Dietary habits and plasma lipid concentrations in a general Japanese population.

INTRODUCTION: Accumulating data on the associations between food consumption and lipid composition in the body is essential for understanding the effects of dietary habits on health. OBJECTIVES: As part of omics research in the Tohoku Medical Megabank Community-Based Cohort Study, this study sought to reveal the dietary impact on plasma lipid concentration in a Japanese population. METHODS: We conducted a correlation analysis of food consumption and plasma lipid concentrations measured using mass spectrometry, for 4032 participants in Miyagi Prefecture, Japan. RESULTS: Our analysis revealed 83 marked correlations between six food categories and the concentrations of plasma lipids in nine subclasses. Previously reported associations, including those between seafood consumption and omega-3 fatty acids, were validated, while those between dairy product consumption and odd-carbon-number fatty acids (odd-FAs) were validated for the first time in an Asian population. Further analysis suggested that dairy product consumption is associated with odd-FAs via sphingomyelin (SM), which suggests that SM is a carrier of odd-FAs. These results are important for understanding odd-FA metabolism with regards to dairy product consumption. CONCLUSION: This study provides insight into the dietary impact on plasma lipid concentration in a Japanese population.

Identification of predictive biomarkers for diagnosis and radiation sensitivity of uterine cervical cancer using wide-targeted metabolomics.

AIM: Uterine cervical cancer (UCC) is the fourth most common cancer in women, responsible for more than 300 000 deaths worldwide. Its early detection, by cervical cytology, and prevention, by vaccinating against human papilloma virus, greatly contribute to reducing cervical cancer mortality in women. However, penetration of the effective prevention of UCC in Japan remains low. Plasma metabolome analysis is widely used for biomarker discovery and the identification of cancer-specific metabolic pathways. Here, we aimed to identify predictive biomarkers for the diagnosis and radiation sensitivity of UCC using wide-targeted plasma metabolomics. METHODS: We analyzed 628 metabolites in plasma samples obtained from 45 patients with UCC using ultra-high-performance liquid chromatography with tandem mass spectrometry. RESULTS: The levels of 47 metabolites were significantly increased and those of 75 metabolites were significantly decreased in patients with UCC relative to healthy controls. Increased levels of arginine and ceramides, and decreased levels of tryptophan, ornithine, glycosylceramides, lysophosphatidylcholine, and phosphatidylcholine were characteristic of patients with UCC. Comparison of metabolite profiles in groups susceptible and non-susceptible to radiation therapy, a treatment for UCC, revealed marked variations in polyunsaturated fatty acid, nucleic acid, and arginine metabolism in the group not susceptible to treatment. CONCLUSIONS: Our findings suggest that the metabolite profile of patients with UCC may be an important indicator for distinguishing these patients from healthy cohorts, and may also be useful for predicting sensitivity to radiotherapy.

Global Proteomics for Identifying the Alteration Pathway of Niemann-Pick Disease Type C Using Hepatic Cell Models.

Niemann-Pick disease type C (NPC) is an autosomal recessive disorder with progressive neurodegeneration. Although the causative genes were previously identified, NPC has unclear pathophysiological aspects, and patients with NPC present various symptoms and onset ages. However, various novel biomarkers and metabolic alterations have been investigated; at present, few comprehensive proteomic alterations have been reported in relation to NPC. In this study, we aimed to elucidate proteomic alterations in NPC and perform a global proteomics analysis for NPC model cells. First, we developed two NPC cell models by knocking out NPC1 using CRISPR/Cas9 (KO1 and KO2). Second, we performed a label-free (LF) global proteomics analysis. Using the LF approach, more than 300 proteins, defined as differentially expressed proteins (DEPs), changed in the KO1 and/or KO2 cells, while the two models shared 35 DEPs. As a bioinformatics analysis, the construction of a protein-protein interaction (PPI) network and an enrichment analysis showed that common characteristic pathways such as ferroptosis and mitophagy were identified in the two model cells. There are few reports of the involvement of NPC in ferroptosis, and this study presents ferroptosis as an altered pathway in NPC. On the other hand, many other pathways and DEPs were previously suggested to be associated with NPC, supporting the link between the proteome analyzed here and NPC. Therapeutic research based on these results is expected in the future.

Exploration of urine metabolic biomarkers for new-onset, untreated pediatric epilepsy: A gas and liquid chromatography mass spectrometry-based metabolomics study.

OBJECTIVE: The discovery of objective indicators for recent epileptic seizures will help confirm the diagnosis of epilepsy and evaluate therapeutic effects. Past studies had shortcomings such as the inclusion of patients under treatment and those with various etiologies that could confound the analysis results significantly. We aimed to minimize such confounding effects and to explore the small molecule biomarkers associated with the recent occurrence of epileptic seizures using urine metabolomics. METHODS: This is a multicenter prospective study. Subjects included pediatric patients aged 2 to 12 years old with new-onset, untreated epilepsy, who had had the last seizure within 1 month before urine collection. Controls included healthy children aged 2 to 12 years old. Those with underlying or chronic diseases, acute illnesses, or recent administration of medications or supplements were excluded. Targeted metabolome analysis of spot urine samples was conducted using gas chromatography (GC)- and liquid chromatography (LC)-tandem mass spectrometry (MS/MS). RESULTS: We enrolled 17 patients and 21 controls. Among 172 metabolites measured by GC/MS/MS and 41 metabolites measured by LC/MS/MS, only taurine was consistently reduced in the epilepsy group. This finding was subsequently confirmed by the absolute quantification of amino acids. No other metabolites were consistently altered between the two groups. CONCLUSIONS: Urine metabolome analysis, which covers a larger number of metabolites than conventional biochemistry analyses, found no consistently altered small molecule metabolites except for reduced taurine in epilepsy patients compared to healthy controls. Further studies with larger samples, subjects with different ages, expanded target metabolites, and the investigation of plasma samples are required.

Identification of predictive biomarkers for endometrial cancer diagnosis and treatment response monitoring using plasma metabolome profiling.

BACKGROUND: Endometrial cancer (EMC) is the most common female genital tract malignancy with an increasing prevalence in many countries including Japan, a fact that renders early detection and treatment necessary to protect health and fertility. Although early detection and treatment are necessary to further improve the prognosis of women with endometrial cancer, biomarkers that accurately reflect the pathophysiology of EMC patients are still unclear. Therefore, it is clinically critical to identify biomarkers to assess diagnosis and treatment efficacy to facilitate appropriate treatment and development of new therapies for EMC. METHODS: In this study, wide-targeted plasma metabolome analysis was performed to identify biomarkers for EMC diagnosis and the prediction of treatment responses. The absolute quantification of 628 metabolites in plasma samples from 142 patients with EMC was performed using ultra-high-performance liquid chromatography with tandem mass spectrometry. RESULTS: The concentrations of 111 metabolites increased significantly, while the concentrations of 148 metabolites decreased significantly in patients with EMC compared to healthy controls. Specifically, LysoPC and TGs, including unsaturated fatty acids, were reduced in patients with stage IA EMC compared to healthy controls, indicating that these metabolic profiles could be used as early diagnostic markers of EMC. In contrast, blood levels of amino acids such as histidine and tryptophan decreased as the risk of recurrence increased and the stages of EMC advanced. Furthermore, a marked increase in total TG and a decrease in specific TGs and free fatty acids including polyunsaturated fatty acids levels were observed in patients with EMC. These results suggest that the polyunsaturated fatty acids in patients with EMC are crucial for disease progression. CONCLUSIONS: Our data identified specific metabolite profiles that reflect the pathogenesis of EMC and showed that these metabolites correlate with the risk of recurrence and disease stage. Analysis of changes in plasma metabolite profiles could be applied for the early diagnosis and monitoring of the course of treatment of EMC patients.

Comprehensive study of metabolic changes induced by a ketogenic diet therapy using GC/MS- and LC/MS-based metabolomics.

OBJECTIVE: The ketogenic diet (KD), a high-fat and low-carbohydrate diet, is effective for a subset of patients with drug-resistant epilepsy, although the mechanisms of the KD have not been fully elucidated. The aims of this observational study were to investigate comprehensive short-term metabolic changes induced by the KD and to explore candidate metabolites or pathways for potential new therapeutic targets. METHODS: Subjects included patients with intractable epilepsy who had undergone the KD therapy (the medium-chain triglyceride [MCT] KD or the modified Atkins diet using MCT oil). Plasma and urine samples were obtained before and at 2-4 weeks after initiation of the KD. Targeted metabolome analyses of these samples were performed using gas chromatography-tandem mass spectrometry (GC/MS/MS) and liquid chromatography-tandem mass spectrometry (LC/MS/MS). RESULTS: Samples from 10 and 11 patients were analysed using GC/MS/MS and LC/MS/MS, respectively. The KD increased ketone bodies, various fatty acids, lipids, and their conjugates. In addition, levels of metabolites located upstream of acetyl-CoA and propionyl-CoA, including catabolites of branched-chain amino acids and structural analogues of γ-aminobutyric acid and lactic acid, were elevated. CONCLUSIONS: The metabolites that were significantly changed after the initiation of the KD and related metabolites may be candidates for further studies for neuronal actions to develop new anti-seizure medications.

Reduced glutathione level in the aqueous humor of patients with primary open-angle glaucoma and normal-tension glaucoma.

Glaucoma is a leading cause of blindness worldwide in older people. Profiling the aqueous humor, including the metabolites it contains, is useful to understand physiological and pathological conditions in the eye. In the current study, we used mass spectrometry (MS) to characterize the aqueous humor metabolomic profile and biological features of patients with glaucoma. Aqueous humor samples were collected during trabeculectomy surgery or cataract surgery and analyzed with global metabolomics. We included 40 patients with glaucoma (32 with POAG, 8 with NTG) and 37 control subjects in a discovery study. VIP analysis revealed five metabolites that were elevated and three metabolites that were reduced in the glaucoma patients. The identified metabolomic profile had an area under the receiver operating characteristic curve of 0.953. Among eight selected metabolites, the glutathione level was significantly decreased in association with visual field defects. Moreover, in a validation study to confirm the reproducibility of our findings, the glutathione level was reduced in NTG and POAG patients compared with a cataract control group. Our findings demonstrate that aqueous humor profiling can help to diagnose glaucoma and that various aqueous humor metabolites are correlated with clinical parameters in glaucoma patients. In addition, glutathione is clearly reduced in the aqueous humor of glaucoma patients with both IOP-dependent and IOP-independent disease subtypes. These findings indicate that antioxidant agents in the aqueous humor reflect glaucomatous optic nerve damage and that excessive oxidative stress may be involved in the pathogenesis of glaucoma.

Nrf2 deficiency deteriorates diabetic kidney disease in Akita model mice.

Oxidative stress is an essential component in the progression of diabetic kidney disease (DKD), and the transcription factor NF-E2-related factor-2 (Nrf2) plays critical roles in protecting the body against oxidative stress. To clarify the roles of Nrf2 in protecting against DKD, in this study we prepared compound mutant mice with diabetes and loss of antioxidative defense. Specifically, we prepared compound Ins2Akita/+ (Akita) and Nrf2 knockout (Akita::Nrf2-/-) or Akita and Nrf2 induction (Akita::Keap1FA/FA) mutant mice. Eighteen-week-old Akita::Nrf2-/- mice showed more severe diabetic symptoms than Akita mice. In the Akita::Nrf2-/- mouse kidneys, the glomeruli showed distended capillary loops, suggesting enhanced mesangiolysis. Distal tubules showed dilation and an increase in 8-hydroxydeoxyguanosine-positive staining. In the Akita::Nrf2-/- mouse kidneys, the expression of glutathione (GSH) synthesis-related genes was decreased, and the actual GSH level was decreased in matrix-assisted laser desorption/ionization mass spectrometry imaging analysis. Akita::Nrf2-/- mice exhibited severe inflammation and enhancement of infiltrated macrophages in the kidney. To further examine the progression of DKD, we compared forty-week-old Akita mouse kidney compounds with Nrf2-knockout or Nrf2 mildly induced (Akita::Keap1FA/FA) mice. Nrf2-knockout Akita (Akita::Nrf2-/-) mice displayed severe medullary cast formation, but the formation was ameliorated in Akita::Keap1FA/FA mice. Moreover, in Akita::Keap1FA/FA mice, tubule injury and inflammation-related gene expression were significantly suppressed, which was evident in Akita::Nrf2-/- mouse kidneys. These results demonstrate that Nrf2 contributes to the protection of the kidneys against DKD by suppressing oxidative stress and inflammation.

Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories.

In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories.

Plasma metabolic disturbances during pregnancy and postpartum in women with depression.

Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or without (n = 222) PPD. Gas chromatogram-mass spectrometry was used to analyze plasma metabolites at these two time points. Among the 170 objected plasma metabolites, principal component analysis distinguished pregnancy and postpartum metabolites but failed to discriminate women with and without PPD. Compared to women without PPD, those with PPD exhibited 37 metabolites with disparate changes during pregnancy and the 1-month postpartum period and an enriched citrate cycle. Machine learning and multivariate statistical analysis identified two or three compounds that could be potential biomarkers for PPD prediction during pregnancy. Our findings suggest metabolic disturbances in women with depression and may help to elucidate metabolic processes associated with PPD development.

Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics.

Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.

Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values.

Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual's current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.

Nrf2 plays a critical role in the metabolic response during and after spaceflight.

Space travel induces stresses that contribute to health problems, as well as inducing the expression of Nrf2 (NF-E2-related factor-2) target genes that mediate adaptive responses to oxidative and other stress responses. The volume of epididymal white adipose tissue (eWAT) in mice increases during spaceflight, a change that is attenuated by Nrf2 knockout. We conducted metabolome analyses of plasma from wild-type and Nrf2 knockout mice collected at pre-flight, in-flight and post-flight time points, as well as tissues collected post-flight to clarify the metabolic responses during and after spaceflight and the contribution of Nrf2 to these responses. Plasma glycerophospholipid and sphingolipid levels were elevated during spaceflight, whereas triacylglycerol levels were lower after spaceflight. In wild-type mouse eWAT, triacylglycerol levels were increased, but phosphatidylcholine levels were decreased, and these changes were attenuated in Nrf2 knockout mice. Transcriptome analyses revealed marked changes in the expression of lipid-related genes in the liver and eWAT after spaceflight and the effects of Nrf2 knockout on these changes. Based on these results, we concluded that space stress provokes significant responses in lipid metabolism during and after spaceflight; Nrf2 plays critical roles in these responses.

Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis.

The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed models to evaluate pregnancy status and predict gestational age using omics data from blood biospecimens; however, less invasive methods are desired. Here we propose a model to predict gestational age, using urinary metabolite information. In our prospective cohort study, we collected 2741 urine samples from 187 healthy pregnant women, 23 patients with hypertensive disorders of pregnancy, and 14 patients with spontaneous preterm birth. Using gas chromatography-tandem mass spectrometry, we identified 184 urinary metabolites that showed dynamic systematic changes in healthy pregnant women according to gestational age. A model to predict gestational age during normal pregnancy progression was constructed; the correlation coefficient between actual and predicted weeks of gestation was 0.86. The predicted gestational ages of cases with hypertensive disorders of pregnancy exhibited significant progression, compared with actual gestational ages. This is the first study to predict gestational age in normal and complicated pregnancies by using urinary metabolite information. Minimally invasive urinary metabolomics might facilitate changes in the prediction of gestational age in various clinical settings.

Polymyxins as novel and safe mucosal adjuvants to induce humoral immune responses in mice.

There is currently an urgent need to develop safe and effective adjuvants for enhancing vaccine-induced antigen-specific immune responses. We demonstrate here that intranasal immunization with clinically used polypeptide antibiotics, polymyxin B (PMB) and colistin (CL), along with ovalbumin (OVA), increases OVA-specific humoral immune responses in a dose-dependently manner at both mucosal and systemic compartments. Enhanced immunity by boosting was found to persist during 8 months of observation. Moreover, mice intranasally immunized with OVA plus various doses of PMB or CL showed neither inflammatory responses in the nasal cavity and olfactory bulbs nor renal damages, compared to those given OVA alone. These data suggest that polymyxins may serve as novel and safe mucosal adjuvants to induce humoral immune responses. The polymyxin adjuvanticity was found to be independent of endotoxins liberated by its bactericidal activity, as indicated by similar enhancing effects of PMB in lipopolysaccharide (LPS)-hyporesponsive and LPS-susceptible mice. However, despite the presence of preexisting anti-PMB antibodies, we observed no reduction in the adjuvant function of polymyxins when they were given intranasally. Furthermore, the titers of OVA-specific Abs in mice intranasally immunized with OVA plus PMB or CL were significantly higher than those in mice administered with polymyxin analogues, such as polymyxin B nonapeptide and colistin methanesulfonate. The levels of released ß-hexosaminidase and histamine in mast cell culture supernatants stimulated by PMB or CL were also significantly higher than those stimulated by their analogues. These results suggest that both the hydrophobic carbon chain and hydrophilic cationic cyclic peptide contribute to the mucosal adjuvanticity of PMB and CL.