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

Longitudinal Lipidomic Profile of Subclinical Peripheral Artery Disease in American Indians: The Strong Heart Family Study

Introduction

Peripheral artery disease (PAD) and dyslipidemia are both independent predictors of cardiovascular disease, but the association between individual lipid species and subclinical PAD, assessed by ankle-brachial index (ABI), is lacking in large-scale longitudinal studies.

Methods

We used liquid chromatography-mass spectrometry to repeatedly measure 1,542 lipid species from 1,886 American Indian adults attending 2 clinical examinations (mean ~5 years apart) in the Strong Heart Family Study. We used generalized estimating equation models to identify baseline lipid species associated with change in ABI and the Cox frailty regression to examine whether lipids associated with change in ABI were also associated with incident coronary heart disease (CHD). We also examined the longitudinal association between change in lipid species and change in ABI and the cross-sectional association of individual lipids with ABI. All models were adjusted for age, sex, body mass index, smoking, alcohol use, hypertension, estimated glomerular filtration rate, diabetes, and lipid-lowering medication.

Results

Baseline levels of 120 lipid species, including glycerophospholipids, glycerolipids, fatty acids, and sphingomyelins, were associated with change in ABI. Among these, higher baseline levels of 3 known lipids (phosphatidylinositol[16:0/20:4], triacylglycerol[48:2], triacylglycerol[55:1]) were associated with a lower risk of CHD (hazard ratios [95% CIs] ranged from 0.67 [0.46-0.99] to 0.76 [0.58-0.99]), while cholesterol was associated with a higher risk of CHD (hazard ratio [95% CI] = 1.37 [1.00-1.87]). Longitudinal changes in 32 lipids were significantly associated with change in ABI during 5-year follow-up. Plasma levels of glycerophospholipids, triacylglycerols, and glycosylceramides were significantly associated with ABI in the cross-sectional analysis.

Conclusion

Altered plasma lipidome is significantly associated with subclinical PAD in American Indians beyond traditional risk factors. If validated, the identified lipid species may serve as novel biomarkers for PAD in this high-risk but understudied population.

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.

Kidney function-related protection of polysaccharides from red kidney bean and small black soybean via urine metabolomics in type 2 diabetic rats

Diabetic nephropathy is a significant microvascular complication of diabetes mellitus. Crude polysaccharides extracted from red kidney beans and small black soybeans (RK, SB) have demonstrated promising antidiabetic effects in type 2 diabetic rats. This study evaluated the protective effects of RK and SB on kidney function in diabetic rats by examining kidney markers and urine metabolism. It also investigated the impact of pure polysaccharides (RKP, SBP) to pinpoint the active component of RK and SB. Findings indicated that RK and SB influenced kidney function by affecting the kidney index and key urine metabolites, like citric acid and cis-aconitic acid, linked to the TCA cycle and phenylalanine metabolism. Furthermore, a higher dose (400 mg/kg) of RKP and SBP was more effective in treating kidney damage in diabetic models than the optimal 200 mg/kg dose of RK and SB. This was shown by better regulation of urea nitrogen and uric acid levels, improved kidney tissue health seen in HE staining, and fewer red-stained lipid droplets in the kidney, as indicated by Oil Red O staining. Overall, this study provided additional evidence to support RKP and SBP as a functional ingredients production in the food industry.

A specific metabolomic and lipidomic signature reveals the postpartum resolution of gestational diabetes mellitus or its evolution to type 2 diabetes in rat

Gestational diabetes mellitus (GDM) represents a major public health concern due to adverse maternal postpartum and long-term outcomes. Current strategies to manage GDM fail to reduce the maternal risk to develop later impaired glucose tolerance (IGT) and type 2 diabetes (T2D). In a rodent model of diet-induced GDM without obesity, we explored the perinatal metabolic adaptations in dams with gestational IGT followed by either persistent or resolved postpartum IGT. Female Sprague-Dawley rats were fed a high-fat high-sucrose (HFHS) or a chow [control group (CTL)] diet, 1 wk before mating and throughout gestation (G). Following parturition, HFHS dams were randomized to two subgroups: one switched to a chow diet and the other one maintained on an HFHS diet throughout lactation (L). Oral glucose tolerance tests (OGTTs) were performed, and plasma metabolome-lipidome were characterized at G12 and L12. We found that 1) in GDM-pregnant dams, IGT was associated with incomplete fatty acid oxidation (FAO), enhanced gluconeogenesis, altered insulin signaling, and oxidative stress; 2) improved glucose tolerance postpartum seemed to restore complete FAO along with elevation of nervonic acid-containing sphingomyelins, assumed to impart β-cell protection; and 3) persistence of IGT after delivery was associated with metabolites known to predict the early onset of insulin and leptin resistance, with maintained liver dysfunction. Our findings shed light on the impact of postpartum IGT evolution on maternal metabolic outcome after an episode of GDM. They suggest innovative strategies, implemented shortly after delivery and targeted on these biomarkers, should be explored to curb or delay the transition from GDM to T2D in these mothers.NEW & NOTEWORTHY Specific metabolomic/lipidomic features are associated with GDM postpartum outcomes. GDM-pregnant dams exhibit partial fatty acid oxidation and boosted gluconeogenesis. Resolution of postpartum IGT relies on nervonic acid-sphingomyelin, a β-cell protector. Postpartum IGT persistence suggests muscle insulin resistance and liver dysfunction.

Differential lipids in euthyroid pregnant women with positive TPOAb and its correlation with clinical parameters

Introduction

Pregnant women with subclinical hypothyroidism or clinical hypothyroidism often exhibit lipid metabolism disorders and are correlated with adverse pregnant outcomes. It was suggested that isolated positive thyroid peroxidase antibody (TPOAb) served as a risk factor for adverse outcomes. However, little was known about the lipid metabolism profile in pregnant women with isolated positive TPOAb. The purpose of this prospective observational study was to investigate the expression of lipid profiles among euthyroid pregnant women with positive TPOAb during there early pregnancy and to analyze their correlation with thyroid function.

Methods

Non-targeted liquid chromatography-mass spectrometry (LC-MS) technology was used to perform lipidomics analysis on serum samples collected during early pregnancy from pregnant women who with isolated positive TPOAb and those in the healthy control group. Partial least squares-discriminant analysis (PLS-DA), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis, and correlation analysis were conducted to explore differential lipid molecules and their associations with clinical parameters.

Results

A total of 90 pregnant women in the first trimester were enrolled in the analysis: 46 were TPOAb-positive euthyroid pregnant women, and 44 were healthy pregnant women. A total of 1238 lipid molecules were identified, and 202 differential lipid molecules were screened between the two groups. KEGG pathway enrichment analysis revealed that the differentially expressed lipids participate in several pathways. Correlation analysis showed LPC(20:4), LPC(18:0), LPC(22:4), LPC(22:5), LPC(18:1), PC(20:1/20:4) were both positively correlated with TPOAb titers and sCD40L. LPC(20:0) was positively correlated with the level of remnant cholesterol (RC) and PC(20:1/20:4) was negatively correlated with RC.

Discussion

The lipid profile of isolated TPOAb-positive euthyroid pregnant women was significantly different from that of healthy pregnant women and involved in several pathways. The pathophysiological role of altered lipid molecules should be further investigated since they might be potential biomarkers for adverse pregnancy outcome in pregnant women with isolated positive TPOAb.

Effects of Hypertriglyceridemia With or Without NEFA Elevation on β-cell Function and Insulin Clearance and Sensitivity

CONTEXT

Hypertriglyceridemia is a risk factor for developing type 2 diabetes (T2D) and might contribute to its pathogenesis either directly or through elevation of nonesterified fatty acids (NEFAs).

OBJECTIVE

This study aimed at comparing the glucometabolic effects of acute hypertriglyceridemia alone or combined with NEFA elevation in subjects without diabetes.

METHODS

Twenty-two healthy lean volunteers underwent 5-hour intravenous infusions of either saline or Intralipid, without (n = 12) or with heparin (I + H; n = 10) to activate the release of NEFAs. Oral glucose tolerance tests (OGTTs) were performed during the last 3 hours of infusion. Insulin sensitivity, insulin secretion rate (ISR), model-derived β-cell function, and insulin clearance were measured after 2 hours of lipid infusion and during the OGTTs.

RESULTS

In fasting conditions, both lipid infusions increased plasma insulin and ISR and reduced insulin clearance without affecting plasma glucose and insulin sensitivity. These effects on insulin and ISR were more pronounced for I + H than Intralipid alone. During the OGTT, the lipid infusions markedly impaired glucose tolerance, increased plasma insulin and ISR, and decreased insulin sensitivity and clearance, without significant group differences. Intralipid alone inhibited glucose-stimulated insulin secretion (ie, β-cell glucose sensitivity) and increased β-cell potentiation, whereas I + H had neutral effects on these β-cell functions.

CONCLUSION

In healthy nonobese subjects, mild acute hypertriglyceridemia directly reduces glucose tolerance and insulin sensitivity and clearance, and has selective and opposite effects on β-cell function that are neutralized by NEFAs. These findings provide new insight into plausible biological signals that generate and sustain insulin resistance and chronic hyperinsulinemia in the development of T2D.

Molecular pathological characteristics and mechanisms of the liver in metabolic disease-susceptible transgenic pigs

AIMS

This study aimed to explore the molecular pathological mechanisms of the liver in metabolic disease-susceptible transgenic pigs via multiomics analysis.

MATERIALS AND METHODS

The triple-transgenic (PNPLA3I148M-GIPRdn-hIAPP) pig model (TG pig) was successfully constructed in our laboratory via the CRISPR/Cas9 technique previously described. Wild-type (WT) pigs and TG pigs after 2 or 12 months of high-fat and high-sucrose diet (HFHSD) induction (WT2, TG2, WT12, and TG12 groups, respectively) were used as materials. The transcriptome, metabolome, and lipidome were used to investigate the molecular mechanisms of the liver in pigs.

KEY FINDINGS

The TG2 pigs presented mild metaflammation and insulin resistance (IR) which was similar to WT12 pigs. Compared with the other three groups, the TG12 pigs presented severe hepatocyte ballooning, fat deposition, and portal area fibrosis. The transcriptome data suggested that the TG2 pigs presented upregulated gene expression in the extracellular matrix (ECM). The TG12 pigs presented more severe metaflammation and exhibited imbalanced glycolipid metabolism. Interestingly, genes such as ETNPPL, GABBR2, and BMP8B might be key regulatory targets for liver injury. The metabolome and lipidome suggested that long-chain polyunsaturated fatty acids (LCPUFAs) and phospholipids with corresponding LCPUFAs were remodelled. Importantly, bis(monoacylglycerol) phosphates (BMPs) and sulfatides (SLs) could be the key regulatory metabolites in liver injury.

SIGNIFICANCE

ETNPPL, GABBR2, and BMP8B might be potential therapeutic targets for liver injury. BMPs and SLs might be biomarkers for the diagnosis and treatment of liver diseases.

Serum Medium-Chain Fatty Acids and the Risk of Incident Diabetes: Findings From the 4C Study

CONTEXT

Emerging studies have revealed associations between dietary medium-chain fatty acids (MCFAs) and glucose homeostasis. However, the relationship between serum MCFAs and the incidence of diabetes, and potential interactions with genetic predisposition, remains unclear in prospective cohort studies.

OBJECTIVE

This work aimed to investigate associations and genetic susceptibility between serum MCFAs and diabetes risk.

METHODS

We investigated baseline serum MCFAs (n = 5) in a nested case-control study comprising incident diabetes cases (n = 1707) and matched normoglycemic control individuals (n = 1707) from the China Cardiometabolic Disease and Cancer Cohort Study. Associations between MCFAs and type 2 diabetes mellitus (T2DM) were examined, both overall and stratified by diabetes genetic susceptibility. Genetic risk scores (GRS) were calculated based on 86 T2DM-associated genetic variants.

RESULTS

In the fully adjusted conditional logistic regression model, serum octanoic acid and nonanoic acid exhibited inverse dose-response relationships with diabetes risk, showing odds ratios (95% CI) of 0.90 (0.82-0.98) and 0.84 (0.74-0.95), respectively. Subgroup analysis demonstrated that inverse associations between MCFAs and incident diabetes were more pronounced among individuals with physical inactivity (Pinteraction = .042, .034, and .037, for octanoic, nonanoic and decanoic acid, respectively). Moreover, inverse associations of octanoic acid with diabetes risk were notably enhanced among individuals with high genetic risk compared to those with low genetic risk. Statistically significant interactions were observed between octanoic acid and GRS on T2DM risk (Pinteraction = .003).

CONCLUSION

These findings provide evidence supporting inverse associations between serum MCFAs and T2DM risk, and reveal potential interplay between genetic susceptibility and circulating octanoic acid in modulating diabetes risk.

Lipidomics identified novel cholesterol-independent predictors for risk of incident coronary heart disease: Mediation of risk from diabetes and aggravation of risk by ambient air pollution

INTRODUCTION

Previous lipidomics studies have identified various lipid predictors for cardiovascular risk, however, with limited predictive increment, sometimes using too many predictor variables at the expense of practical efficiency.

OBJECTIVES

To search for lipid predictors of future coronary heart disease (CHD) with stronger predictive power and efficiency to guide primary intervention.

METHODS

We conducted a prospective nested case-control study involving 1,621 incident CHD cases and 1:1 matched controls. Lipid profiling of 161 lipid species for baseline fasting plasma was performed by liquid chromatography-mass spectrometry.

RESULTS

In search of CHD predictors, seven lipids were selected by elastic-net regression during over 90% of 1000 cross-validation repetitions, and the derived composite lipid score showed an adjusted odds ratio of 3.75 (95% confidence interval: 3.15, 4.46) per standard deviation increase. Addition of the lipid score into traditional risk model increased c-statistic to 0.736 by an increment of 0.077 (0.063, 0.092). From the seven lipids, we found mediation of CHD risk from baseline diabetes through sphingomyelin (SM) 41:1b with a considerable mediation proportion of 36.97% (P < 0.05). We further found that the positive associations of phosphatidylcholine (PC) 36:0a, SM 41:1b, lysophosphatidylcholine (LPC) 18:0 and LPC 20:3 were more pronounced among participants with higher exposure to fine particulate matter or its certain components, also to ozone for LPC 18:0 and LPC 20:3, while the negative association of cholesteryl ester (CE) 18:2 was attenuated with higher black carbon exposure (P < 0.05).

CONCLUSION

We identified seven lipid species with greatest predictive increment so-far achieved for incident CHD, and also found novel biomarkers for CHD risk stratification among individuals with diabetes or heavy air pollution exposure.

m6A-driven NAT10 translation facilitates fatty acid metabolic rewiring to suppress ferroptosis and promote ovarian tumorigenesis through enhancing ACOT7 mRNA acetylation

RNA epigenetic modifications have been implicated in cancer progression. However, the interplay between distinct RNA modifications and its role in cancer metabolism remain largely unexplored. Our study demonstrates that N-acetyltransferase 10 (NAT10) is notably upregulated in ovarian cancer (OC), correlating with poor patient prognosis. IGF2BP1 enhances the translation of NAT10 mRNA in an m6A-dependent manner in OC cells. NAT10 drives tumorigenesis by mediating N4-acetylcytidine (ac4C) modification of ACOT7 mRNA, thereby augmenting its stability and translation. This NAT10-ACOT7 axis modulates fatty acid metabolism in cancer cells and promotes tumor progression by suppressing ferroptosis. Additionally, our research identifies fludarabine as a small molecule inhibitor targeting NAT10, inhibits the ac4C modification and expression of ACOT7 mRNA. By using cell derived xenograft model and patient derived organoid model, we show that fludarabine effectively suppresses ovarian tumorigenesis. Overall, our study highlights the pivotal role of the NAT10-ACOT7 axis in the malignant cancer progression, underscoring the potential of targeting NAT10-mediated ac4C modification as a viable therapeutic strategy for this disease.

Improvement in Glycolipid Metabolism Parameters After Supplementing Fish Oil-Derived Omega-3 Fatty Acids Is Associated with Gut Microbiota and Lipid Metabolites in Type 2 Diabetes Mellitus

BACKGROUND/OBJECTIVES

This study aimed to investigate the effects of fish oil-derived omega-3 polyunsaturated fatty acids (omega-3 PUFAs) on gut microbiota and serum lipid metabolites in T2DM.

METHODS

In a three-month, randomized, double-blind, placebo-controlled study, 110 T2DM patients received either fish oil (n = 55) or corn oil (n = 55) capsules daily. Serum lipids, glycemic parameters, gut microbiota diversity, and lipidomics were assessed.

RESULTS

This study found that fish oil-derived omega-3 PUFAs intervention did not significantly lower the fasting plasma glucose levels when compared with the baseline level (p > 0.05). However, serum fasting blood glucose (p = 0.039), glycosylated hemoglobin levels (p = 0.048), HOMA-IR (p = 0.022), total cholesterol (p < 0.001), triglyceride (p = 0.034), LDL cholesterol (p = 0.048), and non-HDL levels (p = 0.046) were significantly lower in the fish oil group compared with the corn oil group after three months of intervention. Also, it altered glycerophospholipid metabolism and gut microbiota. After three months, the fish oil group showed a significantly lower abundance of Desulfobacterota compared with the corn oil control group (p = 0.003), with reduced levels of Colidextribacter (p = 0.002), Ralstonia (p = 0.021), and Klebsiella (p = 0.013). Conversely, the abundance of Limosilactobacillus (p = 0.017), Lactobacillus (p = 0.011), and Haemophilus (p = 0.018) increased significantly. In addition, relevant glycolipid metabolism indicators showed significant correlations with the altered profiles of serum lipid metabolites, intestinal bacteria, and fungi.

CONCLUSIONS

This study highlights the impact of fish oil-derived omega-3 PUFAs on intestinal microbiota structure and function in patients with type 2 diabetes. The observed decrease in pathogenic bacterial species and the enhancement of beneficial species may have significant implications for gut health and systemic inflammation, both of which are pivotal in managing diabetes. Further research is warranted to comprehensively elucidate the long-term benefits and underlying mechanisms of these microbiota alterations.

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.

Nobiletin promotes lipolysis of white adipose tissue in a circadian clock-dependent manner

Nobiletin has been reported to protect against obesity-related metabolic disorders by enhancing the circadian rhythm; however its effects on lipid metabolism in adipose tissue are unclear. In this study, mice were fed with high-fat diet (HFD) for four weeks firstly and gavaged with 50 or 200 mg/kg bodyweight/day nobiletin at Zeitgeber time (ZT) 4 for another four weeks while still receiving HFD. At the end of the 8-week experimental period, the mice were sacrificed at ZT4 or ZT8 on the same day. Mature 3T3-L1 adipocytes were treated with nobiletin in the presence or absence of siBmal1, siRora, siRorc, SR8278 or SR9009. Nobiletin reduced the weight of white adipose tissue (WAT) and the size of adipocytes in WAT. At ZT4, nobiletin decreased the TG, TC and LDL-c levels and increased serum FFA level and glucose tolerance. Nobiletin triggered the lipolysis of mesenteric and epididymal WAT at both ZT4 and ZT16. Nobiletin increased the level of RORγ at ZT16, that of BMAL1 and PPARγ at ZT4, and that of ATGL at both ZT4 and ZT16. Nobiletin increased lipolysis and ATGL levels in 3T3-L1 adipocytes in Bmal1- or Rora/c- dependent manner. Dual luciferase assay indicated that nobiletin enhanced the transcriptional activation of RORα/γ on Atgl promoter and decreased the repression of RORα/γ on PPARγ-binding PPRE. Promoter deletion analysis indicated that nobiletin inhibited the suppression of PPARγ-mediated Atgl transcription by RORα/γ. Taken together, nobiletin elevated lipolysis in WAT by increasing ATGL levels through activating the transcriptional activity of RORα/γ and decreasing the repression of RORα/γ on PPARγ-binding PPRE.

Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy

BACKGROUND

Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk.

OBJECTIVES

This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss.

METHODS

We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses.

RESULTS

We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance.

CONCLUSIONS

Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study was registered at clinicaltrials.gov as NCT01777893 (https://clinicaltrials.gov/study/NCT01777893).

Exploring age and gender disparities in cardiometabolic phenotypes and lipidomic signatures among Chinese adults: a nationwide cohort study

Understanding sex disparities in modifiable risk factors across the lifespan is essential for crafting individualized intervention strategies. We aim to investigate age-related sex disparity in cardiometabolic phenotypes in a large nationwide Chinese cohort. A total of 254,670 adults aged 40 years or older were selected from a population-based cohort in China. Substantial sex disparities in the prevalence of metabolic diseases were observed across different age strata, particularly for dyslipidemia and its components. Generalized additive models were employed to characterize phenotype features, elucidating how gender differences evolve with advancing age. Half of the 16 phenotypes consistently exhibited no sex differences, while four (high-density lipoprotein [HDL] cholesterol, apolipoprotein A1, diastolic blood pressure, and fasting insulin) displayed significant sex differences across all age groups. Triglycerides, apolipoprotein B, non-HDL cholesterol, and total cholesterol demonstrated significant age-dependent sex disparities. Notably, premenopausal females exhibited significant age-related differences in lipid levels around the age of 40-50 years, contrasting with the relatively stable associations observed in males and postmenopausal females. Menopause played an important but not sole role in age-related sex differences in blood lipids. Sleep duration also had an age- and sex-dependent impact on lipids. Lipidomic analysis and K-means clustering further revealed that 58.6% of the 263 measured lipids varied with sex and age, with sphingomyelins, cholesteryl esters, and triacylglycerols being the most profoundly influenced lipid species by the combined effects of age, sex, and their interaction. These findings underscore the importance of age consideration when addressing gender disparities in metabolic diseases and advocate for personalized, age-specific prevention and management.

Decreased plasma docosahexaenoic acid concentration in chronic obstructive pulmonary disease patients with pulmonary Hypertension: Findings from human lipidomics and transcriptomics analysis

Oxylipins derived from polyunsaturated fatty acids (PUFAs) are important endogenous signaling molecules, but are little characterized in pulmonary hypertension (PH) due to chronic obstructive pulmonary disease (COPD). In this study, we identified novel plasma oxylipins associated with PH risk in COPD patients. The plasma oxylipin profiles of COPD patients without PH (COPD-noPH) or with PH (COPD-PH) were obtained from discovery and validation cohort, using the process of LC-MS/MS analysis. There was a significant decrease in the plasma levels of both free docosahexaenoic acid (DHA) and DHA-derived oxylipins in the COPD-PH group. The multivariable logistic regression model identified DHA and four DHA-derived oxylipins (13-HDHA, 10-HDHA, 8-HDHA and 16-HDHA) exhibited significant differences between the two groups after adjusting for sex, BMI, FEV1% predicted, and smoking status. The diagnostic value of these metabolites was further evaluated through ROC curve analysis. The transcriptome profiles in peripheral blood mononuclear cells (PBMCs) of COPD-PH patients and COPD-PH patients were detected through high-throughput sequencing. The enrichment analysis revealed that the upregulated differentially expressed genes (DEGs) were highly enriched in the interferon signaling pathway. In addition, DHA supplementation proved that DHA may inhibit the development of pH by reducing the secretion of interferons derived from PBMCs. This conjecture was further confirmed by the higher level of serum interferon-γ and interferon-α2 of COPD-PH patients than that of COPD-noPH patients. The present study highlights that decreased DHA and DHA-derived oxylipins levels are suggestive of a higher risk of pH development in COPD cases.

Development and validation of a plasmalogen score as an independent modifiable marker of metabolic health: population based observational studies and a placebo-controlled cross-over study

BACKGROUND

Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle.

METHODS

We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years).

FINDINGS

In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21-0.43), 0.39 (95% CI 0.25-0.61) and 0.42 (95% CI 0.30-0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56-0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score.

INTERPRETATION

The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings.

FUNDING

National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

High coverage of targeted lipidomics revealed lipid changes in the follicular fluid of patients with insulin-resistant polycystic ovary syndrome and a positive correlation between plasmalogens and oocyte quality

Background

Polycystic ovary syndrome with insulin resistance (PCOS-IR) is the most common endocrine and metabolic disease in women of reproductive age, and low fertility in PCOS patients may be associated with oocyte quality; however, the molecular mechanism through which PCOS-IR affects oocyte quality remains unknown.

Methods

A total of 22 women with PCOS-IR and 23 women without polycystic ovary syndrome (control) who underwent in vitro fertilization and embryo transfer were recruited, and clinical information pertaining to oocyte quality was analyzed. Lipid components of follicular fluid (FF) were detected using high-coverage targeted lipidomics, which identified 344 lipid species belonging to 19 lipid classes. The exact lipid species associated with oocyte quality were identified.

Results

The number (rate) of two pronuclear (2PN) zygotes, the number (rate) of 2PN cleaved embryos, and the number of high-quality embryos were significantly lower in the PCOS-IR group. A total of 19 individual lipid classes and 344 lipid species were identified and quantified. The concentrations of the 19 lipid species in the normal follicular fluid (control) ranged between 10-3 mol/L and 10-9 mol/L. In addition, 39 lipid species were significantly reduced in the PCOS-IR group, among which plasmalogens were positively correlated with oocyte quality.

Conclusions

This study measured the levels of various lipids in follicular fluid, identified a significantly altered lipid profile in the FF of PCOS-IR patients, and established a correlation between poor oocyte quality and plasmalogens in PCOS-IR patients. These findings have contributed to the development of plasmalogen replacement therapy to enhance oocyte quality and have improved culture medium formulations for oocyte in vitro maturation (IVM).

Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study

There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.

Differences in diacylglycerol acyltransferases expression patterns and regulation cause distinct hepatic triglyceride deposition in fish

Triglyceride (TAG) deposition in the liver is associated with metabolic disorders. In lower vertebrate, the propensity to accumulate hepatic TAG varies widely among fish species. Diacylglycerol acyltransferases (DGAT1 and DGAT2) are major enzymes for TAG synthesis. Here we show that large yellow croaker (Larimichthys crocea) has significantly higher hepatic TAG level than that in rainbow trout (Oncorhynchus mykiss) fed with same diet. Hepatic expression of DGATs genes in croaker is markedly higher compared with trout under physiological condition. Meanwhile, DGAT1 and DGAT2 in both croaker and trout are required for TAG synthesis and lipid droplet formation in vitro. Furthermore, oleic acid treatment increases DGAT1 expression in croaker hepatocytes rather than in trout and has no significant difference in DGAT2 expression in two fish species. Finally, effects of various transcription factors on croaker and trout DGAT1 promoter are studied. We find that DGAT1 is a target gene of the transcription factor CREBH in croaker rather than in trout. Overall, hepatic expression and transcriptional regulation of DGATs display significant species differences between croaker and trout with distinct hepatic triglyceride deposition, which bring new perspectives on the use of fish models for studying hepatic TAG deposition.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus

BACKGROUND

In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state.

METHODS

An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D.

RESULTS

A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D.

CONCLUSIONS

Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Genetic and lipidomic analyses reveal the key role of lipid metabolism for cold tolerance in maize

Lipid remodeling is crucial for cold tolerance in plants. However, the precise alternations of lipidomics during cold responses remain elusive, especially in maize (Zea mays L.). In addition, the key genes responsible for cold tolerance in maize lipid metabolism have not been identified. Here, we integrate lipidomic, transcriptomic, and genetic analysis to determine the profile of lipid remodeling caused by cold stress. We find that the homeostasis of cellular lipid metabolism is essential for maintaining cold tolerance of maize. Also, we detect 210 lipid species belonging to 13 major classes, covering phospholipids, glycerides, glycolipids, and free fatty acids. Various lipid metabolites undergo specific and selective alterations in response to cold stress, especially mono-/di-unsaturated lysophosphatidic acid, lysophosphatidylcholine, phosphatidylcholine, and phosphatidylinositol, as well as polyunsaturated phosphatidic acid, monogalactosyldiacylglycerol, diacylglycerol, and triacylglycerol. In addition, we identify a subset of key enzymes, including ketoacyl-acyl-carrier protein synthase II (KAS II), acyl-carrier protein 2 (ACP2), male sterility33 (Ms33), and stearoyl-acyl-carrier protein desaturase 2 (SAD2) involved in glycerolipid biosynthetic pathways are positive regulators of maize cold tolerance. These results reveal a comprehensive lipidomic profile during the cold response of maize and provide genetic resources for enhancing cold tolerance in crops.

Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes

Gestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.

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.

Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment

Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned.

Machine learning for predicting diabetic metabolism in the Indian population using polar metabolomic and lipidomic features

AIMS

To identify metabolite and lipid biomarkers of diabetes in the Indian subpopulation in newly diagnosed diabetic and long-term diabetic individuals. To utilize the global polar metabolomic and lipidomic profiles to predict the susceptibility of an individual to diabetes using machine learning algorithms.

MATERIALS AND METHODS

87 individuals, including healthy, newly diabetic, and long-term diabetics on medication, were included in the study. Post consent, their serum was used to isolate polar metabolome and lipidome. NMR and LCMS were used to identify the polar metabolites and lipids, respectively. Statistical analysis was done to determine significantly altered molecules. NMR and LCMS comprehensive data were utilized to generate diabetic models using machine learning algorithms. 10 more individuals (pre-diabetic) were recruited, and their polar metabolomic and lipidomic profiles were generated. Pre-diabetic metabolic profiles were then utilized to predict the diabetic status of the metabolome and lipidome beyond glucose levels.

RESULTS

Mannose, Betaine, Xanthine, Triglyceride (38:1), Sphingomyelin (d63:7), and Phosphatidic acid (37:2) are some of the top key biomarkers of diabetes. The predictive model generated showed the receiver operating characteristic area under the curve (ROC-AUC) as 1 on both test and validation data indicating excellent accuracy. This model then predicted the diabetic closeness of the metabolism of pre-diabetic individuals based on probability scores.

CONCLUSION

Polar metabolic and lipid profile of diabetic individuals is very different from that of healthy individuals. Lipid profile alters before the polar metabolic profile in diabetes-susceptible individuals. Without regard to glucose, the diabetic closeness of the metabolism of any individual can be determined.

Metabolite profiles of diabetes mellitus and response to intervention in anti-hyperglycemic drugs

Type 2 diabetes mellitus (T2DM) has become a major health problem, threatening the quality of life of nearly 500 million patients worldwide. As a typical multifactorial metabolic disease, T2DM involves the changes and interactions of various metabolic pathways such as carbohydrates, amino acid, and lipids. It has been suggested that metabolites are not only the endpoints of upstream biochemical processes, but also play a critical role as regulators of disease progression. For example, excess free fatty acids can lead to reduced glucose utilization in skeletal muscle and induce insulin resistance; metabolism disorder of branched-chain amino acids contributes to the accumulation of toxic metabolic intermediates, and promotes the dysfunction of β-cell mitochondria, stress signal transduction, and apoptosis. In this paper, we discuss the role of metabolites in the pathogenesis of T2DM and their potential as biomarkers. Finally, we list the effects of anti-hyperglycemic drugs on serum/plasma metabolic profiles.

Multiomics Approaches Identify Biomarkers for BAT Thermogenesis

Brown adipose tissue (BAT) thermogenesis confers beneficial effects on metabolic diseases such as obesity and type-2 diabetes. Nevertheless, the mechanism and lipid driving the process that evokes this response have not been investigated yet. Here, a multiomics approach of integrative transcriptomics and lipidomics is used to explore the mechanism of regulating thermogenesis in BAT and providing promising lipid biomarkers and biomarker genes for thermogenic activators as antiobesity drugs. Lipidomics analysis demonstrated that a high abundance of glycerophospholipids and sphingolipids was more significant in BAT than in WAT. Enrichment analysis of upregulated DEGs between WAT and BAT screened suggested that the differences were mainly involved in lipid metabolism. Besides, β3-adrenergic agonist stimulation reduced the levels of TAG and DAG and increased the content of PC, PE, CL, and LPC and expression of genes involved in thermogenesis, fatty acid elongation, and glycerophospholipid metabolism in BAT. In this study, based on interpreting the inherent characterization of BAT as thermogenic tissue through comparison with WAT as fat storage tissue, adrenergic stimulation-induced BAT thermogenesis further identified specific lipid biomarkers (7 TAG species, 10 PC species, 1 LPC species, and 1 CL species) and Elovl3 and Crat gene biomarkers, which may provide targets for combating obesity by boosting BAT thermogenesis.

Lipid metabolic links between serum pyrethroid levels and the risk of incident type 2 diabetes: A mediation study in the prospective design

Emerging evidence revealed that pyrethroids and circulating lipid metabolites are involved in incident type 2 diabetes (T2D). However, the pyrethroid-associated lipid profile and its potential role in the association of pyrethroids with T2D remain unknown. Metabolome-wide association or mediation analyses were performed among 1006 pairs of T2D cases and matched controls nested within the prospective Dongfeng-Tongji cohort. We identified 59 lipid metabolites significantly associated with serum deltamethrin levels, of which eight were also significantly associated with serum fenvalerate (false discovery rate [FDR] < 0.05). Pathway enrichment analysis showed that deltamethrin-associated lipid metabolites were significantly enriched in the glycerophospholipid metabolism pathway (FDR = 0.02). Furthermore, we also found that several deltamethrin-associated lipid metabolites (i.e., phosphatidylcholine [PC] 32:0, PC 34:4, cholesterol ester 20:0, triacylglycerol 52:5 [18:2]), and glycerophosphoethanolamine-enriched latent variable mediated the association between serum deltamethrin levels and T2D risk, with the mediated proportions being 44.81%, 15.92%, 16.85%, 16.66%, and 22.86%, respectively. Serum pyrethroids, particularly deltamethrin, may lead to an altered circulating lipid profile primarily in the glycerophospholipid metabolism pathway represented by PCs and lysophosphatidylcholines, potentially mediating the association between serum deltamethrin and T2D. The study provides a new perspective in elucidating the potential mechanisms through which pyrethroid exposure might induce T2D.

Multi-omics profiling reveals rhythmic liver function shaped by meal timing

Post-translational modifications (PTMs) couple feed-fast cycles to diurnal rhythms. However, it remains largely uncharacterized whether and how meal timing organizes diurnal rhythms beyond the transcriptome. Here, we systematically profile the daily rhythms of the proteome, four PTMs (phosphorylation, ubiquitylation, succinylation and N-glycosylation) and the lipidome in the liver from young female mice subjected to either day/sleep time-restricted feeding (DRF) or night/wake time-restricted feeding (NRF). We detect robust daily rhythms among different layers of omics with phosphorylation the most nutrient-responsive and succinylation the least. Integrative analyses reveal that clock regulation of fatty acid metabolism represents a key diurnal feature that is reset by meal timing, as indicated by the rhythmic phosphorylation of the circadian repressor PERIOD2 at Ser971 (PER2-pSer971). We confirm that PER2-pSer971 is activated by nutrient availability in vivo. Together, this dataset represents a comprehensive resource detailing the proteomic and lipidomic responses by the liver to alterations in meal timing.

Hibernation and plasma lipids in free-ranging brown bears-implications for diabetes

Brown bears (Ursus arctos) prepare for winter by overeating and increasing adipose stores, before hibernating for up to six months without eating, drinking, and with minimal movement. In spring, the bears exit the den without any damage to organs or physiology. Recent clinical research has shown that specific lipids and lipid profiles are of special interest for diseases such as diabetes type 1 and 2. Furthermore, rodent experiments show that lipids such as sulfatide protects rodents against diabetes. As free-ranging bears experience fat accumulation and month-long physical inactivity without developing diabetes, they could possibly be affected by similar protective measures. In this study, we investigated whether lipid profiles of brown bears are related to protection against hibernation-induced damage. We sampled plasma from 10 free-ranging Scandinavian brown bears during winter hibernation and repeated sampling during active state in the summer period. With quantitative shotgun lipidomics and liquid chromatography-mass spectrometry, we profiled 314 lipid species from 26 lipid classes. A principal component analysis revealed that active and hibernation samples could be distinguished from each other based on their lipid profiles. Six lipid classes were significantly altered when comparing plasma from active state and hibernation: Hexosylceramide, phosphatidylglycerol, and lysophosphatidylglycerol were higher during hibernation, while phosphatidylcholine ether, phosphatidylethanolamine ether, and phosphatidylinositol were lower. Additionally, sulfatide species with shorter chain lengths were lower, while longer chain length sulfatides were higher during hibernation. Lipids that are altered in bears are described by others as relevant for and associated with diabetes, which strengthens their position as potential effectors during hibernation. From this analysis, a range of lipids are suggested as potential protectors of bear physiology, and of potential importance in diabetes.

Diet-Related Lipidomic Signatures and Changed Type 2 Diabetes Risk in a Randomized Controlled Feeding Study With Mediterranean Diet and Traditional Chinese or Transitional Diets

OBJECTIVE

Few trials studied the links of food components in different diets with their induced lipidomic changes and related metabolic outcomes. Thus, we investigated specific lipidomic signatures with habitual diets and modified diabetes risk by using a trial and a cohort.

RESEARCH DESIGN AND METHODS

We included 231 Chinese with overweight and prediabetes in a randomized feeding trial with Mediterranean, traditional, or transitional diets (control diet) from February to September 2019. Plasma lipidomic profiles were measured at baseline, third month, and sixth month by high-throughput targeted liquid chromatography-mass spectrometry. Associations of the identified lipids with habitual dietary intakes were examined in another lipidomic database of a Chinese cohort (n = 1,117). The relationships between diet-induced changes of lipidomic species and diabetes risk factors were further investigated through both individual lipids and relevant modules in the trial.

RESULTS

Out of 364 lipidomic species, 26 altered across groups, including 12 triglyceride (TAG) fractions, nine plasmalogens, four phosphatidylcholines (PCs), and one phosphatidylethanolamine. TAG fractions and PCs were associated with habitual fish intake while plasmalogens were associated with red meat intake in the cohort. Of the diet-related lipidomic metabolites, 10 TAG fractions and PC(16:0/22:6) were associated with improved Matsuda index (β = 0.12 to 0.42; PFDR < 0.030). Two plasmalogens were associated with deteriorated fasting glucose (β = 0.29 to 0.31; PFDR < 0.014). Similar results were observed for TAG and plasmalogen related modules.

CONCLUSIONS

These fish- and red meat-related lipidomic signatures sensitively reflected different diets and modified type 2 diabetes risk factors, critical for optimizing dietary patterns.

Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations

BACKGROUND

Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles.

OBJECTIVES

Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles.

METHODS

We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts.

RESULTS

Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED.

CONCLUSIONS

Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.

The ER calcium channel Csg2 integrates sphingolipid metabolism with autophagy

Sphingolipids are ubiquitous components of membranes and function as bioactive lipid signaling molecules. Here, through genetic screening and lipidomics analyses, we find that the endoplasmic reticulum (ER) calcium channel Csg2 integrates sphingolipid metabolism with autophagy by regulating ER calcium homeostasis in the yeast Saccharomyces cerevisiae. Csg2 functions as a calcium release channel and maintains calcium homeostasis in the ER, which enables normal functioning of the essential sphingolipid synthase Aur1. Under starvation conditions, deletion of Csg2 causes increases in calcium levels in the ER and then disturbs Aur1 stability, leading to accumulation of the bioactive sphingolipid phytosphingosine, which specifically and completely blocks autophagy and induces loss of starvation resistance in cells. Our findings indicate that calcium homeostasis in the ER mediated by the channel Csg2 translates sphingolipid metabolism into autophagy regulation, further supporting the role of the ER as a signaling hub for calcium homeostasis, sphingolipid metabolism and autophagy.

Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial

BACKGROUND

The effects of replacing dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) and/or polyunsaturated fatty acids (PUFAs) on the plasma lipidome in relation to the cardiometabolic disease (CMD) risk are poorly understood.

OBJECTIVES

We aimed to assess the impact of substituting dietary SFAs with unsaturated fatty acids (UFAs) on the plasma lipidome and examine the relationship between lipid metabolites modulated by diet and CMD risk.

METHODS

Plasma fatty acid (FA) concentrations among 16 lipid classes (within-class FAs) were measured in a subgroup from the Dietary Intervention and VAScular function (DIVAS) parallel randomized controlled trial (n = 113/195), which consisted of three 16-wk diets enriched in SFAs (target SFA:MUFA:n-6PUFA ratio = 17:11:4% total energy [TE]), MUFAs (9:19:4% TE), or a MUFA/PUFA mixture (9:13:10% TE). Similar lipidomics analyses were conducted in the European investigation into Cancer and Nutrition (EPIC)-Potsdam prospective cohort study (specific case/cohorts: n = 775/1886 for type 2 diabetes [T2D], n = 551/1671 for cardiovascular disease [CVD]). Multiple linear regression and multivariable Cox models identified within-class FAs sensitive to replacement of dietary SFA with UFA in DIVAS and their association with CMD risk in EPIC-Potsdam. Elastic-net regression models identified within-class FAs associated with changes in CMD risk markers post-DIVAS interventions.

RESULTS

DIVAS high-UFA interventions reduced plasma within-class FAs associated with a higher CVD risk in EPIC-Potsdam, especially SFA-containing glycerolipids and sphingolipids (e.g., diacylglycerol (20:0) z-score = -1.08; SE = 0.17; P value < 10^-8), whereas they increased those inversely associated with CVD risk. The results on T2D were less clear. Specific sphingolipids and phospholipids were associated with changes in markers of endothelial function and ambulatory blood pressure, whereas higher low-density lipoprotein cholesterol concentrations were characterized by higher plasma glycerolipids containing lauric and stearic acids.

CONCLUSIONS

These results suggest a mediating role of plasma lipid metabolites in the association between dietary fat and CMD risk. Future research combining interventional and observational findings will further our understanding of the role of dietary fat in CMD etiology. This trial was registered in ClinicalTrials.gov as NCT01478958.

Saturated fatty acids increase LPI to reduce FUNDC1 dimerization and stability and mitochondrial function

Ectopic lipid deposition and mitochondrial dysfunction are common etiologies of obesity and metabolic disorders. Excessive dietary uptake of saturated fatty acids (SFAs) causes mitochondrial dysfunction and metabolic disorders, while unsaturated fatty acids (UFAs) counterbalance these detrimental effects. It remains elusive how SFAs and UFAs differentially signal toward mitochondria for mitochondrial performance. We report here that saturated dietary fatty acids such as palmitic acid (PA), but not unsaturated oleic acid (OA), increase lysophosphatidylinositol (LPI) production to impact on the stability of the mitophagy receptor FUNDC1 and on mitochondrial quality. Mechanistically, PA shifts FUNDC1 from dimer to monomer via enhanced production of LPI. Monomeric FUNDC1 shows increased acetylation at K104 due to dissociation of HDAC3 and increased interaction with Tip60. Acetylated FUNDC1 can be further ubiquitinated by MARCH5 for proteasomal degradation. Conversely, OA antagonizes PA-induced accumulation of LPI, and FUNDC1 monomerization and degradation. A fructose-, palmitate-, and cholesterol-enriched (FPC) diet also affects FUNDC1 dimerization and promotes its degradation in a non-alcoholic steatohepatitis (NASH) mouse model. We thus uncover a signaling pathway that orchestrates lipid metabolism with mitochondrial quality.

The roles of dietary lipids and lipidomics in gut-brain axis in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM), one of the main types of Noncommunicable diseases (NCDs), is a systemic inflammatory disease characterized by dysfunctional pancreatic β-cells and/or peripheral insulin resistance, resulting in impaired glucose and lipid metabolism. Genetic, metabolic, multiple lifestyle, and sociodemographic factors are known as related to high T2DM risk. Dietary lipids and lipid metabolism are significant metabolic modulators in T2DM and T2DM-related complications. Besides, accumulated evidence suggests that altered gut microbiota which plays an important role in the metabolic health of the host contributes significantly to T2DM involving impaired or improved glucose and lipid metabolism. At this point, dietary lipids may affect host physiology and health via interaction with the gut microbiota. Besides, increasing evidence in the literature suggests that lipidomics as novel parameters detected with holistic analytical techniques have important roles in the pathogenesis and progression of T2DM, through various mechanisms of action including gut-brain axis modulation. A better understanding of the roles of some nutrients and lipidomics in T2DM through gut microbiota interactions will help develop new strategies for the prevention and treatment of T2DM. However, this issue has not yet been entirely discussed in the literature. The present review provides up-to-date knowledge on the roles of dietary lipids and lipidomics in gut-brain axis in T2DM and some nutritional strategies in T2DM considering lipids- lipidomics and gut microbiota interactions are given.

Precise Metabolomics Defines Systemic Metabolic Dysregulation Distinct to Acute Myocardial Infarction Associated With Diabetes

BACKGROUND

Acute myocardial infarction (AMI) is a leading cause of death and disability. Diabetes is an important risk factor and a common comorbidity in AMI patients. The higher mortality risk of diabetes-AMI relative to nondiabetes-AMI indicates a need for specific treatment to improve clinical outcome. However, the global metabolic dysregulation of AMI complicated with diabetes is still unclear. We aim to systematically interrogate changes in the metabolic microenvironment immediate to AMI episodes in the absence or presence of diabetes.

METHODS

In this work, quantitative metabolomics was used to investigate plasma metabolic differences between diabetes-AMI (n=59) and nondiabetes-AMI (n=59) patients. A diverse array of perturbed metabolic pathways involving carbohydrate metabolism, lipid metabolism, glycolysis, tricarboxylic acid cycle, and amino acid metabolism emerged.

RESULTS

In all, our omics-oriented approach defined a metabolic signature of afflicted mitochondrial function aggravated by concurrent diabetes in AMI patients. In particular, our analyses uncovered N-lactoyl-phenylalanine and lysophosphatidylcholines as key functional metabolites that skewed the metabolic picture of diabetes-AMI relative to nondiabetes-AMI. N-lactoyl-phenylalanine was strongly associated with metabolic indicators reflective of mitochondrial overload and negatively correlated with HbA1c (glycosylated hemoglobin, type A1C) specifically in hyperglycemic AMI, suggestive of its central role in glucose utilization and mitochondrial energy production instrumental to the clinical outcome of diabetes-AMI. Reductions in lysophosphatidylcholines, which were negatively correlated with blood glucose and inflammatory markers, might further compromise glucose expenditure and aggravate inflammation leading to poorer prognosis in diabetes-AMI.

CONCLUSIONS

As circulating metabolite levels are amenable to therapeutic intervention, such shifts in metabolic signatures provide new clues and potential therapeutic targets specific to the treatment of diabetes-AMI.

The Landscape of Lipid Metabolism in Lung Cancer: The Role of Structural Profiling

The aim of this study was to explore the relationship between lipids with different structural features and lung cancer (LC) risk and identify prospective biomarkers of LC. Univariate and multivariate analysis methods were used to screen for differential lipids, and two machine learning methods were used to define combined lipid biomarkers. A lipid score (LS) based on lipid biomarkers was calculated, and a mediation analysis was performed. A total of 605 lipid species spanning 20 individual lipid classes were identified in the plasma lipidome. Higher carbon atoms with dihydroceramide (DCER), phosphatidylethanolamine (PE), and phosphoinositols (PI) presented a significant negative correlation with LC. Point estimates revealed the inverse associated with LC for the n-3 PUFA score. Ten lipids were identified as markers with an area under the curve (AUC) value of 0.947 (95%, CI: 0.879-0.989). In this study, we summarized the potential relationship between lipid molecules with different structural features and LC risk, identified a panel of LC biomarkers, and demonstrated that the n-3 PUFA of the acyl chain of lipids was a protective factor for LC.

Hawthorn total flavonoids ameliorate ambient fine particulate matter-induced insulin resistance and metabolic abnormalities of lipids in mice

Recent studies have shown a strong correlation between ambient fine particulate matter (PM2.5) exposure and diabetes risk, including abnormal lipid accumulation and systemic insulin resistance (IR). Hawthorn total flavonoids (HF) are the main groups of active substances in Hawthorn, which showed anti-hyperlipidemic and anti-hyperglycemic effects. Therefore, we hypothesized that HF may attenuate PM2.5-induced IR and abnormal lipid accumulation. Female C57BL/6 N mice were randomly assigned to the filtered air exposure (FA) group, concentrated PM2.5 exposure (PM) group, PM2.5 exposure maintained on a low-dose HF diet (LHF) group, and PM2.5 exposure maintained on a high-dose HF diet (HHF) group for an 8-week PM2.5 exposure using a whole-body exposure device. Body glucose homeostasis, lipid profiles in the liver and serum, and enzymes responsible for hepatic lipid metabolism were measured. We found that exposure to PM2.5 impaired glucose tolerance and insulin sensitivity. In addition, triacylglycerol (TAG) in serum elevated, whereas hepatic TAG levels were decreased after PM2.5 exposure, accompanied by inhibited fatty acid uptake, lipogenesis, and lipolysis in the liver. HF administration, on the other hand, balanced the hepatic TAG levels by increasing fatty acid uptake and decreasing lipid export, leading to alleviated systemic IR and hyperlipidemia in PM2.5-exposed mice. Therefore, HF administration may be an effective strategy to protect against PM2.5-induced IR and metabolic abnormalities of lipids.

Plasma Metabolomics Reveals Systemic Metabolic Alterations of Subclinical and Clinical Hypothyroidism

CONTEXT

Clinical hypothyroidism (CH) and subclinical hypothyroidism (SCH) have been linked to various metabolic comorbidities but the underlying metabolic alterations remain unclear. Metabolomics may provide metabolic insights into the pathophysiology of hypothyroidism.

OBJECTIVE

We explored metabolic alterations in SCH and CH and identify potential metabolite biomarkers for the discrimination of SCH and CH from euthyroid individuals.

METHODS

Plasma samples from a cohort of 126 human subjects, including 45 patients with CH, 41 patients with SCH, and 40 euthyroid controls, were analyzed by high-resolution mass spectrometry-based metabolomics. Data were processed by multivariate principal components analysis and orthogonal partial least squares discriminant analysis. Correlation analysis was performed by a Multivariate Linear Regression analysis. Unbiased Variable selection in R algorithm and 3 machine learning models were utilized to develop prediction models based on potential metabolite biomarkers.

RESULTS

The plasma metabolomic patterns in SCH and CH groups were significantly different from those of control groups, while metabolite alterations between SCH and CH groups were dramatically similar. Pathway enrichment analysis found that SCH and CH had a significant impact on primary bile acid biosynthesis, steroid hormone biosynthesis, lysine degradation, tryptophan metabolism, and purine metabolism. Significant associations for 65 metabolites were found with levels of thyrotropin, free thyroxine, thyroid peroxidase antibody, or thyroglobulin antibody. We successfully selected and validated 17 metabolic biomarkers to differentiate 3 groups.

CONCLUSION

SCH and CH have significantly altered metabolic patterns associated with hypothyroidism, and metabolomics coupled with machine learning algorithms can be used to develop diagnostic models based on selected metabolites.

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.

Prognostic implication of lipidomics in patients with coronary total occlusion undergoing PCI

BACKGROUND

Predictors of prognosis in patients with coronary chronic total occlusion (CTO) undergoing elective percutaneous coronary intervention (PCI) have remained lacking. Lipidomic profiling enables researchers to associate lipid species with disease progression and may improve the prediction of cardiovascular events.

METHODS

In the present study, 781 lipids were measured by targeted lipidomic profiling in 350 individuals (50 healthy controls, 50 patients with coronary artery disease and 250 patients with CTO). L1-regularized logistic regression was used to identify lipid species associated with adverse cardiovascular events and create predicting models, which were verified by 10-fold cross-validation (200 repeats). Comparisons were made between a traditional model constructed with clinical characteristics alone and a combined model built with both lipidomic data and traditional factors.

RESULTS

Twenty-four lipid species were dysregulated exclusively in patients with CTO, most of which belonged to sphingomyelin (SM) and triacylglycerol (TAG). Compared with traditional risk factors, new model combining lipids and traditional factors had significantly improved performance in predicting adverse cardiovascular events in CTO patients after PCI (area under the curve, 0.870 vs. 0.726, p < .05; Akaike information criterion, 129 versus 156; net reclassification improvement, 0.312, p < .001; integrated discrimination improvement, 0.244, p < .001). Nomogram was built based on the incorporated model and proved efficient by Kaplan-Meier method.

CONCLUSIONS

Lipidomic profiling revealed lipid species which may participate in the formation of CTO and could contribute to the risk stratification in CTO patients undergoing PCI.

High-coverage targeted lipidomics could reveal lipid alterations and evaluate therapeutic efficacy of membranous nephropathy

BACKGROUND

Membrane nephropathy (MN) often presents as nephrotic syndrome with characteristic lipid metabolism that could not be explained by lipid indicators commonly used in clinical practice. Studies have shown that invigorating spleen and qi, activating blood and detoxication in the treatment of MN is an effective method proved by randomized controlled clinical trial. However, the alterations of lipid profile before and after traditional Chinese medicine (TCM) treatment and the related lipid markers that affect the therapeutic effect have not been fully clarified.

METHODS

We analyzed plasma lipid profiles of 92 patients with MN before and after TCM treatment by high-coverage targeted lipidomics.

RESULTS

675 lipids were identified, of which 368 stably expressed lipids (coefficient of variation less than 30% and deletion value less than 10%) were eventually included for statistical analysis. 105 lipids were altered mainly including spingolipids, glycerides, glycerophosholipid, fatty acyl and steroids, among which, the abundance of ceramides (Cers), sphingomyelins (SMs), diacylglycerols (DGs), phosphatidylcholines (PCs) were lower than those before treatment with statistically significant difference. The WGCNA network to analyze the correlation between the collective effect and the therapeutic effect showed that the triglyceride (TG) molecules were most relevant to the therapeutic effect. Analysis of 162 triglyceride molecules showed that 11 TGs were significantly down-regulated in the effective group which were concentrated in carbon atom number of 52-56 and double bond number of 0-4. TGs molecules including TG56:2-FA20:0, TG56:2-FA20:1, TG56:3-FA20:0 and TG56:5-FA20:2 were most closely related to the therapeutic effect of TCM after adjusting the influence of clinical factors. ROC curve analysis showed that these four lipids could further improve the predictive efficacy of treatment based on clinical indicators.

CONCLUSION

Our work demonstrated that the therapeutic effect of invigorating spleen and qi, activating blood and detoxication in the treatment of MN may be exerted by regulating lipid metabolism. High-coverage targeted lipidomics provided a non-invasive tool for discovery of lipid markers to improve the predictive efficacy of TCM therapy.

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.

The role of NMR-based circulating metabolic biomarkers in development and risk prediction of new onset type 2 diabetes

Associations of circulating metabolic biomarkers with type 2 diabetes (T2D) and their added value for risk prediction are uncertain among Chinese adults. A case-cohort study included 882 T2D cases diagnosed during 8-years' follow-up and a subcohort of 789 participants. NMR-metabolomic profiling quantified 225 plasma biomarkers in stored samples taken at recruitment into the study. Cox regression yielded adjusted hazard ratios (HRs) for T2D associated with individual biomarkers, with a set of biomarkers incorporated into an established T2D risk prediction model to assess improvement in discriminatory ability. Mean baseline BMI (SD) was higher in T2D cases than in the subcohort (25.7 [3.6] vs. 23.9 [3.6] kg/m²). Overall, 163 biomarkers were significantly and independently associated with T2D at false discovery rate (FDR) controlled p < 0.05, and 138 at FDR-controlled p < 0.01. Branched chain amino acids (BCAA), apolipoprotein B/apolipoprotein A1, triglycerides in VLDL and medium and small HDL particles, and VLDL particle size were strongly positively associated with T2D (HRs 1.74-2.36 per 1 SD, p < 0.001). HDL particle size, cholesterol concentration in larger HDL particles and docosahexaenoic acid levels were strongly inversely associated with T2D (HRs 0.43-0.48, p < 0.001). With additional adjustment for plasma glucose, most associations (n = 147 and n = 129 at p < 0.05 and p < 0.01, respectively) remained significant. HRs appeared more extreme among more centrally adipose participants for apolipoprotein B/apolipoprotein A1, BCAA, HDL particle size and docosahexaenoic acid (p for heterogeneity ≤ 0.05). Addition of 31 selected biomarkers to an established T2D risk prediction model modestly, but significantly, improved risk discrimination (c-statistic 0.86 to 0.91, p < 0.001). In relatively lean Chinese adults, diverse metabolic biomarkers are associated with future risk of T2D and can help improve established risk prediction models.

Cardiovascular effects of traffic-related air pollution: A multi-omics analysis from a randomized, crossover trial

A system-wide cardiovascular response to traffic-related air pollution (TRAP) has been rarely described. To systemically understand the mechanisms underlying cardiovascular effects of TRAP, we conducted a randomized, crossover trial in 56 young adults, who engaged in two 4-hour exposure sessions on a main road and in a park, alternately. We measured personal exposures to traffic-related air pollutants (TRAPs), including fine and ultrafine particulate matter, black carbon, nitrogen dioxide, and carbon monoxide. Lipidomics, targeted proteomics, urine metabolomics, targeted biomarkers, ambulatory blood pressure and electrocardiogram were measured. We used linear mixed-effects models to estimate the associations. The exposures to TRAPs except for fine particulate matter in the road session were 2-3 times higher. We observed elevated blood pressure and decreased heart rate variability (HRV) after TRAP exposure, accompanied by dozens of molecular alterations involving systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and lipid metabolism. Pathways like vascular smooth muscle cell proliferation and biomarkers like trimethylamine N-Oxide might also be disturbed. Some of these TRAP-related molecular biomarkers were also associated with changes of blood pressure or HRV. Our results provided systematical mechanistic profiling for the cardiovascular effects of TRAP using multi omics, which may have implications in TRAP control.