Serum Lipids in Association With Type 2 Diabetes Risk and Prevalence in a Chinese Population

Lysophosphatidylinositols Are Upregulated After Human β-Cell Loss and Potentiate Insulin Release

In this study, we identified new lipid species associated with the loss of pancreatic β-cells triggering diabetes. We performed lipidomics measurements on serum from prediabetic mice lacking β-cell prohibitin-2 (a model of monogenic diabetes) patients without previous history of diabetes but scheduled for pancreaticoduodenectomy resulting in the acute reduction of their β-cell mass (∼50%), and patients with type 2 diabetes (T2D). We found lysophosphatidylinositols (lysoPIs) were the main circulating lipid species altered in prediabetic mice. The changes were confirmed in the patients with acute reduction of their β-cell mass and in those with T2D. Increased lysoPIs significantly correlated with HbA1c (reflecting glycemic control), fasting glycemia, and disposition index, and did not correlate with insulin resistance or obesity in human patients with T2D. INS-1E β-cells as well as pancreatic islets isolated from nondiabetic mice and human donors exposed to exogenous lysoPIs showed potentiated glucose-stimulated and basal insulin secretion. Finally, addition of exogenous lysoPIs partially rescued impaired glucose-stimulated insulin secretion in islets from mice and humans in the diabetic state. Overall, lysoPIs appear to be lipid species upregulated in the prediabetic stage associated with the loss of β-cells and that support the secretory function of the remaining β-cells.

ARTICLE HIGHLIGHTS

Circulating lysophosphatidylinositols (lysoPIs) are increased in situations associated with β-cell loss in mice and humans such as (pre-)diabetes, and hemipancreatectomy. Pancreatic islets isolated from nondiabetic mice and human donors, as well as INS-1E β-cells, exposed to exogenous lysoPIs exhibited potentiated glucose-stimulated and basal insulin secretion. Addition of exogenous lysoPIs partially rescued impaired glucose-stimulated insulin secretion in islets from mice and humans in the diabetic state. LysoPIs appear as lipid species being upregulated already in the prediabetic stage associated with the loss of β-cells and supporting the function of the remaining β-cells.

Gut Microbiota Combined with Serum Metabolomics to Investigate the Hypoglycemic Effect of Actinidia arguta Leaves

Actinidia arguta leaves (AAL) are an excellent source of bioactive components for the food industry and possess many functional properties. However, the hypoglycemic effect and mechanism of AAL remain unclear. The aim of this work was to investigate the potential hypoglycemic effect of AAL and explore its possible mechanism using 16S rRNA sequencing and serum metabolomics in diabetic mice induced by high-fat feeding in combination with streptozotocin injection. A total of 25 flavonoids from AAL were isolated and characterized, and the contents of the extract from the AAL ranged from 0.14 mg/g DW to 8.97 mg/g DW. The compound quercetin (2) had the highest content of 8.97 ± 0.09 mg/g DW, and the compound kaempferol-3-O-(2'-O-D-glucopyl)-β-D-rutinoside (12) had the lowest content of 0.14 ± 0.01 mg/g DW. In vivo experimental studies showed that AAL reduced blood glucose and cholesterol levels, improved insulin sensitivity, and ameliorated oxidative stress and liver and kidney pathological damage. In addition, gut microbiota analysis found that AAL significantly reduced the F/B ratio, enriched the beneficial bacteria Bacteroides and Bifidobacterium, and inhibited the harmful bacteria Lactobacillus and Desulfovibrio, thereby playing an active role in intestinal imbalance. In addition, metabolomics analysis showed that AAL could improve amino acid metabolism and arachidonic acid metabolism, thereby exerting a hypoglycemic effect. This study confirmed that AAL can alleviate type 2 diabetes mellitus (T2DM) by regulating intestinal flora and interfering with related metabolic pathways, providing a scientific basis for its use as a dietary supplement and for further exploration of the mechanism of AAL against T2DM.

Specific triacylglycerol, diacylglycerol, and lyso-phosphatidylcholine species for the prediction of type 2 diabetes: a ~ 16-year prospective study in Chinese

Background

Bioactive lipids play an important role in insulin secretion and sensitivity, contributing to the pathophysiology of type 2 diabetes (T2D). This study aimed to identify novel lipid species associated with incident T2D in a nested case–control study within a long-term prospective Chinese community-based cohort with a median follow-up of ~ 16 years.

Methods

Plasma samples from 196 incident T2D cases and 196 age- and sex-matched non-T2D controls recruited from the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS) were first analyzed using untargeted lipidomics. Potential predictive lipid species selected by the Boruta analysis were then verified by targeted lipidomics. The associations between these lipid species and incident T2D were assessed. Effects of novel lipid species on insulin secretion in mouse islets were investigated.

Results

Boruta analysis identified 16 potential lipid species. After adjustment for body mass index (BMI), triacylglycerol/high-density lipoprotein (TG/HDL) ratio and the presence of prediabetes, triacylglycerol (TG) 12:0_18:2_22:6, TG 16:0_11:1_18:2, TG 49:0, TG 51:1 and diacylglycerol (DG) 18:2_22:6 were independently associated with increased T2D risk, whereas lyso-phosphatidylcholine (LPC) O-16:0, LPC P-16:0, LPC O-18:0 and LPC 18:1 were independently associated with decreased T2D risk. Addition of the identified lipid species to the clinical prediction model, comprised of BMI, TG/HDL ratio and the presence of prediabetes, achieved a 3.8% improvement in the area under the receiver operating characteristics curve (AUROC) (p = 0.0026). Further functional study revealed that, LPC O-16:0 and LPC O-18:0 significantly potentiated glucose induced insulin secretion (GSIS) in a dose-dependent manner, whereas neither DG 18:2_22:6 nor TG 12:0_18:2_22:6 had any effect on GSIS.

Conclusions

Addition of the lipid species substantially improved the prediction of T2D beyond the model based on clinical risk factors. Decreased levels of LPC O-16:0 and LPC O-18:0 may contribute to the development of T2D via reduced insulin secretion.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01677-4.

Change in fatty acid composition of plasma triglyceride caused by a 2 week comprehensive risk management for diabetes: A prospective observational study of type 2 diabetes patients with supercritical fluid chromatography/mass spectrometry-based semi-target lipidomic analysis

AIMS/INTRODUCTION

Hypertriglyceridemia is common in patients with diabetes. Although the fatty acid (FA) composition of triglycerides (TGs) is suggested to be related to the pathology of diabetes and its complications, changes in the fatty acid composition caused by diabetes treatment remain unclear. This study aimed to identify short-term changes in the fatty acid composition of plasma triglycerides after diabetes treatment.

MATERIALS AND METHODS

This study was a sub-analysis of a prospective observational study of patients with type 2 diabetes aged between 20 and 75 years who were hospitalized to improve glycemic control (n = 31). A lipidomic analysis of plasma samples on the 2nd and 16th hospital days was conducted by supercritical fluid chromatography coupled with mass spectrometry.

RESULTS

In total, 104 types of triglycerides with different compositions were identified. Most of them tended to decrease after treatment. In particular, triglycerides with a lower carbon number and fewer double bonds showed a relatively larger reduction. The inclusion of FA 14:0 (myristic acid), as a constituent of triglyceride, was significantly associated with a more than 50%, and statistically significant, reduction (odds ratio 39.0; P < 0.001). The total amount of FA 14:0 as a constituent of triglycerides also decreased significantly, and its rate of decrease was the greatest of all the fatty acid constituents.

CONCLUSIONS

A 2 week comprehensive risk management for diabetes resulted in decreased levels of plasma triglycerides and a change in the fatty acid composition of triglycerides, characterized by a relatively large reduction in FA 14:0 as a constituent of triglycerides.

Saturated fatty acid biomarkers and risk of cardiometabolic diseases: A meta-analysis of prospective studies

Background and aims

Evidence regarding associations of circulating saturated fatty acids (SFAs) with chronic diseases is mixed. The objective of this study was to determine the associations between total or individual SFA biomarkers and the risk of cardiometabolic diseases.

Methods

Four electronic databases were searched from inception to March 2022. Three investigators independently assessed for inclusion and extracted data. Random-effects or fixed-effects models was used to estimate the pooled relative risks (RRs) and corresponding 95% confidence intervals (CIs) for the association of total or individual SFA biomarkers, including even-chain SFAs (e.g., 14:0, myristic acid; 16:0, palmitic acid; 18:0, stearic acid), odd-chain SFAs (e.g., 15:0, pentadecanoic acid; 17:0, margaric acid) and very-long-chain SFAs (VLCSFAs; e.g., 20:0, arachidic acid; 22:0, behenic acid; 24:0, lignoceric acid), with risk of incident type 2 diabetes (T2D), cardiovascular disease [CVD; coronary heart disease (CHD) inclusive of stroke], CHD and stroke.

Results

A total of 49 prospective studies reported in 45 articles were included. Higher concentration of circulating total SFAs was associated with an increasing risk of cardiometabolic diseases, the risk increased significantly by 50% for CVD (95%CI:1.31–1.71), 63% for CHD (95%CI:1.38–1.94), 38% for stroke (95%CI:1.05–1.82), respectively. Similarly, levels of even-chain SFAs were positively associated with higher risk of chronic diseases, with RRs ranging from 1.15 to 1.43. In contrast, the risk of cardiometabolic diseases was reduced with increasing odd-chain SFA levels, with RRs ranging from 0.62 to 0.91. A higher level of VLCSFAs corresponded to 19% reduction in CVD. Further dose-response analysis indicated that each 50% increment in percentage of total SFAs in circulating was associated with an 8% higher risk of T2D (RR: 1.08, 95%CI: 1.02–1.14) and trends toward higher risk of CVD (RR: 1.15, 95%CI: 0.98–1.34). Inverse linear relationships were observed between 17:0 biomarker and T2D or CVD risk.

Conclusion

Our findings support the current recommendations of reducing intake of saturated fat as part of healthy dietary patterns. Further studies are needed to confirm our findings on these SFAs in relation to cardiometabolic outcomes and to elucidate underlying mechanisms.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022329182], identifier [CRD42022329182].

Single Point Insulin Sensitivity Estimator for predicting type 2 diabetes mellitus in obese adolescents

PURPOSE

The prevalence of adolescents with type 2 diabetes mellitus (T2DM) has rapidly increased in Korea over the past few decades with the increase in the number of obese adolescents. The single point insulin sensitivity estimator (SPISE) was recently introduced as a surrogate marker for insulin sensitivity to predict T2DM in adults. We aimed to determine risk factors for T2DM in obese adolescents, including SPISE.

METHODS

This retrospective study included 104 adolescents diagnosed with T2DM at Korea University Hospital between January 2010 and December 2020. We compared clinical and biochemical parameters and the SPISE of normoglycemic overweight and obese individuals with those of prediabetic and diabetic adolescents to determine risk factors for T2DM. Receiver operating characteristic analysis was performed with the Youden index to determine the cutoff point of SPISE.

RESULTS

Frequency of fatty liver and family history of T2DM were significantly higher and SPISE level was significantly lower in patients with T2DM than in normoglycemic overweight/obese and prediabetic adolescents (p<0.01). A family history of T2DM, fatty liver, and SPISE value below the cutoff point (4.49) were identified as significant risk factors for T2DM in multiple logistic regression analysis after controlling for age, sex, and body mass index standard deviation score (p<0.01).

CONCLUSION

Family history of T2DM, fatty liver, and low SPISE (<4.49) are risk factors that can independently affect the occurrence of T2DM in obese adolescents. Among these risk factors, SPISE is a promising marker for predicting adolescent T2DM; careful monitoring of these individuals is needed to prevent progression to T2DM.

Circulating amino acids and acylcarnitines correlated with different CAC score ranges in diabetic postmenopausal women using LC-MS/MS based metabolomics approach

BACKGROUND

Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls.

METHODS

Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls (n = 20), patients with diabetes and without CVD (n = 16), diabetes with low risk of CVD (n = 11), and diabetes with a high risk of CVD (n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC-MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis.

RESULTS

The study included women aged from 50-80 years with 5-30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients.

CONCLUSION

Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).

A Lipid Signature with Perturbed Triacylglycerol Co-Regulation, Identified from Targeted Lipidomics, Predicts Risk for Type 2 Diabetes and Mediates the Risk from Adiposity in Two Prospective Cohorts of Chinese Adults

BACKGROUND

The roles of individual and co-regulated lipid molecular species in the development of type 2 diabetes (T2D) and mediation from metabolic risk factors remain unknown.

METHODS

We conducted profiling of 166 plasma lipid species in 2 nested case-control studies within 2 independent cohorts of Chinese adults, the Dongfeng-Tongji and the Jiangsu non-communicable disease cohorts. After 4.61 (0.15) and 7.57 (1.13) years' follow-up, 1039 and 520 eligible participants developed T2D in these 2 cohorts, respectively, and controls were 1:1 matched to cases by age and sex.

RESULTS

We found 27 lipid species, including 10 novel ones, consistently associated with T2D risk in the 2 cohorts. Differential correlation network analysis revealed significant correlations of triacylglycerol (TAG) 50:3, containing at least one oleyl chain, with 6 TAGs, at least 3 of which contain the palmitoyl chain, all downregulated within cases relative to controls among the 27 lipids in both cohorts, while the networks also both identified the oleyl chain-containing TAG 50:3 as the central hub. We further found that 13 of the 27 lipids consistently mediated the association between adiposity indicators (body mass index, waist circumference, and waist-to-height ratio) and diabetes risk in both cohorts (all P < 0.05; proportion mediated: 20.00%, 17.70%, and 17.71%, and 32.50%, 28.73%, and 33.86%, respectively).

CONCLUSIONS

Our findings suggested notable perturbed co-regulation, inferred from differential correlation networks, between oleyl chain- and palmitoyl chain-containing TAGs before diabetes onset, with the oleyl chain-containing TAG 50:3 at the center, and provided novel etiological insight regarding lipid dysregulation in the progression from adiposity to overt T2D.

Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies

BACKGROUND

Due to the rapidly increasing availability of metabolomics data in prospective studies, an update of the meta evidence on metabolomics and type 2 diabetes risk is warranted.

PURPOSE

To conduct an updated systematic review and meta-analysis of plasma, serum, and urine metabolite markers and incident type 2 diabetes.

DATA SOURCES

We searched PubMed and Embase until 6 March 2021.

STUDY SELECTION

We selected prospective observational studies where investigators used high-throughput techniques to investigate the relationship between plasma, serum, or urine metabolites and incident type 2 diabetes.

DATA EXTRACTION

Baseline metabolites per-SD risk estimates and 95% CIs for incident type 2 diabetes were extracted from all eligible studies.

DATA SYNTHESIS

A total of 61 reports with 71,196 participants and 11,771 type 2 diabetes cases/events were included in the updated review. Meta-analysis was performed for 412 metabolites, of which 123 were statistically significantly associated (false discovery rate-corrected P < 0.05) with type 2 diabetes risk. Higher plasma and serum levels of certain amino acids (branched-chain, aromatic, alanine, glutamate, lysine, and methionine), carbohydrates and energy-related metabolites (mannose, trehalose, and pyruvate), acylcarnitines (C4-DC, C4-OH, C5, C5-OH, and C8:1), the majority of glycerolipids (di- and triacylglycerols), (lyso)phosphatidylethanolamines, and ceramides included in meta-analysis were associated with higher risk of type 2 diabetes (hazard ratio 1.07-2.58). Higher levels of glycine, glutamine, betaine, indolepropionate, and (lyso)phosphatidylcholines were associated with lower type 2 diabetes risk (hazard ratio 0.69-0.90).

LIMITATIONS

Substantial heterogeneity (I2 > 50%, τ2 > 0.1) was observed for some of the metabolites.

CONCLUSIONS

Several plasma and serum metabolites, including amino acids, lipids, and carbohydrates, are associated with type 2 diabetes risk.

Serum lipidomics profiles reveal potential lipid markers for prediabetes and type 2 diabetes in patients from multiple communities

OBJECTIVE

Dyslipidemia is a hallmark of diabetes mellitus (DM). However, specific lipid molecules closely associated with the initiation and progression of diabetes remain unclear. We used a pseudotargeted lipidomics approach to evaluate the complex lipid changes that occurred long before the diagnosis of type 2 diabetes mellitus (T2DM) and to identify novel lipid markers for screening prediabetes mellitus (PreDM) and T2DM in patients from multiple communities.

METHODS

Four hundred and eighty-one subjects consisting of T2DM, three subtypes of PreDM, and normal controls (NC) were enrolled as discovery cohort. Serum lipidomic profiles of 481 subjects were analyzed using an ultrahigh performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ-MS)-based pseudotargeted lipidomics method. The differential lipid molecules were further validated in an independent case-control study consisting of 150 PreDM, 234 T2DM and 94 NC.

RESULTS

Multivariate discriminative analyses show that lipidomics data have considerable potential for identifying lipidome differences among T2DM, subtypes of PreDM and NC. Statistical associations of lipid (sub)species display significant variations in 11 lipid (sub)species levels for T2DM and distinctive differences in 8 lipid (sub)species levels between prediabetic and normoglycemic individuals, with further differences in 8 lipid (sub)species levels among subtypes of PreDM. Adjusted for sex, age and BMI, only two lipid (sub)species of fatty acid (FA) and phosphatidylcholine (PC) were associated at p< 0.05 for PreDM (all) and subtypes of PreDM. The defined lipid markers not only significantly improve the diagnostic accuracy of PreDM and T2DM but also effectively evaluating the risk of developing into each subtype of PreDM and T2DM when addition of age, sex, BMI, and FPG, respectively.

CONCLUSIONS

Our findings improve insights into the lipid metabolic complexity and interindividual variations among subtypes of PreDM and T2DM, beyond the well-known differences in dyslipidemia in clinic.

Beta-adrenergic receptors gene polymorphisms are associated with cardiac contractility and blood pressure variability

Beta-adrenergic receptors (beta-ARs) play a pivotal role in the cardiovascular regulation. In the human heart beta1- and beta2-ARs dominate in atria as well as in ventricle influencing heart rate and myocardial contractility. Some single nucleotide polymorphisms (SNPs) of beta-ARs might influence cardiovascular function. However, the influence of beta-AR genes SNPs on hemodynamic parameters at rest and their reactivity under stress is still not well known. We aimed to explore the associations between four selected beta-ARs gene polymorphisms and selected cardiovascular measures in eighty-seven young healthy subjects. While in beta1-AR polymorphism rs1801252 no significant association was observed, second beta1-AR polymorphism rs1801253 was associated with decreased cardiac output and cardiac index during all phases and with decreased flow time corrected and ejection time index at rest and during mental arithmetics. Polymorphism rs1042713 in beta2-AR was associated with alterations in blood pressure variability at rest and during head-up-tilt, while rs1042714 was associated predominantly with decreased parameters of cardiac contractility at rest and during mental arithmetics. We conclude that complex analysis of various cardiovascular characteristics related to the strength of cardiac contraction and blood pressure variability can reveal subtle differences in cardiovascular sympathetic nervous control associated with beta-ARs polymorphisms.

Effect of Metabolite Levels on Type 2 Diabetes Mellitus and Glycemic Traits: A Mendelian Randomization Study

OBJECTIVE

To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits.

METHODS

Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P < 5 × 10-8) were selected from public genome-wide association studies, and single-nucleotide polymorphisms of outcomes were obtained from the Diabetes Genetics Replication and Meta-analysis consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related Traits Consortium for fasting glucose, insulin, and glycated hemoglobin (HbA1c). The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis.

RESULTS

The β estimates per 1-SD increase of arachidonic acid (AA) level was 0.16 (95% CI, 0.078-0.242; P < 0.001). Genetic predisposition to higher plasma AA levels were associated with higher fasting glucose levels (β 0.10 [95% CI, 0.064-0.134], P < 0.001), higher HbA1c levels (β 0.04 [95% CI, 0.027-0.061]), and lower fasting insulin levels (β -0.025 [95% CI, -0.047 to -0.002], P = 0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have a positive causal effect on glycemic traits.

CONCLUSIONS

Our findings suggest that AA and 2-HBA may have causal associations on T2DM and glycemic traits. This is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM.

Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies

The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.

A longitudinal study of plasma acylcarnitines throughout pregnancy and associations with risk of gestational diabetes mellitus

BACKGROUND & AIMS

Prospective and longitudinal data on the association between acylcarnitines and gestational diabetes (GDM) are lacking. This study aims to prospectively investigate 28 acylcarnitines in relation to subsequent GDM risk.

METHODS

Within the NICHD Fetal Growth Studies-Singleton Cohort, plasma levels of acylcarnitines and cardiometabolic biomarkers were measured at gestational week (GW) 10-14, 15-26, 23-31, and 33-39 among 107 GDM cases and 214 controls.

RESULTS

At GW 10-14, per standard deviation (SD) increased level of C14:1-OH was associated with a 55% increased risk of GDM after adjusting for major risk factors for GDM [OR (95% CI): 1.55 (1.05-2.29)]. At GW 15-26, C4, C8:1 and C16:1-OH were associated with an increased risk of GDM [OR (95% CI) for per SD increase: 1.42 (1.01-2.00), 1.41 (1.02-1.96), and 1.77 (1.10-2.84), respectively]. Whereas increased C10 and C18 were related to lower risk of GDM [OR (95% CI) for per SD increase: 0.74 (0.55-1.00), and 0.69 (0.49-0.97), respectively]. Moreover, we observed correlations of individual acylcarnitine with multiple clinical markers implicated in glucose homeostasis and cardiometabolic function among non-GDM women.

CONCLUSIONS

Our results demonstrate that several plasma acylcarnitine species are differentially associated with GDM risk by chain length. Future studies are warranted to investigate the distinct roles of individual acylcarnitine in glucose homeostasis in pregnancy.

Lipidomics Identified Lyso-Phosphatidylcholine and Phosphatidylethanolamine as Potential Biomarkers for Diagnosis of Laryngeal Cancer

Background

Laryngeal cancer (LaC) remains one of the most common tumors of the respiratory tract with higher incidence in men than in women. The larynx is a small but vital organ on the neck. The dysfunction of the larynx can cause serious health problems such as hoarseness, respiratory distress, and dysphonia. Many lipids (e.g. phospholipid, cholesterol, fatty acid) have been recognized as a crucial role in tumorigenesis. However, the lipid biomarkers are lacking and the lipid molecular pathogenesis of LaC is still unclear.

Methods

This study aims to identify new LaC-related lipid biomarkers used for the diagnosis or early diagnosis of LaC and to uncover their molecular characteristics. Thus, we conducted serum and tissue nontargeted lipidomics study from LaC patients (n = 29) and normal controls (NC) (n = 36) via ultra-high performance liquid chromatography (UHPLC) coupled with high resolution mass spectrometry (HRMS). Multivariate and univariate statistics analyses were used to discriminate LaC patients from NC.

Results

As expected, a lipid panel including LPC (16:0) and PE (18:0p_20:4) was defined to distinguish the LaC patients from healthy individuals with very high diagnosis performance (area under the curve (AUC) value = 1.000, sensitivity value = 1.000, and specificity value = 1.000). In addition, the levels of Cer, CerG1, SM, PC, PC-O, PE, PI, PS, and ChE in the LaC group significantly increased as compared with the NC group. However, the levels of LPC, LPC-O, LPE, LPE-p, and DG in the LaC group significantly deceased when the one was compared with the NC group. Among significantly changed lipid species, lysophospholipids containing a palmitoyl chain or an arachidonic acid acyl chain remarkably decreased and phospholipids including a palmitoyl chain or an arachidonic acid acyl chain increased in the LaC patients.

Conclusion

Our results not only indicate that lipidomics is powerful tool to explore abnormal lipid metabolism for the laC, but suggest that lysophospholipids and phospholipids may serve as potential biomarkers for diagnosis of LaC.

Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis

BACKGROUND

We aimed to explore metabolite biomarkers that could be used to identify pre-diabetes and type 2 diabetes mellitus (T2DM) using systematic review and meta-analysis.

METHODS

Four databases, the Cochrane Library, EMBASE, PubMed and Scopus were selected. A random effect model and a fixed effect model were applied to the results of forest plot analyses to determine the standardized mean difference (SMD) and 95% confidence interval (95% CI) for each metabolite. The SMD for every metabolite was then converted into an odds ratio to create an metabolite biomarker profile.

RESULTS

Twenty-four independent studies reported data from 14,131 healthy individuals and 3499 patients with T2DM, and 14 included studies reported 4844 healthy controls and a total of 2139 pre-diabetes patients. In the serum and plasma of patients with T2DM, compared with the healthy participants, the concentrations of valine, leucine, isoleucine, proline, tyrosine, lysine and glutamate were higher and that of glycine was lower. The concentrations of isoleucine, alanine, proline, glutamate, palmitic acid, 2-aminoadipic acid and lysine were higher and those of glycine, serine, and citrulline were lower in prediabetic patients. Metabolite biomarkers of T2DM and pre-diabetes revealed that the levels of alanine, glutamate and palmitic acid (C16:0) were significantly different in T2DM and pre-diabetes.

CONCLUSIONS

Quantified multiple metabolite biomarkers may reflect the different status of pre-diabetes and T2DM, and could provide an important reference for clinical diagnosis and treatment of pre-diabetes and T2DM.

Underlying dyslipidemia postpartum in women with a recent GDM pregnancy who develop type 2 diabetes

Approximately, 35% of women with Gestational Diabetes (GDM) progress to Type 2 Diabetes (T2D) within 10 years. However, links between GDM and T2D are not well understood. We used a well-characterised GDM prospective cohort of 1035 women following up to 8 years postpartum. Lipidomics profiling covering >1000 lipids was performed on fasting plasma samples from participants 6–9 week postpartum (171 incident T2D vs. 179 controls). We discovered 311 lipids positively and 70 lipids negatively associated with T2D risk. The upregulation of glycerolipid metabolism involving triacylglycerol and diacylglycerol biosynthesis suggested activated lipid storage before diabetes onset. In contrast, decreased sphingomyelines, hexosylceramide and lactosylceramide indicated impaired sphingolipid metabolism. Additionally, a lipid signature was identified to effectively predict future diabetes risk. These findings demonstrate an underlying dyslipidemia during the early postpartum in those GDM women who progress to T2D and suggest endogenous lipogenesis may be a driving force for future diabetes onset.

Integrated biomarker for type 2 diabetes mellitus and impaired fasting glucose based on metabolomics analysis using ultra-high performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry

RATIONALE

The prevalence of type 2 diabetes mellitus (T2DM) is increasing but its early diagnosis in high risk populations remains challenging using only fasting blood glucose (FBG) or hemoglobin A1c measurements. It is, therefore, important to search for an integrated biomarker for early diagnosis by determining metabolites associated with the progression of the disease.

METHODS

We recruited 149 participants (51 T2DM patients, 50 individuals with impaired fasting glucose (IFG) and 48 normal glucose tolerance subjects). Their serum samples were analyzed based on a metabolomics approach using ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS). The changes in metabolites were profiled and evaluated using univariate and multivariate analyses. Furthermore, a biomarker model was established and the potential biomarkers were evaluated using binary logistic regression analysis and receiver operating characteristic analysis with AUC (area under the curve). Pathway analysis of differential metabolites was performed to reveal the important biological information.

RESULTS

Thirty-eight differential metabolites were identified as significantly associated with T2DM patients and 23 differential metabolites with IFG individuals, mainly amino acids, carnitines, and phospholipids. By evaluating 17 potential biomarkers, we defined a novel integrated biomarker consisting of 2-acetolactate, 2-hydroxy-2,4-pentadienoate, L-arabinose and L-glutamine. The AUCs of the integrated biomarker with IFG and T2DM patients were 0.874 and 0.994, respectively, which showed a superior diagnostic performance. The levels of 2-acetolactate and 2-hydroxy-2,4-pentadienoate were strongly positively correlated with FBG, while L-glutamine and L-arabinose were strongly negatively associated with FBG. After pathway analysis, it was suggested that the majority of the influenced metabolic pathways associated with diabetes referred to amino acid metabolism.

CONCLUSIONS

The integrated biomarker could diagnose IFG and T2DM with a superior diagnostic performance. This finding provides support for novel biomarkers in the diagnosis and treatment of diabetes.

Biomarkers of fatty acids and risk of type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies

We aimed to quantify and generate comprehensive evidence on the associations of different fatty acids (FAs) with the risk of type 2 diabetes mellitus (T2DM). PubMed, MEDLINE, and Embase were searched for prospective cohort studies that examined the association between FA biomarkers and the risk of T2DM published before 18 May 2020. Random-effects meta-analyses of the effects of FA concentration on T2DM were performed. Thirty-three studies involving 95,810 adults (19,904 cases) were included. Divergent associations of different types of FAs with type 2 diabetes were observed. The pooled relative risk (RRs) of T2DM comparing the top versus the bottom tertile of saturated FAs (C14:0, C16:0, C18:0, total saturated FAs), monounsaturated FA (C16:1 n-7), polyunsaturated FA (C20:3 n-6, C22:4 n-6), and Δ-6-desaturase activities ranged from 1.19 to 1.80. Interestingly, unlike previous studies, we found a negative correlation between odd-chain saturated FAs (C15:0, C17:0), trans-FAs (trans-C16:1 n-7), total n-6, Δ-5-desaturase activities and risk of T2DM. The pooled RRs of T2DM comparing the top versus the bottom tertile of these FAs ranged from 0.62 to 0.78. No associations with T2DM were observed for the other FAs. Considerable heterogeneity was observed in our study, and no definitive conclusions can be made until further investigation has been carried out.

Contributions of amino acid, acylcarnitine and sphingolipid profiles to type 2 diabetes risk among South-Asian Surinamese and Dutch adults

INTRODUCTION

People of South Asian origin are at high risk of type 2 diabetes (T2D), but the underpinning mechanisms are not fully understood. We determined ethnic differences in acylcarnitine, amino acid and sphingolipid concentrations and determined the associations with T2D.

RESEARCH DESIGN AND METHODS

Associations between these metabolites and incident T2D among Dutch and South-Asian Surinamese were determined in participants from the Healthy Life in an Urban Setting (HELIUS) study (Amsterdam, the Netherlands) using Prentice-weighted Cox regression. The HELIUS study includes 95 incident T2D cases and a representative subcohort of 700 people from a cohort of 5977 participants with a mean follow-up of 4 years.

RESULTS

Concentrations of acylcarnitines were comparable between both ethnic groups. Amino acid and lactosylceramide concentrations were higher among South-Asian Surinamese than Dutch (eg, isoleucine 65.7 (SD 16.3) vs 60.7 (SD 15.6) µmol/L). Ceramide concentrations were lower among South-Asian Surinamese than Dutch (eg, Cer d18:1 8.48 (SD 2.04) vs 9.08 (SD 2.29) µmol/L). Metabolic dysregulation preceded T2D without evidence for a multiplicative interaction by ethnicity. Most amino acids and (dihydro)ceramides were associated with increased risk (eg, Cer d18:1 HR 2.38, 95% CI 1.81 to 3.12) while acylcarnitines, glycine, glutamine and lactosylceramides were associated with decreased risk for T2D (eg, LacCer d18:2 HR 0.56, 95% CI 0.42 to 0.77).

CONCLUSIONS

Overall, these data suggest that the disturbances underlying amino acid and sphingolipid metabolism may be predictive of T2D risk in populations of both South Asian and European background. These observations may be used as starting point to unravel the underlying metabolic disturbances.

Plasma Phospholipids with Long-Chain Polyunsaturated Fatty Acids and Dihydroceramides at the Crossroads of Iron Stores and Insulin Resistance

SCOPE

Iron plays an important role in the pathogenesis of insulin resistance (IR) and type 2 diabetes. Recent studies suggest a role of specific lipids in the induction of IR, but the potential relationships between iron and lipid metabolites in relation to IR have not been explored. Therefore, the aim of the study is to evaluate the association among iron, IR, and the lipidome.

METHODS AND RESULTS

The plasma lipidome, IR, parameters of iron metabolism, and several cytokines and adipokines in 65 overweight/obese participants are measured. Measurements of IR correlate positively with ferritin, a measure of iron storage (r = 0.35, p = 0.005), and negatively with adiponectin (r = -0.30, p = 0.02). The serum ferritin/adiponectin ratio has a stronger association with IR (r = 0.41, p < 0.001). From multivariate analyses adjusted for age, sex, and BMI, several phospholipids containing long chain polyunsaturated fatty acids (PUFA) with 20-22 carbons (phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, and a phosphatidylserine), are positively associated with ferritin and the ferritin/adiponectin ratio. Two dihydroceramides (Cer(18:0/22:0), Cer(18:0/24:0)) and several diglycerides and triglycerides, mainly comprised of C14:0, C16:0, C18:0, C18:1, and C18:2, also have positive correlations with ferritin and the ferritin/adiponectin ratio.

CONCLUSIONS

The positive associations between these lipid species and ferritin or the ferritin/adiponectin ratio suggest a potential crosstalk between iron and lipid metabolism in obesity and IR.

High-Coverage Targeted Lipidomics Reveals Novel Serum Lipid Predictors and Lipid Pathway Dysregulation Antecedent to Type 2 Diabetes Onset in Normoglycemic Chinese Adults

OBJECTIVE

Comprehensive assessment of serum lipidomic aberrations before type 2 diabetes mellitus (T2DM) onset has remained lacking in Han Chinese. We evaluated changes in lipid coregulation antecedent to T2DM and identified novel lipid predictors for T2DM in individuals with normal glucose regulation (NGR).

RESEARCH DESIGN AND METHODS

In the discovery study, we tested 667 baseline serum lipids in subjects with incident diabetes and propensity score-matched control subjects (n = 200) from a prospective cohort comprising 3,821 Chinese adults with NGR. In the validation study, we tested 250 lipids in subjects with incident diabetes and matched control subjects (n = 724) from a pooled validation cohort of 14,651 individuals with NGR covering five geographical regions across China. Differential correlation network analyses revealed perturbed lipid coregulation antecedent to diabetes. The predictive value of a serum lipid panel independent of serum triglycerides and 2-h postload glucose was also evaluated.

RESULTS

At the level of false-discovery rate <0.05, 38 lipids, including triacylglycerols (TAGs), lyso-phosphatidylinositols, phosphatidylcholines, polyunsaturated fatty acid (PUFA)-plasmalogen phosphatidylethanolamines (PUFA-PEps), and cholesteryl esters, were significantly associated with T2DM risk in the discovery and validation cohorts. A preliminary study found most of the lipid predictors were also significantly associated with the risk of prediabetes. Differential correlation network analysis revealed that perturbations in intraclass (i.e., non-PUFA-TAG and PUFA-TAGs) and interclass (i.e., TAGs and PUFA-PEps) lipid coregulation preexisted before diabetes onset. Our lipid panel further improved prediction of incident diabetes over conventional clinical indices.

CONCLUSIONS

These findings revealed novel changes in lipid coregulation existing before diabetes onset and expanded the current panel of serum lipid predictors for T2DM in normoglycemic Chinese individuals.

Circulating Saturated Fatty Acids and Incident Type 2 Diabetes: A Systematic Review and Meta-Analysis

The effect of saturated fatty acids (SFAs) on incident type 2 diabetes (T2D) is controversial and few have systematically appraised the evidence. We conducted a comprehensive search of prospective studies examining these relationships that were published in PubMed, Web of Science, or EMBASE from 21 February 1989 to 21 February 2019. A total of 19 studies were included for systematic review and 10 for meta-analysis. We estimated the summarized relative risk (RR) and 95% confidence interval (95% CI) using a random (if I² > 50%) or a fixed effects model (if I² ≤ 50%). Although the included studies reported inconclusive results, the majority supported a protective effect of odd-chain and an adverse impact of even-chain SFAs. Meta-analysis showed that the per standard deviation (SD) increase in odd-chain SFAs was associated with a reduced risk of incident T2D (C15:0: 0.86, 0.76–0.98; C17:0: 0.76, 0.59–0.97), while a per SD increase in one even-chain SFA was associated with an increased risk of incident T2D (C14:0: 1.13, 1.09–1.18). No associations were found between other SFAs and incident T2D. In conclusion, our findings suggest an overall protective effect of odd-chain SFAs and the inconclusive impact of even- and very-long-chain SFAs on incident T2D.

Serum Amino Acids in Association with Prevalent and Incident Type 2 Diabetes in A Chinese Population

We aimed to simultaneously examine the associations of both essential and non-essential amino acids with both prevalent and incident type 2 diabetes in a Chinese population. A case-control study was nested within the Singapore Chinese Health Study. Participants included 144 cases with prevalent and 160 cases with incident type 2 diabetes and 304 controls. Cases and controls were individually matched on age, sex, and date of blood collection. Baseline serum levels of 9 essential and 10 non-essential amino acids were measured using liquid chromatography tandem mass spectrometry. We identified that five essential (isoleucine, leucine, lysine, phenylalanine, and valine) and five non-essential (alanine, glutamic acid, glutamine, glycine, and tyrosine) amino acids were associated with the prevalence of type 2 diabetes; four essential (isoleucine, leucine, tryptophan, and valine) and two non-essential (glutamine and tyrosine) amino acids were associated with the incidence of type 2 diabetes. Of these, valine and tyrosine independently led to a significant improvement in risk prediction of incident type 2 diabetes. This study demonstrates that both essential and non-essential amino acids were associated with the risk for prevalent and incident type 2 diabetes, and the findings could aid in diabetes risk assessment in this Chinese population.

Serum metabolite profile associated with incident type 2 diabetes in Koreans: findings from the Korean Genome and Epidemiology Study

The identification of metabolic alterations in type 2 diabetes (T2D) is useful for elucidating the pathophysiology of the disease and in classifying high-risk individuals. In this study, we prospectively examined the associations between serum metabolites and T2D risk in a Korean community-based cohort (the Ansan-Ansung cohort). Data were obtained from 1,939 participants with available metabolic profiles and without diabetes, cardiovascular disease, or cancer at baseline. The acylcarnitine, amino acid, amine, and phospholipid levels in fasting serum samples were analyzed by targeted metabolomics. During the 8-year follow-up period, we identified 282 cases of incident T2D. Of all metabolites measured, 22 were significantly associated with T2D risk. Specifically, serum levels of alanine, arginine, isoleucine, proline, tyrosine, valine, hexose and five phosphatidylcholine diacyls were positively associated with T2D risk, whereas lyso-phosphatidylcholine acyl C17:0 and C18:2 and other glycerophospholipids were negatively associated with T2D risk. The associated metabolites were further correlated with T2D-relevant risk factors such as insulin resistance and triglyceride indices. In addition, a healthier diet (as measured by the modified recommended food score) was independently associated with T2D risk. Alterations of metabolites such as amino acids and choline-containing phospholipids appear to be associated with T2D risk in Korean adults.

Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches

PURPOSE OF THE REVIEW

Causality has been demonstrated for few of the many putative risk factors for type 2 diabetes (T2D) emerging from observational epidemiology. Genetic approaches are increasingly being used to infer causality, and in this review, we discuss how genetic discoveries have shaped our understanding of the causal role of factors associated with T2D.

RECENT FINDINGS

Genetic discoveries have led to the identification of novel potential aetiological factors of T2D, including the protective role of peripheral fat storage capacity and specific metabolic pathways, such as the branched-chain amino acid breakdown. Consideration of specific genetic mechanisms contributing to overall lipid levels has suggested that distinct physiological processes influencing lipid levels may influence diabetes risk differentially. Genetic approaches have also been used to investigate the role of T2D and related metabolic traits as causal risk factors for other disease outcomes, such as cancer, but comprehensive studies are lacking. Genome-wide association studies of T2D and metabolic traits coupled with high-throughput molecular phenotyping and in-depth characterisation and follow-up of individual loci have provided better understanding of aetiological factors contributing to T2D.