We discuss the possibility that gut-derived microbial metabolites fuel the development of the metabolic syndrome and type 2 diabetes. Graphical abstract.
| S-EPMC7641949 | biostudies-literature
Project description:BackgroundAlthough an increased arterial stiffness has been associated with traditional coronary risk factors, the risk factors and pathology of arterial stiffness remain unclear. In this study, we aimed to identify the plasma metabolites associated with arterial stiffness in patients with type 2 diabetes mellitus.MethodsWe used the metabolomic data of 209 patients with type 2 diabetes as the first dataset for screening. To form the second dataset for validation, we enlisted an additional 31 individuals with type 2 diabetes. The non-targeted metabolome analysis of fasting plasma samples using gas chromatography coupled with mass spectrometry and the measurement of brachial-ankle pulse wave velocity (baPWV) were performed.ResultsA total of 65 annotated metabolites were detected. In the screening dataset, there were statistically significant associations between the baPWV and plasma levels of indoxyl sulfate (r = 0.226, p = 0.001), mannitol (r = 0.178, p = 0.010), mesoerythritol (r = 0.234, p = 0.001), and pyroglutamic acid (r = 0.182, p = 0.008). Multivariate regression analyses revealed that the plasma levels of mesoerythritol were significantly (β = 0.163, p = 0.025) and that of indoxyl sulfate were marginally (β = 0.124, p = 0.076) associated with baPWV, even after adjusting for traditional coronary risk factors. In the independent validation dataset, there was a statistically significant association between the baPWV and plasma levels of indoxyl sulfate (r = 0.430, p = 0.016). However, significant associations between the baPWV and plasma levels of the other three metabolites were not confirmed.Conclusions/interpretationThe plasma levels of indoxyl sulfate were associated with arterial stiffness in Japanese patients with type 2 diabetes. Although the plasma levels of mannitol, mesoerythritol, and pyroglutamic acid were also associated with arterial stiffness, further investigation is needed to verify the results.
| S-EPMC7291560 | biostudies-literature
Project description:Aims/hypothesisThe aims of the present work were to identify plasma metabolites that predict future type 2 diabetes, to investigate the changes in identified metabolites among individuals who later did or did not develop type 2 diabetes over time, and to assess the extent to which inclusion of predictive metabolites could improve risk prediction.MethodsWe established a nested case-control study within the Swedish prospective population-based Västerbotten Intervention Programme cohort. Using untargeted liquid chromatography-MS metabolomics, we analysed plasma samples from 503 case-control pairs at baseline (a median time of 7 years prior to diagnosis) and samples from a subset of 187 case-control pairs at 10 years of follow-up. Discriminative metabolites between cases and controls at baseline were optimally selected using a multivariate data analysis pipeline adapted for large-scale metabolomics. Conditional logistic regression was used to assess associations between discriminative metabolites and future type 2 diabetes, adjusting for several known risk factors. Reproducibility of identified metabolites was estimated by intra-class correlation over the 10 year period among the subset of healthy participants; their systematic changes over time in relation to diagnosis among those who developed type 2 diabetes were investigated using mixed models. Risk prediction performance of models made from different predictors was evaluated using area under the receiver operating characteristic curve, discrimination improvement index and net reclassification index.ResultsWe identified 46 predictive plasma metabolites of type 2 diabetes. Among novel findings, phosphatidylcholines (PCs) containing odd-chain fatty acids (C19:1 and C17:0) and 2-hydroxyethanesulfonate were associated with the likelihood of developing type 2 diabetes; we also confirmed previously identified predictive biomarkers. Identified metabolites strongly correlated with insulin resistance and/or beta cell dysfunction. Of 46 identified metabolites, 26 showed intermediate to high reproducibility among healthy individuals. Moreover, PCs with odd-chain fatty acids, branched-chain amino acids, 3-methyl-2-oxovaleric acid and glutamate changed over time along with disease progression among diabetes cases. Importantly, we found that a combination of five of the most robustly predictive metabolites significantly improved risk prediction if added to models with an a priori defined set of traditional risk factors, but only a marginal improvement was achieved when using models based on optimally selected traditional risk factors.Conclusions/interpretationPredictive metabolites may improve understanding of the pathophysiology of type 2 diabetes and reflect disease progression, but they provide limited incremental value in risk prediction beyond optimal use of traditional risk factors.
| S-EPMC6448991 | biostudies-literature
Project description:ObjectiveTo examine the association of bradykinin and related peptides with the development of diabetic nephropathy lesions in 243 participants with type 1 diabetes (T1D) from the Renin-Angiotensin System Study who, at baseline, were normoalbuminuric, normotensive and had normal or increased glomerular filtration rate (GFR).DesignPlasma concentrations of bradykinin and related peptides were measured at baseline by quantitative mass spectrometry. All participants were randomly assigned at baseline to receive placebo, enalapril or losartan during the 5 years between kidney biopsies. Kidney morphometric data were available from kidney biopsies at baseline and after 5 years. Relationships of peptides with changes in morphometric variables were assessed using multiple linear regression after adjustment for age, sex, diabetes duration, HbA1c, mean arterial pressure, treatment assignment and, for longitudinal analyses, baseline structure.ResultsBaseline median albumin excretion rate of study participants was 5.0 μg/min, and mean GFR was 128 mL/min/1.73 m2. After multivariable adjustment, higher plasma concentration of bradykinin (1-8) was associated with greater glomerular volume (partial r = 0.191, P = 0.019) and total filtration surface area (partial r = 0.211, P = 0.010), and higher bradykinin (1-7) and hyp3-bradykinin (1-7) were associated with lower cortical interstitial fractional volume (partial r = -0.189, P = 0.011; partial r = -0.164, P = 0.027 respectively). In longitudinal analyses, higher bradykinin was associated with preservation of surface density of the peripheral glomerular basement membrane (partial r = 0.162, P = 0.013), and for participants randomized to losartan, higher hyp3-bradykinin (1-8) was associated with more limited increase in cortical interstitial fractional volume (partial r = -0.291, P = 0.033).ConclusionsHigher plasma bradykinin and related peptide concentrations measured before clinical onset of diabetic nephropathy in persons with T1D were associated with preservation of glomerular structures, suggesting that elevations of these kinin concentrations may reflect adaptive responses to early renal structural changes in diabetic nephropathy.
| S-EPMC5507314 | biostudies-literature
Project description:BackgroundAs part of a clinical proteomics program focused on diabetes and its complications we are looking for new and better protein biomarkers for diabetic nephropathy. The search for new and better biomarkers for diabetic nephropathy has, with a few exceptions, previously focused on either hypothesis-driven studies or urinary based investigations. To date only two studies have investigated the proteome of blood in search for new biomarkers, and these studies were conducted in sera from patients with type 2 diabetes. This is the first reported in depth proteomic study where plasma from type 1 diabetic patients was investigated with the goal of finding improved candidate biomarkers to predict diabetic nephropathy. In order to reach lower concentration proteins in plasma a pre-fractionation step, either hexapeptide bead-based libraries or anion exchange chromatography, was performed prior to surface enhanced laser desorption/ionization time-of-flight mass spectrometry analysis.ResultsProteomic analysis of plasma from a cross-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric, gave rise to 290 peaks clusters of which 16 were selected as the most promising biomarker candidates based on statistical performance, including independent component analysis. Four of the peaks that were discovered have been identified as transthyretin, apolipoprotein A1, apolipoprotein C1 and cystatin C. Several yet unidentified proteins discovered by this novel approach appear to have more potential as biomarkers for diabetic nephropathy.ConclusionThese results demonstrate the capacity of proteomic analysis of plasma, by confirming the presence of known biomarkers as well as revealing new biomarkers for diabetic nephropathy in plasma in type 1 diabetic patients.
| S-EPMC2827395 | biostudies-literature