jMorp: Japanese Multi-Omics Reference Panel update report 2023.

Modern medicine is increasingly focused on personalized medicine, and multi-omics data is crucial in understanding biological phenomena and disease mechanisms. Each ethnic group has its unique genetic background with specific genomic variations influencing disease risk and drug response. Therefore, multi-omics data from specific ethnic populations are essential for the effective implementation of personalized medicine. Various prospective cohort studies, such as the UK Biobank, All of Us and Lifelines, have been conducted worldwide. The Tohoku Medical Megabank project was initiated after the Great East Japan Earthquake in 2011. It collects biological specimens and conducts genome and omics analyses to build a basis for personalized medicine. Summary statistical data from these analyses are available in the jMorp web database (https://jmorp.megabank.tohoku.ac.jp), which provides a multidimensional approach to the diversity of the Japanese population. jMorp was launched in 2015 as a public database for plasma metabolome and proteome analyses and has been continuously updated. The current update will significantly expand the scale of the data (metabolome, genome, transcriptome, and metagenome). In addition, the user interface and backend server implementations were rewritten to improve the connectivity between the items stored in jMorp. This paper provides an overview of the new version of the jMorp.

Metabolic reprogramming in Nrf2-driven proliferation of normal rat hepatocytes.

BACKGROUND AND AIMS: Cancer cells reprogram their metabolic pathways to support bioenergetic and biosynthetic needs and to maintain their redox balance. In several human tumors, the Keap1-Nrf2 system controls proliferation and metabolic reprogramming by regulating the pentose phosphate pathway (PPP). However, whether this metabolic reprogramming also occurs in normal proliferating cells is unclear. APPROACH AND RESULTS: To define the metabolic phenotype in normal proliferating hepatocytes, we induced cell proliferation in the liver by 3 distinct stimuli: liver regeneration by partial hepatectomy and hepatic hyperplasia induced by 2 direct mitogens: lead nitrate (LN) or triiodothyronine. Following LN treatment, well-established features of cancer metabolic reprogramming, including enhanced glycolysis, oxidative PPP, nucleic acid synthesis, NAD + /NADH synthesis, and altered amino acid content, as well as downregulated oxidative phosphorylation, occurred in normal proliferating hepatocytes displaying Nrf2 activation. Genetic deletion of Nrf2 blunted LN-induced PPP activation and suppressed hepatocyte proliferation. Moreover, Nrf2 activation and following metabolic reprogramming did not occur when hepatocyte proliferation was induced by partial hepatectomy or triiodothyronine. CONCLUSIONS: Many metabolic changes in cancer cells are shared by proliferating normal hepatocytes in response to a hostile environment. Nrf2 activation is essential for bridging metabolic changes with crucial components of cancer metabolic reprogramming, including the activation of oxidative PPP. Our study demonstrates that matured hepatocytes exposed to LN undergo cancer-like metabolic reprogramming and offers a rapid and useful in vivo model to study the molecular alterations underpinning the differences/similarities of metabolic changes in normal and neoplastic hepatocytes.

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.

Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS).

The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study used an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability, functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.

Oral alkalinizing supplementation suppressed intrarenal reactive oxidative stress in mild-stage chronic kidney disease: a randomized cohort study.

BACKGROUND: The beneficial effects of oral supplements with alkalinizing agents in patients with chronic kidney disease (CKD) have been limited to the severe stages. We investigated whether two types of supplements, sodium bicarbonate (SB) and potassium citrate/sodium citrate (PCSC), could maintain renal function in patients with mild-stage CKD. METHODS: This was a single-center, open-labeled, randomized cohort trial. Study participants with CKD stages G2, G3a, and G3b were enrolled between March 2013 and January 2019 and randomly assigned by stratification according to age, sex, estimated glomerular filtration rate (eGFR), and diabetes. They were followed up for 6 months (short-term study) for the primary endpoints and extended to 2 years (long-term study) for the secondary endpoints. Supplementary doses were adjusted to achieve an early morning urinary pH of 6.8-7.2. We observed renal dysfunction or new-onset cerebrovascular disease and evaluated urinary surrogate markers for renal injury. RESULTS: Overall, 101 participants were registered and allocated to three groups: standard (n = 32), SB (n = 34), and PCSC (n = 35). Two patients in the standard group attained the primary endpoints (renal stones and overt proteinuria) but were not statistically significant. There was one patient in the standard reduced eGFR during the long-term study (p = 0.042 by ANOVA). SB increased proteinuria (p = 0.0139, baseline vs. 6 months), whereas PCSC significantly reduced proteinuria (p = 0.0061, baseline vs. 1 year, or p = 0.0186, vs. 2 years) and urinary excretion of 8-hydroxy-2'-deoxyguanosine (p = 0.0481, baseline vs. 6 months). CONCLUSION: This study is the first to report supplementation of PCSC reduced intrarenal oxidative stress in patients with mild-stage CKD.

Decreased ß-hydroxybutyrate and ketogenic amino acid levels in depressed human adults.

ß-hydroxybutyrate (BHB) is a major ketone body synthesized mainly in the liver mitochondria and is associated with stress and severity of depression in humans. It is known to alleviate depressive-like behaviors in mouse models of depression. In this study, plasma BHB, ketogenic and glucogenic amino acids selected from the Tohoku Medical Megabank Project Community-Based Cohort Study were analysed and measured using nuclear magnetic resonance spectroscopy. The Center for Epidemiologic Studies Depression Scale (CES-D) was utilized to select adult participants with depressive symptoms (CES-D ≥ 16; n = 5722) and control participants (CES-D < 16; n = 18,150). We observed significantly reduced plasma BHB, leucine, and tryptophan levels in participants with depressive symptoms. Using social defeat stress (SDS) mice models, we found that BHB levels in mice sera increased after acute SDS, but showed no change after chronic SDS, which differed from human plasma results. Furthermore, acute SDS increased mitochondrial BHB levels in the prefrontal cortex at 6 h. In contrast, chronic SDS significantly increased the amount of food intake but reduced hepatic mitochondrial BHB levels in mice. Moreover, gene transcriptions of voltage-dependent anion-selective channel 1 (Vdac1) and monocarboxylic acid transporter 1 (Mct1), major molecules relevant to mitochondrial biogenesis and BHB transporter, significantly decreased in the liver and PFC after chronic SDS exposure. These results provide evidence that hepatic and prefrontal mitochondrial biogenesis plays an important role in BHB synthesis under chronic stress and in humans with depressive symptoms.

Genome-wide association study of the risk of chronic kidney disease and kidney-related traits in the Japanese population: J-Kidney-Biobank.

Chronic kidney disease (CKD) is a syndrome characterized by a gradual loss of kidney function with decreased estimated glomerular filtration rate (eGFR), which may be accompanied by an increase in the urine albumin-to-creatinine ratio (UACR). Although trans-ethnic genome-wide association studies (GWASs) have been conducted for kidney-related traits, there have been few analyses in the Japanese population, especially for the UACR trait. In this study, we conducted a GWAS to identify loci related to multiple kidney-related traits in Japanese individuals. First, to detect loci associated with CKD, eGFR, and UACR, we performed separate GWASs with the following two datasets: 475 cases of CKD diagnosed at seven university hospitals and 3471 healthy subjects (dataset 1) and 3664 cases of CKD-suspected individuals with eGFR <60 ml/min/1.73 m2 or urinary protein ≥ 1+ and 5952 healthy subjects (dataset 2). Second, we performed a meta-analysis between these two datasets and detected the following associated loci: 10 loci for CKD, 9 loci for eGFR, and 22 loci for UACR. Among the loci detected, 22 have never been reported previously. Half of the significant loci for CKD were shared with those for eGFR, whereas most of the loci associated with UACR were different from those associated with CKD or eGFR. The GWAS of the Japanese population identified novel genetic components that were not previously detected. The results also suggest that the group primarily characterized by increased UACR possessed genetically different features from the group characterized by decreased eGFR.

jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population.

In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

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.

Maternal Baseline Characteristics and Perinatal Outcomes: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study.

BACKGROUND: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study was launched in 2013 to evaluate the complex interactions of genetic and environmental factors in multifactorial diseases. The present study describes the maternal baseline profile and perinatal data of participating mothers and infants. METHODS: Expectant mothers living in Miyagi Prefecture were recruited from obstetric facilities or affiliated centers between 2013 and 2017. Three sets of self-administered questionnaires were collected, and the medical records were reviewed to obtain precise information about each antenatal visit and each delivery. Biospecimens, including blood, urine, umbilical cord blood, and breast milk, were collected for the study biobank. The baseline maternal sociodemographic characteristics, results of screening tests, and obstetric outcomes were analyzed according to the maternal age group. RESULTS: A total of 23,406 pregnancies involving 23,730 fetuses resulted in 23,143 live births. Younger maternal participants had a tendency toward a higher incidence of threatened abortion and threatened premature labor, while older age groups exhibited a significantly higher rate of low lying placenta, placenta previa, gestational diabetes, and hypertensive disorders of pregnancy. CONCLUSIONS: The present study clearly shows the distribution of maternal baseline characteristics and the range of perinatal outcomes according to maternal age group. This cohort study can provide strategic information for creating breakthroughs in the pathophysiology of perinatal, developmental, and noncommunicable diseases by collaborative data visiting or sharing.

Study Profile of the Tohoku Medical Megabank Community-Based Cohort Study.

BACKGROUND: We established a community-based cohort study to assess the long-term impact of the Great East Japan Earthquake on disaster victims and gene-environment interactions on the incidence of major diseases, such as cancer and cardiovascular diseases. METHODS: We asked participants to join our cohort in the health check-up settings and assessment center based settings. Inclusion criteria were aged 20 years or over and living in Miyagi or Iwate Prefecture. We obtained information on lifestyle, effect of disaster, blood, and urine information (Type 1 survey), and some detailed measurements (Type 2 survey), such as carotid echography and calcaneal ultrasound bone mineral density. All participants agreed to measure genome information and to distribute their information widely. RESULTS: As a result, 87,865 gave their informed consent to join our study. Participation rate at health check-up site was about 70%. The participants in the Type 1 survey were more likely to have psychological distress than those in the Type 2 survey, and women were more likely to have psychological distress than men. Additionally, coastal residents were more likely to have higher degrees of psychological distress than inland residents, regardless of sex. CONCLUSION: This cohort comprised a large sample size and it contains information on the natural disaster, genome information, and metabolome information. This cohort also had several detailed measurements. Using this cohort enabled us to clarify the long-term effect of the disaster and also to establish personalized prevention based on genome, metabolome, and other omics information.

Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia.

The purpose of the present study was to identify a plasma protein biomarker able to predict pre-eclampsia (PE). Comprehensive quantitative proteomics using mass spectrometry with sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) was applied to plasma samples of 7 PE and 14 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE), and 11 proteins were selected as candidates potentially able to differentiate the two groups. Plasmas collected at gestational weeks 14-24 from 36 PE and 120 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE) were used to conduct selected reaction monitoring quantification analysis, optimize protein combinations and conduct internal validation, which consisted of 30 iterations of 10-fold cross-validation using multivariate logistic regression and receiver operating characteristic (ROC) analysis. The combination of afamin, fibronectin, and sex-hormone-binding globulin was selected as the best candidate. The 3-protein combination predictive model (predictive equation and cut-off value) generated using the internal validation subjects was successfully validated in another group of validation subjects (36 PE and 54 healthy (for PE subjects, plasma samples were taken before onset of PE)) and showed good predictive performance, with the area under the curve (AUC) 0.835 and odds ratio 13.43. In conclusion, we newly identified a 3-protein combination biomarker and established a predictive equation and cut-off value that can predict the onset of PE based on analysis of plasma samples collected during gestational weeks 14-24.

Amino-acid selective isotope labeling enables simultaneous overlapping signal decomposition and information extraction from NMR spectra.

Signal overlapping is a major bottleneck for protein NMR analysis. We propose a new method, stable-isotope-assisted parameter extraction (SiPex), to resolve overlapping signals by a combination of amino-acid selective isotope labeling (AASIL) and tensor decomposition. The basic idea of Sipex is that overlapping signals can be decomposed with the help of intensity patterns derived from quantitative fractional AASIL, which also provides amino-acid information. In SiPex, spectra for protein characterization, such as 15N relaxation measurements, are assembled with those for amino-acid information to form a four-order tensor, where the intensity patterns from AASIL contribute to high decomposition performance even if the signals share similar chemical shift values or characterization profiles, such as relaxation curves. The loading vectors of each decomposed component, corresponding to an amide group, represent both the amino-acid and relaxation information. This information link provides an alternative protein analysis method that does not require "assignments" in a general sense; i.e., chemical shift determinations, since the amino-acid information for some of the residues allows unambiguous assignment according to the dual selective labeling. SiPex can also decompose signals in time-domain raw data without Fourier transform, even in non-uniformly sampled data without spectral reconstruction. These features of SiPex should expand biological NMR applications by overcoming their overlapping and assignment problems.

Correction: Biallelic GALM pathogenic variants cause a novel type of galactosemia.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Identification of novel biomarkers of hepatocellular carcinoma by high-definition mass spectrometry: Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry and desorption electrospray ionization mass spectrometry imaging.

RATIONALE: Hepatocellular carcinoma (HCC) is a highly malignant disease for which the development of prospective or prognostic biomarkers is urgently required. Although metabolomics is widely used for biomarker discovery, there are some bottlenecks regarding the comprehensiveness of detected features, reproducibility of methods, and identification of metabolites. In addition, information on localization of metabolites in tumor tissue is needed for functional analysis. Here, we developed a wide-polarity global metabolomics (G-Met) method, identified HCC biomarkers in human liver samples by high-definition mass spectrometry (HDMS), and demonstrated localization in cryosections using desorption electrospray ionization MS imaging (DESI-MSI) analysis. METHODS: Metabolic profiling of tumor (n = 38) and nontumor (n = 72) regions in human livers of HCC was performed by an ultrahigh-performance liquid chromatography quadrupole time-of-flight MS (UHPLC/QTOFMS) instrument equipped with a mixed-mode column. The HCC biomarker candidates were extracted by multivariate analyses and identified by matching values of the collision cross section and their fragment ions on the mass spectra obtained by HDMS. Cryosections of HCC livers, which included both tumor and nontumor regions, were analyzed by DESI-MSI. RESULTS: From the multivariate analysis, m/z 904.83 and m/z 874.79 were significantly high and low, respectively, in tumor samples and were identified as triglyceride (TG) 16:0/18:1(9Z)/20:1(11Z) and TG 16:0/18:1(9Z)/18:2(9Z,12Z) using the synthetic compounds. The TGs were clearly localized in the tumor or nontumor areas of the cryosection. CONCLUSIONS: Novel biomarkers for HCC were identified by a comprehensive and reproducible G-Met method with HDMS using a mixed-mode column. The combination analysis of UHPLC/QTOFMS and DESI-MSI revealed that the different molecular species of TGs were associated with tumor distribution and were useful for characterizing the progression of tumor cells and discovering prospective biomarkers.

jMorp: Japanese Multi Omics Reference Panel.

We developed jMorp, a new database containing metabolome and proteome data for plasma obtained from >5000 healthy Japanese volunteers from the Tohoku Medical Megabank Cohort Study, which is available at https://jmorp.megabank.tohoku.ac.jp. Metabolome data were measured by proton nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS), while proteome data were obtained by nanoLC-MS. We released the concentration distributions of 37 metabolites identified by NMR, distributions of peak intensities of 257 characterized metabolites by LC-MS, and observed frequencies of 256 abundant proteins. Additionally, correlation networks for the metabolites can be observed using an interactive network viewer. Compared with some existing databases, jMorp has some unique features: (i) Metabolome data were obtained using a single protocol in a single institute, ensuring that measurement biases were significantly minimized; (ii) The database contains large-scale data for healthy volunteers with various health records and genome data and (iii) Correlations between metabolites can be easily observed using the graphical viewer. Metabolites data are becoming important intermediate markers for evaluating the health states of humans, and thus jMorp is an outstanding resource for a wide range of researchers, particularly those in the fields of medical science, applied molecular biology, and biochemistry.

Design and Progress of Oral Health Examinations in the Tohoku Medical Megabank Project.

In order to assess the long-term impact of the Great East Japan Earthquake on the oral health of disaster victims and to evaluate gene-environmental interactions in the development of major oral diseases and oral-systemic associations, the oral part of two large-scale genome cohort studies by the Tohoku Medical Megabank Organization (ToMMo), including the Community-based cohort (CommCohort) study and the Birth and Three-Generation cohort (BirThree) study, have been conducted. The study population comprised 32,185 subjects, including 16,886 participants in the CommCohort study and 15,299 participants in the BirThree cohort study, recruited from 2013 to 2017. The oral studies consist of a questionnaire regarding oral hygiene behavior, clinical examinations by dentists, and oral plaque and saliva sampling for microbiome analyses, which were carried out at seven community support centers in Miyagi prefecture. The median age of all participants was 55.0 years, and 66.1% of participants were women. Almost all participants reported that they brushed their teeth more than once a day. The median number of present teeth was 27.0, and the decayed, missing and filled tooth number was 16.0, with a significant difference according to age and sex. The median periodontal pocket and clinical attachment level was 2.48 mm and 4.00 mm, respectively. Periodontal parameters increased significantly according to age, except for the accumulation of dental calculus. The oral part of these extensive cross-sectional studies provides a unique and important platform for future studies on oral health and diseases that elicit through interactions with systemic diseases, lifestyles, life events and genetic backgrounds, and contributes to researches clarifying the long-term effects of disasters on oral health.

Metabolic Profiling of the Cerebrospinal Fluid in Pediatric Epilepsy.

To characterize metabolic profiles within the central nervous system in epilepsy, we performed gas chromatography-tandem mass spectrometry (GC-MS/MS)-based metabolome analysis of the cerebrospinal fluid (CSF) in pediatric patients with and without epilepsy. The CSF samples obtained from 64 patients were analyzed by GC-MS/MS. Multivariate analyses were performed for two age groups, 0-5 years of age and 6-17 years of age, to elucidate the effects of epilepsy and antiepileptic drugs on the metabolites. In patients aged 0-5 years (22 patients with epilepsy, 13 without epilepsy), epilepsy patients had reduced 2-ketoglutaric acid and elevated pyridoxamine and tyrosine. In patients aged 6-17 years (12 with epilepsy, 17 without epilepsy), epilepsy patients had reduced 1,5-anhydroglucitol. Valproic acid was associated with elevated 2-aminobutyric acid, 2-ketoisocaproic acid, 4-hydroxyproline, acetylglycine, methionine, N-acetylserine, and serine. Reduced energy metabolism and alteration of vitamin B6 metabolism may play a role in epilepsy in young children. The roles of 1,5-anhydroglucitol in epilepsy in older children and in levetiracetam and zonisamide treatment remain to be explained. Valproic acid influenced the levels of amino acids and related metabolites involved in the metabolism of serine, methionine, and leucine.

Value of global metabolomics in association with diagnosis and clinicopathological factors of renal cell carcinoma.

Renal cell carcinoma (RCC) is a malignant tumor that currently lacks clinically useful biomarkers indicative of early diagnosis or disease status. RCC has commonly been diagnosed based on imaging results. Metabolomics offers a potential technology for discovering biomarkers and therapeutic targets by comprehensive screening of metabolites from patients with various cancers. We aimed to identify metabolites associated with early diagnosis and clinicopathological factors in RCC using global metabolomics (G-Met). Tumor and nontumor tissues were sampled from 20 cases of surgically resected clear cell RCC. G-Met was performed by liquid chromatography mass spectrometry and important metabolites specific to RCC were analyzed by multivariate statistical analysis for cancer diagnostic ability based on area under the curve (AUC) and clinicopathological factors (tumor volume, pathological T stage, Fuhrman grade, presence of coagulation necrosis and distant metastasis). We identified 58 metabolites showing significantly increased levels in tumor tissues, 34 of which showed potential early diagnostic ability (AUC >0.8), but 24 did not discriminate between tumor and nontumor tissues (AUC ≤0.8). We recognized 6 pathways from 9 metabolites with AUC >0.8 and 7 pathways from 10 metabolites with AUC ≤0.8 about malignant status. Clinicopathological factors involving malignant status correlated significantly with metabolites showing AUC ≤0.8 (p = 0.0279). The tricarboxylic acid cycle (TCA) cycle, TCA cycle intermediates, nucleotide sugar pathway and inositol pathway were characteristic pathways for the malignant status of RCC. In conclusion, our study found that metabolites and their pathways allowed discrimination between early diagnosis and malignant status in RCC according to our G-Met protocol.