Deep Lipidomics in Human Plasma: Cardiometabolic Disease Risk and Effect of Dietary Fat Modulation

Association of plant-based diet indexes with the metabolomic profile

Plant-based diets have gained attention for their potential benefits on both human health and environmental sustainability. The objective of this study was to investigate the association of plant-based dietary patterns with the endogenous metabolites of healthy individuals and identify metabolites that may act as mediators of the associations between dietary intake and modifiable disease risk factors. Adherence to plant-based dietary patterns was assessed for 170 healthy adults using plant-based diet indexes (PDI). Individuals with higher healthful PDI had lower BMI and fasting glucose and higher HDL-C, while those with higher unhealthful PDI had higher BMI, triacylglycerol and fasting glucose and lower HDL-C. Unhealthful PDI was associated with higher levels of several amino acids and biogenic amines previously associated with cardiometabolic diseases and an opposite pattern was observed for healthful PDI. Furthermore, healthful PDI was associated with higher levels of glycerophosphocholines containing very long-chain fatty acids. Glutamate, isoleucine, proline, tyrosine, α-aminoadipate and kynurenine had a statistically significant mediation effect on the associations between PDI scores and LDL-C, HDL-C and fasting glucose. These findings contribute to the growing evidence supporting the role of plant-based diets in promoting metabolic health and shed light on the potential mechanisms explaining their beneficial health effects.

Glucocorticoid resistance remodels liver lipids and prompts lipogenesis, eicosanoid, and inflammatory pathways

We have previously demonstrated that the glucocorticoid receptor β (GRβ) isoform induces hepatic steatosis in mice fed a normal chow diet. The GRβ isoform inhibits the glucocorticoid-binding isoform GRα, reducing responsiveness and inducing glucocorticoid resistance. We hypothesized that GRβ regulates lipids that cause metabolic dysfunction. To determine the effect of GRβ on hepatic lipid classes and molecular species, we overexpressed GRβ (GRβ-Ad) and vector (Vec-Ad) using adenovirus delivery, as we previously described. We fed the mice a normal chow diet for 5 days and harvested the livers. We utilized liquid chromatography-mass spectrometry (LC-MS) analyses of the livers to determine the lipid species driven by GRβ. The most significant changes in the lipidome were monoacylglycerides and cholesterol esters. There was also increased gene expression in the GRβ-Ad mice for lipogenesis, eicosanoid synthesis, and inflammatory pathways. These indicate that GRβ-induced glucocorticoid resistance may drive hepatic fat accumulation, providing new therapeutic advantages.

The Non-Targeted Lipidomic-Based Classifier Reveals Two Candidate Biomarkers for Ischemic Stroke in Hypertensive Individuals

Introduction

Traditional clinical risk factors are insufficient to estimate the residual risk of large-vessel ischemic stroke. Non-targeted lipidomic techniques provide an opportunity to evaluate these risks.

Methods

Plasma samples were collected from 113 hypertensive individuals, including 55 individuals at high risk of ischemic stroke and 58 matched individuals, in a prospective nested case-control cohort. To identify dysregulated lipid metabolites, we conducted multivariate and univariate analyses. A classifier based on a cross-validated procedure was employed to select the optimal combination of lipid species and their ratios.

Results

We identified 23 dysregulated lipid species in patients with and without ischemic stroke, including 16 (69.6%) up-regulated and 7 (30.4%) down-regulated lipid species. Through internal cross-validation, the optimal combination of two lipid features (phosphatidylcholine 34:2 and triglyceride 18:1/18:1/22:1 / phosphatidylcholine 34:2, referred to as ischemic stroke-related 2 lipid features - IS2LP) was selected, leading to a more precise prediction probability for ischemic stroke within 3.9 years. In the comparison of different risk factors, the traditional risk score, the IS2LP risk score, and the combination of the traditional risk score with IS2LP yield AUC values of 0.613(95% CI:0.509-0.717), 0.833(95% CI:0.755-0.911), and 0.843(95% CI:0.777-0.916), respectively. The combination of the traditional risk score and IS2LP exhibited significantly improved discriminative performance, with an integrated discrimination improvement (IDI) of 0.31 (p<0.001) and a continuous net reclassification improvement (NRI) of 1.06 (p < 0.001) compared to the traditional risk score.

Conclusion

We identified new lipidomic biomarkers associated with the futural event of large-vessel ischemic stroke. These lipid species could serve as potential blood biomarkers for assessing the residual risk of ischemic stroke in hypertensive individuals.

Longitudinal associations of an exposome score with serum metabolites from childhood to adolescence

Environmental and lifestyle factors, including air pollution, impaired diet, and low physical activity, have been associated with cardiometabolic risk factors in childhood and adolescence. However, environmental and lifestyle exposures do not exert their physiological effects in isolation. This study investigated associations between an exposome score to measure the impact of multiple exposures, including diet, physical activity, sleep duration, air pollution, and socioeconomic status, and serum metabolites measured using LC-MS and NMR, compared to the individual components of the score. A general population of 504 children aged 6-9 years at baseline was followed up for eight years. Data were analysed with linear mixed-effects models using the R software. The exposome score was associated with 31 metabolites, of which 12 metabolites were not associated with any individual exposure category. These findings highlight the value of a composite score to predict metabolic changes associated with multiple environmental and lifestyle exposures since childhood.

Lipidome changes due to improved dietary fat quality inform cardiometabolic risk reduction and precision nutrition

Current cardiometabolic disease prevention guidelines recommend increasing dietary unsaturated fat intake while reducing saturated fats. Here we use lipidomics data from a randomized controlled dietary intervention trial to construct a multilipid score (MLS), summarizing the effects of replacing saturated fat with unsaturated fat on 45 lipid metabolite concentrations. In the EPIC-Potsdam cohort, a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (-32%; 95% confidence interval (95% CI): -21% to -42%) and type 2 diabetes (-26%; 95% CI: -15% to -35%). We built a closely correlated simplified score, reduced MLS (rMLS), and observed that beneficial rMLS changes, suggesting improved dietary fat quality over 10 years, were associated with lower diabetes risk (odds ratio per standard deviation of 0.76; 95% CI: 0.59 to 0.98) in the Nurses' Health Study. Furthermore, in the PREDIMED trial, an olive oil-rich Mediterranean diet intervention primarily reduced diabetes incidence among participants with unfavorable preintervention rMLS levels, suggestive of disturbed lipid metabolism before intervention. Our findings indicate that the effects of dietary fat quality on the lipidome can contribute to a more precise understanding and possible prediction of the health outcomes of specific dietary fat modifications.

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).

The Lipidomic Profile Is Associated with the Dietary Pattern in Subjects with and without Diabetes Mellitus from a Mediterranean Area

Lipid functions can be influenced by genetics, age, disease states, and lifestyle factors, particularly dietary patterns, which are crucial in diabetes management. Lipidomics is an expanding field involving the comprehensive exploration of lipids from biological samples. In this cross-sectional study, 396 participants from a Mediterranean region, including individuals with type 1 diabetes (T1D), type 2 diabetes (T2D), and non-diabetic individuals, underwent lipidomic profiling and dietary assessment. Participants completed validated food frequency questionnaires, and lipid analysis was conducted using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC/MS). Multiple linear regression models were used to determine the association between lipid features and dietary patterns. Across all subjects, acylcarnitines (AcCa) and triglycerides (TG) displayed negative associations with the alternate Healthy Eating Index (aHEI), indicating a link between lipidomic profiles and dietary habits. Various lipid species (LS) showed positive and negative associations with dietary carbohydrates, fats, and proteins. Notably, in the interaction analysis between diabetes and the aHEI, we found some lysophosphatidylcholines (LPC) that showed a similar direction with respect to aHEI in non-diabetic individuals and T2D subjects, while an opposite direction was observed in T1D subjects. The study highlights the significant association between lipidomic profiles and dietary habits in people with and without diabetes, particularly emphasizing the role of healthy dietary choices, as reflected by the aHEI, in modulating lipid concentrations. These findings underscore the importance of dietary interventions to improve metabolic health outcomes, especially in the context of diabetes management.

A pseudo-targeted metabolomics for discovery of potential biomarkers of cardiac hypertrophy in rats

Cardiac hypertrophy (CH) is one of the stages in the occurrence and development of severe cardiovascular diseases, and exploring its biomarkers is beneficial for delaying the progression of severe cardiovascular diseases. In this research, we established a comprehensive and highly efficient pseudotargeted metabolomics method, which demonstrated a superior capacity to identify differential metabolites when compared to traditionaluntargeted metabolomics. The intra/inter-day precision and reproducibility results proved the method is reliable and precise. The established method was then applied to seek the potential differentiated metabolic biomarkers of cardiac hypertrophy (CH) rats, and oxylipins, phosphorylcholine (PC), lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE), Krebs cycle intermediates, carnitines, amino acids, and bile acids were disclosed to be the possible differentiate components. Their metabolic pathway analysis revealed that the potential metabolic alterations in CH rats were mainly associated with phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, citrate cycle, glyoxylate and dicarboxylate metabolism, and tyrosine metabolism. In sum, this research provided a comprehensiveand reliable LC-MS/MS MRM platform for pseudo-targeted metabolomics investigation of disease condition, and some interesting potential biomarkers were disclosed for CH, which merit further exploration in the future.

Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases low-density lipoprotein apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial

BACKGROUND

The substitution of monounsaturated acids (MUFAs) for saturated fatty acids (SFAs) is recommended for cardiovascular disease prevention but its impact on lipoprotein metabolism in subjects with dyslipidemia associated with insulin resistance (IR) remains largely unknown.

OBJECTIVES

This study aimed to evaluate the impact of substituting MUFAs for SFAs on the in vivo kinetics of apolipoprotein (apo)B-containing lipoproteins and on the plasma lipidomic profile in adults with IR-induced dyslipidemia.

METHODS

Males and females with dyslipidemia associated with IR (n = 18) were recruited for this crossover double-blind randomized controlled trial. Subjects consumed, in random order, a diet rich in SFAs (SFAs: 13.4%E; MUFAs: 14.4%E) and a diet rich in MUFAs (SFAs: 7.1%E; MUFAs: 20.7%E) in fully controlled feeding conditions for periods of 4 wk each, separated by a 4-wk washout. At the end of each diet, fasting plasma samples were taken together with measurements of the in vivo kinetics of apoB-containing lipoproteins.

RESULTS

Substituting MUFAs for SFAs had no impact on triglyceride-rich lipoprotein apoB-48 fractional catabolic rate (FCR) (Δ = -8.9%, P = 0.4) and production rate (Δ = 0.0%, P = 0.9), although it decreased very low-density lipoprotein apoB-100 pool size (PS) (Δ = -22.5%; P = 0.01). This substitution also reduced low-density lipoprotein cholesterol (LDL-C) (Δ = -7.0%; P = 0.01), non-high-density lipoprotein cholesterol (Δ = -2.5%; P = 0.04), and LDL apoB-100 PS (Δ = -6.0%; P = 0.05). These differences were partially attributed to an increase in LDL apoB-100 FCR (Δ = +1.6%; P = 0.05). The MUFA diet showed reduced sphingolipid concentrations and elevated glycerophospholipid levels compared with the SFA diet.

CONCLUSIONS

This study demonstrated that substituting dietary MUFAs for SFAs decreases LDL-C levels and LDL PS by increasing LDL apoB-100 FCR and results in an overall improved plasma lipidomic profile in individuals with IR-induced lipidemia.

TRIAL REGISTRATION

This trial was registered as clinicaltrials.gov as NCT03872349.

Omega-3 Fatty Acids and Risk of Ischemic Stroke in REGARDS

We examined associations between lipidomic profiles and incident ischemic stroke in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Plasma lipids (n = 195) were measured from baseline blood samples, and lipids were consolidated into underlying factors using exploratory factor analysis. Cox proportional hazards models were used to test associations between lipid factors and incident stroke, linear regressions to determine associations between dietary intake and lipid factors, and the inverse odds ratio weighting (IORW) approach to test mediation. The study followed participants over a median (IQR) of 7 (3.4-11) years, and the case-cohort substudy included 1075 incident ischemic stroke and 968 non-stroke participants. One lipid factor, enriched for docosahexaenoic acid (DHA, an omega-3 fatty acid), was inversely associated with stroke risk in a base model (HR = 0.84; 95%CI 0.79-0.90; P = 8.33 × 10-8) and fully adjusted model (HR = 0.88; 95%CI 0.83-0.94; P = 2.79 × 10-4). This factor was associated with a healthy diet pattern (β = 0.21; 95%CI 0.12-0.30; P = 2.06 × 10-6), specifically with fish intake (β = 1.96; 95%CI 0.95-2.96; P = 1.36 × 10-4). DHA was a mediator between fish intake and incident ischemic stroke (30% P = 5.78 × 10-3). Taken together, DHA-containing plasma lipids were inversely associated with incident ischemic stroke and mediated the relationship between fish intake and stroke risk.

Protocol for evaluating the effects of the Reducing Cardiometabolic Diseases Risk dietary pattern in the Chinese population with dyslipidaemia: a single-centre, open-label, dietary intervention study

INTRODUCTION

Cardiometabolic disease (CMD) is the leading cause of mortality in China. A healthy diet plays an essential role in the occurrence and development of CMD. Although the Chinese heart-healthy diet is the first diet with cardiovascular benefits, a healthy dietary pattern that fits Chinese food culture that can effectively reduce the risk of CMD has not been found.

METHODS/DESIGN

The study is a single-centre, open-label, randomised controlled trial aimed at evaluating the effect of the Reducing Cardiometabolic Diseases Risk (RCMDR) dietary pattern in reducing the risk of CMDs in people with dyslipidaemia and providing a reference basis for constructing a dietary pattern suitable for the prevention of CMDs in the Chinese population. Participants are men and women aged 35-45 years with dyslipidaemia in Tianjin. The target sample size is 100. After the run-in period, the participants will be randomised to the RCMDR dietary pattern intervention group or the general health education control group with a 1:1 ratio. The intervention phases will last 12 weeks, with a dietary intervention of 5 working days per week for participants in the intervention group. The primary outcome variable is the cardiometabolic risk score. The secondary outcome variables are blood lipid, blood pressure, blood glucose, body composition indices, insulin resistance and 10-year risk of cardiovascular diseases.

ETHICS AND DISSEMINATION

The study complies with the Measures for Ethical Review of Life Sciences and Medical Research Involving Human Beings and the Declaration of Helsinki. Signed informed consent will be obtained from all participants. The study has been approved by the Medical Ethics Committee of the Second Hospital of Tianjin Medical University (approval number: KY2023020). The results from the study will be disseminated through publications in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry (ChiCTR2300072472).

Comprehensive analysis of phospholipid in milk and their biological roles as nutrients and biomarkers

Phospholipids (PL) have garnered significant attention due to their physiological activities. Milk and other dairy products are important dietary sources for humans and have been extensively used to analyze the presence of PL by various analytical techniques. In this paper, the analysis techniques of PL were reviewed with the eight trigrams of phospholipidomics and a comprehensive fingerprint of 1295 PLs covering 8 subclasses in milk and other dairy products, especially. Technology is the primary productive force. Based on phospholipidomics technology, we further review the relationship between the composition of PL and factors that may be involved in processing and experimental operation, and emphasized the significance of the biological role played by PL in dietary supplements and biomarkers (production, processing and clinical research), and providing the future research directions.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study

INTRODUCTION

Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites.

RESEARCH DESIGN AND METHODS

This study is based on 1124 participants aged 61-82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin.

RESULTS

Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1-4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models.

CONCLUSIONS

Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed.

Low sphingolipid levels predict poor survival in patients with alcohol-related liver disease

Background & Aims

Alcohol-related hepatitis (AH) and alcohol-related cirrhosis are grave conditions with poor prognoses. Altered hepatic lipid metabolism can impact disease development and varies between different alcohol-related liver diseases. Therefore, we aimed to investigate lipidomics and metabolomics at various stages of alcohol-related liver diseases and their correlation with survival.

Methods

Patients with newly diagnosed alcohol-related cirrhosis, who currently used alcohol (ALC-A), stable outpatients with decompensated alcohol-related cirrhosis with at least 8 weeks of alcohol abstinence (ALC), and patients with AH, were compared with each other and with healthy controls (HC). Circulating lipids and metabolites were analysed using HPLC and mass spectrometry.

Results

Forty patients with ALC, 95 with ALC-A, 30 with AH, and 42 HC provided plasma. Lipid levels changed according to disease severity, with generally lower levels in AH and cirrhosis than in the HC group; this was most pronounced for AH, followed by ALC-A. Nine out of 10 free fatty acids differed between cirrhosis groups by relative increases of 0.12-0.66 in ALC compared with the ALC-A group (p <0.0005). For metabolomics, total bile acids increased by 19.7, 31.3, and 80.4 in the ALC, ALC-A, and AH groups, respectively, compared with HC (all p <0.0001). Low sphingolipid ([d42:1] and [d41:1]) levels could not predict 180-day mortality (AUC = 0.73, p = 0.95 and AUC = 0.73, p = 0.95) more accurately than the model for end-stage liver disease score (AUC = 0.71), but did predict 90-day mortality (AUC d42:1 = 0.922, AUC d41:1 = 0.893; pd42:1 = 0.005, pd41:1 = 0.007) more accurately than the MELD score AUCMELD = 0.70, pMELD = 0.19).

Conclusions

Alcohol-related severe liver disease is characterised by low lipid levels progressing with severity of liver disease, especially low sphingomyelins, which also associate to poor prognoses.

Impact and implications

Lipidomics has the potential to diagnose and risk stratify patients with liver diseases. Lipidomics differed between patients with alcohol-related hepatitis and alcohol-related cirrhosis with and without recent alcohol use. Furthermore, lipidomics could predict short-term mortality and might be suitable as a prognostic tool in the future.

Clinical Trials Registration

Scientific Ethics Committee of the Capital Region of Denmark, journal no. H-21013476.

Plasma lipidomic profiling reveals six candidate biomarkers for the prediction of incident stroke in patients with hypertension

INTRODUCTION

The burden of stroke in patients with hypertension is very high, and its prediction is critical.

OBJECTIVES

We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension.

METHODS

This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension.

RESULTS

Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783-0.957).

CONCLUSIONS

We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke.

Unraveling the link between dietary factors and cardiovascular metabolic diseases: Insights from a two-sample Mendelian Randomization investigation

BACKGROUND

When specific nutrients are inadequate, vulnerability to cardiovascular and metabolic illnesses increases. The data linking dietary nutrition with these illnesses, however, has been sparse in the past observational research and randomized controlled trials.

OBJECTIVES

A Mendelian randomization (MR) analysis was performed to assess the influence of macronutrients (fat, protein, sugar, and carbohydrates) and micronutrients (β-carotene, folate, calcium, iron, copper, magnesium, phosphorus, selenium, zinc, vitamin C, vitamin D, vitamin B, and vitamin B12) on the susceptibility to cardiovascular metabolic disorders, including coronary artery disease, heart failure, ischemic stroke, and type 2 diabetes.

METHODS

We employed a two-sample Mendelian randomization (MR) analysis, utilizing inverse variance weighting and conducting comprehensive sensitivity assessments. We obtained publicly accessible summary data from separate cohorts comprising individuals of European ancestry. The level of statistical significance was established at a threshold of P < 0. 00074.

RESULTS

Based on our research findings, we have established a causal association between the consumption of circulating fat and the development of cardiovascular and metabolic diseases. The study found that an increase of one standard deviation in fat consumption was associated with a decreased risk of heart failure, with an odds ratio of 0. 56 (95 % CI: 0. 40-0. 79; p = 0. 0007). Notably, various sensitivity analyses confirmed the robustness of this association. Conversely, we did not find any significant correlation between other dietary components and the risk of cardiovascular and metabolic disorders.

CONCLUSION

Our research findings demonstrate a conspicuous impact of dietary fat consumption on the susceptibility to heart failure, independent of coronary artery disease, diabetes, and stroke. Consequently, it is indicated that dietary factors are unrelated to the predisposition to cardiovascular metabolic disorders.

Inter-organ crosstalk during development and progression of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by tissue-specific insulin resistance and pancreatic β-cell dysfunction, which result from the interplay of local abnormalities within different tissues and systemic dysregulation of tissue crosstalk. The main local mechanisms comprise metabolic (lipid) signalling, altered mitochondrial metabolism with oxidative stress, endoplasmic reticulum stress and local inflammation. While the role of endocrine dysregulation in T2DM pathogenesis is well established, other forms of inter-organ crosstalk deserve closer investigation to better understand the multifactorial transition from normoglycaemia to hyperglycaemia. This narrative Review addresses the impact of certain tissue-specific messenger systems, such as metabolites, peptides and proteins and microRNAs, their secretion patterns and possible alternative transport mechanisms, such as extracellular vesicles (exosomes). The focus is on the effects of these messengers on distant organs during the development of T2DM and progression to its complications. Starting from the adipose tissue as a major organ relevant to T2DM pathophysiology, the discussion is expanded to other key tissues, such as skeletal muscle, liver, the endocrine pancreas and the intestine. Subsequently, this Review also sheds light on the potential of multimarker panels derived from these biomarkers and related multi-omics for the prediction of risk and progression of T2DM, novel diabetes mellitus subtypes and/or endotypes and T2DM-related complications.

Exploring a novel therapeutic strategy: the interplay between gut microbiota and high-fat diet in the pathogenesis of metabolic disorders

In the past two decades, the rapid increase in the incidence of metabolic diseases, including obesity, diabetes, dyslipidemia, non-alcoholic fatty liver disease, hypertension, and hyperuricemia, has been attributed to high-fat diets (HFD) and decreased physical activity levels. Although the phenotypes and pathologies of these metabolic diseases vary, patients with these diseases exhibit disease-specific alterations in the composition and function of their gut microbiota. Studies in germ-free mice have shown that both HFD and gut microbiota can promote the development of metabolic diseases, and HFD can disrupt the balance of gut microbiota. Therefore, investigating the interaction between gut microbiota and HFD in the pathogenesis of metabolic diseases is crucial for identifying novel therapeutic strategies for these diseases. This review takes HFD as the starting point, providing a detailed analysis of the pivotal role of HFD in the development of metabolic disorders. It comprehensively elucidates the impact of HFD on the balance of intestinal microbiota, analyzes the mechanisms underlying gut microbiota dysbiosis leading to metabolic disruptions, and explores the associated genetic factors. Finally, the potential of targeting the gut microbiota as a means to address metabolic disturbances induced by HFD is discussed. In summary, this review offers theoretical support and proposes new research avenues for investigating the role of nutrition-related factors in the pathogenesis of metabolic disorders in the organism.

Blood-Derived Lipid and Metabolite Biomarkers in Cardiovascular Research from Clinical Studies: A Recent Update

The primary prevention, early detection, and treatment of cardiovascular disease (CVD) have been long-standing scientific research goals worldwide. In the past decades, traditional blood lipid profiles have been routinely used in clinical practice to estimate the risk of CVDs such as atherosclerotic cardiovascular disease (ASCVD) and as treatment targets for the primary prevention of adverse cardiac events. These blood lipid panel tests often fail to fully predict all CVD risks and thus need to be improved. A comprehensive analysis of molecular species of lipids and metabolites (defined as lipidomics and metabolomics, respectively) can provide molecular insights into the pathophysiology of the disease and could serve as diagnostic and prognostic indicators of disease. Mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based lipidomics and metabolomics analysis have been increasingly used to study the metabolic changes that occur during CVD pathogenesis. In this review, we provide an overview of various MS-based platforms and approaches that are commonly used in lipidomics and metabolomics workflows. This review summarizes the lipids and metabolites in human plasma/serum that have recently (from 2018 to December 2022) been identified as promising CVD biomarkers. In addition, this review describes the potential pathophysiological mechanisms associated with candidate CVD biomarkers. Future studies focused on these potential biomarkers and pathways will provide mechanistic clues of CVD pathogenesis and thus help with the risk assessment, diagnosis, and treatment of CVD.

High dietary intake of unsaturated fatty acids is associated with improved insulin resistance - a cross-sectional study based on the NHANES database

BACKGROUND

A moderate intake of unsaturated fatty acids (UFA) is associated positively with improved insulin resistance. The aim of this study was to investigate the relationship between the dietary intake of unsaturated fatty acids/total fats (UFA/TF) and insulin resistance.

METHODS

15,560 participants were selected from the National Health and Nutrition Examination Survey (NHANES) database enrolled between March 2017 and 2020, and excluded those under 20 years of age, pregnant, or with missing data for key research items. Finally, 7,630 participants were included in the study. R software was used for data analysis that included: (1) general descriptive statistics; (2) comparison of differences in baseline information of three UFA/TF groups, namely low, medium, and high ratios; (3) calculation of the correlation between the UFA/TF ratio and markers of insulin resistance: triglyceride-glucose index (TyG) and homeostatic model assessment for insulin resistance (HOMA-IR); (4) stratification of the study subjects into two groups, with or without insulin resistance, using a cut-off value of HOMA-IR ≥ 2, followed by logistic regression analysis to examine the relationship between UFA/TF and insulin resistance status in the two groups; and (5) further stratification of the subjects according to age, gender, body mass index (BMI), race, total energy intake, total protein, total carbohydrate, total sugars, total dietary fiber, total fat, alcohol consumption, diabetes, hypercholesterolemia to analyze the impact of UFA/TF on insulin resistance status in different subgroups.

RESULTS

(1) A high UFA/TF level was associated with a low TyG index and HOMA-IR [β (vs. TyG index) = -0.559, 95% CI: (-0.821~-0.297), P < 0.001; β (vs. HOMA-IR) = -0.742, 95% CI: (-1.083~-0.402), P < 0.001]. This negative relationship became more pronounced when UFA/TF exceeded 57.9% (i.e., the higher group). (2) Logistic regression analysis showed that a higher UFA/TF level was associated with a lower risk of developing insulin resistance [Q3 vs. Q1: 0.838 (95%CI: 0.709 ~ 0.991); P for trend = 0.038]. After adjusting for covariates such as gender, age, and BMI, this protective effect remained significant (P value < 0.05). (3) Analysis also showed that increased UFA/TF intake reduced the risk of developing insulin resistance (OR = 0.266, 95% CI: (0.075 ~ 0.946), P = 0.041). Subgroup analysis showed that although elevated UFA/TF intake showed no statistically significant difference in its effect in most subgroups, the large study population in this study provides valuable insights on potential changes. Increased UFA/TF intake may confer relatively greater benefits within specific subgroups, particularly among the elderly [Q3 age group, OR = 0.114, 95%CI: (0.012 ~ 1.078), P = 0.058], females [OR = 0.234, 95%CI: (0.041 ~ 1.333), P = 0.102], those with a BMI ≤ 25 kg/m²[OR = 0.191, 95%CI: (0.016 ~ 2.344), P = 0.196], and individuals without hypercholesterolemia [OR = 0.207, 95%CI: (0.042 ~ 1.013), P = 0.0519]. The impact of high UFA/TF levels within subgroups based on the presence or absence of coronary heart disease and stroke displayed contrasting trends. In those without coronary heart disease, there was a significant protective effect against insulin resistance [OR = 0.254, 95% CI: (0.07 ~ 0.929), P = 0.0384], while in the stroke subgroup, a significantly protective effect against insulin resistance was observed [OR = 0.002, 95%CI: (0 ~ 0.695), P = 0.0376].

CONCLUSION

A high dietary intake of UFA relative to total fat consumption could be a protective factor against the risk of developing insulin resistance.

Nutritional metabolomics: Recent developments and future needs

Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on the recent developments and updates in the field, including the analytical methodologies that encompass improved instrument sensitivity, sampling techniques and data integration (multiomics). Metabolomics has advanced the discovery and validation of dietary biomarkers and their implementation in health research. Metabolomics has come to play an important role in the understanding of the role of small molecules resulting from the diet-microbiota interactions when gut microbiota research has shifted towards improving the understanding of the activity and functionality of gut microbiota rather than composition alone. Currently, metabolomics plays an emerging role in precision nutrition and the recent developments therein are discussed.

Distinct patterns of personalised dietary advice delivered by a metabotype framework similarly improve dietary quality and metabolic health parameters: secondary analysis of a randomised controlled trial

Background

In a 12-week randomised controlled trial, personalised nutrition delivered using a metabotype framework improved dietary intake, metabolic health parameters and the metabolomic profile compared to population-level dietary advice. The objective of the present work was to investigate the patterns of dietary advice delivered during the intervention and the alterations in dietary intake and metabolic and metabolomic profiles to obtain further insights into the effectiveness of the metabotype framework.

Methods

Forty-nine individuals were randomised into the intervention group and subsequently classified into metabotypes using four biomarkers (triacylglycerol, HDL-C, total cholesterol, glucose). These individuals received personalised dietary advice from decision tree algorithms containing metabotypes and individual characteristics. In a secondary analysis of the data, patterns of dietary advice were identified by clustering individuals according to the dietary messages received and clusters were compared for changes in dietary intake and metabolic health parameters. Correlations between changes in blood clinical chemistry and changes in metabolite levels were investigated.

Results

Two clusters of individuals with distinct patterns of dietary advice were identified. Cluster 1 had the highest percentage of messages delivered to increase the intake of beans and pulses and milk and dairy products. Cluster 2 had the highest percentage of messages delivered to limit the intake of foods high in added sugar, high-fat foods and alcohol. Following the intervention, both patterns improved dietary quality assessed by the Alternate Mediterranean Diet Score and the Alternative Healthy Eating Index, nutrient intakes, blood pressure, triacylglycerol and LDL-C (p ≤ 0.05). Several correlations were identified between changes in total cholesterol, LDL-C, triacylglycerol, insulin and HOMA-IR and changes in metabolites levels, including mostly lipids (sphingomyelins, lysophosphatidylcholines, glycerophosphocholines and fatty acid carnitines).

Conclusion

The findings indicate that the metabotype framework effectively personalises and delivers dietary advice to improve dietary quality and metabolic health.

Clinical trial registration

isrctn.com, identifier ISRCTN15305840.

Association of Serum Very-Long-Chain Saturated Fatty Acids With Changes in Insulin Sensitivity and β-Cell Function: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort

A unique group of circulating very-long-chain saturated fatty acids (VLCSFAs), including arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0), have been associated with a lower risk of type 2 diabetes, although associations with early metabolic risk phenotypes preceding type 2 diabetes have received limited study. We aimed to examine the associations of VLCSFAs with longitudinal changes in insulin sensitivity and β-cell function in a cohort at risk for type 2 diabetes. VLCSFAs in the four main serum pools (phospholipid, triacylglycerol, cholesteryl ester, and nonesterified fatty acid) were extracted from fasting baseline samples (n = 467). Generalized estimating equations were used to determine the associations between VLCSFAs and changes over 9 years in validated indices of insulin sensitivity (HOMA2-%S [insulin sensitivity as percentage of normal population and ISI) and β-cell function (insulinogenic index [IGI], IGI divided by HOMA-insulin resistance [IGI/IR], and insulin secretion sensitivity index 2 [ISSI-2]). Associations of VLCSFAs with outcomes were strongest in the triacylglycerol lipid pool: 20:0 was positively associated with both insulin sensitivity and β-cell function (5.01% increase in HOMA2-%S and 4.01-6.28% increase in IGI/IR and ISSI-2 per SD increase in 20:0); 22:0 was positively associated with insulin sensitivity, with a 6.55% increase in HOMA2-%S and a 5.80% increase in ISI per SD increase in 22:0. Lastly, 24:0 was positively associated with insulin sensitivity and β-cell function (7.94-8.45% increase in HOMA2-%S and ISI, and a 4.61-6.93% increase in IGI/IR and ISSI-2 per SD increase in 24:0). Fewer significant associations were observed in the cholesteryl ester and nonesterified pools. Overall, our results indicate positive longitudinal associations of VLCSFAs with insulin sensitivity and β-cell function, especially within the triacylglycerol pool.

ARTICLE HIGHLIGHTS

The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study

Lipid signaling is involved in longevity regulation, but which specific lipid molecular species affect human biological aging remains largely unknown. We investigated the relation between complex lipids and DNA methylation-based metrics of biological aging among 4181 participants (mean age 55.1 years (range 30.0-95.0)) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. The absolute concentration of 14 lipid classes, covering 964 molecular species and 267 fatty acid composites, was measured by Metabolon Complex Lipid Panel. DNA methylation-based metrics of biological aging (AgeAccelPheno and AgeAccelGrim) were calculated based on published algorithms. Epigenome-wide association analyses (EWAS) of biological aging-associated lipids and pathway analysis were performed to gain biological insights into the mechanisms underlying the effects of lipidomics on biological aging. We found that higher levels of molecular species belonging to neutral lipids, phosphatidylethanolamines, phosphatidylinositols, and dihydroceramides were associated with faster biological aging, whereas higher levels of lysophosphatidylcholine, hexosylceramide, and lactosylceramide species were associated with slower biological aging. Ceramide, phosphatidylcholine, and lysophosphatidylethanolamine species with odd-numbered fatty acid tail lengths were associated with slower biological aging, whereas those with even-numbered chain lengths were associated with faster biological aging. EWAS combined with functional pathway analysis revealed several complex lipids associated with biological aging as important regulators of known longevity and aging-related pathways.

Lipid Profile after Pharmacologic Discontinuation and Restoration of Menstruation in Women with Endometriosis: A 12-Month Observational Prospective Study

The lipid profile is affected following menstrual cessation (MC). We aimed to evaluate the effects of goserelin-induced MC and subsequent menstrual restoration (MR) on lipid metabolism. Premenopausal women with histologically verified endometriosis (n = 15) received goserelin monthly for 6 months (6mο), resulting in MC, and were followed-up for another 6 months after MR (12mο). Serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), lipoprotein a ([Lp(a)] and lipidomics were measured at baseline, 6mo and 12mo. Shotgun quantitative deep lipidomics were determined at the level of lipid class category, subclass, species, and fatty acyl chain lengths and degree of saturation. TC (p = 0.006), LDL-C (p = 0.028), HDL-C (p = 0.002), and apoA1 (p = 0.013) increased during goserelin-induced MC and remained practically unchanged during MR. TG, apoB, and Lp(a) did not change. From the deep lipidomics analysis, multivariate statistical analysis demonstrated profound alterations in lipid species with MC, whereas no statistically valid models could be fitted for the restoration period. In conclusion, GnRH-analog-induced MC alters lipid profiles at various levels, from standard blood lipid and lipoprotein profiles to several lipid species as detected by lipidomics analysis. Changes largely persist for at least 6 m after MR.

Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study

OBJECTIVE

We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk.

METHODS

This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out.

RESULTS

LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%.

CONCLUSION

Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937.

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.

Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications

Lipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profile in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two sex and age-matched groups: obese (body mass index-BMI ≥ 30 kg/m2; n = 36) and non-obese (BMI < 30 kg/m2; n = 36). The lipidomic profiles were evaluated in plasma using 1H nuclear magnetic resonance (1H-NMR) spectroscopy. Obese individuals had higher waist circumference (p < 0.001), visceral adiposity index (p = 0.029), homeostatic model assessment insulin resistance (HOMA-IR) (p = 0.010), and triacylglycerols (TAG) levels (p = 0.018). 1H-NMR analysis identified higher amounts of saturated lipid metabolite fragments, lower levels of unsaturated lipids, and some phosphatidylcholine species in the obese group. Two powerful machine learning (ML) models-k-nearest neighbors (kNN) and XGBoost (XGB) were employed to characterize the lipidomic profile of obese individuals. The results revealed metabolic alterations associated with obesity in the NMR signals. The models achieved high accuracy of 86% and 81%, respectively. The feature importance analysis identified signal at 1.50-1.60 ppm (-CO-CH2-CH2-, Cholesterol and fatty acid in TAG, Phospholipids) to have the highest importance in the two models.

Lipidomics and pancreatic cancer risk in two prospective studies

Pancreatic ductal carcinoma (PDAC) is highly fatal with limited understanding of mechanisms underlying its carcinogenesis. We comprehensively investigated whether lipidomic measures were associated with PDAC in two prospective studies. We measured 904 lipid species and 252 fatty acids across 15 lipid classes in pre-diagnostic serum (up to 24 years) in a PDAC nested-case control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, NCT00002540) with 332 matched case-control sets including 272 having serial blood samples and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, NCT00342992) with 374 matched case-control sets. Controls were matched to cases by cohort, age, sex, race, and date at blood draw. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) per one-standard deviation increase in log-lipid concentrations within each cohort, and combined ORs using fixed-effects meta-analyses. Forty-three lipid species were associated with PDAC (false discovery rate, FDR ≤ 0.10), including lysophosphatidylcholines (LPC, n = 2), phosphatidylethanolamines (PE, n = 17), triacylglycerols (n = 13), phosphatidylcholines (PC, n = 3), diacylglycerols (n = 4), monoacylglycerols (MAG, n = 2), cholesteryl esters (CE, n = 1), and sphingomyelins (n = 1). LPC(18:2) and PE(O-16:0/18:2) showed significant inverse associations with PDAC at the Bonferroni threshold (P value < 5.5 × 10-5). The fatty acids LPC[18:2], LPC[16:0], PC[15:0], MAG[18:1] and CE[22:0] were significantly associated with PDAC (FDR < 0.10). Similar associations were observed in both cohorts. There was no significant association for the differences between PLCO serial lipidomic measures or heterogeneity by follow-up time overall. Results support that the pre-diagnostic serum lipidome, including 43 lipid species from 8 lipid classes and 5 fatty acids, is associated with PDAC.

Long-term consumption of different doses of Grifola frondosa affects immunity and metabolism: correlation with intestinal mucosal microbiota and blood lipids

Grifola frondosa (GF) is an edible mushroom with hypoglycemic and hypolipidemic effects. In this study, the specific pathogen-free male mice were randomized into the normal (NM), low-dose GF (LGF), medium-dose GF (MGF), and high-dose GF (HGF) groups. The LGF, MGF, and HGF groups were fed with 1.425 g/(kg d), 2.85 g/(kg d), and 5.735 g/(kg d) of GF solution for 8 weeks. After feeding with GF solution, compared with the NM group, the thymus index was significantly increased in the LGF group, and TC, TG, and LDL of mice were significantly increased in the HGF group, while HDL was significantly decreased. Compared with the NM group, the uncultured Bacteroidales bacterium, Ligilactobacillus increased in the LGF group, and Candidatus Arthromitus increased in the MGF group. The characteristic bacteria of the HGF group included Christensenellaceae R7, unclassified Clostridia UCG 014, unclassified Eubacteria coprostanoligenes, and Prevotellaceae Ga6A1. Among them, Ligilactobacillus showed a negative correlation with HDL. Unclassified Eubacterium coprostanoligenes group and Ligilactobacillus showed a positive correlation with TG. In summary, our experiments evidenced that GF improves lipid metabolism disorders by regulating the intestinal microbiota, providing a new pathway for hypolipidemic using GF dietary.

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.

Lipid Profiling Reveals Lipidomic Signatures of Weight Loss Interventions

Obesity is an epidemic all around the world. Weight loss interventions that are effective differ from each other with regard to various lipidomic responses. Here, we aimed to find lipidomic biomarkers that are related to beneficial changes in weight loss. We adopted an untargeted liquid chromatography with tandem mass spectrometry (LC-MS/MS) method to measure 953 lipid species for Exercise (exercise intervention cohort, N = 25), 1388 lipid species for LSG (laparoscopic sleeve gastrectomy cohort, N = 36), and 886 lipid species for Cushing (surgical removal of the ACTH-secreting pituitary adenomas cohort, N = 25). Overall, the total diacylglycerol (DG), triacylglycerol (TG), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), and sphingomyelin (SM) levels were associated with changes in BMI, glycated hemoglobin (HbA1c), triglyceride, and total cholesterol according to weight loss interventions. We found that 73 lipid species changed among the three weight loss interventions. We screened 13 lipid species with better predictive accuracy in diagnosing weight loss situations in either Exercise, LSG, or Cushing cohorts (AUROC > 0.7). More importantly, we identified three phosphatidylcholine (PC) lipid species, PC (14:0_18:3), PC (31:1), and PC (32:2) that were significantly associated with weight change in three studies. Our results highlight potential lipidomic biomarkers that, in the future, could be used in personalized approaches involving weight loss interventions.

Gut microbiome lipid metabolism and its impact on host physiology

Metabolites produced by commensal gut microbes impact host health through their recognition by the immune system and their influence on numerous metabolic pathways. Notably, the gut microbiota can both transform and synthesize lipids as well as break down dietary lipids to generate secondary metabolites with host modulatory properties. Although lipids have largely been consigned to structural roles, particularly in cell membranes, recent research has led to an increased appreciation of their signaling activities, with potential impacts on host health and physiology. This review focuses on studies that highlight the functions of bioactive lipids in mammalian physiology, with a special emphasis on immunity and metabolism.