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

Associations of Palmito-leic Acid and Nervonic Acid Hexosylceramides with Type 2 Diabetes Mellitus in a Prospective Nested Case-control Study Among Chinese Population

OBJECTIVES

We aimed to evaluate the associations of hexosylceramides (HexCers) and their ratio with incident type 2 diabetes mellitus (T2DM) and explore underlying mechanisms.

METHODS

We conducted a nested case-control study using the Suzhou chronic disease cohort including 234 T2DM cases and 468 controls, 1:2 matched on age (±2 y) and sex. HexCer(d18:1/16:1) and HexCer(d18:1/24:1) were measured by targeted UPLC-MS/MS. Multivariable conditional logistic regression was used to estimate the associations of these HexCer species and their ratio with T2DM risk.

RESULTS

After adjustment for potential confounders, compared with the lowest quartile, the highest quartile of HexCer(d18:1/24:1) was positively associated with T2DM risk (OR: 1.91; 95%CI, 1.12, 3.26; P-trend <0.05). The ratio of HexCer(d18:1/24:1) to HexCer(d18:1/16:1) showed a positive association with T2DM risk (OR: 1.89; 95%CI, 1.13, 3.18; P-trend <0.05). On the natural log scale, each SD increases in HexCer(d18:1/24:1) and its ratio to HexCer(d18:1/16:1) increased by 29% and 30%, respectively. No significant association for HexCer(d18:1/16:1) was found. Additive value of HexCer(d18:1/24:1) or HexCer(d18:1/24:1)/HexCer(d18:1/16:1) ratio for prediction of T2DM above traditional risk factors.

CONCLUSIONS

HexCer(d18:1/24:1) and its ratio to HexCer(d18:1/16:1) are positively associated with incident T2DM in a community-based Chinese population. Future studies are warranted to confirm our findings.

Integrative metabolomics and genomics reveal molecular signatures for type 2 diabetes and its cardiovascular complications

BACKGROUND

Metabolites are pivotal in the biological process underlying type 2 diabetes (T2D) and its cardiovascular complications. Nevertheless, their contributions to these diseases have not been comprehensively evaluated, particularly in East Asian ancestry. This study aims to elucidate the metabolic underpinnings of T2D and its cardiovascular complications and leverage multi-omics integration to uncover the molecular pathways involved.

METHOD

This study included 1180 Chinese participants from the Zhejiang Metabolic Syndrome Cohort (ZMSC). A total of 1912 metabolites were profiled using high-coverage widely targeted and non-targeted metabolic techniques. Multivariable logistic regression models and orthogonal partial least squares discriminant analysis were used to identify T2D-related metabolites. A metabolome-wide genome-wide association study (GWAS) in ZMSC, followed by two-sample Mendelian randomization (MR) analyses, was conducted to explore potential causal metabolite-T2D associations. To enhance cross-ancestry generalizability, MR analyses were conducted in European ancestry to explore the potential causal effects of serum metabolites on T2D and its cardiovascular complications. Furthermore, multi-omics evidence was integrated to explore the underlying molecular mechanisms.

RESULTS

We identified six metabolites associated with T2D in Chinese, supported by metabolome analysis and genetic-informed causal inference. These included two potential protective factors (PC [O-16:0/0:0] and its derivative LPC [O-16:0]) and four potential risk factors ([R]-2-hydroxybutyric acid, 2-methyllactic acid, eplerenone, and rauwolscine). Cross-ancestry metabolome-wide analysis further revealed four shared potential causal metabolites, highlighting the potential protective role of creatine for T2D. Through multi-omics integration, we revealed a potential regulatory path initialized by a genetic variant near CPS1 (coding for a urea cycle-related mitochondrial enzyme) influencing serum creatine levels and subsequently modulating the risk of T2D. MR analyses further demonstrated that nine urea cycle-related metabolites significantly influence cardiovascular complications of T2D.

CONCLUSION

Our study provides novel insights into the metabolic underpinnings of T2D and its cardiovascular complications, emphasizing the role of urea cycle-related metabolites in disease risk and progression. These findings advance our understanding of circulating metabolites in the etiology of T2D, offering potential biomarkers and therapeutic targets for future research.

RESEARCH INSIGHTS

WHAT IS CURRENTLY KNOWN ABOUT THIS TOPIC?: Metabolites are crucial for understanding diabetes biology.Multi-omics integration aids in revealing complex mechanisms. WHAT IS THE KEY RESEARCH QUESTION?: How do serum metabolites affect diabetes and its cardiovascular outcomes? WHAT IS NEW?: Novel diabetes-related metabolites identified in Chinese populations.Consistent metabolites associated with diabetes and glycemic traits in East Asians and Europeans.Emphasizing the role of urea cycle pathway in cardiometabolic disease. HOW MIGHT THIS STUDY INFLUENCE CLINICAL PRACTICE?: Findings could guide diabetes prevention and personalized management strategies.

Multi-tissue metabolomics reveal mtDNA- and diet-specific metabolite profiles in a mouse model of cardiometabolic disease

RATIONALE

Excess consumption of sugar- and fat-rich foods has heightened the prevalence of cardiometabolic disease, which remains a driver of cardiovascular disease- and type II diabetes-related mortality globally. Skeletal muscle insulin resistance is an early feature of cardiometabolic disease and is a precursor to diabetes. Insulin resistance risk varies with self-reported race, whereby African-Americans have a greater risk of diabetes development relative to their White counterparts. Self-reported race is strongly associated with mitochondrial DNA (mtDNA) haplogroups, and previous reports have noted marked differences in bioenergetic and metabolic parameters in cells belonging to distinct mtDNA haplogroups, but the mechanism of these associations remains unknown. Additionally, distinguishing nuclear DNA (nDNA) and mtDNA contributions to cardiometabolic disease remains challenging in humans. The Mitochondrial-Nuclear eXchange (MNX) mouse model enables in vivo preclinical investigation of the role of mtDNA in cardiometabolic disease development, and has been implemented in studies of insulin resistance, fatty liver disease, and obesity in previous reports.

METHODS

Six-week-old male C57nDNA:C57mtDNA and C3HnDNA:C3HmtDNA wild-type mice, and C57nDNA:C3HmtDNA and C3HnDNA:C57mtDNA MNX mice, were fed sucrose-matched high-fat (45% kcal fat) or control diet (10% kcal fat) until 12 weeks of age (n = 5/group). Mice were weighed weekly and total body fat was collected at euthanasia. Gastrocnemius skeletal muscle and plasma metabolomes were characterized using untargeted dual-chromatography mass spectrometry; both hydrophilic interaction liquid chromatography (HILIC) and C18 columns were used, in positive- and negative-ion modes, respectively.

RESULTS

Comparative analyses between nDNA-matched wild-type and MNX strains demonstrated significantly increased body fat percentage in mice possessing C57mtDNA regardless of nDNA background. High-fat diet in mice possessing C57mtDNA was associated with differential abundance of phosphatidylcholines, lysophosphatidylcholines, phosphatidylethanolamines, and glucose. Conversely, high-fat diet in mice possessing C3HmtDNA was associated with differential abundance of phosphatidylcholines, cardiolipins, and alanine. Glycerophospholipid metabolism and beta-alanine signaling pathways were enriched in skeletal muscle and plasma, indicating mtDNA-directed priming of mitochondria towards oxidative stress and increased fatty acid oxidation in C57nDNA:C57mtDNA wild-type and C3HnDNA:C57mtDNA MNX mice, relative to their nDNA-matched counterparts. In mtDNA-matched mice, C57mtDNA was associated with metabolite co-expression related to the pentose phosphate pathway and sugar-related metabolism; C3HmtDNA was associated with branched chain amino acid metabolite co-expression.

CONCLUSIONS

These results reveal novel nDNA-mtDNA interactions that drive significant changes in metabolite levels. Alterations to key metabolites involved in mitochondrial bioenergetic dysfunction and electron transport chain activity are implicated in elevated beta-oxidation during high-fat diet feeding; abnormally elevated rates of beta-oxidation may be a key driver of insulin resistance. The results reported here support the hypothesis that mtDNA influences cardiometabolic disease-susceptibility by modulating mitochondrial function and metabolic pathways.

Altered liver lipidome markedly overlaps with human plasma lipids at diabetes risk and reveals adipose-liver interaction

Present study explores the role of liver lipidome in driving T2D-associated metabolic changes. Elevated liver triacylglycerols, reduced PUFAs, and 86 differentially abundant lipid species were identified in diabetes-prone mice. Of these altered lipid species, 82 markedly overlap with human plasma lipids associated with T2D/CVD risk. Pathway enrichment highlighted sphingolipid metabolism, however, only five of all genes involved in the pathway were differentially expressed in the liver. Interestingly, overlap with adipose tissue transcriptome was much higher (57 genes), pointing toward an active adipose-liver interaction. Next, the integration of liver lipidome and transcriptome identified strongly correlated lipid-gene networks highlighting ceramide [Cer(22:0)], dihydroceramide(24:1), and triacylglycerol(58:6) playing a central role in transcriptional regulation. Putative molecular targets of Cer(22:0) were altered (Cyp3a44, Tgf-β1) in primary mouse hepatocytes treated with Cer(22:0). Early alteration of liver lipidome markedly depends on adipose tissue expression pattern and provides substantial evidence linking early liver lipidome alterations and risk of T2D.

Plasma Lipid Metabolites, Clinical Glycemic Predictors, and Incident Type 2 Diabetes

OBJECTIVE

Plasma metabolite profiling has uncovered several nonglycemic markers of incident type 2 diabetes (T2D). We investigated whether such biomarkers provide information about specific aspects of T2D etiology, such as impaired fasting glucose and impaired glucose tolerance, and whether their association with T2D risk varies by race.

RESEARCH DESIGN AND METHODS

Untargeted plasma metabolite profiling was performed of participants in the FINRISK 2002 cohort (n = 7,564). Cox regression modeling was conducted to identify metabolites associated with incident T2D during 14 years of follow-up. Metabolites were clustered into pathways using Gaussian graphical modeling. Clusters enriched for T2D biomarkers were further examined for covariation with fasting plasma glucose (FPG), 2-h postchallenge plasma glucose (2hPG), HbA1c, or fasting insulin. Validation analyses and tests of interaction with race were performed in the Atherosclerosis Risk in Communities (ARIC) study.

RESULTS

Two clusters of metabolites, representing diacylglycerols (DAGs) and phosphatidylcholines (PCs), contained the largest number of metabolite associations with incident T2D. DAGs associated with increased T2D incidence (hazard ratio [HR] 1.22; 95% CI 1.14-1.30) independent of FPG, HbA1c, and fasting insulin, but not 2hPG. PCs were inversely associated with T2D risk (HR 0.78; 95% CI 0.71-0.85) independent of FPG, 2hPG, HbA1c, and fasting insulin. No significant interaction between DAGs or PCs and race was observed.

CONCLUSIONS

Fasting DAGs may capture information regarding T2D risk similar to that represented by 2hPG; PCs may capture aspects of T2D etiology that differ from those represented by conventional biomarkers. The direction of effect and strength of DAG and PC associations with incident T2D are similar across European and African Americans.

Ten metabolites-based algorithm predicts the future development of type 2 diabetes in Chinese

INTRODUCTION

Type 2 diabetes (T2D) is a heterogeneous metabolic disease with large variations in the relative contributions of insulin resistance and β-cell dysfunction across different glucose tolerance subgroups and ethnicities. A more precise yet feasible approach to categorize risk preceding T2D onset is urgently needed. This study aimed to identify potential metabolic biomarkers that could contribute to the development of T2D and investigate whether their impact on T2D is mediated through insulin resistance and β-cell dysfunction.

METHODS

A non-targeted metabolomic analysis was performed in plasma samples of 196 incident T2D cases and 196 age- and sex-matched non-T2D controls recruited from a long-term prospective Chinese community-based cohort with a follow-up period of ∼ 16 years.

RESULTS

Metabolic profiles revealed profound perturbation of metabolomes before T2D onset. Overall metabolic shifts were strongly associated with insulin resistance rather than β-cell dysfunction. In addition, 188 out of the 578 annotated metabolites were associated with insulin resistance. Bi-directional mediation analysis revealed putative causal relationships among the metabolites, insulin resistance and T2D risk. We built a machine-learning based prediction model, integrating the conventional clinical risk factors (age, BMI, TyG index and 2hG) and 10 metabolites (acetyl-tryptophan, kynurenine, γ-glutamyl-phenylalanine, DG(18:2/22:6), DG(38:7), LPI(18:2), LPC(P-16:0), LPC(P-18:1), LPC(P-20:0) and LPE(P-20:0)) (AUROC = 0.894, 5.6% improvement comparing to the conventional clinical risk model), that successfully predicts the development of T2D.

CONCLUSIONS

Our findings support the notion that the metabolic changes resulting from insulin resistance, rather than β-cell dysfunction, are the primary drivers of T2D in Chinese adults. Metabolomes as a valuable phenotype hold potential clinical utility in the prediction of T2D.

Essential trace element and phosphatidylcholine remodeling: Implications for body composition and insulin resistance

BACKGROUND

Recent studies indicated that bioactive lipids of phosphatidylcholines (PCs) and lysophosphatidylcholines (LysoPCs) predict unhealthy metabolic phenotypes, but results remain inconsistent. To fill this knowledge gap, we investigated whether essential trace elements affect PC-Lyso PC remodeling pathways and the risk of insulin resistance (IR).

METHODS

Anthropometric and blood biochemical data (glucose, insulin, and lipoprotein-associated phospholipase A2 (Lp-PLA2)) were obtained from 99 adults. Blood essential/probably essential trace elements and lipid metabolites were respectively measured by inductively coupled plasma mass spectrometry (ICP-MS), and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS).

RESULT AND CONCLUSION

Except for LysoPC (O-18:0/0:0), an inverse V shape was observed between body weight and PC and LysoPC species. A Pearson correlation analysis showed that essential/probably-essential metals (Se, Cu, and Ni: r=-0.4∼-0.7) were negatively correlated with PC metabolites but positively correlated with LysoPC (O-18:0/0:0) (Se, Cu, and Ni: r=0.85-0.64). Quantile-g computation showed that one quantile increase in essential metals was associated with a 2.16-fold increase in serum Lp-PLA2 (β=2.16 (95 % confidence interval (CI): 0.34, 3.98), p=0.023), which are key enzymes involved in PC/Lyso PC metabolism. An interactive analysis showed that compared to those with the lowest levels (reference), individuals with the highest levels of serum PCs (pooled, M2) and the lowest essential/probably essential metals (M1) were associated with a healthier body composition and had a 76 % decreased risk of IR (odds ratio (OR)=0.24 (95 % CI: 0.06, 0.90), p<0.05). In contrast, increased exposure to LysoPC(O-18:0/0:0) (M2) and essential metals (M2) exhibited an 8.22-times highest risk of IR (OR= 8.22 (2.07, 32.57), p<0.05) as well as an altered body composition. In conclusion, overexposure to essential/probably essential trace elements may promote an unhealthy body weight and IR through modulating PC/LysoPC remodeling pathways.

Pharmacokinetics of soy-derived lysophosphatidylcholine compared with that of glycerophosphocholine: a randomized controlled trial

Lysophosphatidylcholine (LPC) is present in various foods and contains a choline moiety such as in glycerophosphocholine (GPC). However, the potential of LPC as a choline source remains unclear. This study investigated the single-dose pharmacokinetics of 480 mg soy-derived LPC in 12 healthy men compared with that of either soy oil with the same lipid amount (placebo) or GPC with the same choline amount. Both LPC and GPC supplementation increased plasma choline, serum phospholipid, and serum triglyceride concentrations, but neither of them significantly elevated plasma trimethylamine N-oxide concentration. In addition, although the intake of LPC slightly increased plasma LPC16:0, LPC18:2, and total LPC concentrations, their concentrations remained within physiological ranges. No adverse events were attributed to the LPC supplementation. To the best of our knowledge, this study is the first to compare LPC and GPC pharmacokinetics in humans and shows that LPC can be a source of choline.

Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes

PURPOSE

The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR.

METHODS

A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry.

RESULTS

The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients.

CONCLUSION

Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.

Decreased in n-3 DHA enriched triacylglycerol in small extracellular vesicles of diabetic patients with cardiac dysfunction

PURPOSE

Diabetic cardiomyopathy is the leading cause of death in diabetic patients, and the mechanism by which factors other than hyperglycemia contribute to the development of diabetic cardiomyopathy is unknown. Serum small extracellular vesicles (sEVs) carry bioactive proteins or nuclei, which enter into remote tissues and modulate cell functions. However, in diabetic conditions, the changes of lipids carried by sEVs has not been identified. Our study aims to explore the changes of lipids in sEVs in diabetic patients with cardiovascular disease, we hope to provide new ideas for understanding the role of lipid metabolism in the pathogenesis of diabetic cardiomyopathy.

METHODS

SEVs samples derived from serum of health controls (Ctrl), diabetic patients without cardiovascular diseases (DM), and diabetic patients with cardiovascular diseases (DM-CAD) were used for lipidomics analysis. Because AC16 cells are also treated with those sEVs to confirm the entrance of cells and effects on insulin sensitivity, a lipidomics analysis on cells was also performed.

RESULTS AND CONCLUSIONS

In this study, we found that docosahexaenoic acid (DHA)-triacylglycerides of sEVs from serums of DM-CAD patients decreased significantly, and those sEVs could enter into AC16 cells and diminish insulin sensitivity. In addition, DHA-triacylglycerides were also decreased in cells treated with sEVs from DM-CAD. Therefore, DHA-triacylglycerides carried by sEVs may mediate intercellular signaling and be associated with the incidence of diabetic cardiovascular complications.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.