Deciphering the lipid-cancer nexus: comprehensive Mendelian randomization analysis of the associations between lipid profiles and digestive system cancer susceptibility.

BACKGROUND: Digestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear. METHODS: Using a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results. RESULTS: Significant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships. CONCLUSION: Our findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.

Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies.

BACKGROUND: A better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention. METHODS: We included 623 matched case-control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini-Hochberg method was used to correct for multiple comparisons. RESULTS: Sphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways. CONCLUSIONS: This is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.

Lipidomic profiling of human serum enables detection of pancreatic cancer.

Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.

Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients.

Malignant cells differ from benign ones in their metabolome and it is largely unknown whether this difference is reflected in the metabolic profile of their microvesicles (MV), which are secreted into the blood of cancer patients. Here, they are present together with MV from the various blood and endothelial cells. Harvesting MV from 78 breast cancer patients (BC) and 30 controls, we characterized the whole blood MV metabolome using targeted and untargeted mass spectrometry. Especially (lyso)-phosphatidylcholines and sphingomyelins were detected in a relevant abundance. Eight metabolites showed a significant discriminatory power between BC and controls. High concentrations of lysoPCaC26:0 and PCaaC38:5 were associated with shorter overall survival. Comparing BC subtype-specific metabolome profiles, 24 metabolites were differentially expressed between luminal A and luminal B. Pathway analysis revealed alterations in the glycerophospholipid metabolism for the whole cancer cohort and in the ether lipid metabolism for the molecular subtype luminal B. Although this mixture of blood-derived MV contains only a minor number of tumor MV, a combination of metabolites was identified that distinguished between BC and controls as well as between molecular subtypes, and was predictive for overall survival. This suggests that these metabolites represent promising biomarkers and, moreover, that they may be functionally relevant for tumor progression.

Biomarkers of mammographic density in premenopausal women.

BACKGROUND: While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. METHODS: A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers' Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. RESULTS: Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. CONCLUSIONS: We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

Longitudinal associations of physical activity with plasma metabolites among colorectal cancer survivors up to 2 years after treatment.

We investigated longitudinal associations of moderate-to-vigorous physical activity (MVPA) and light-intensity physical activity (LPA) with plasma concentrations of 138 metabolites after colorectal cancer (CRC) treatment. Self-reported physical activity data and blood samples were obtained at 6 weeks, and 6, 12 and 24 months post-treatment in stage I-III CRC survivors (n = 252). Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQp180 kit). Linear mixed models were used to evaluate confounder-adjusted longitudinal associations. Inter-individual (between-participant differences) and intra-individual associations (within-participant changes over time) were assessed as percentage difference in metabolite concentration per 5 h/week of MVPA or LPA. At 6 weeks post-treatment, participants reported a median of 6.5 h/week of MVPA (interquartile range:2.3,13.5) and 7.5 h/week of LPA (2.0,15.8). Inter-individual associations were observed with more MVPA being related (FDR-adjusted q-value < 0.05) to higher concentrations of arginine, citrulline and histidine, eight lysophosphatidylcholines, nine diacylphosphatidylcholines, 13 acyl-alkylphosphatidylcholines, two sphingomyelins, and acylcarnitine C10:1. No intra-individual associations were found. LPA was not associated with any metabolite. More MVPA was associated with higher concentrations of several lipids and three amino acids, which have been linked to anti-inflammatory processes and improved metabolic health. Mechanistic studies are needed to investigate whether these metabolites may affect prognosis.

Prospective analysis of circulating metabolites and endometrial cancer risk.

BACKGROUND: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. RESULTS: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. CONCLUSION: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.

Distinct lipid signatures are identified in the plasma of rats with chronic inflammation induced by estradiol benzoate and sex hormones.

INTRODUCTION: Prostatitis is likely to occur in younger or middle-aged men, while prostate cancer is likely to occur in older men. Although amino acids and lipids as biomarkers of prostate cancer have been examined using prostate cancer cell lines/tissues, no previous studies have evaluated amino acids or lipids as potential chronic prostatitis biomarkers. OBJECTIVES: The study's aim was to identify amino acids and lipids that could serve as potential biomarkers of chronic prostatitis. METHODS: We profiled the amino acids and lipids found in plasma from rats collected in a previous study. In brief, a total of 148 Sprague-Dawley rats (offspring) were dosed with estradiol benzoate (EB) on postnatal days (PNDs) 1, 3 and 5, and subsequently dosed with testosterone (T)/estradiol (E) tubes via subcutaneous implants from PND 90 to 200. Plasma was collected on PNDs 30, 90, 100, 145 and 200. Analysis was conducted with a Xevo TQ-S triple-quadrupole mass spectrometer using a Biocrates AbsoluteIDQ p180 kit. RESULTS: Plasma acylcarnitines [(C2, C16:1, C18, C18:1, C18:1-OH, and C18:2)], glycerophospholipids (lysophosphatidylcholine-acyl, -di-acyl, and -di-acyl acyl-alkyl) and sphingomyelins [SM (OH) C16:1, SM C18:0, SM C18:1, and SM C20:2] significantly increased on PND 145, when chronic inflammation was observed in the dorsolateral prostate of rats dosed with EB, T, and E. No statistical significances of amino acid levels were observed in the EB + T + E group on PND 145. CONCLUSION: Exposure to EB, T, and E altered lipid levels in rat plasma with chronic prostate inflammation. These findings suggest that the identified lipids may be predictive chronic prostatitis biomarkers. The results require confirmation through additional nonclinical and human studies.

Plasma lipidomic analysis of sphingolipids in patients with large artery atherosclerosis cerebrovascular disease and cerebral small vessel disease.

BACKGROUND: Sphingolipids mainly consist of ceramides (Cer), sphingomyelins (SM) and glycosphingolipids. Sphingolipids are related with coronary heart disease and metabolic disease, but there're few studies about cerebrovascular disease. The purpose was to detect sphingolipids in plasma of patients with large artery atherosclerosis (LAA) cerebrovascular disease and cerebral small vessel disease (CSVD) to explore the similarities and differences of pathogenesis of the two subtypes. METHODS: 20 patients with LAA cerebrovascular disease, 20 patients with age-related CSVD, 10 patients with Fabry disease and 14 controls were enrolled from October 2017 to January 2019. Ultra-high performance liquid chromatography-quadruple-time-of-flight mass spectrometry/mass spectrometry was used to determine sphingolipids. Univariate combined with multivariate analysis was used for comparison. Receiver operating characteristic curves were used to determine sensitivities and specificities. RESULTS: 276 sphingolipids were detected, including 39 Cer, 3 ceramide phosphates, 72 glycosphingolipids and 162 SM. (1) Cer (d36:3), Cer (d34:2), Cer (d38:6), Cer (d36:4) and Cer (d16:0/18:1) were increased in LAA; SM (d34:1), Cer (d34:2), Cer (d36:4), Cer (d16:0/18:1), Cer (d38:6), Cer (d36:3) and Cer (d32:0) were increased in age-related CSVD. (2) Cer (d36:4) and SM (d34:1) were increased in age-related CSVD compared with LAA. (3) Total trihexosyl ceramides were increased in Fabry group compared with control (P<0.05); SM (d34:1) was increased in Fabry group. CONCLUSIONS: Ceramides are increased in both LAA and age-related CSVD, which may be related to similar risk factors and pathophysiological process of arteriosclerosis; SM is increased in both age-related CSVD and Fabry disease, suggesting that increased SM may be associated with CSVD. Glycosphingolipids, trihexosylceramides in particular, are increased in Fabry disease.

Plasma Ceramides and Sphingomyelins of Pediatric Patients Increase in Primary Ciliary Dyskinesia but Decrease in Cystic Fibrosis.

We investigated plasma sphingomyelin (CerPCho) and ceramide (Cer) levels in pediatric patients with cystic fibrosis (CF) and primary ciliary dyskinesia (PCD). Plasma samples were obtained from CF (n = 19) and PCD (n = 7) patients at exacerbation, discharge, and stable periods. Healthy children (n = 17) of similar age served as control. Levels of 16-24 CerPCho and 16-24 Cer were measured by LC-MS/MS. Concentrations of all CerPCho and Cer species measured at exacerbation were significantly lower in patients with CF than PCD. 16, 18, 24 CerPCho, and 22, 24 Cer in exacerbation; 18, 24 CerPCho, and 18, 20, 22, 24 Cer at discharge; 18, 24 CerPCho and 24 Cer at stable period were significantly lower in CF patients than healthy children (p < 0.001 and p < 0.05). All CerPCho and Cer levels of PCD patients were significantly higher except 24 CerPCho and 24 Cer during exacerbation, 24 CerPCho at discharge, and 18, 22 CerPCho levels at stable period (p < 0.001 and p < 0.05) compared with healthy children. There was no significant difference among exacerbation, discharge, and stable periods in each group for Cer and CerPCho levels. This is the first study measuring plasma Cer and CerPCho levels in PCD and third study in CF patients. The dramatic difference in plasma levels of most CerPCho and Cer species found between two diseases suggest that cilia pathology in PCD and CFTR mutation in CF seem to alter sphingolipid metabolism possibly in opposite directions.

Plasma metabolites associated with colorectal cancer stage: Findings from an international consortium.

Colorectal cancer is the second most common cause of cancer-related death globally, with marked differences in prognosis by disease stage at diagnosis. We studied circulating metabolites in relation to disease stage to improve the understanding of metabolic pathways related to colorectal cancer progression. We investigated plasma concentrations of 130 metabolites among 744 Stages I-IV colorectal cancer patients from ongoing cohort studies. Plasma samples, collected at diagnosis, were analyzed with liquid chromatography-mass spectrometry using the Biocrates AbsoluteIDQ™ p180 kit. We assessed associations between metabolite concentrations and stage using multinomial and multivariable logistic regression models. Analyses were adjusted for potential confounders as well as multiple testing using false discovery rate (FDR) correction. Patients presented with 23, 28, 39 and 10% of Stages I-IV disease, respectively. Concentrations of sphingomyelin C26:0 were lower in Stage III patients compared to Stage I patients (pFDR < 0.05). Concentrations of sphingomyelin C18:0 and phosphatidylcholine (diacyl) C32:0 were statistically significantly higher, while citrulline, histidine, phosphatidylcholine (diacyl) C34:4, phosphatidylcholine (acyl-alkyl) C40:1 and lysophosphatidylcholines (acyl) C16:0 and C17:0 concentrations were lower in Stage IV compared to Stage I patients (pFDR < 0.05). Our results suggest that metabolic pathways involving among others citrulline and histidine, implicated previously in colorectal cancer development, may also be linked to colorectal cancer progression.

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case-control sets from EPIC.

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.

A Multi-Cohort Metabolomics Analysis Discloses Sphingomyelin (32:1) Levels to be Inversely Related to Incident Ischemic Stroke.

BACKGROUND AND PURPOSE: To search for novel pathophysiological pathways related to ischemic stroke using a metabolomics approach. METHODS: We identified 204 metabolites in plasma by liquid chromatography mass spectrometry in 3 independent population-based samples (TwinGene, Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) and Uppsala Longitudinal Study of Adult Men). TwinGene was used for discovery and the other 2 samples were meta-analyzed as replication. In PIVUS, traditional cardiovascular (CV) risk factors, multiple markers of subclinical CV disease, markers of coagulation/fibrinolysis were measured and analyzed in relation to top metabolites. RESULTS: In TwinGene (177 incident cases, median follow-up 4.3 years), levels of 28 metabolites were associated with incident ischemic stroke at a false discover rate (FDR) of 5%. In the replication (together 194 incident cases, follow-up 10 and 12 years, respectively), only sphingomyelin (32:1) was significantly associated (HR .69 per SD change, 95% CI .57-0.83, P value = .00014; FDR <5%) when adjusted for systolic blood pressure, diabetes, smoking, low density lipoportein (LDL)- and high density lipoprotein (HDL), body mass index (BMI) and atrial fibrillation. In PIVUS, sphingomyelin (32:1) levels were significantly related to both LDL- and HDL-cholesterol in a positive fashion, and to serum triglycerides, BMI and diabetes in a negative fashion. Furthermore, sphingomyelin (32:1) levels were related to vasodilation in the forearm resistance vessels, and inversely to leukocyte count (P < .0069 and .0026, respectively). CONCLUSIONS: An inverse relationship between sphingomyelin (32:1) and incident ischemic stroke was identified, replicated, and characterized. A possible protective role for sphingomyelins in stroke development has to be further investigated in additional experimental and clinical studies.

Circulating Lysophosphatidylcholines, Phosphatidylcholines, Ceramides, and Sphingomyelins and Ovarian Cancer Risk: A 23-Year Prospective Study.

BACKGROUND: Experimental evidence supports a role of lipid dysregulation in ovarian cancer progression. We estimated associations with ovarian cancer risk for circulating levels of four lipid groups, previously hypothesized to be associated with ovarian cancer, measured 3-23 years before diagnosis. METHODS: Analyses were conducted among cases (N = 252) and matched controls (N = 252) from the Nurses' Health Studies. We used logistic regression adjusting for risk factors to investigate associations of lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs), ceramides (CERs), and sphingomyelins (SMs) with ovarian cancer risk overall and by histotype. A modified Bonferroni approach (0.05/4 = 0.0125, four lipid groups) and the permutation-based Westfall and Young approach were used to account for testing multiple correlated hypotheses. Odds ratios (ORs; 10th-90th percentile), and 95% confidence intervals of ovarian cancer risk were estimated. All statistical tests were two-sided. RESULTS: SM sum was statistically significantly associated with ovarian cancer risk (OR = 1.97, 95% CI = 1.16 to 3.32; P = .01/permutation-adjusted P = .20). C16:0 SM, C18:0 SM, and C16:0 CERs were suggestively associated with risk (OR = 1.95-2.10; P = .004-.01; permutation-adjusted P = .08-.21). SM sum, C16:0 SM, and C16:0 CER had stronger odds ratios among postmenopausal women (OR = 2.16-3.22). Odds ratios were similar for serous/poorly differentiated and endometrioid/clear cell tumors, although C18:1 LPC and LPC to PC ratio were suggestively inversely associated, whereas C18:0 SM was suggestively positively associated with risk of endometrioid/clear cell tumors. No individual metabolites were associated with risk when using the permutation-based approach. CONCLUSIONS: Elevated levels of circulating SMs 3-23 years before diagnosis were associated with increased risk of ovarian cancer, regardless of histotype, with stronger associations among postmenopausal women. Further studies are required to validate and understand the role of lipid dysregulation in ovarian carcinogenesis.

Low-density lipoprotein aggregation is inhibited by apolipoprotein J-derived mimetic peptide D-[113-122]apoJ.

Mimetic peptides are promising therapeutic agents for atherosclerosis prevention. A 10-residue class G* peptide from apolipoprotein J (apoJ), namely, D-[113-122]apoJ, possesses anti-inflammatory and anti-atherogenic properties. This prompted us to determine its effect on the aggregation process of low-density lipoprotein (LDL) particles, an early event in the development of atherosclerosis. LDL particles with and without [113-122]apoJ peptide were incubated at 37 °C with sphingomyelinase (SMase) or were left to aggregate spontaneously at room temperature. The aggregation process was analyzed by size-exclusion chromatography (SEC), native gradient gel electrophoresis (GGE), absorbance at 405 nm, dynamic light scattering (DLS), and transmission electronic microscopy (TEM). In addition, circular dichroism was used to determine changes in the secondary structure of apoB, and SDS-PAGE was performed to assess apoB degradation. At an equimolar ratio of [113-122]apoJ peptide to apoB-100, [113-122]apoJ inhibited both SMase-induced or spontaneous LDL aggregation. All methods showed that [113-122]apoJ retarded the progression of SMase-induced LDL aggregation at long incubation times. No effect of [113-122]apoJ on apoB secondary structure was observed. Binding experiments showed that [113-122]apoJ presents low affinity for native LDL but binds readily to LDL during the first stages of aggregation. Laurdan fluorescence experiments showed that mild aggregation of LDL resulted in looser lipid packaging, which was partially prevented by D-[113-122]apoJ. These results demonstrate that [113-122]apoJ peptide prevents SMase-induced LDL aggregation at an equimolar ratio and opens the possibility for the use of this peptide as a therapeutic tool.

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.

Uric acid and sphingomyelin enhance autophagy in iPS cell-originated cardiomyocytes through lncRNA MEG3/miR-7-5p/EGFR axis.

This study aimed to determine the metabolites associated with ventricular septal defect (VSD) and the underlying mechanisms. Blood samples and thymus tissues were collected from VSD patients to perform LC-MS-based metabolomics assay and generate iPS cell-derived cardiomyocytes, respectively. VSD rat model was used in vivo study. RT-PCR, western blotting, immunohistochemistry, luciferase activity assay, GFP-LC3 adenovirus and GFP and RFP tfLC3 assay, and transmission electron microscopy were performed to investigate the underlying mechanisms. The metabolites uric acid (UA) and sphingomyelin (SM) increased in the serum of VSD patients, along with enhanced autophagy. The combination of UA and SM treatment could promote autophagy and inhibit EGFR and AKT3 expressions. Overexpression of EGFR and AKT3 suppressed autophagy in UA and SM-treated cardiomyocytes, respectively. Also, lncRNA MEG3 knockdown and overexpression could enhance and inhibit autophagy in UA and SM-treated cardiomyocytes, respectively, through targeting miR-7-5p. Moreover, miR-7-5p mimics and inhibitors promoted and inhibited autophagy in UA and SM-treated cardiomyocytes, respectively, via target EGFR. In VSD rat model, upregulation of MEG3 could reverse high level of autophagy and decrease serum UA and SM. In conclusion, UA and SM are essential VSD-associated metabolic biomarkers and MEG3/miR-7-5p/EGFR axis is critical to the regulation of autophagy in cardiomyocytes.

Plasma metabolomic profiling of amino acids and polar lipids in Iranian obese adults.

BACKGROUND: Obesity, widely recognized as a serious health concern, is characterized by profoundly altered metabolism. However, the intermediate metabolites involved in this change remain largely unknown. OBJECTIVE: We conducted targeted metabolomics profiling to identify moieties associated with adult obesity. METHODS: In this case-control study of Iranian adults, 200 obese patients were compared with 100 controls based on 104 metabolites profiled by a targeted metabolomic approach using liquid chromatography coupled to triple quadrupole mass spectrometry (LC-MS/MS). The analysis comprised acylcarnitines, diacyl-phosphatidylcholines (PCaa), acyl-alkyl-phosphatidylcholines (PCae), sphingomyelins (SM), lyso-phospholipids (LPC) and amino acids. We performed multivariable linear regression to identify metabolites associated with obesity, adjusting for age, sex, total energy intake, total physical activity, smoking, and alcohol consumption. The Bonferroni correction was used to adjust for multiple testing. RESULTS: A pattern of 19 metabolites was significantly associated with obesity. Branched chain amino acids, alanine, glutamic acid, proline, tyrosine LPCa C16:1, PCaa C32:1, PCaa C32:2 and PCaa C38:3 were positively, while serine, asparagine, LPCa C18:1, LPCa C18:2, LPCe C18:0, PCae C34:3, PCae C38:4 and PCae C40:6 were negatively associated with obesity (all p < 0.00048). CONCLUSIONS: A metabolomic profile containing 9 amino acids and 10 polar lipids may serve as a potential biomarker of adult obesity. Further studies are warranted to replicate these findings as well as investigate potential changes in this profile after weight reduction.

Potential Nutritional and Metabolomic Advantages of High Fat Oral Supplementation in Pancreatectomized Pancreaticobiliary Cancer Patients.

We examined the effect of high fat oral nutritional supplement (HFS) on the nutritional status, oral intake, and serum metabolites of postoperative pancreaticobiliary cancer patients. Pancreaticobiliary cancer patients were voluntarily recruited. The HFS group received postoperative oral high fat supplementation (80% of total calories from fat; n = 12) until discharge; the control group (non-HFS; n = 9) received none. Dietary intake, anthropometry, blood chemistry, nutritional risk index (NRI), and serum metabolites analyzed by liquid chromatography tandem mass spectrometry were evaluated. Overall, cumulative caloric supply via parental and oral/enteral routes were not different between groups. However, oral fat intake, caloric intake, and NRI scores of the HFS group were higher than those of the non-HFS group with increased oral meal consumption. Oral caloric, fat, and meal intakes correlated with NRI scores. Metabolomics analysis identified 195 serum metabolites pre-discharge. Oral fat intake was correlated with 42 metabolites relevant to the glycerophospholipid pathway. Oral high fat-specific upregulation of sphingomyelin (d18:1/24:1), a previously reported pancreatic cancer-downregulated metabolite, and lysophosphatidylcholine (16:0) were associated with NRI scores. Provision of HFS in postoperative pancreatic cancer patients may facilitate the recovery of postoperative health status by increasing oral meal intake, improving nutritional status, and modulating serum metabolites.

Choline and choline-related nutrients in regular and preterm infant growth.

BACKGROUND: Choline is an essential nutrient, with increased requirements during development. It forms the headgroup of phosphatidylcholine and sphingomyelin in all membranes and many secretions. Phosphatidylcholine is linked to cell signaling as a phosphocholine donor to synthesize sphingomyelin from ceramide, a trigger of apoptosis, and is the major carrier of arachidonic and docosahexaenoic acid in plasma. Acetylcholine is important for neurodevelopment and the placental storage form for fetal choline supply. Betaine, a choline metabolite, functions as osmolyte and methyl donor. Their concentrations are all tightly regulated in tissues. CLINCAL IMPACT: During the fetal growth spurt at 24-34-week postmenstrual age, plasma choline is higher than beyond 34 weeks, and threefold higher than in pregnant women [45 (36-60) µmol/L vs. 14 (10-17) µmol/L]. The rapid decrease in plasma choline after premature birth suggests an untimely reduction in choline supply, as cellular uptake is proportional to plasma concentration. Supply via breast milk, with phosphocholine and α-glycerophosphocholine as its major choline components, does not prevent such postnatal decrease. Moreover, high amounts of liver PC are secreted via bile, causing rapid hepatic choline turnover via the enterohepatic cycle, and deficiency in case of pancreatic phospholipase A2 deficiency or intestinal resection. Choline deficiency causes hepatic damage and choline accretion at the expense of the lungs and other tissues. CONCLUSION: Choline deficiency may contribute to the impaired lean body mass growth and pulmonary and neurocognitive development of preterm infants despite adequate macronutrient supply and weight gain. In this context, a reconsideration of current recommendations for choline supply to preterm infants is required.