Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry

Comprehensive mapping of saliva by multiomics in children with idiopathic nephrotic syndrome

AIM

Saliva can reflect an individual's physiological status or susceptibility to systemic disease. However, little attention has been given to salivary analysis in children with idiopathic nephrotic syndrome (INS). We aimed to perform a comprehensive analysis of saliva from INS children.

METHODS

A total of 18 children (9 children with INS and 9 normal controls) were recruited. Saliva was collected from each INS patient in the acute and remission phases. 16S rRNA gene sequencing, widely targeted metabolomics, and 4D-DIA proteomics were performed.

RESULTS

Actinobacteria and Firmicutes were significantly enriched in the pretreatment group compared with the normal control group, while Bacteroidota and Proteobacteria were significantly decreased. A total of 146 metabolites were identified as significantly different between INS children before treatment and normal controls, which covers 17 of 23 categories. KEGG enrichment analysis revealed three significantly enriched pathways, including ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and terpenoid backbone biosynthesis (P < 0.05). A total of 389 differentially expressed proteins were selected between INS children before treatment and normal controls. According to the KEGG and GO enrichment analyses of the KOGs, abnormal ribosome structure and function and humoral immune disorders were the most prominent differences between INS patients and normal controls in the proteomic analysis.

CONCLUSION

Oral microbiota dysbiosis may modulate the metabolic profile of saliva in children with INS. It is hypothesized that children with INS might have "abnormal ribosome structure and function" and "humoral immune disorders".

The current use of proteomics and metabolomics in glomerulonephritis: a systematic literature review

BACKGROUND

Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy in the United Kingdom. Metabolomics and proteomics can characterise, identify and quantify an individual's protein and metabolite make-up. These techniques have been optimised and can be performed on samples including kidney tissue, blood and urine. Utilising omic techniques in nephrology can uncover disease pathophysiology and transform the diagnostics and treatment options for glomerulonephritis.

OBJECTIVES

To evaluate the utility of metabolomics and proteomics using mass spectrometry and nuclear magnetic resonance in glomerulonephritis.

METHODS

The systematic review was registered on PROSPERO (CRD42023442092). Standard and extensive Cochrane search methods were used. The latest search date was March 2023. Participants were of any age with a histological diagnosis of glomerulonephritis. Descriptive analysis was performed, and data presented in tabular form. An area under the curve or p-value was presented for potential biomarkers discovered.

RESULTS

Twenty-seven studies were included (metabolomics (n = 9)), and (proteomics (n = 18)) with 1818 participants. The samples analysed were urine (n = 19) blood (n = 4) and biopsy (n = 6). The typical outcome themes were potential biomarkers, disease phenotype, risk of progression and treatment response.

CONCLUSION

This review shows the potential of metabolomic and proteomic analysis to discover new disease biomarkers that may influence diagnostics and disease management. Further larger-scale research is required to establish the validity of the study outcomes, including the several proposed biomarkers.

Metabolome panels as potential noninvasive biomarkers for primary glomerulonephritis sub-types: meta-analysis of profiling metabolomics studies

Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ - 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.

Metabolomic profiles in serum and urine uncover novel biomarkers in children with nephrotic syndrome

BACKGROUND

Nephrotic syndrome is common in children and adults worldwide, and steroid-sensitive nephrotic syndrome (SSNS) accounts for 80%. Aberrant metabolism involvement in early SSNS is sparsely studied, and its pathogenesis remains unclear. Therefore, the goal of this study was to investigate the changes in initiated SSNS patients-related metabolites through serum and urine metabolomics and discover the novel potential metabolites and metabolic pathways.

METHODS

Serum samples (27 SSNS and 56 controls) and urine samples (17 SSNS and 24 controls) were collected. Meanwhile, the non-targeted analyses were performed by ultra-high-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) to determine the changes in SSNS. We applied the causal inference model, the DoWhy model, to assess the causal effects of several selected metabolites. An ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to validate hits (D-mannitol, dulcitol, D-sorbitol, XMP, NADPH, NAD, bilirubin, and α-KG-like) in 41 SSNS and 43 controls. In addition, the metabolic pathways were explored.

RESULTS

Compared to urine, the metabolism analysis of serum samples was more clearly discriminated at SSNS. 194 differential serum metabolites and five metabolic pathways were obtained in the SSNS group. Eight differential metabolites were identified by establishing the diagnostic model for SSNS, and four variables had a positive causal effect. After validation by targeted MS, except XMP, others have similar trends like the untargeted metabolic analysis.

CONCLUSION

With untargeted metabolomics analysis and further targeted quantitative analysis, we found seven metabolites may be new biomarkers for risk prediction and early diagnosis for SSNS.

Metabolomics Profiling of Nephrotic Syndrome towards Biomarker Discovery

Nephrotic syndrome (NS) is a kidney illness characterized by excessive proteinuria, hypoalbuminemia, edema, and hyperlipidemia, which may lead to kidney failure and necessitate renal transplantation. End-stage renal disease, cardiovascular issues, and mortality are much more common in those with NS. Therefore, the present study aimed to identify potential new biomarkers associated with the pathogenesis and diagnosis of NS. The liquid chromatography–mass spectrometry (LC–MS) metabolomics approach was applied to profile the metabolome of human serum of patients with NS. A total of 176 metabolites were significantly altered in NS compared to the control. Arginine, proline, and tryptophan metabolism; arginine, phenylalanine, tyrosine, and tryptophan biosynthesis were the most common metabolic pathways dysregulated in NS. Furthermore, alanyl-lysine and isoleucyl-threonine had the highest discrimination between NS and healthy groups. The candidate biomarkers may lead to understanding the possible metabolic alterations associated with NS and serve as potential diagnostic biomarkers.

Metabolomics analysis of serum in pediatric nephrotic syndrome based on targeted and non-targeted platforms

BACKGROUND AND AIMS

Nephrotic syndrome (NS) is a common pediatric urinary system disease. The aim in this work was to investigate the changes in pediatric NS-related metabolites through serum metabolomics, and explore the new potential metabolites and differential metabolic pathways.

METHODS

Serum samples from 40 pediatric patients with nephrotic syndrome and 40 healthy controls were collected. The targeted and non-targeted metabolomics analyses were performed to determine the metabolic changes in pediatric NS. Based on multivariate statistical analysis and the regression model, the serum potential metabolites were screened and different metabolic pathways were explored.

RESULTS

39 differential metabolites in pediatric NS were obtained based on the metabolomics analysis. 12 differential metabolites (serine, C18: 2 (EFA), C18: 2 (FFA), Isonuatigenin 3- [rhamnosyl- (1- > 2) -glucoside], C18: 4 (EFA), C18: 4 (FFA), caprylic acid, citric acid, methylmalonic acid, caproic acid, canavalioside and uroporphyrin were identified to establish the diagnostic model for pediatric NS. Five metabolic pathways including TCA cycle, amino acid metabolism, bile acid biosynthesis, linoleate metabolism and glyoxylate and dicarboxylate metabolism were the key differential metabolic pathways.

CONCLUSION

These data elucidated the metabolic alterations associated with pediatric NS and suggested a new diagnosis model for monitoring pediatric NS. The current study provides the useful information to bridge the gaps in our understanding of the metabolic alterations associated with pediatric NS and might facilitate the characterization of pediatric NS patients by performing serum metabolomics.

Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease

The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repository, we aimed to identify urinary mRNA biomarkers that can predict histological severity and disease progression in patients with DKD in whom the diagnosis and histologic grade has been confirmed by kidney biopsy. We identified 30 DKD-specific mRNA candidates based on the analysis of the GEO datasets. Among these, there were significant alterations in the urinary levels of 17 mRNAs in patients with DKD, compared with healthy controls. Four urinary mRNAs-LYZ, C3, FKBP5, and G6PC-reflected tubulointerstitial inflammation and fibrosis in kidney biopsy and could predict rapid progression to end-stage kidney disease independently of the baseline eGFR (tertile 1 vs. tertile 3; adjusted hazard ratio of 9.68 and 95% confidence interval of 2.85-32.87, p < 0.001). In conclusion, we demonstrated that urinary mRNA signatures have a potential to indicate the pathologic status and predict adverse renal outcomes in patients with DKD.

Exposure of ultrafine particulate matter causes glutathione redox imbalance in the hippocampus: A neurometabolic susceptibility to Alzheimer's pathology

Particulate matter (PM) exposure is related to an increased risk of sporadic Alzheimer's disease (AD), the pathogenesis of which is explained by chronic neurometabolic disturbance. Therefore, PM-induced alterations in neurometabolism might herald AD. We aimed to identify brain region-specific changes in metabolic pathways associated with ultrafine particle (UFP) exposure and to determine whether such metabolic alterations are linked to susceptibility to AD. We constructed UFP exposure chambers and generated UFP by the pyrolysis method, which produces no toxic oxidized by-products of combustion, such as NOx and CO. Twenty male C57BL6 mice (11-12 months old) were exposed either to UFP or room air in the chambers for 3 weeks. One week following completion of UFP exposure, regional brain tissues, including the olfactory bulb, cortex, hippocampus, and cerebellum, were obtained and analyzed by metabolomics based on GC-MS and LC-MS, western blot analysis, and immunohistochemistry. Our results demonstrated that the metabolomic phenotype was distinct within the 4 different anatomical regions following UFP exposure. The highest level of metabolic change was identified in the hippocampus, a vulnerable region involved in AD pathogenesis. In this region, one of the key changes was perturbed redox homeostasis via alterations in the methionine-glutathione pathway. UFP exposure also induced oxidative stress and neuroinflammation, and importantly, increased Alzheimer's beta-amyloid levels in the hippocampus. These results suggest that inhaled UFP-induced perturbation in hippocampal redox homeostasis has a role in the pathogenesis of AD. Therefore, chronic exposure to UFP should be regarded as a cumulative environmental risk factor for sporadic AD.

Predicting and Defining Steroid Resistance in Pediatric Nephrotic Syndrome Using Plasma Metabolomics

INTRODUCTION

Nephrotic syndrome (NS) is a kidney disease that affects both children and adults. Glucocorticoids have been the primary therapy for >60 years but are ineffective in approximately 20% of children and approximately 50% of adult patients. Unfortunately, patients with steroid-resistant NS (SRNS; vs. steroid-sensitive NS [SSNS]) are at high risk for both glucocorticoid-induced side effects and disease progression.

METHODS

We performed proton nuclear magnetic resonance (1H NMR) metabolomic analyses on plasma samples (n = 86) from 45 patients with NS (30 SSNS and 15 SRNS) obtained at initial disease presentation before glucocorticoid initiation and after approximately 7 weeks of glucocorticoid therapy to identify candidate biomarkers able to either predict SRNS before treatment or define critical molecular pathways/targets regulating steroid resistance.

RESULTS

Stepwise logistic regression models identified creatinine concentration and glutamine concentration (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 0.99-1.02) as 2 candidate biomarkers predictive of SRNS, and malonate concentration (OR: 0.94; 95% CI: 0.89-1.00) as a third candidate predictive biomarker using a similar model (only in children >3 years). In addition, paired-sample analyses identified several candidate biomarkers with the potential to identify mechanistic molecular pathways/targets that regulate clinical steroid resistance, including lipoproteins, adipate, pyruvate, creatine, glucose, tyrosine, valine, glutamine, and sn-glycero-3-phosphcholine.

CONCLUSION

Metabolomic analyses of serial plasma samples from children with SSNS and SRNS identified elevated creatinine and glutamine concentrations, and reduced malonate concentrations, as auspicious candidate biomarkers to predict SRNS at disease onset in pediatric NS, as well as additional candidate biomarkers with the potential to identify mechanistic molecular pathways that may regulate clinical steroid resistance.

Urinary myo-inositol is associated with the clinical outcome in focal segmental glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) have similar initial histological findings; however, their prognoses are distinct. Therefore, it is of great importance to discriminate FSGS from MCD in the early phase of disease and predict clinical prognosis. A discovery set of 184 urine samples (61 healthy control, 80 MCD, and 43 FSGS) and a validation set of 61 urine samples (12 healthy control, 26 MCD, and 23 FSGS) were collected at the time of kidney biopsy. Metabolic profiles were examined using nuclear magnetic resonance spectroscopy. Of 70 urinary metabolites, myo-inositol was significantly higher in FSGS patients than in control patients (discovery set, 2.34-fold, P < 0.001; validation set, 2.35-fold, P = 0.008) and MCD patients (discovery set, 2.48-fold, P = 0.002; validation set, 1.69-fold, P = 0.042). Myo-inositol showed an inverse relationship with the initial estimated glomerular filtration rate (eGFR) and was associated with the plasma level of soluble urokinase-type plasminogen activator receptor in FSGS patients. Myo-inositol treatment ameliorated the decreased expression of ZO-1 and synaptopodin in an in vitro FSGS model, and as myo-inositol increased, myo-inositol oxygenase tissue expression decreased proportionally to eGFR. Furthermore, urinary myo-inositol exhibited an increase in the power to discriminate FSGS patients, and its addition could better predict the response to initial treatment. In conclusion, urinary myo-inositol may be an important indicator in the diagnosis and treatment of FSGS patients.

Fermented Cordyceps militaris Extract Prevents Hepatosteatosis and Adipocyte Hypertrophy in High Fat Diet-Fed Mice

Nonalcoholic fatty liver diseases (NAFLD) is characterized by accumulation of lipid droplets in the liver. The objective of this study was to evaluate protective effects of fermented Cordyceps militaris extract by Pediococcus pentosaceus ON188 (ONE) against hepatosteatosis and obesity in mice fed a high-fat diet (HFD). Eight-week-old male C57BL/6J mice were fed HFD mixed with ONE for four weeks and its effects on hepatosteatosis and obesity were examined. Although ONE did not change food intake, it reduced body weights of mice at administration dose of 200 mg/kg/day. Activities of lactate dehydrogenase (LDH), aspartate transaminase (AST), and alanine transaminase (ALT) as plasma parameters were reduced by ONE in a dose-dependent manner. Hepatic lipid droplets and triglyceride (TG) levels were also reduced by ONE due to upregulation of fatty acid oxidizing genes such as carnithine palmitoyltransferase (CPT1) and peroxisomal proliferator activated receptor α(PPARα) mediated by induction of sphingosine kinase 2 (SPHK2). In epididymal fat tissue, sizes of adipocytes were significantly reduced by ONE in a dose-dependent manner. This is mainly due to suppression of lipogenesis and upregulation of adipocyte browning genes. Collectively, these results suggest that fermented ONE can activate fatty acid oxidation via SPHK2 in the liver. It can also suppress lipogenesis and activate browning in adipose tissue. Thus, ONE might have potential to be used for the development of functional foods against liver dysfunction and obesity.

Fermented Cordyceps militaris Extract Ameliorates Hepatosteatosis via Activation of Fatty Acid Oxidation

Nonalcoholic fatty liver disease is a progressive disease involving the accumulation of lipid droplets in the liver. In this study, we investigated the anti-hepatosteatosis effects of fermented Cordyceps militaris extract (CME) in AML-12 hepatocytes. Although the levels of adenosine and cordycepin were reduced in the extracts of CM grown on germinated soybean (GSCE) and fermented CM grown on germinated soybean (GSC) by Pediococcus pentosaceus ON188 (ON188E), the expression of fatty acid oxidation (FAO) genes were upregulated only by GSC-ON188E treatment in a dose-dependent manner. In contrast, a lipogenic gene, stearoyl Coenzyme A desaturase 1, was downregulated by ON188E. Formation of intracellular lipid droplets by the addition of oleic acid was reduced by ON188E to levels observed in WY14643-treated cells. When cells were treated with ON188E, sphingosine kinase 2 mainly responsible for hepatic sphingosine 1-phosphate (S1P) synthesis was upregulated and S1P was elevated. Collectively, the fermented GSC extract activates FAO through elevation of S1P synthesis and has potential as a therapeutic for hepatosteatosis.

Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.

Brain Metabolomics Reveal the Antipyretic Effects of Jinxin Oral Liquid in Young Rats by Using Gas Chromatography⁻Mass Spectrometry

Pyrexia is considered as a part of host's defense response to the invasion of microorganisms or inanimate matter recognized as pathogenic or alien, which frequently occurs in children. Jinxin oral liquid (JXOL) is a traditional Chinese medicine formula that has been widely used to treat febrile children in China. Experimental fever was induced by injecting yeast into young male Sprague-Dawley rats (80 ± 20 g) and the rectal temperature subsequently changed. Four hours later, the excessive production of interleukin (IL)-1β and prostaglandin (PG) E2 induced by yeast was regulated to normal by JXOL administration. A rat brain metabolomics investigation of pyrexia of yeast and antipyretic effect of JXOL was performed using gas chromatography-mass spectrometry (GC-MS). Clear separation was achieved between the model and normal group. Twenty-two significantly altered metabolites were found in pyretic rats as potential biomarkers of fever. Twelve metabolites, significantly adjusted by JXOL to help relieve pyrexia, were selected out as biomarkers of antipyretic mechanism of JXOL, which were involved in glycolysis, purine metabolism, tryptophan mechanism, etc. In conclusion, the brain metabolomics revealed potential biomarkers in the JXOL antipyretic process and the associated pathways, which may aid in advanced understanding of fever and therapeutic mechanism of JXOL.

Pediococcus pentosaceus-Fermented Cordyceps militaris Inhibits Inflammatory Reactions and Alleviates Contact Dermatitis

Cordyceps militaris is a medicinal mushroom used to treat immune-related diseases in East Asia. We investigated the anti-inflammatory effect of the extract of C. militaris grown on germinated Rhynchosia nulubilis (GRC) fermented with Pediococcus pentosaceus ON89A isolated from onion (GRC-ON89A) in vivo as well as in vitro. The anti-inflammatory effect of GRC-ON89A was investigated in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. The total polyphenol content (TPC) and total flavonoid content (TFC) in the GRC-ON89A ethanol extract were significantly increased compared to that in GRC. GRC-ON89A hexane fraction (GRC-ON89A-Hex) inhibited the release of nitric oxide (NO) compared to that of the LPS-treated control without cytotoxicity in LPS-stimulated RAW 264.7 macrophages. GRC-ON89A-Hex decreased the inducible NO synthase (iNOS), cyclooxygenase 2 (COX2), and tumor necrosis factor (TNF)-α mRNA expression in LPS-stimulated RAW 264.7 macrophages. In addition, pre-treatment with GRC-ON89A-Hex significantly inhibited LPS-stimulated phosphorylation of mitogen-activated protein kinases (MAPKs) and nuclear factor (NF)-κB. To induce allergic contact dermatitis (ACD), 1-fluoro-2, 4-dinitrofluorobenzene (DNFB) was applied to the surface of the right ears of C57BL/6N mice. GRC-ON89A reduced the ear swelling and thickness in DNFB-induced ACD mice. This study demonstrates the potential usefulness of GRC-ON89A as an anti-inflammatory dietary supplement or drug.

Comparative assessment of Graves' disease and main extrathyroidal manifestation, Graves' ophthalmopathy, by non-targeted metabolite profiling of blood and orbital tissue

Graves' disease (GD) is an autoimmune disorder that causes the overproduction of thyroid hormones and consequent cascade of systemic metabolism dysfunction. Moreover, Graves' ophthalmopathy (GO) is the main extrathyroidal manifestation of Graves' disease (GD). The goal of the study was to identify metabolic signatures in association with diagnostic biomarkers of GD without GO and GO, respectively. Ninety metabolites were profiled and analyzed based on a non-targeted primary metabolite profiling from plasma samples of 21 GD patients without GO, 26 subjects with GO, and 32 healthy subjects. Multivariate statistics showed a clear discrimination between healthy controls and disease group (R2Y = 0.518, Q2 = 0.478) and suggested a biomarker panel consisting of 10 metabolites. Among them, most of metabolites showed the positive association with the levels of thyrotropin receptor antibodies. With combination of proline and 1,5-anhydroglucitol, which were identified as GO-specific modulators, the re-constructed biomarker model greatly improved the statistical power and also facilitated simultaneous discrimination among healthy control, GO, and GD without GO groups (AUC = 0.845-0.935). Finally, the comparative analysis of tissue metabolite profiles from GO patients proposed putative metabolic linkage between orbital adipose/connective tissues and the biofluidic consequences, in which fumarate, proline, phenylalanine, and glycerol were coordinately altered with the blood metabolites.

A review of validated biomarkers obtained through metabolomics

INTRODUCTION

Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.

The future perspective: metabolomics in laboratory medicine for inborn errors of metabolism

Metabolomics can be described as a simultaneous and comprehensive analysis of small molecules in a biological sample. Recent technological and bioinformatics advances have facilitated large-scale metabolomic studies in many areas, including inborn errors of metabolism (IEMs). Despite significant improvements in the diagnosis and treatment of some IEMs, it is still challenging to understand how genetic variation affects disease progression and susceptibility. In addition, a search for new more personalized therapies and a growing demand for tools to monitor the long-term metabolic effects of existing therapies set the stage for metabolomics integration in preclinical and clinical studies. While targeted metabolomics approach is a common practice in biochemical genetics laboratories for biochemical diagnosis and monitoring of IEMs, applications of untargeted metabolomics in the clinical laboratories are still in infancy, facing some challenges. It is however, expected in the future to dramatically change the scope and utility of the clinical laboratory playing a significant role in patient management. This review provides an overview of targeted and global, large-scale metabolomic studies applied to investigate various IEMs. We discuss an existing and prospective clinical applications of metabolomics in IEMs for better diagnosis and deep understanding of complex metabolic perturbations associated with the etiology of inherited metabolic disorders.

A comprehensive narrative review of diagnostic biomarkers in human primary membranous nephropathy

Membranous nephropathy (MN) is relatively major cause of nephrotic syndrome in adults which is recognized as an organ-specific autoimmune disease. The etiology of most cases is idiopathic, whereas the secondary MN is caused by systemic autoimmune diseases, infections, medications and malignancies. The idiopathic disease is developed by the formation of sub-epithelial immune complex deposits most likely due to binding the circulating auto-antibodies to intrinsic antigen on podocytes. The major auto antibody is the anti-phospholipase A2 receptor (anti-PLA2R), however, it is not enough sensitive. Several attempts for diagnostic biomarker identification by modern analytical technologies have been devoted recently. This article reviews the biomarker candidates for primary type of MN that are detected by different approaches on human subjects.

Potential metabolomic biomarkers for reliable diagnosis of Behcet's disease using gas chromatography/ time-of-flight-mass spectrometry

OBJECTIVES

Although many diagnostic criteria of Behcet's disease (BD) have been developed and revised by experts, diagnosing BD is still complicated and challenging. No metabolomic studies on serum have been attempted to improve the diagnosis and to identify potential biomarkers of BD. The purposes of this study were to investigate distinctive metabolic changes in serum samples of BD patients and to identify metabolic candidate biomarkers for reliable diagnosis of BD using the metabolomics platform.

METHODS

Metabolomic profiling of 90 serum samples from 45 BD patients and 45 healthy controls (HCs) were performed via gas chromatography with time-of-flight mass spectrometry (GC/TOF-MS) with multivariate statistical analyses.

RESULTS

A total of 104 metabolites were identified from samples. The serum metabolite profiles obtained from GC/TOF-MS analysis can distinguish BD patients from HC group in discovery set. The variation values of the partial least squared-discrimination analysis (PLS-DA) model are R²X of 0.246, R²Y of 0.913 and Q² of 0.852, respectively, indicating strong explanation and prediction capabilities of the model. A panel of five metabolic biomarkers, namely, decanoic acid, fructose, tagatose, linoleic acid and oleic acid were selected and adequately validated as putative biomarkers of BD (sensitivity 100%, specificity 97.1%, area under the curve 0.998) in the discovery set and independent set. The PLS_DA model showed clear discrimination of BD and HC groups by the five metabolic biomarkers in independent set.

CONCLUSIONS

This is the first report on characteristic metabolic profiles and potential metabolite biomarkers in serum for reliable diagnosis of BD using GC/TOF-MS.

Exploratory metabolomics of biomarker identification for the internet gaming disorder in young Korean males

The main aim of the current research is to characterize the molecular dynamics related to internet gaming disorder (IGD) using non-targeted plasma metabolite profiling based on gas-chromatography time-of-flight mass spectrometry (GC-TOF MS). IGD is a psychiatric disorder instigated by excessive and prolonged internet gaming, which shared many pathological symptoms with attention deficit hyperactivity disorder (ADHD). The prevalence of the disorder has been rapidly increased particularly in East Asia countries (5.9% in South Korea) compared to Europe or North America (0.3-1.0% in United States and 1.16% in Germany). Thus we comparably explored the correlation between plasma metabolites and internet addiction severity in IGD patients, and potential biomarker composite in combination with clinical parameters. The systematic metabolite profiling of 54 blood samples (normal user, N=28 and IGD, N=24) identified a total of 104 metabolites out of 1212 metabolic feature, and revealed unique relation of co-linearly regressed set of plasma metabolites (arabitol, myo-inositol, methionine, pyrrole-2-carboxylic acid, and aspartic acid) with internet addiction severity scale (R=0.795). In addition, orthogonal partial least squared discriminant analysis (OPLS-DA) and receiver operating characteristic (ROC) analysis identified the potential biomarker cluster that simultaneously discriminated the different types of the psychiatric status. The potential biomarker re-composite was comprehensively evaluated by a receiver operating characteristic (ROC) analysis where the AUCs were 0.890, 0.880, 1.000, and 0.935 for control, IGD, AD and IGD+AD, respectively (N=18, 19, 5, and 10) against the others. This exploratory method may provide robustness of predictive diagnosis in population screening of IGD. The identified metabolic features, the relatedness with clinical parameters, and the putative biochemical linkage will hopefully aid future pathological studies in IGD.