The role of serum lipid in predicting coronary artery lesions and intravenous immunoglobulin resistance in Kawasaki disease: a cohort study.

OBJECTIVE: To assess the predictive value of the serum lipid profile for initial intravenous immunoglobulin (IVIG) resistance and coronary artery lesions (CALs) in patients with Kawasaki disease (KD). METHODS: This retrospective cohort study enrolled patients with KD and divided them into IVIG-responsive and IVIG-resistant groups. They were also stratified based on the presence of CALs (CALs and non-CALs groups). Clinical, echocardiographic and biochemical values were evaluated. A subgroup analysis was performed on complete and incomplete KD. Predictors of initial IVIG resistance and CALs were determined by multivariate logistic regression analysis. RESULTS: A total of 649 KD patients were enrolled: 151 had CALs and 76 had initial IVIG resistance. Low-density lipoprotein cholesterol (LDL-C) was significantly lower in the IVIG-resistant group than in the IVIG-responsive group. LDL-C and apolipoprotein (Apo) B were significantly lower in the CALs group compared with the non-CALs group. Multivariate logistic regression failed to identify the serum lipid profile (LDL-C, Apo A or Apo B) as an independent risk factor for initial IVIG resistance or CALs in KD patients. CONCLUSION: KD patients might have dyslipidaemia in the acute phase, but the serum lipid profile might not be suitable as a single predictor for initial IVIG resistance or CALs.

The association between alcohol consumption and blood lipids in Chinese children and adolescent: findings from the China Health and Nutrition Survey.

BACKGROUND: Alcohol consumption by children and adolescents is receiving increasing attention. It may cause dyslipidemia, a risk factor for cardiovascular disease. However, the association between alcohol consumption and blood lipids in children and adolescents is unclear, and so we aimed to characterize this association. METHODS: Data from the China Health and Nutrition Survey were extracted from children and adolescents aged 7-18 years for whom information was available on alcohol consumption. The population was divided into drinking and nondrinking groups. The χ2, Student's t, or Mann-Whitney U test was used to compare groups. Univariate and multivariate linear regression and propensity score matching (PSM) analysis were used to identify the association between alcohol consumption and blood lipids. RESULTS: This study included 408 children and adolescents with 35 drinkers and 373 nondrinkers. The drinkers had significantly lower values of total cholesterol (TC) (3.8 mmol/L for nondrinkers versus 3.5 mmol/L for drinkers, p = 0.002) and high-density lipoprotein cholesterol (HDL-C) (1.3 mmol/L for nondrinkers versus 1.2 mmol/L for drinkers, p = 0.007), but not for low-density lipoprotein cholesterol (LDL-C) (2.1 mmol/L for nondrinkers versus 2.0 mmol/L for drinkers, p = 0.092) or triglyceride (TG) (0.9 mmol/L for nondrinkers versus 0.8 mmol/L for drinkers, p = 0.21). The univariate and multivariate analyses led to the same conclusions. After PSM there was still a significant negative association between alcohol consumption and TC or HDL-C. CONCLUSION: Alcohol consumption in children and adolescents exhibited significant negative associated with TC and HDL-C, but not with LDL-C or TG. These findings need to be confirmed in future prospective research, and the health effects of blood lipid changes caused by drinking in children and adolescents need to be clarified.

Low-density lipoprotein particle profiles compared with standard lipids measurements in the association with asymptomatic intracranial artery stenosis.

The Shiga Epidemiological Study of Subclinical Atherosclerosis was conducted in Kusatsu City, Shiga, Japan, from 2006 to 2008. Participants were measured for LDL-p through nuclear magnetic resonance technology. 740 men participated in follow-up and underwent 1.5 T brain magnetic resonance angiography from 2012 to 2015. Participants were categorized as no-ICAS, and ICAS consisted of mild-ICAS (1 to < 50%) and severe-ICAS (≥ 50%) in any of the arteries examined. After exclusion criteria, 711 men left for analysis, we used multiple logistic regression to examine the association between lipid profiles and ICAS prevalence. Among the study participants, 205 individuals (28.8%) had ICAS, while 144 individuals (20.3%) demonstrated discordance between LDL-c and LDL-p levels. The discordance "low LDL-c-high LDL-p" group had the highest ICAS risk with an adjusted OR (95% CI) of 2.78 (1.55-5.00) in the reference of the concordance "low LDL-c-low LDL-p" group. This was followed by the concordance "high LDL-c-high LDL-p" group of 2.56 (1.69-3.85) and the discordance "high LDL-c-low LDL-p" group of 2.40 (1.29-4.46). These findings suggest that evaluating LDL-p levels alongside LDL-c may aid in identifying adults at a higher risk for ICAS.

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort.

BACKGROUND: Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. METHODS: We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. RESULTS: Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. CONCLUSION: Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study.

BACKGROUND: Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese. METHODS: The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression. RESULTS: The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term (P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term (P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods (P > 0.05). CONCLUSION: The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.

Lipids, apolipoproteins and gestational diabetes mellitus: a Mendelian randomization study.

BACKGROUND: This study investigates the causal relationship between lipid traits and GDM in an effort to better understand the aetiology of GDM. METHODS: Employing a two-sample Mendelian Randomization (MR) framework, we used Single Nucleotide Polymorphisms (SNPs) as instrumental variables to examine the impact of lipids and apolipoproteins on GDM. The research comprised univariable and multivariable MR analyses, with a prime focus on individual and combined effects of lipid-related traits. Statistical techniques included the fixed-effect inverse variance weighted (IVW) method and supplementary methods such as MR-Egger for comprehensive assessment. RESULTS: Our findings revealed the following significant associations: apoA-I and HDL cholesterol were inversely correlated with GDM risk, while triglycerides showed a positive correlation. In multivariable analysis, apoA-I consistently exhibited a strong causal link with GDM, even after adjusting for other lipids and Body Mass Index (BMI). CONCLUSION: The study demonstrates a significant causal relationship between apoA-I and GDM risk.

Comparative study of melasma in patients before and after treatment based on lipomics.

BACKGROUND: Skin barrier alterations play a crucial function in melasma development. Past researches have demonstrated variations in lipid content between the epidermis of melasma lesions and normal tissues, along with the varied expression of lipid-related genes in melasma. This study aimed to analyze the lipidome profiles of skin surface lipids (SSL) in patients with melasma before and after treatment to understand associated abnormalities. METHODS: Melasma was treated with tranexamic acid orally and hydroquinone cream topically. Disease was assessed using the Melasma Area and Severity Index (MASI), and the impact to life was evaluated with Melasma Quality of Life (MELASQoL) score. Epidermal melanin particles were observed using reflection confocal microscopy (RCM), whereas epidermal pigment and blood vessel morphology were observed using dermoscopy, and SSL samples were collected. Specific information regarding alterations in lipid composition was obtained through multivariate analysis of the liquid chromatography-mass spectrometry data. RESULTS: After treatment, patients with melasma exhibited decreased MASI and MELASQoL scores (P < 0.001); RCM revealed reduced melanin content in the lesions, and dermoscopy revealed fewer blood vessels. Fifteen lipid subclasses and 382 lipid molecules were identified using lipidomic assays. The expression levels of total lipids, phosphatidylcholine, and phosphatidylethanolamine in the melasma lesions decreased after treatment (P < 0.05). CONCLUSION: This study revealed alterations in the SSL composition after effective melasma treatment, suggesting a compensatory role for lipids in melasma barrier function. The mechanism involving SSL and the lipid barrier, which influences melasma's occurrence, needs further elucidation.

Synchronizing positive effect of vitamin C and chromium on hyper lipidemia, hyperglycemia, liver enzymes and BMI of diabetes mellitus type 2 patients.

This study investigates the combined effect of vitamin C and chromium on BMI, lipid profile, LFTs and HbA1c of Diabetes Mellitus type 2 patients. This is randomized controlled trial study. For this study a total of 60 patients (n=28 female, n=32 male) Diabetes Mellitus type 2 patients were selected. They were divided into treatment group (vitamin C (500mg) Chromium (200µg) and control group (placebo) comprising thirty patients per group. Mean age in control group and treatment group is 33± 5.729 and 33±7.017 respectively. Statistical analysis showed significant results of lipid profile; total cholesterol (mg/dl) 198±66.1 P=0.008, High-Density Lipoprotein 38±7.5, P<0.001, Low Density Lipoprotein (LDL) (mg/dl) 105.1±22.4, P=0.002 and Triglycerides 191±64.3, P=0.02 are respectively. Levels of serum ALT (u/l) (34.7±9.1, P<0.001) and AST (u/l) (31.6 ±8.6, P<0.001) were significantly lower as compared to control group. HbA1c percentages were also normalized (5.45±0.2, P<.001) as compared to group 2. BMI values were also improved (P=0.01) after treatment. Combined supplementation of vitamin C and chromium reduce the plasma lipid percentage, blood glucose levels and also improve the ALT and AST functions.

Effect of Salvia hispanica (Chia seeds) and Foeniculum vulgare (Fennel seeds) against weight-loss and lipid profile in obese human subjects.

Increased levels of bad cholesterol in the body result in increasing blood pressure and weight gain. The rate of mortality in people, especially who are obese, is increasing due to absence of organic sources of fiber in their diets. Chia and fennel seeds are rich sources of fiber. The objective of this study was to evaluate the combined effect of Salvia hispanica (Chia seeds) and Foeniculum vulgare (Fennel seeds) against weight-loss and lipid profile in obese human subjects. The research was conducted on obese people aged 25 to 40 years at the Jinnah Hospital Lahore. The study design was randomized control trial (RCT). The sample size was calculated and was divided in-to two groups. With the duration of study being 3 months, pre-testing of all the participants was done. Group 1 was control group, given placebo treatment and Group 2 was an intervention group and given chia and fennel seeds. Post-testing was done and data were analyzed. Results showed that chia and fennel seeds have significant effect (p <0.05) on BMI and lipid profile hence, both are beneficial for lowering body weight and improving LDL, HDL, serum triglycerides and total cholesterol levels.

Association Between Smoking and Lipid Profile in Men Aged 35 to 70 Years: Dose-Response Analysis.

Dyslipidemia is linked to various health complications, including cardiovascular disease and inflammation. This study aimed to assess the association between smoking and lipid profile in the Tabari cohort population. Data from the Tabari Cohort Study involving 4,149 men were analyzed. A standardized questionnaire collected smoking history, while blood samples measured lipid levels and anthropometric measurements were recorded. Statistical analysis utilized chi-square tests and logistic regression, adjusting for potential confounders. The prevalence of smoking was 893 (21.52%; urban: 20.6%, mountainous: 23.8%, significant level: .024). The adjusted odds ratio (OR) of low high-density lipoprotein (HDL) among smokers 1.48 (95% confidence interval [CI]: 1.25-1.77, p < .001) was the same as non-smokers. The adjusted OR of high low-density lipoprotein (LDL) in men with 1 to 10, 11 to 20, and more than 20 cigarettes per day was 0.95 (95% CI: 0.73-1.25), 1.30 (95% CI: 0.99-1.71), and 2.64 (95% CI: 1.32-5.27) and low HDL was equal to 1.34 (95% CI: 1.06-1.68), 1.61 (95% CI: 1.26-2.05), and 2.24 (95% CI: 1.13-4.42) compared with non-smokers, respectively. The study findings indicate that smoking is associated with lower HDL levels, even after adjusting for potential confounders. The odds of low HDL and high LDL increases with higher smoking intensity. The low HDL and high LDL levels in individuals smoking over 20 cigarettes/day, respectively, show a 2.24-fold and a 2.64-fold increased odds compared to non-smokers. These findings highlight the importance of smoking cessation in relation to lipid profiles and related health risks.

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.

Effects of acute and chronic stair-climbing exercise on metabolic health: A systematic review.

Stair climbing exercise (SE) provides a feasible approach to elevate physical activity, but the effects on metabolic health are unclear. We systematically reviewed the currently available evidence on the effects of SE on fasting and postprandial glycaemia and lipidaemia. Studies were included if they investigated the effects of acute or chronic (at least 2 weeks) SE on fasting and/or postprandial glycaemic (insulin and glucose) and lipidaemic (triacylglycerols and non-esterified fatty acids) responses in healthy, prediabetic or type 2 diabetic adult populations. PubMed, Web of Science and Scopus were searched for eligible studies until July 2022. A total of 25 studies (14 acute and 11 chronic) were eligible for review. Acute bout(s) of SE can reduce postprandial glycaemia in individuals with prediabetes and type 2 diabetes (8 of 9 studies), but not in normoglycemic individuals. The effects of acute SE on postprandial lipidaemic responses and SE training on both fasting and postprandial glycaemia/lipidaemia were unclear. Acute SE may reduce postprandial glucose concentrations in people with impaired glycaemic control, but high-quality studies are needed. More studies are needed to determine the effect of chronic SE training on postprandial glucose and lipid responses, and the acute effects of SE on lipid responses.

Metabolomic Alterations in Methotrexate Treatment of Moderate-to-Severe Psoriasis.

BACKGROUND Aberrant lipid metabolism alterations in skin tissue, blood, or urine have been implicated in psoriasis. Here, we examined lipid metabolites related to psoriasis and their association with the age of disease onset. MATERIAL AND METHODS Differences in lipid metabolites before and after methotrexate (MTX) treatment were evaluated. The discovery cohort and validation cohort consisted of 50 and 46 patients, respectively, with moderate-to-severe psoriasis. After MTX treatment, the patients were divided into response (Psoriasis Area and Severity Index [PASI] 75 and above) and non-response (PASI below 75) groups, blood was collected for serum metabolomics, and multivariate statistical analysis was performed. RESULTS We detected 1546 lipid metabolites. The proportion of the top 3 metabolites was as follows: triglycerides (TG, 34.8%), phospholipids (PE, 14.5%), phosphatidylcholine (PC, 12.4%); diglycerides (DG) (16: 1/18: 1), and DG (18: 1/18: 1) showed strong positive correlations with onset age. There were marked changes in TG (16: 0/18: 0/20: 0), TG (18: 0/18: 0/22: 0), TG (14: 0/18: 0/22: 0), TG (14: 0/20: 0/20: 0), lysophosphatidylcholine (LPC) (16: 0/0: 0), LPC (18: 0/0: 0), LPC (14: 0/0: 0), and LPC (18: 1/0: 0) levels before and after 12 weeks of MTX treatment. The glycerophospholipid metabolic pathway was implicated in psoriasis development. Of the 96 recruited patients, 35% were MTX responders and 65% non-responders. PE (34: 4) and PE (38: 1) levels were significantly different between the groups. Obvious differences in lipid metabolism were found between early-onset (<40 years) and late-onset (≥40 years) psoriasis. Significant changes in serum lipid profile before and after MTX treatment were observed. CONCLUSIONS The specific lipid level changes in responders may serve as an index for MTX treatment efficacy evaluation.

Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese.

To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut­off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle­aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.

Isotretinoin's Effect on Fasting Lipid Profile in Acne Patients.

OBJECTIVE: To determine the isotretinoin's effect on fasting lipid profile in patients with acne. STUDY DESIGN: Observational study. Place and Duration of the Study: Outpatient Department of Dermatology, Dow International Medical College, Dow University of Health Sciences, Karachi, Pakistan, from 22nd June to 21st December 2022. METHODOLOGY: Patients of clinically moderate and severe acne were selected and prescribed a dose of 0.5mg /kg cap isotretinoin for 6 months. They were advised to get a fasting lipid profile at the baseline and then after two months of isotretinoin therapy. National Cancer Institute Common Terminology Criteria for Adverse Events v5.0 grading system and Adult Treatment Panel III were used for the grading of abnormalities. McNemar Bowker test was used to assess the difference in variables [serum triglycerides (TGs), cholesterol, high-density lipoproteins (HDL), and low-density lipoproteins (LDL)] at the baseline and after 2 months follow-up. RESULTS: A total of 214 patients were evaluated. After 2 months of isotretinoin therapy, TGs and cholesterol levels were elevated to higher grade in 2% of the patients. Likewise in 1% of patients, LDL levels rised to higher grade. Moreover, HDL levels declined to lower grade in 2% of the patients taking isotretinoin. CONCLUSION: Insignificant alterations in the various serum lipid parameters were observed in acne patients during isotretinoin therapy. It is advisable to obtain a baseline fasting lipid profile in all acne patients on isotretinoin and repeated in those with baseline abnormal levels and in patients with a clinical sign of metabolic syndrome and a family history of dyslipidemias. KEY WORDS: Acne, Hyperlipidemias, Isotretinoin, Laboratory monitoring.

Association between lipid profiles and cigarette smoke among adults in the Persian cohort (Shahedieh) study.

OBJECTIVES: Exposure to cigarette smoke introduces a large amount of nicotine into the bloodstream through the lungs. So, smoking can be a risk factor for many diseases. The present study was conducted to investigate the effect of active and passive cigarette smoke on the blood lipid profile and dyslipidemia. METHODS: This cross-sectional study was performed on 5052 individuals who participated in the recruitment phase of the Shahedieh cohort study. A logistic regression model was used to investigate the relationship between smoking exposure status and lipid profiles. RESULTS: The prevalence of abnormal low-density lipoprotein-cholesterol (LDL-C), abnormal HDL-C, abnormal total cholesterol (TC), abnormal triglyceride (TG), and dyslipidemia were 254 (5.00%), 562 (11.10%), 470 (9.30%), 1008 (20.00%), and 1527 (30.20%), respectively. Adjusting for confounders, it was observed that current smokers had higher odds of having abnormal HDL-C [OR (95% CI), 2.90 (2.28-3.69)], abnormal TG [OR (95% CI), 1.71 (1.38-2.13)] and dyslipidemia [OR (95% CI), 1.86 (1.53-2.25)]. Ex-smokers also had greater odds of abnormal HDL-C [OR (95% CI), 1.51 (1.06-2.16)] compared to non-smokers who were not exposed to cigarette smoke. CONCLUSIONS: The findings indicated that current smokers had higher TG and lower HDL. So, necessary measures should be taken to reduce smoking. The findings also showed that the prevalence of abnormal TG and HDL in ex-smokers was lower than in current smokers. Therefore, the existence of incentive policies to quit smoking seems necessary.

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.

INTRODUCTION: Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects. OBJECTIVES: To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations. METHODS: A dual extraction method involving 80% methanol followed by MTBE (methyl tert-butyl ether) extraction enables the analysis of free fatty acids, polar metabolites, and lipids. Extracts from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days were analyzed using HILIC chromatography coupled to Q Exactive Plus mass spectrometer or reversed-phase liquid chromatography coupled to MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility. RESULTS: Lipidomics analysis of 6 mouse tissues and plasma allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that (1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; (2) the impact on lysophosphatidylcholine (lysoPC) and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations; (3) increase of intestinal tricarboxylic acid (TCA) cycle intermediates after metformin treatment. CONCLUSION: The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

Exploration of the application potential of serum multi-biomarker model in colorectal cancer screening.

Analyzing blood lipid and bile acid profile changes in colorectal cancer (CRC) patients. Evaluating the integrated model's diagnostic significance for CRC. Ninety-one individuals with colorectal cancer (CRC group) and 120 healthy volunteers (HC group) were selected for comparison. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoproteins (Apo) A1, ApoA2, ApoB, ApoC2, and ApoC3 were measured using immunoturbidimetric and colorimetric methods. Additionally, LC-MS/MS was employed to detect fifteen bile acids in the serum, along with six tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigens (CA) 125, CA19-9, CA242, CA50, and CA72-4. Group comparisons utilized independent sample t-tests and Mann-Whitney U tests. A binary logistic regression algorithm was applied to fit the indicators and establish a screening model; the diagnostic accuracy of individual Indicators and the model was analyzed using receiver operating characteristic (ROC) curves. The CRC group showed significantly lower levels in eight serum lipid indicators and eleven bile acids compared to the HC group (P < 0.05). Conversely, serum levels of TG, CA19-9, and CEA were elevated (P < 0.05). Among the measured parameters, ApoA2 stands out for its strong correlation with the presence of CRC, showcasing exceptional screening efficacy with an area under the curve (AUC) of 0.957, a sensitivity of 85.71%, and a specificity of 93.33%. The screening model, integrating ApoA1, ApoA2, lithocholic acid (LCA), and CEA, attained an impressive AUC of 0.995, surpassing the diagnostic accuracy of individual lipids, bile acids, and tumor markers. CRC patients manifest noteworthy alterations in both blood lipids and bile acid profiles. A screening model incorporating ApoA1, ApoA2, LCA, and CEA provides valuable insights for detecting CRC.

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer.

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Background: Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods: Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results: A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.