Metabolite profiles and the risk of developing diabetes.
Ontology highlight
ABSTRACT:
SUBMITTER: Wang TJ
PROVIDER: S-EPMC3126616 | biostudies-literature | 2011 Apr
REPOSITORIES: biostudies-literature
Publications
Metabolite profiles and the risk of developing diabetes.
Wang Thomas J TJ Larson Martin G MG Vasan Ramachandran S RS Cheng Susan S Rhee Eugene P EP McCabe Elizabeth E Lewis Gregory D GD Fox Caroline S CS Jacques Paul F PF Fernandez Céline C O'Donnell Christopher J CJ Carr Stephen A SA Mootha Vamsi K VK Florez Jose C JC Souza Amanda A Melander Olle O Clish Clary B CB Gerszten Robert E RE
Nature medicine 20110320 4
Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography-tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting ...[more]
Similar Datasets
Project description:Aims/hypothesisPlant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes.MethodsWithin three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified.ResultsWe identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05).Conclusions/interpretationPlasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.
| S-EPMC9810389 | biostudies-literature
Project description:Identifying novel biomarkers of type 2 diabetes risk may improve prediction and prevention among individuals at high risk of the disease and elucidate new biological pathways relevant to diabetes development. We performed plasma metabolite profiling in the Diabetes Prevention Program (DPP), a completed trial that randomized high-risk individuals to lifestyle, metformin, or placebo interventions. Previously reported markers, branched-chain and aromatic amino acids and glutamine/glutamate, were associated with incident diabetes (P < 0.05 for all), but these associations were attenuated upon adjustment for clinical and biochemical measures. By contrast, baseline levels of betaine, also known as glycine betaine (hazard ratio 0.84 per SD log metabolite level, P = 0.02), and three other metabolites were associated with incident diabetes even after adjustment. Moreover, betaine was increased by the lifestyle intervention, which was the most effective approach to preventing diabetes, and increases in betaine at 2 years were also associated with lower diabetes incidence (P = 0.01). Our findings indicate betaine is a marker of diabetes risk among high-risk individuals both at baseline and during preventive interventions and they complement animal models demonstrating a direct role for betaine in modulating metabolic health.
| S-EPMC4839205 | biostudies-literature
Project description:Novel biomarkers of type 2 diabetes (T2D) and response to preventative treatment in individuals with similar clinical risk may highlight metabolic pathways that are important in disease development. We profiled 331 metabolites in 2,015 baseline plasma samples from the Diabetes Prevention Program (DPP). Cox models were used to determine associations between metabolites and incident T2D, as well as whether associations differed by treatment group (i.e., lifestyle [ILS], metformin [MET], or placebo [PLA]), over an average of 3.2 years of follow-up. We found 69 metabolites associated with incident T2D regardless of treatment randomization. In particular, cytosine was novel and associated with the lowest risk. In an exploratory analysis, 35 baseline metabolite associations with incident T2D differed across the treatment groups. Stratification by baseline levels of several of these metabolites, including specific phospholipids and AMP, modified the effect that ILS or MET had on diabetes development. Our findings highlight novel markers of diabetes risk and preventative treatment effect in individuals who are clinically at high risk and motivate further studies to validate these interactions.
| S-EPMC6868469 | biostudies-literature
Project description:A growing body of evidence suggests that diabetes is a risk factor for endometrial cancer incidence. However, most of these studies used case-control study designs and did not adjust for obesity, an established risk factor for endometrial cancer. In addition, few epidemiological studies have examined the association between diabetes treatment and endometrial cancer risk. The objective of this study was to assess the relationships among diabetes, diabetes treatment and endometrial cancer risk in postmenopausal women participating in the Women's Health Initiative (WHI).A total of 88 107 postmenopausal women aged 50-79 years who were free of cancer and had no hysterectomy at baseline were followed until date of endometrial cancer diagnosis, death, hysterectomy or loss to follow-up, whichever came first. Endometrial cancers were confirmed by central medical record and pathology report review. Multivariate Cox proportional hazards regression models were used to estimate hazard ratios (HRs) (95% confidence interval (CI)) for diagnosis of diabetes and metformin treatment as risk factors for endometrial cancer.Over a mean of 11 years of follow-up, 1241 endometrial cancers developed. In the primary analysis that focused on prevalent diabetes at enrolment, compared with women without diabetes, women with self-reported diabetes, and the subset of women with treated diabetes, had significantly higher risk of endometrial cancer without adjusting for BMI (HR=1.44, 95% CI: 1.13-1.85 for diabetes, HR=1.57, 95% CI: 1.19-2.07 for treated diabetes). However after adjusting for BMI, the associations between diabetes, diabetes treatment, diabetes duration and the risk of endometrial cancer became non-significant. Elevated risk was noted when considering combining diabetes diagnosed at baseline and during follow-up as time-dependent exposure (HR=1.31, 95% CI: 1.08-1.59) even after adjusting for BMI. No significant association was observed between metformin use and endometrial cancer risk.Our results suggest that the relationship observed in previous research between diabetes and endometrial cancer incidence may be largely confounded by body weight, although some modest independent elevated risk remains.
| S-EPMC4183842 | biostudies-other
Project description:Several previous studies have shown that oral microbial disorders may be closely related to the occurrence and development of type 2 diabetes mellitus (T2DM). However, whether the function of oral microorganisms and their metabolites have changed in patients with T2DM who have not suffered from any oral diseases has not been reported. We performed metagenomic analyses and nontargeted metabolic analysis of saliva and supragingival plaque samples from patients with T2DM who have not suffered any oral diseases and normal controls. We found that periodontal pathogens such as Porphyromonas gingivalis and Prevotella melaninogenica were significantly enriched, while the abundances of dental caries pathogens such as Streptococcus mutans and Streptococcus sobrinus were not significantly different in patients with T2DM compared to those in normal controls. Metabolomic analyses showed that the salivary levels of cadaverine and L-(+)-leucine of patients with T2DM were significantly higher than those of normal controls, while the supragingival plaque levels of N-acetyldopamine and 3,4-dimethylbenzoic acid in patients with T2DM were significantly higher than those in the normal controls. Additionally, we identified the types of oral microorganisms related to the changes in the levels of circulating metabolites, and the oral microorganisms were involved in the dysregulation of harmful metabolites such as cadaverine and n, n-dimethylarginine. Overall, our study first described the changes in the composition of oral microorganisms and their metabolites in patients with T2DM who have not suffered any oral diseases, which will provide a direct basis for finding oral biomarkers for early warning of oral diseases in T2DM. IMPORTANCE The incidence of oral diseases in type 2 diabetic patients might increase, and the severity might also be more serious. At present, the relationship between oral microorganisms and type 2 diabetes mellitus (T2DM) has become a hot topic in systemic health research. However, whether the function of oral microorganisms and their metabolites have changed in patients with T2DM who have not suffered from any oral diseases has not been reported. We found that even if the oral condition of T2DM is healthy, their oral microbes and metabolites have changed, thus increasing the risk of periodontal disease. Our study first described the changes in the composition of oral microorganisms and their metabolites in T2DM who have not suffered any oral diseases and revealed the correlation between oral microorganisms and their metabolites, which will provide a direct basis for finding oral biomarkers for early warning of oral diseases in patients with T2DM.
| S-EPMC9927158 | biostudies-literature
Project description:ScopeConsumption of meat has been associated with a higher risk of type 2 diabetes (T2D), but if plasma metabolite profiles associated with these foods reflect this relationship is unknown. The objective is to identify a metabolite signature of consumption of total meat (TM), red meat (RM), processed red meat (PRM), and fish and examine if they are associated with T2D risk.Methods and resultsThe discovery population includes 1833 participants from the PREDIMED trial. The internal validation sample includes 1522 participants with available 1-year follow-up metabolomic data. Associations between metabolites and TM, RM, PRM, and fish are evaluated with elastic net regression. Associations between the profiles and incident T2D are estimated using Cox regressions. The profiles included 72 metabolites for TM, 69 for RM, 74 for PRM, and 66 for fish. After adjusting for T2D risk factors, only profiles of TM (Hazard Ratio (HR): 1.25, 95% CI: 1.06-1.49), RM (HR: 1.27, 95% CI: 1.07-1.52), and PRM (HR: 1.27, 95% CI: 1.07-1.51) are associated with T2D.ConclusionsThe consumption of TM, its subtypes, and fish is associated with different metabolites, some of which have been previously associated with T2D. Scores based on the identified metabolites for TM, RM, and PRM show a significant association with T2D risk.
| S-EPMC9722604 | biostudies-literature
Project description:Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals' future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population.
| S-EPMC4496670 | biostudies-literature
Project description:We investigated data-driven and hypothesis-driven dietary patterns and their association to plasma metabolite profiles and subsequent colorectal cancer (CRC) risk in 680 CRC cases and individually matched controls. Dietary patterns were identified from combined exploratory/confirmatory factor analysis. We assessed association to LC-MS metabolic profiles by random forest regression and to CRC risk by multivariable conditional logistic regression. Principal component analysis was used on metabolite features selected to reflect dietary exposures. Component scores were associated to CRC risk and dietary exposures using partial Spearman correlation. We identified 12 data-driven dietary patterns, of which a breakfast food pattern showed an inverse association with CRC risk (OR per standard deviation increase 0.89, 95% CI 0.80-1.00, p = 0.04). This pattern was also inversely associated with risk of distal colon cancer (0.75, 0.61-0.96, p = 0.01) and was more pronounced in women (0.69, 0.49-0.96, p = 0.03). Associations between meat, fast-food, fruit soup/rice patterns and CRC risk were modified by tumor location in women. Alcohol as well as fruit and vegetables associated with metabolite profiles (Q2 0.22 and 0.26, respectively). One metabolite reflecting alcohol intake associated with increased CRC risk, whereas three metabolites reflecting fiber, wholegrain, and fruit and vegetables associated with decreased CRC risk.
| S-EPMC10817924 | biostudies-literature
Project description:BackgroundEpidemiologic studies suggest phthalate metabolite concentrations are associated with type 2 diabetes. GDM is a strong risk factor for type 2 diabetes. Little is known about phthalates and GDM risk factors (i.e. 1st trimester body mass index (BMI), gestational weight gain (GWG), and 2nd trimester glucose levels).MethodsA total of 350 women participating in Lifecodes pregnancy cohort (Boston, MA), delivered at term and had pregnancy urinary phthalate metabolite concentrations. Nine specific gravity-adjusted urinary phthalate metabolites were evaluated. General linear regression was used to assess associations between quartiles of phthalate metabolites and continuous 1st trimester BMI and late 2nd trimester blood glucose. Linear mixed models were used for total GWG. Multivariable logistic regression was used for phthalate concentrations and categorized GWG and impaired glucose tolerance defined as glucose≥140mg/dL based on a 50-gram glucose load test. Models were adjusted for potential confounders.ResultsThere were no associations between 1st trimester urinary phthalate metabolite concentrations and 1st trimester BMI. Mono-ethyl phthalate concentrations averaged across pregnancy were associated with a 2.17 increased odds of excessive GWG (95% CI: 0.98, 4.79). Second trimester mono-ethyl phthalate was associated with increased odds of impaired glucose tolerance (adj. OR: 7.18; 95% CI: 1.97, 26.15). A summary measure of di-2-ethylhexyl phthalate metabolite concentrations were inversely associated with impaired glucose tolerance (adj. OR: 0.25; adj. 95% CI: 0.08, 0.85).ConclusionsHigher exposure to mono-ethyl phthalate, a metabolite of the parent compound of di-ethyl phthalate, may be associated with excessive GWG and impaired glucose tolerance; higher di-2-ethylhexyl phthalate was associated with reduced odds of impaired glucose tolerance.
| S-EPMC5304919 | biostudies-literature
Project description:BackgroundMetabolomics profiles were consistently associated with type 2 diabetes (T2D) risk, but evidence on long-term metabolite changes and T2D incidence is lacking. We examined the associations of 10-year plasma metabolite changes with subsequent T2D risk.MethodsWe conducted a nested T2D case-control study (n=244 cases, n=244 matched controls) within the Nurses' Health Study. Repeated metabolomics profiling (170 targeted metabolites) was conducted in participant blood specimens from 1989/1990 and 2000/2001, and T2D occurred between 2002 and 2008. We related 10-year metabolite changes (Δ-values) to subsequent T2D risk using conditional logistic models, adjusting for baseline metabolite levels and baseline levels and concurrent changes of BMI, diet quality, physical activity, and smoking status.FindingsThe 10-year changes of thirty-one metabolites were associated with subsequent T2D risk (false discovery rate-adjusted p-values [FDR]<0.05). The top three high T2D risk-associated 10-year changes were (odds ratio [OR] per standard deviation [SD], 95%CI): Δisoleucine (2.72, 1.97-3.79), Δleucine (2.53, 1.86-3.47), and Δvaline (1.93, 1.52-2.44); other high-risk-associated metabolite changes included alanine, tri-/diacylglycerol-fragments, short-chain acylcarnitines, phosphatidylethanolamines, some vitamins, and bile acids (ORs per SD between 1.31and 1.82). The top three low T2D risk-associated 10-year metabolite changes were (OR per SD, 95% CI): ΔN-acetylaspartic acid (0.54, 0.42-0.70), ΔC20:0 lysophosphatidylethanolamine (0.68, 0.56-0.82), and ΔC16:1 sphingomyelin (0.68, 0.56-0.83); 10-year changes of other sphingomyelins, plasmalogens, glutamine, and glycine were also associated with lower subsequent T2D risk (ORs per SD between 0.66 and 0.78).InterpretationRepeated metabolomics profiles reflecting the long-term deterioration of amino acid and lipid metabolism are associated with subsequent risk of T2D.
| S-EPMC8733263 | biostudies-literature