Metabolomics for laboratory diagnostics

Assessment of progression of pulmonary fibrosis based on metabonomics and analysis of intestinal microbiota

The main purpose of this study was to explore the changes of biomarkers in different developmental stages of bleomycin-induced pulmonary fibrosis (PF) in rats via comprehensive pathophysiology, UPLC-QTOF/MS metabonomic technology, and 16S rRNA gene sequencing of intestinal microbiota. The rats were randomly divided into normal control and 1-, 2- and 4-week model group. The rat model of PF was established by one-time intratracheal instillation of bleomycin. The levels of inflammatory and fibrosis-related factors such as hydroxyproline (HYP), type III procollagen (COL-III), type IV collagen (COL-IV), hyaluronidase (HA), laminin (LN), interleukin (IL)-1β, IL-6, malondialdehyde (MDA) increased and superoxide dismutase (SOD) decreased as the PF cycle progressed. In the 1-, 2- and 4-week model group, 2, 19 and 18 potential metabolic biomarkers and 3, 16 and 12 potential microbial biomarkers were detected, respectively, which were significantly correlated. Glycerophospholipid metabolism pathway was observed to be an important pathway affecting PF at 1, 2 and 4 weeks; arginine and proline metabolism pathways significantly affected PF at 2 weeks. Linoleic acid metabolism pathway exhibited clear metabolic abnormalities at 2 and 4 weeks of PF, and alpha-linolenic acid metabolism pathway significantly affected PF at 4 weeks.

Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

[Characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome]

OBJECTIVES

To study the characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome (OSAHS).

METHODS

A total of 31 children aged 4-6 years with OSAHS were prospectively enrolled as the test group, and 24 healthy children aged 4-6 years were included as the control group. Relevant clinical indicators were recorded. Fecal samples were collected, and non-targeted metabolomics analysis using liquid chromatography-mass spectrometry was performed to detect all metabolites.

RESULTS

A total of 206 metabolites were detected, mainly amino acids and their derivatives. There was a significant difference in the overall composition of intestinal metabolites between the test and control groups (P<0.05). Eighteen different metabolites were selected, among which six (N-acetylmethionine, L-methionine, L-lysine, DL-phenylalanine, L-tyrosine, and L-isoleucine) had receiver operating characteristic curve areas greater than 0.7 for diagnosing OSAHS. Among them, N-acetylmethionine had the largest area under the curve, which was 0.807, with a sensitivity of 70.83% and a specificity of 80.65%. Correlation analysis between different metabolites and clinical indicators showed that there were positive correlations between the degree of tonsil enlargement and enterolactone, between uric acid and phenylacetaldehyde, between blood glucose and acetylmethionine, and between cholesterol and 9-bromodiphenyl and procaine (P<0.05). There were negative correlations between the degree of tonsil enlargement and N-methyltyramine, aspartate aminotransferase and indolepropionic acid and L-isoleucine, between alanine aminotransferase and DL-phenylalanine, between indolepropionic acid and L-isoleucine, between uric acid and hydroxyquinoline, and between urea nitrogen and N,N-dicyclohexylurea (P<0.05). The metabolic functional pathways affected by differential metabolites mainly included riboflavin metabolism, arginine and proline metabolism, pantothenic acid and coenzyme A biosynthesis, cysteine and methionine metabolism, lysine degradation and glutathione metabolism.

CONCLUSIONS

Intestinal metabolites and metabolic functions are altered in children aged 4-6 years with OSAHS, primarily involving amino acid metabolism disorders. The screened differential intestinal metabolites have potential screening and diagnostic value as biomarkers for OSAHS.

Metabolomics efficiently discriminates monozygotic twins in peripheral blood

Monozygotic (MZ) twins cannot be distinguished using conventional forensic STR typing because they present identical STR genotypings. However, MZ twins do not always live in the same environment and often have different dietary and other lifestyle habits. Metabolic profiles are deyermined by individual characteristics and are also influenced by the environment in which they live. Therefore, they are potential markers capable of identifying MZ twins. Moreover, the production of proteins varies from organism to organism and is influenced by both the physiological state of the body and the external environment. Hence, we used metabolomics and proteomics to identify metabolites and proteins in peripheral blood to discriminate MZ twins. We identified 1749 known metabolites and 622 proteins in proteomic analysis. The metabolic profiles of four pairs of MZ twins revealed minor differences in intra-MZ twins and major differences in inter-MZ twins. Each pair of MZ twins exhibited distinct characteristics, and four metabolites-methyl picolinate, acesulfame, paraxanthine, and phenylbenzimidazole sulfonic acid-were observed in all four MZ twin pairs. These four differential exogenous metabolites conincidently show that the different external environments and life styles can be well distinguished by metabolites, considering that twins do not all have the same eating habits and living environments. Moreover, MZ twins showed different protein profiles in serum but not in whole blood. Thus, our results indicate that differential metabolites provide potential biomarkers for the personal identification of MZ twins in forensic medicine.

Stereoselective Amine-omics Using Heavy Atom Isotope Labeled l- and d-Marfey's Reagents

Biological amines and amino acids play essential roles in many biochemical processes. The chemical complexity of biological samples is challenging, and the selective identification and quantification of amines and amino acid stereoisomers would be very useful for amine-focused "amino-omics" studies. Many amines and amino acids are chiral, and their stereoisomers cannot be resolved on achiral media without chiral derivatization. In prior studies, we demonstrated the use of Marfey's reagent─a chiral derivatization reagent for amines and phenolic OH groups─for the LC-MS/MS resolution and quantification of amines and amino acid stereoisomers. In this study, a heavy atom isotope labeled Marfey's reagent approach for the stereoselective detection and quantification of amines and amino acids was developed. Heavy (13C2) l-Marfey's (Hl-Mar) and heavy (2H3) d-Marfey's (Hd-Mar) were synthesized from 13C2-l-Ala and 2H3-d-Ala, respectively. Both light and heavy Marfey's reagents were used to derivatize standard amine mixtures, which were analyzed by LC-QToF-HRMS. Aligned peak lists were comparatively analyzed by light vs heavy Mar mass differences to identify mono-, di-, and tri-Marfey's adducts and then by the retention time difference between l- and d-Mar derivatives to identify stereoisomers. This approach was then applied to identify achiral and chiral amine and amino acid components in a methicillin-resistant Staphylococcus aureus (MRSA) extract. This approach shows high analytical selectivity and reproducibility.

Metabolic profiling during COVID-19 infection in humans: Identification of potential biomarkers for occurrence, severity and outcomes using machine learning

BACKGROUND

After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity.

METHODS

Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models.

RESULTS

The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness.

CONCLUSIONS

Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Development and trends in metabolomics studies in psoriasis: A bibliometric analysis of related research from 2011 to 2024

Background

Psoriasis is a chronic, inflammatory skin disease with autoimmune characteristics. Recent research has made significant progress in the field of psoriasis metabolomics. However, there is a lack of bibliometric analysis on metabolomics of psoriasis. The objective of this study is to utilize bibliometrics to present a comprehensive understanding of the knowledge structure and research hotspots in psoriasis within the field of metabolomics.

Methods

We conducted a bibliometric analysis by searching the Web of Science Core Collection database for publications on metabolomics in psoriasis from 2011 to 2024. To perform this analysis, we utilized tools such as VOSviewers, CiteSpace, and the R package "bibliometrix".

Results

A total of 307 articles from 47 countries, with the United States and China leading the way, were included in the analysis. The publications focusing on metabolomics in psoriasis have shown a steady year-on-year growth. The Medical University of Bialystok is the main research institution. The International Journal of Molecular Sciences emerges as the prominent journal in the field, while the Journal of Investigative Dermatology stands out as the highly co-cited publication. A total of 2029 authors contributed to these publications, with Skrzydlewska Elzbieta, Baran Anna, Flisiak Iwona, Murakami Makoto being the most prolific contributors. Notably, Armstrong April W. received the highest co-citation. Investigating the mechanisms of metabolomics in the onset and progression of psoriasis, as well as exploring therapeutic strategies, represents the primary focus of this research area. Emerging research hotspots encompass inflammation, lipid metabolism, biomarker, metabolic syndrome, obesity, and arthritis.

Conclusion

The results of this study indicate that metabolism-related research is thriving in psoriasis, with a focus on the investigation of metabolic targets and interventions within the metabolic processes. Metabolism is expected to be a hot topic in future psoriasis research.

Biomarkers of bipolar disorder based on metabolomics: A systematic review

Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.

Metabolomics for the diagnosis of bladder cancer: A systematic review

Objective

Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.

Methods

A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.

Results

The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.

Conclusion

The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.

Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

Gentiopicroside improves non-alcoholic steatohepatitis by activating PPARα and suppressing HIF1

Gentiopicroside (GPS) is a highly water-soluble small-molecule drug and the main bioactive secoiridoid glycoside of Gentiana scabra that has been shown to have hepatoprotective effects against non-alcoholic steatohepatitis (NASH), a form of non-alcoholic fatty liver disease (NAFLD) that can progress to cirrhosis and hepatocellular carcinoma. However, the effects of GPS on NASH and the underlying mechanisms remain obscure. Firstly, a high-fat, high-cholesterol (HFHC) diet and a high-sugar solution containing d-fructose and d-glucose were used to establish a non-alcoholic steatohepatitis (NASH) mice model. Secondly, we confirmed GPS supplementation improve metabolic abnormalities and reduce inflammation in NASH mice induced by HFHC and high-sugar solution. Then we used metabolomics to investigate the mechanisms of GPS in NASH mice. Metabolomics analysis showed GPS may work through the Peroxisome Proliferator-Activated Receptor (PPAR) signaling pathway and glycine, serine, and threonine metabolism. Functional metabolites restored by GPS included serine, glycine, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Western blot and qRT-PCR analysis confirmed GPS improve NASH by regulating PPARα and Hypoxia-Inducible Factor-1α (HIF-1α) signaling pathways. In vitro, studies further demonstrated EPA and DHA enhance fatty acid oxidation through the PPARα pathway, while serine and glycine inhibit oxidative stress through the HIF-1α pathway in palmitic acid-stimulated HepG2 cells. Our results suggest GPS's anti-inflammatory and anti-steatosis effects in NASH progression are related to the suppression of HIF-1α through the restoration of L-serine and glycine and the activation of PPARα through increased EPA and DHA.

Profiling canine mammary tumors: A potential model for studying human breast cancer

Despite all clinical progress recorded in the last decades, human breast cancer (HBC) remains a major challenge worldwide both in terms of its incidence and its management. Canine mammary tumors (CMTs) share similarities with HBC and represent an alternative model for HBC. The utility of the canine model in studying HBC relies on their common features, include spontaneous development, subtype classification, mutational profile, alterations in gene expression profile, and incidence/prevalence. This review describes the similarities between CMTs and HBC regarding genomic landscape, microRNA expression alteration, methylation, and metabolomic changes occurring during mammary gland carcinogenesis. The primary purpose of this review is to highlight the advantages of using the canine model as a translational animal model for HBC research and to investigate the challenges and limitations of this approach.

Determining predictive metabolomic biomarkers of meniscal injury in dogs with cranial cruciate ligament rupture

OBJECTIVES

This study used hydrogen nuclear magnetic resonance spectroscopy for the first time to examine differences in the metabolomic profile of stifle joint synovial fluid from dogs with cranial cruciate ligament rupture with and without meniscal injuries, in order to identify biomarkers of meniscal injury. Identifying a biomarker of meniscal injury could then ultimately be used to design a minimally invasive diagnostic test for meniscal injuries in dogs.

MATERIALS AND METHODS

Stifle joint synovial fluid was collected from dogs undergoing stifle joint surgery or arthrocentesis for lameness investigations. We used multi-variate statistical analysis using principal component analysis and univariate statistical analysis using one-way analysis of variance and analysis of co-variance to identify differences in the metabolomic profile between dogs with cranial cruciate ligament rupture and meniscal injury, cranial cruciate ligament rupture without meniscal injury, and neither cranial cruciate ligament rupture nor meniscal injury, taking into consideration clinical variables.

RESULTS

A total of 154 samples of canine synovial fluid were included in the study. Sixty-four metabolites were annotated to the hydrogen nuclear magnetic resonance spectroscopy spectra. Six spectral regions were found to be significantly altered (false discovery rate adjusted P-value <0.05) between groups with cranial cruciate ligament rupture with and without meniscal injury, including three attributed to nuclear magnetic resonance mobile lipids [mobile lipid -CH3 (P=0.016), mobile lipid -n(CH3 )3 (P=0.017), mobile unsaturated lipid (P=0.031)].

CLINICAL SIGNIFICANCE

We identified an increase in nuclear magnetic resonance mobile lipids in the synovial fluid of dogs with meniscal injury which are of interest as potential biomarkers of meniscal injury.

Exploiting volatile fingerprints for bladder cancer diagnosis: A scoping review of metabolomics and sensor-based approaches

Bladder cancer (BC) represents a significant global health concern, for which early detection is essential to improve patient outcomes. This review evaluates the potential of the urinary volatile organic compounds (VOCs) as biomarkers for detecting and staging BC. The methods used include gas chromatography-mass spectrometry (GC-MS)-based metabolomics and electronic-nose (e-nose) sensors. The GC-MS studies that have been published reveal diverse results in terms of diagnostic performance. The sensitivities range from 27 % to an impressive 97 %, while specificities vary between 43 % and 94 %. Furthermore, the accuracies reported in these studies range from 80 to 89 %. In the urine of BC patients, a total of 80 VOCs were discovered to be significantly altered when compared to controls. These VOCs encompassed a variety of chemical classes such as alcohols, aldehydes, alkanes, aromatic compounds, fatty acids, ketones, and terpenoids, among others. Conversely, e-nose-based studies displayed sensitivities from 60 to 100 %, specificities from 53 to 96 %, and accuracies from 65 to 97 %. Interestingly, conductive polymer-based sensors performed better, followed by metal oxide semiconductor and optical sensors. GC-MS studies have shown improved performance in detecting early stages and low-grade tumors, providing valuable insights into staging. Based on these findings, VOC-based diagnostic tools hold great promise for early BC detection and staging. Further studies are needed to validate biomarkers and their classification performance. In the future, advancements in VOC profiling technologies may significantly contribute to improving the overall survival and quality of life for BC patients.

The regulatory effect of Angelicae Sinensis Radix on neuroendocrine-immune network and sphingolipid metabolism in CUMS-induced model of depression

ETHNOPHARMACOLOGICAL RELEVANCE

Conventional antidepressants therapy remains unsatisfactory due to the disadvantages of delayed clinical onset of action and side effects. Traditional Chinese Medicine (TCM) with good efficacy and higher safety have received much attention. Angelicae Sinensis Radix (AS), a well-known TCM, has been proved to exhibit the efficacy of antidepression recently.

AIM OF THE STUDY

The purpose of this study was to investigate the potential anti-depressant mechanisms of AS based on chronic unpredictable mild stress (CUMS) rat model.

MATERIALS AND METHODS

In this study, behavioral experiments, molecular biology techniques, and ultra performance liquid chromatography-triple-time of flight mass spectrometer (UPLC-Triple-TOF/MS) were combined to explore the potential antidepressant mechanisms of AS based on CUMS rat model.

RESULTS

The results demonstrated that AS could reduce the contents of serum hypothalamic-pituitary-adrenal (HPA) axis hormones in CUMS rats, including corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol (CORT). In addition, AS regulated the percentage of CD4+ T lymphocytes, the ratio of CD4+/CD8+, and the levels of serum cytokines such as IL-1β, IL-4, IL-6, and TNF-α in CUMS rats. Lipidomics showed that 31 lipids were related to depression and AS could regulate the lipid metabolism alteration induced by CUMS, particularly sphingolipid metabolism. Finally, the key proteins in sphingolipid metabolic pathways in hippocampus of CUMS rats could be back-regulated by AS, including serine palmitoyl transferase (SPTLC2), ceramide synthase (CerS2), sphingomyelinase (SPHK1), and neutral sphingomyelinase (nSMase).

CONCLUSION

AS could alleviate NEI network disorder and restore the levels of sphingolipid metabolites and key proteins in CUMS rats. The underlying mechanism by which AS relieved depression-like behavior in CUMS rats may be through modulation of NEI and disturbances in sphingolipid metabolism.

Discovery of potential biomarkers for osteoporosis using LC/GC-MS metabolomic methods

Purpose

For early diagnosis of osteoporosis (OP), plasma metabolomics of OP was studied by untargeted LC/GC-MS in a Chinese elderly population to find possible diagnostic biomarkers.

Methods

A total of 379 Chinese community-dwelling older adults aged ≥65 years were recruited for this study. The BMD of the calcaneus was measured using quantitative ultrasound (QUS), and a T value ≤-2.5 was defined as OP. Twenty-nine men and 47 women with OP were screened, and 29 men and 36 women were matched according to age and BMI as normal controls using propensity matching. Plasma from these participants was first analyzed by untargeted LC/GC-MS, followed by FC and P values to screen for differential metabolites and heatmaps and box plots to differentiate metabolites between groups. Finally, metabolic pathway enrichment analysis of differential metabolites was performed based on KEGG, and pathways with P ≤ 0.05 were selected as enrichment pathways.

Results

We screened metabolites with FC>1.2 or FC<1/1.2 and P<0.05 and found 33 differential metabolites in elderly men and 30 differential metabolites in elderly women that could be potential biomarkers for OP. 2-Aminomuconic acid semialdehyde (AUC=0.72, 95% CI 0.582-0.857, P=0.004) is highly likely to be a biomarker for screening OP in older men. Tetradecanedioic acid (AUC=0.70, 95% CI 0.575-0.818, P=0.004) is highly likely to be a biomarker for screening OP in older women.

Conclusion

These findings can be applied to clinical work through further validation studies. This study also shows that metabolomic analysis has great potential for application in the early diagnosis and recurrence monitoring of OP in elderly individuals.

Metabolic Patterns of High-Invasive and Low-Invasive Oral Squamous Cell Carcinoma Cells Using Quantitative Metabolomics and 13C-Glucose Tracing

Most current metabolomics studies of oral squamous cell carcinoma (OSCC) are mainly focused on identifying potential biomarkers for early screening and diagnosis, while few studies have investigated the metabolic profiles promoting metastasis. In this study, we aimed to explore the altered metabolic pathways associated with metastasis of OSCC. Here, we identified four OSCC cell models (CAL27, HN6, HSC-3, SAS) that possess different invasive heterogeneity via the transwell invasion assay and divided them into high-invasive (HN6, SAS) and low-invasive (CAL27, HSC-3) cells. Quantitative analysis and stable isotope tracing using [U-13C6] glucose were performed to detect the altered metabolites in high-invasive OSCC cells, low-invasive OSCC cells and normal human oral keratinocytes (HOK). The metabolic changes in the high-invasive and low-invasive cells included elevated glycolysis, increased fatty acid metabolism and an impaired TCA cycle compared with HOK. Moreover, pathway analysis demonstrated significant differences in fatty acid biosynthesis; arachidonic acid (AA) metabolism; and glycine, serine and threonine metabolism between the high-invasive and low-invasive cells. Furthermore, the high-invasive cells displayed a significant increase in the percentages of 13C-glycine, 13C-palmitate, 13C-stearic acid, 13C-oleic acid, 13C-AA and estimated FADS1/2 activities compared with the low-invasive cells. Overall, this exploratory study suggested that the metabolic differences related to the metastatic phenotypes of OSCC cells were concentrated in glycine metabolism, de novo fatty acid synthesis and polyunsaturated fatty acid (PUFA) metabolism, providing a comprehensive understanding of the metabolic alterations and a basis for studying related molecular mechanisms in metastatic OSCC cells.

Serum metabolic alterations in peritoneal dialysis patients with excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS-metabolite-target network and the protein-protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.

The Integration of the Metabolome and Transcriptome for Dendrobium nobile Lindl. in Response to Methyl Jasmonate

Dendrobium nobile Lindl., as an endangered medicinal plant within the genus Dendrobium, is widely distributed in southwestern China and has important ecological and economic value. There are a variety of metabolites with pharmacological activity in D. nobile. The alkaloids and polysaccharides contained within D. nobile are very important active components, which mainly have antiviral, anti-tumor, and immunity improvement effects. However, the changes in the compounds and functional genes of D. nobile induced by methyl jasmonate (MeJA) are not clearly understood. In this study, the metabolome and transcriptome of D. nobile were analyzed after exposure to MeJA. A total of 377 differential metabolites were obtained through data analysis, of which 15 were related to polysaccharide pathways and 35 were related to terpenoids and alkaloids pathways. Additionally, the transcriptome sequencing results identified 3256 differentially expressed genes that were discovered in 11 groups. Compared with the control group, 1346 unigenes were differentially expressed in the samples treated with MeJA for 14 days (TF14). Moreover, the expression levels of differentially expressed genes were also significant at different growth and development stages. According to GO and KEGG annotations, 189 and 99 candidate genes were identified as being involved in terpenoid biosynthesis and polysaccharide biosynthesis, respectively. In addition, the co-expression analysis indicated that 238 and 313 transcription factors (TFs) may contribute to the regulation of terpenoid and polysaccharide biosynthesis, respectively. Through a heat map analysis, fourteen terpenoid synthetase genes, twenty-three cytochrome P450 oxidase genes, eight methyltransferase genes, and six aminotransferase genes were identified that may be related to dendrobine biosynthesis. Among them, one sesquiterpene synthase gene was found to be highly expressed after the treatment with MeJA and was positively correlated with the content of dendrobine. This study provides important and valuable metabolomics and transcriptomic information for the further understanding of D. nobile at the metabolic and molecular levels and provides candidate genes and possible intermediate compounds for the dendrobine biosynthesis pathway, which lays a certain foundation for further research on and application of Dendrobium.

Lung proteomics combined with metabolomics reveals molecular characteristics of inflammation-related lung tumorigenesis induced by B(a)P and LPS

Inflammatory microenvironment may take a promoting role in lung tumorigenesis. However, the molecular characteristics underlying inflammation-related lung cancer remains unknown. In this work, the inflammation-related lung tumorigenesis mouse model was established by treated with B(a)P (1 mg/mouse, once a week for 4 weeks), followed by LPS (2.5 μg/mouse, once every 3 weeks for five times), the mice were sacrificed 30 weeks after exposure. TMT-labeled quantitative proteomics and untargeted metabolomics were used to interrogate differentially expressed proteins and metabolites in different mouse cancer tissues, followed by integrated crosstalk between proteomics and metabolomics through Spearman's correlation analysis. The result showed that compared with the control group, 103 proteins and 37 metabolites in B(a)P/LPS group were identified as significantly altered. By searching KEGG pathway database, proteomics pathways such as Leishmaniasis, Asthma and Intestinal immune network for IgA production, metabolomics pathways such as Vascular smooth muscle contraction, Linoleic acid metabolism and cGMP-PKG signaling pathway were enriched. A total of 22 pathways were enriched after conjoint analysis of the proteomic and metabolomics, and purine metabolism pathway, the unique metabolism-related pathway, which included significantly altered protein (adenylate cyclase 4, ADCY4) and metabolites (L-Glutamine, guanosine monophosphate (GMP), adenosine and guanosine) was found. Results suggested purine metabolism may contribute to the inflammation-related lung tumorigenesis, which may provide novel clues for the therapeutic strategies of inflammation-related lung cancer.

The Kynurenine/Tryptophan Ratio as a Promising Metabolomic Biomarker for Diagnosing the Spectrum of Tuberculosis Infection and Disease

The metabolic system and immunology used to be seen as distinct fields of study. Recent developments in our understanding of how the immune system operates in health and disease have connected these fields to complex systems. An effective technique for identifying probable abnormalities of metabolic homeostasis brought on by disease is metabolomics, which is defined as the thorough study of small molecule metabolic intermediates within a biological system that collectively make up the metabolome. A prognostic metabolic biomarker with adequate prognostic accuracy for tuberculosis progression has recently been created. The rate-limiting host enzyme for the conversion of tryptophan to kynurenine, indoleamine 2,3-dioxygenase (IDO), is greatly elevated in the lungs of tuberculosis disease patients. Targeted study on tryptophan in tuberculosis disease indicates that such decreases may also resembled this upregulation. Although tuberculosis diagnosis has improved with the use of interferon release assay and tuberculosis nucleic acid amplification, tuberculosis control is made difficult by the lack of a biomarker to diagnose active tuberculosis disease. We hope that the reader of this work can develop an understanding of the advantages of metabolomics testing, particularly as a sort of testing that can be used for both diagnosing and monitoring a patient's response to treatment for tuberculosis.

Metabolomics insights into the effects of pre-pregnancy lead exposure on bone metabolism in pregnant rats

Today's women of childbearing age with a history of high lead (Pb) exposure in childhood have large Pb body burdens, which increases Pb release during pregnancy by promoting bone Pb mobilisation. The purpose of this study was to investigate the metabolic mechanisms underlying bone Pb mobilisation and explore the bone metabolism-related pathways during pregnancy. Drinking water containing 0.05% sodium acetate or Pb acetate was provided to weaned female rats for 4 weeks followed by a 4-week washout period, and then rats were co-caged with healthy males of the same age until pregnancy. Blood and bone tissues of the female rats were collected at gestational day (GD) 3 (early pregnancy), GD 10 (middle pregnancy), and GD 17 (late pregnancy), respectively. Pb and calcium concentrations, biomarkers for bone turnover, bone microstructure, serum metabolomics, and metabolic indicators were intensively analyzed. The results demonstrated that pre-pregnancy Pb exposure elevated blood lead levels (BLLs) at GD17, accompanied by a negative correlation between BLLs and trabecular bone Pb levels. Meanwhile, Pb-exposed rats had low bone mass and aberrant bone architecture with a larger number of mature osteoclasts (OCs) compared to the control group. Moreover, the metabolomics uncovered that Pb exposure caused mitochondrial dysfunction, such as enhanced oxidative stress and inflammatory response, and suppressed energy metabolism. Additionally, the levels of ROS, MDA, IL-1β, and IL-18 involved in redox and inflammatory pathways of bone tissues were significantly increased in the Pb-exposed group, while antioxidant SOD and energy metabolism-related indicators including ATP levels, Na+-K+-ATPase, and Ca2+-Mg2+-ATPase activities were significantly decreased. In conclusion, pre-pregnancy Pb exposure promotes bone Pb mobilisation and affects bone microstructure in the third trimester of pregnancy, which may be attributed to OC activation and mitochondrial dysfunction.

Recent omics advances in hair aging biology and hair biomarkers analysis

Aging is a complex natural process that leads to a decline in physiological functions, which is visible in signs such as hair graying, thinning, and loss. Although hair graying is characterized by a loss of pigment in the hair shaft, the underlying mechanism of age-associated hair graying is not fully understood. Hair graying and loss can have a significant impact on an individual's self-esteem and self-confidence, potentially leading to mental health problems such as depression and anxiety. Omics technologies, which have applications beyond clinical medicine, have led to the discovery of candidate hair biomarkers and may provide insight into the complex biology of hair aging and identify targets for effective therapies. This review provides an up-to-date overview of recent omics discoveries, including age-associated alterations of proteins and metabolites in the hair shaft and follicle, and highlights the significance of hair aging and graying biomarker discoveries. The decline in hair follicle stem cell activity with aging decreased the regeneration capacity of hair follicles. Cellular senescence, oxidative damage and altered extracellular matrix of hair follicle constituents characterized hair follicle and hair shaft aging and graying. The review attempts to correlate the impact of endogenous and exogenous factors on hair aging. We close by discussing the main challenges and limitations of the field, defining major open questions and offering an outlook for future research.

The role of the host-microbiome and metabolomics in sarcoidosis

Sarcoidosis is a complex inflammatory fibrotic disease that affects multiple organ systems. It is characterized by the infiltration of lymphocytes and mononuclear phagocytes, which form non-caseating granulomas in affected organs. The lungs and intrathoracic lymph nodes are the most commonly affected organs. The underlying cause of sarcoidosis is unknown, but it is believed to occur in genetically predisposed individuals who are exposed to pathogenic organisms, environmental contaminants, or self and non-self-antigens. Recent research has suggested that the microbiome may play a role in the development of respiratory conditions, including sarcoidosis. Additionally, metabolomic studies have identified potential biomarkers for monitoring sarcoidosis progression. This review will focus on recent microbiome and metabolomic findings in sarcoidosis, with the goal of shedding light on the pathogenesis and possible diagnostic and therapeutic approaches.

Polyphenols Cause Structure Dependent Effects on the Metabolic Profile of Human Hepatocarcinogenic Cells

SCOPE

Although many beneficial health effects are attributed to polyphenols their influence on the human metabolome has not been elucidated yet. The ubiquitous occurrence of polyphenols in the human diet demands comprehensive knowledge about physiological and toxicological effects of these compounds on human cells.

METHODS AND RESULTS

The human hepatocarcinogenic cell line HepG2 is used to elucidate the effects of 13 polyphenols and three respective phenolic degradation products on the human metabolome using HPLC-MS/MS. To investigate structure-activity-relationships, structurally related examples of polyphenols from different compound classes are selected. The analysis of catechins points toward a relation between the degree of hydroxylation and the extent of metabolic effects particularly on the urea cycle and the pentose phosphate pathway (PPP). A correlation between the modulation of the PPP and the stability of the compounds is demonstrated, which may be caused by reactive oxygen species (ROS). The incubation of flavones and alkenylbenzenes demonstrates reduced activity of methoxylated compounds and no impact of the B-ring position.

CONCLUSION

In general, polyphenols induce a multitude of metabolic effects, for example, on energy metabolism, PPP, and urea cycle. These metabolic alterations may be related to the widely reported bioactivity of these compounds such as the anticarcinogenic effects.

Metabolomic analysis for asymptomatic hyperuricemia and gout based on a combination of dried blood spot sampling and mass spectrometry technology

BACKGROUND

Gout is the most common inflammatory arthritis and closely related to metabolic syndrome, leading to excruciating pain and the decline in quality of patients' life. However, the pathogenesis of gout is still unclear, and novel biomarkers are demanded for the early prediction and diagnosis of gout.

OBJECTIVE

This study aimed at profiling the dysregulated metabolic pathways in asymptomatic hyperuricemia (AHU) and gout and elucidating the associations between AHU, gout and metabolomics, which may aid in performing gout screening.

METHODS

A total of 300 participants, including 114 healthy controls, 92 patients with AHU, and 94 patients with gout, were analyzed by using a combination of dried blood spot (DBS) sampling and mass spectrometry (MS) technology. Multiple algorithms were applied to characterize altered metabolic profiles in AHU and gout. The mainly altered metabolites were identified by random forest analysis.

RESULTS

There were significant differences in AHU and gout compared with control group. The altered metabolites were involved in oxidation of fatty acids, carnitine synthesis, urea cycle, and amino acid metabolism in AHU and gout. Random forest classification of 16 metabolites yielded 3 important features to distinguish gout from AHU.

CONCLUSIONS

Distinct metabolomic signatures were observed in AHU and gout. The selected metabolites may have the potential to improve the early detection of gout.

Gas Chromatography-Mass Spectrometry Reveals Stage-Specific Metabolic Signatures of Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a type of chronic rheumatic immune disease, and the crucial point of AS treatment is identifying the correct stage of the disease. However, there is a lack of effective diagnostic methods for AS staging. The primary objective of this study was to perform an untargeted metabolomic approach in AS patients in an effort to reveal metabolic differences between patients in remission and acute stages. Serum samples from 40 controls and 57 AS patients were analyzed via gas chromatography-mass spectrometry (GC-MS). Twenty-four kinds of differential metabolites were identified between the healthy controls and AS patients, mainly involving valine/leucine/isoleucine biosynthesis and degradation, phenylalanine/tyrosine/tryptophan biosynthesis, glutathione metabolism, etc. Furthermore, the levels of fatty acids (linoleate, dodecanoate, hexadecanoate, and octadecanoate), amino acids (serine and pyroglutamate), 2-hydroxybutanoate, glucose, etc., were lower in patients in the acute stage than those in the remission stage, which may be associated with the aggravated inflammatory response and elevated oxidative stress in the acute stage. Multiple stage-specific metabolites were significantly correlated with inflammatory indicators (CRP and ESR). In addition, the combination of serum 2-hydroxybutanoate and hexadecanoate plays a significant role in the diagnosis of AS stages. These metabolomics-based findings provide new perspectives for AS staging, treatment, and pathogenesis studies.

Serum metabolomics study of narcolepsy type 1 based on ultra-performance liquid chromatography-tandem mass spectrometry

Narcolepsy is a chronic and underrecognized sleep disorder characterized by excessive daytime sleepiness and cataplexy. Furthermore, narcolepsy type 1 (NT1) has serious negative impacts on an individual's health, society, and the economy. Currently, many sleep centers lack the means to measure orexin levels in the cerebrospinal fluid. We aimed to analyze the characteristics of metabolite changes in patients with NT1, measured by ultra-performance liquid chromatography-tandem mass spectrometry. A principal component analysis (PCA), an orthogonal partial least square discriminant analysis (OPLS-DA), t tests, and volcano plots were used to construct a model of abnormal metabolic pathways in narcolepsy. We identified molecular changes in serum specimens from narcolepsy patients and compared them with control groups, including dehydroepiandrosterone, epinephrine, N-methyl-D-aspartic acid, and other metabolites, based on an OPLS-loading plot analysis. Nine metabolites yielded an area under the receiver operating curve > 0.75. Meanwhile, seven abnormal metabolic pathways were correlated with differential metabolites, such as metabolic pathways; neuroactive ligand‒receptor interaction; and glycine, serine, and threonine metabolism. To our knowledge, this is the first study to reveal the characteristic metabolite changes in sera from NT1 patients for the selection of potential blood biomarkers and the elucidation of NT1 pathogenesis.

Adaptation of the AbsoluteIDQ p180 kit to the analysis of metabolites in the human aqueous humor

The aim of this study was to use the commercial kit AbsoluteIDQ p180 (Biocrates) for the quantification of metabolites in aqueous humor (AH), as well as to determine the optimal volume of AH that is necessary to obtain reliable and reproducible results. Different volumes of AH (10 µl, 20 µl, and 30 µl) were tested. Of the 188 metabolites measurable with the Biocrates kit, 69 were detected in AH. Depending on the volume used, 41, 51, and 63 metabolites were measured using 10 µl, 20 µl, and 30 µl of AH, respectively. The repeatability of the measurements improved with increasing AH volume. Considering only those metabolites that were obtained with a CV < 15%, 34 metabolites at 10 µl, 41 at 20 µl, and 44 at 30 µl AH were received. On this basis, it can be concluded that the tested method can be successfully applied to analyze metabolites in the human AH. To achieve the most comprehensive detection range and highest repeatability of measurements, it is recommended to use 30 µl AH.

Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics

OBJECTIVE

Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics.

METHODS

Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients.

RESULTS

Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms.

CONCLUSION

Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.

Metabolomic analysis of pig spleen reveals African swine fever virus infection increased acylcarnitine levels to facilitate viral replication

African swine fever (ASF) is a devastating disease caused by the African swine fever virus (ASFV) that adversely affects the pig industry. The spleen is the main target organ of ASFV; however, the function of metabolites in the spleen during ASFV infection is yet to be investigated. To define the metabolic changes in the spleen after ASFV infection, untargeted and targeted metabolomics analyses of spleens from ASFV-infected pigs were conducted. Untargeted metabolomics analysis revealed 540 metabolites with significant differential levels. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that these metabolites were mainly enriched in metabolic pathways, including nucleotide metabolism, purine metabolism, arginine biosynthesis, and neuroactive ligand-receptor interaction. Moreover, 134 of 540 metabolites quantified by targeted metabolomics analysis had differential levels and were enriched in metabolic pathways such as the biosynthesis of cofactors, ABC transporters, and biosynthesis of amino acids. Furthermore, coalition analysis of untargeted and targeted metabolomics data revealed that the levels of acylcarnitines, which are intermediates of fatty acid β-oxidation, were significantly increased in ASFV-infected spleens compared with those in the uninfected spleens. Moreover, inhibiting fatty acid β-oxidation significantly reduced ASFV replication, indicating that fatty acid β-oxidation is essential for this process. To our knowledge, this is the first report presenting the metabolite profiles of ASFV-infected pigs. This study revealed a new mechanism of ASFV-mediated regulation of host metabolism. These findings provide new insights into the pathogenic mechanisms of ASFV, which will benefit the development of target drugs for ASFV replication. IMPORTANCE African swine fever virus, the only member of the Asfarviridae family, relies on hijacking host metabolism to meet the demand for self-replication. However, the change in host metabolism after African swine fever virus (ASFV) infection remains unknown. Here, we analyzed the metabolic changes in the pig spleen after ASFV infection for the first time. ASFV infection increased the levels of acylcarnitines. Inhibition of the production and metabolism of acylcarnitines inhibited ASFV replication. Acylcarnitines are the vital intermediates of fatty acid β-oxidation. This study highlights the critical role of fatty acid β-oxidation in ASFV infection, which may help identify target drugs to control African swine fever disease.

Metabolomics analysis of visceral leishmaniasis based on urine of golden hamsters

BACKGROUND

Leishmaniasis is one of the most neglected tropical diseases and is spread mainly in impoverished regions of the world. Although many studies have focused on the host's response to Leishmania invasion, relatively less is known about the complex processes at the metabolic level, especially the metabolic alterations in the infected hosts.

METHODS

In this study, we conducted metabolomics analysis on the urine of golden hamsters in the presence or absence of visceral leishmaniasis (VL) using the ultra-performance liquid chromatography (UPLC) system tandem high-resolution mass spectrometer (HRMS). The metabolic characteristics of urine samples, along with the histopathological change and the parasite burden of liver and spleen tissues, were detected at 4 and 12 weeks post infection (WPI), respectively.

RESULTS

Amino acid metabolism was extensively affected at both stages of VL progression. Meanwhile, there were also distinct metabolic features at different stages. At 4 WPI, the significantly affected metabolic pathways involved alanine, aspartate and glutamate metabolism, the pentose phosphate pathway (PPP), histidine metabolism, tryptophan metabolism and tyrosine metabolism. At 12 WPI, the markedly enriched metabolic pathways were almost concentrated on amino acid metabolism, including tyrosine metabolism, taurine and hypotaurine metabolism and tryptophan metabolism. The dysregulated metabolites and metabolic pathways at 12 WPI were obviously less than those at 4 WPI. In addition, seven metabolites that were dysregulated at both stages through partial least squares-discriminant analysis (PLS-DA) and receiver-operating characteristic (ROC) tests were screened to be of diagnostic potential. The combination of these metabolites as a potential biomarker panel showed satisfactory performance in distinguishing infection groups from control groups as well as among different stages of infection.

CONCLUSION

Our findings could provide valuable information for further understanding of the host response to Leishmania infection from the aspect of the urine metabolome. The proposed urine biomarker panel could help in the development of a novel approach for the diagnosis and prognosis of VL.

Anomalous Dynamics of Labile Metabolites in Cold Human Blood Detected Using 1H NMR Spectroscopy

Recent efforts in our laboratory have enabled access to an unprecedented number (∼90) of quantifiable metabolites in human blood by a simple nuclear magnetic resonance (NMR) spectroscopy method, which includes energy coenzymes, redox coenzymes, and antioxidants that are fundamental to cellular functions [ J. Magn. Reson. Open 2022, 12-13, 100082]. The coenzymes and antioxidants, however, are notoriously labile and are extremely sensitive to specimen harvesting, extraction, and measurement conditions. This problem is largely underappreciated and carries the risk of grossly inaccurate measurements and incorrect study outcomes. As a part of addressing this challenge, in this study, human blood specimens were comprehensively and quantitatively investigated using 1H NMR spectroscopy. Freshly drawn human blood specimens were treated or not treated with methanol, ethanol, or a mixture of methanol and chloroform, and stored on ice or on bench, at room temperature for different time periods from 0 to 24 h, prior to storing at -80 °C. Interestingly, the labile metabolite levels were stable in blood treated with an organic solvent. However, their levels in blood in untreated samples increased or decreased by factors of up to 5 or more within 3 h. Further, surprisingly, and contrary to the current knowledge about metabolite stability, the variation of coenzyme levels was more dramatic in blood stored on ice than on bench, at room temperature. In addition, unlike the generally observed phenomenon of oxidation of redox coenzymes, reduction was observed in untreated blood. Such preanalytical dynamics of the labile metabolites potentially arises from the active cellular metabolism. From the metabolomics perspective, the massive variation of the labile metabolite levels even in blood stored on ice is alarming and stresses the critical need to immediately quench the cellular metabolism for reliable analyses. Overall, the results provide compelling evidence that warrants a paradigm shift in the sample collection protocol for blood metabolomics involving labile metabolites.

Plasma metabolome identifies potential biomarkers of gastric precancerous lesions and gastric cancer risk

OBJECTIVES

Currently, metabolic biomarkers with great practicability of gastric cancer (GC) and gastric precancerous lesions (GPL) are scarce. Thus, we are devoted to determining the plasma metabolic profiles of patients with GPL or GC and validate candidate biomarkers for disease diagnosis.

METHODS

In this hospital-based case-control study, 68 plasma samples from 27 non-atrophic gastritis (NAG, control), 31 GPL, and 10 GC patients were collected for targeted metabolomics analysis. Univariate and multivariate analyses were used for selecting the differential metabolites. A receiver operating characteristic curve combined with binary logistic regression analysis was performed to test the diagnostic performance of the differential metabolites. Dietary data were obtained using a semiquantitative food frequency questionnaire.

RESULTS

Distinct metabolomic profiles were noted for NAG, GPL, and GC. Compared to the NAG patients, the levels of 5 metabolites in the GPL group and 4 metabolites in the GC group were found to significantly elevate. Compared with the model involving 9 traditional risk factors (AUC: 0.89, 95%CI: 0.78-1.00), Trimethylamine N-oxide, the most significant metabolite (P = 2.00 × 10-5, FDR = 0.003, FC > 2, VIP > 2), showed a good diagnostic performance for the patients with GC (AUC: 0.90, 95%CI: 0.78-1.00), and its diagnostic performance has been further improved with the integration of Rhamnose (AUC: 0.96, 95%CI: 0.89-1.00).

CONCLUSION

In our study, 9 defined metabolites might serve as meaningful biomarkers for identifying the high-risk population of GPL and GC, possibly enhancing the prevention and control of GPL and GC.

Synovial Fluid Metabolome Can Differentiate between Healthy Joints and Joints Affected by Osteoarthritis in Horses

Osteoarthritis (OA) is a common cause of lameness in sport horses with a significant economic impact. The prevention of OA is crucial since no effective treatment is available. This study aimed to apply untargeted metabolomic analysis to investigate the differences in synovial fluid (SF) composition between healthy and OA-affected joints in horses. SF collected from healthy (n.8) and OA (n.11) horses was analyzed using H-NMR analysis. Metabolomic analysis allowed 55 different metabolites to be identified and quantified in SF samples. Nineteen metabolites were found to be differently concentrated in OA compared to control horses. Synovial fluids from the OC group were found to be higher in 1,3-dihydroxyacetone but lower in tryptophan, phenylalanine, tyrosine, uridine, creatinine, creatine, glycine, choline, asparagine, glutamine, arginine, 3-hydroxybutyrate, valine, 2-hydroxyisovalerate, α-ketoisovaleric acid, 3-methyl-2-oxovalerate, 3-hydroxyisobutyrate, isoleucine, and methionine compared to the controls. A variety of SF metabolites significantly changed following joint disease, demonstrating the complex mechanism underlying osteoarthritis in horses and highlighting the value of applying the metabolomic approach in clinical research.

Lipid metabolism in idiopathic pulmonary fibrosis: From pathogenesis to therapy

Idiopathic pulmonary fibrosis (IPF) is a chronic irreversible interstitial lung disease characterized by a progressive decline in lung function. The etiology of IPF is unknown, which poses a significant challenge to the treatment of IPF. Recent studies have identified a strong association between lipid metabolism and the development of IPF. Qualitative and quantitative analysis of small molecule metabolites using lipidomics reveals that lipid metabolic reprogramming plays a role in the pathogenesis of IPF. Lipids such as fatty acids, cholesterol, arachidonic acid metabolites, and phospholipids are involved in the onset and progression of IPF by inducing endoplasmic reticulum stress, promoting cell apoptosis, and enhancing the expression of pro-fibrotic biomarkers. Therefore, targeting lipid metabolism can provide a promising therapeutic strategy for pulmonary fibrosis. This review focuses on lipid metabolism in the pathogenesis of pulmonary fibrosis.

Analysis of Metabolites in Gout: A Systematic Review and Meta-Analysis

(1) Background: Many studies have attempted to explore potential biomarkers for the early detection of gout, but consistent and high levels of evidence are lacking. In this study, metabolomics was used to summarize the changes of metabolites in the literature and explore the potential value of metabolites in predicting the occurrence and development of gout. (2) Methods: We searched the databases including the EMBASE, the Cochrane Library, PubMed, Web of Science, VIP Date, Wanfang Data, and CNKI, and the screening was fulfilled on 30 July 2022. The records were screened according to the inclusion criteria and the risk of bias was assessed. Qualitative analysis was performed for all metabolites, and meta-analysis was performed for metabolite concentrations using random effects to calculate the Std mean difference and 95% confidence interval. (3) Results: A total of 2738 records were identified, 33 studies with 3422 participants were included, and 701 metabolites were identified. The qualitative analysis results showed that compared with the healthy control group, the concentration of 56 metabolites increased, and 22 metabolites decreased. The results of the meta-analysis indicated that 17 metabolites were statistically significant. (4) Conclusions: Metabolites are associated with gout. Some specific metabolites such as uric acid, hypoxanthine, xanthine, KYNA, guanosine, adenosine, creatinine, LB4, and DL-2-Aminoadipic acid have been highlighted in the development of gout.

Moderate hypoxia induces metabolic divergence in circulating monocytes and tissue resident macrophages from Berkeley sickle cell anemia mice

Introduction

Human and murine sickle cell disease (SCD) associated pulmonary hypertension (PH) is defined by hemolysis, nitric oxide depletion, inflammation, and thrombosis. Further, hemoglobin (Hb), heme, and iron accumulation are consistently observed in pulmonary adventitial macrophages at autopsy and in hypoxia driven rodent models of SCD, which show distribution of ferric and ferrous Hb as well as HO-1 and ferritin heavy chain. The anatomic localization of these macrophages is consistent with areas of significant vascular remodeling. However, their contributions toward progressive disease may include unique, but also common mechanisms, that overlap with idiopathic and other forms of pulmonary hypertension. These processes likely extend to the vasculature of other organs that are consistently impaired in advanced SCD.

Methods

To date, limited information is available on the metabolism of macrophages or monocytes isolated from lung, spleen, and peripheral blood in humans or murine models of SCD.

Results

Here we hypothesize that metabolism of macrophages and monocytes isolated from this triad of tissue differs between Berkley SCD mice exposed for ten weeks to moderate hypobaric hypoxia (simulated 8,000 ft, 15.4% O2) or normoxia (Denver altitude, 5000 ft) with normoxia exposed wild type mice evaluated as controls.

Discussion

This study represents an initial set of data that describes the metabolism in monocytes and macrophages isolated from moderately hypoxic SCD mice peripheral lung, spleen, and blood mononuclear cells.

'Nocturomics': transition to omics-driven biomarkers of nocturia, a systematic review and future prospects

OBJECTIVE

To systematically review studies that investigated different biomarkers of nocturia, including omics-driven biomarkers or 'Nocturomics'.

MATERIALS AND METHODS

PubMed® , Scopus® , and Embase® were searched systematically in May 2022 for research papers on biomarkers in physiological fluids and tissues from patients with nocturia. A distinction was made between biomarkers or candidates discovered by omics techniques, referred to as omics-driven biomarkers, and classical biomarkers, measured by standard laboratory techniques and mostly thought from pathophysiological hypothesis.

RESULTS

A total of 13 studies with 18 881 patients in total were included, eight of which focused on classical biomarkers including: atrial natriuretic peptide (ANP), B-type natriuretic peptide (BNP), C-reactive protein (CRP), aldosterone, and melatonin. Five were 'Nocturomics', including one that assessed the microbiome and identified 27 faecal and eight urinary bacteria correlated with nocturia; and four studies that identified candidate metabolomic biomarkers, including fatty acid metabolites, serotonin, glycerol, lauric acid, thiaproline, and imidazolelactic acid among others. To date, no biomarker is recommended in clinical practice. Nocturomics are in an embryonic phase of conception but are developing quickly. Although candidate biomarkers are being identified, none of them are yet validated on a large sample, although some preclinical studies have shown a probable role of fatty acid metabolites as a possible biomarker of circadian rhythm and chronotherapy.

CONCLUSION

Further research is needed to validate biomarkers for nocturia within the framework of a diagnostic and therapeutic precision medicine perspective. We hope this study provides a summary of the current biomarker discoveries associated with nocturia and details future prospects for omics-driven biomarkers.

Metabolomics and its applications in assisted reproductive technology

Metabolomics, an emerging omics technology developed in the post-gene age, is an important part of systems biology. It interprets the pathophysiological state of the subject by quantitatively describing the dynamic changes of metabolites through analytical methods, mainly mass spectrometry (MS) and nuclear magnetic resonance (NMR). Assisted reproductive technology (ART) is a method used to manipulate sperm, oocytes, and embryos to achieve conception. Recently, several studies have reported that metabolomics methods can be used to measure metabolites in ART samples; these metabolites can be used to evaluate the quality of gametes and embryos. This article reviews the progress of research on metabolomics and the application of this technology in the field of ART, thus providing a reference for research and development directions in the future.

Exercise Metabolome: Insights for Health and Performance

Exercise has many benefits for physical and mental well-being. Metabolomics research has allowed scientists to study the impact of exercise on the body by analyzing metabolites released by tissues such as skeletal muscle, bone, and the liver. Endurance training increases mitochondrial content and oxidative enzymes, while resistance training increases muscle fiber and glycolytic enzymes. Acute endurance exercise affects amino acid metabolism, fat metabolism, cellular energy metabolism, and cofactor and vitamin metabolism. Subacute endurance exercise alters amino acid metabolism, lipid metabolism, and nucleotide metabolism. Chronic endurance exercise improves lipid metabolism and changes amino acid metabolism. Acute resistance exercise changes several metabolic pathways, including anaerobic processes and muscular strength. Chronic resistance exercise affects metabolic pathways, resulting in skeletal muscle adaptations. Combined endurance-resistance exercise alters lipid metabolism, carbohydrate metabolism, and amino acid metabolism, increasing anaerobic metabolic capacity and fatigue resistance. Studying exercise-induced metabolites is a growing field, and further research can uncover the underlying metabolic mechanisms and help tailor exercise programs for optimal health and performance.

An Exploratory Study of the Metabolite Profiling from Pesticides Exposed Workers

Pesticides constitute a category of chemical products intended specifically for the control and mitigation of pests. With their constant increase in use, the risk to human health and the environment has increased proportionally due to occupational and environmental exposure to these compounds. The use of these chemicals is associated with several toxic effects related to acute and chronic toxicity, such as infertility, hormonal disorders and cancer. The present work aimed to study the metabolic profile of individuals occupationally exposed to pesticides, using a metabolomics tool to identify potential new biomarkers. Metabolomics analysis was carried out on plasma and urine samples from individuals exposed and non-exposed occupationally, using liquid chromatography coupled with mass spectrometry (UPLC-MS). Non-targeted metabolomics analysis, using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or partial least squares discriminant orthogonal analysis (OPLS-DA), demonstrated good separation of the samples and identified 21 discriminating metabolites in plasma and 17 in urine. The analysis of the ROC curve indicated the compounds with the greatest potential for biomarkers. Comprehensive analysis of the metabolic pathways influenced by exposure to pesticides revealed alterations, mainly in lipid and amino acid metabolism. This study indicates that the use of metabolomics provides important information about complex biological responses.

Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics

INTRODUCTION

Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial.

OBJECTIVES

We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach.

METHODS

Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers.

RESULTS

Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9.

CONCLUSIONS

Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.

The eNOS isoform exhibits increased expression and activation in the main olfactory bulb of nNOS knock-out mice

The main olfactory bulb (MOB) is a neural structure that processes olfactory information. Among the neurotransmitters present in the MOB, nitric oxide (NO) is particularly relevant as it performs a wide variety of functions. In this structure, NO is produced mainly by neuronal nitric oxide synthase (nNOS) but also by inducible nitric oxide synthase (iNOS) and endothelial nitric oxide synthase (eNOS). The MOB is considered a region with great plasticity and the different NOS also show great plasticity. Therefore, it could be considered that this plasticity could compensate for various dysfunctional and pathological alterations. We examined the possible plasticity of iNOS and eNOS in the MOB in the absence of nNOS. For this, wild-type and nNOS knock-out (nNOS-KO) mice were used. We assessed whether the absence of nNOS expression could affect the olfactory capacity of mice, followed by the analysis of the expression and distribution of the NOS isoforms using qPCR and immunofluorescence. NO production in MOB was examined using both the Griess and histochemical NADPH-diaphorase reactions. The results indicate nNOS-KO mice have reduced olfactory capacity. We observed that in the nNOS-KO animal, there is an increase both in the expression of eNOS and NADPH-diaphorase, but no apparent change in the level of NO generated in the MOB. It can be concluded that the level of eNOS in the MOB of nNOS-KO is related to the maintenance of normal levels of NO. Therefore, our findings suggest that nNOS could be essential for the proper functioning of the olfactory system.

[Clinical diagnostic techniques for rare genetic diseases in children: current status, advances, and thoughts]

Rare diseases refer to a group of single diseases with low incidence rates, complex pathogeneses, severe disease conditions, and rapid progression. Most rare diseases have a genetic background and may occur in childhood. Paying attention to the rare genetic diseases in children and performing early diagnosis and treatment can effectively delay the course of disease and improve the quality of life of children. Many rare diseases can be diagnosed with the help of various experimental techniques, but the diagnosis of rare diseases is still not widely understood. This article summarizes the laboratory diagnostic techniques currently used for rare genetic diseases in children, so as to provide clues for the diagnosis and treatment of such diseases and help to enhance the theoretical understanding and precise medical treatment of rare genetic diseases in children.

Metabolomics integrated network pharmacology reveals the mechanism of Ma-Mu-Ran Antidiarrheal Capsules on acute enteritis mice

Acute enteritis (AE) is a type of digestive disease caused by biochemical factors that irritate the intestinal tract or pathogenic bacteria that infect it. In China, Ma-Mu-Ran Antidiarrheal Capsules (MMRAC) have been applied against diarrhea caused by AE and bacillary dysentery for many years, but the underlying mechanisms of their beneficial effects are not known. In the present study, network pharmacology and metabolomics were performed to clarify the active ingredients of MMRAC and explore the specific mechanism of MMRAC on AE mice. A total of 43 active components of MMRAC with 87 anti-AE target genes were identified, and these target genes were enriched in IL-17 and HIF-1 signaling pathways. Integration analysis revealed that purine metabolism was the critical metabolic pathway by which MMRAC exerted its therapeutic effect against AE. Specifically, MAPK14, MMP9, PTGS2, HIF1A, EGLN1, NOS2 were the pivotal targets of MMRAC for the treatment of AE, and Western blot analysis revealed MMRAC to decrease protein levels of these pro-inflammatory signaling molecules. According to molecular docking, these key targets have a strong affinity with the MMRAC compounds. Collectively, MMRAC relieved the colon inflammation of AE mice via regulating inflammatory signaling pathways to reduce hypoxia and improved energy metabolism.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

T regulatory cells metabolism: The influence on functional properties and treatment potential

CD4+CD25highFoxP3+ regulatory T cells (Tregs) constitute a small but substantial fraction of lymphocytes in the immune system. Tregs control inflammation associated with infections but also when it is improperly directed against its tissues or cells. The ability of Tregs to suppress (inhibit) the immune system is possible due to direct interactions with other cells but also in a paracrine fashion via the secretion of suppressive compounds. Today, attempts are made to use Tregs to treat autoimmune diseases, allergies, and rejection after bone marrow or organ transplantation. There is strong evidence that the metabolic program of Tregs is connected with the phenotype and function of these cells. A modulation towards a particular metabolic stage of Tregs may improve or weaken cells’ stability and function. This may be an essential tool to drive the immune system keeping it activated during infections or suppressed when autoimmunity occurs.

Hepatic metabolomics combined with network pharmacology to reveal the correlation between the anti-depression effect and nourishing blood effect of Angelicae Sinensis Radix

Angelicae Sinensis Radix (AS) is reproted to exert anti-depression effect (ADE) and nourishing blood effect (NBE) in a rat model of depression. The correlation between the two therapeutic effects and its underlying mechanisms deserves further study. The current study is designed to explore the underlying mechanisms of correlation between the ADE and NBE of AS based on hepatic metabonomics, network pharmacology and molecular docking. According to metabolomics analysis, 30 metabolites involved in 11 metabolic pathways were identified as the potential metabolites for depression. Furthermore, principal component analysis and correlation analysis showed that glutathione, sphinganine, and ornithine were related to pharmacodynamics indicators including behavioral indicators and hematological indicators, indicating that metabolic pathways such as sphingolipid metabolism were involved in the ADE and NBE of AS. Then, a target-pathway network of depression and blood deficiency syndrome was constructed by network pharmacology analysis, where a total of 107 pathways were collected. Moreover, 37 active components obtained from Ultra Performance Liquid Chromatography-Triple-Time of Flight Mass Spectrometer (UPLC-Triple-TOF/MS) in AS extract that passed the filtering criteria were used for network pharmacology, where 46 targets were associated with the ADE and NBE of AS. Pathway enrichment analysis further indicated the involvement of sphingolipid metabolism in the ADE and NBE of AS. Molecular docking analysis indciated that E-ligustilide in AS extract exhibited strong binding activity with target proteins (PIK3CA and PIK3CD) in sphingolipid metabolism. Further analysis by Western blot verified that AS regulated the expression of PIK3CA and PIK3CD on sphingolipid metabolism. Our results demonstrated that sphingolipid metabolic pathway was the core mechanism of the correlation between the ADE and NBE of AS.