Plasma Metabolic Profiles Research Articles

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer

BackgroundThis study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients.MethodsA total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre‑therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines.ResultsTwenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels.ConclusionSerum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Metabolomic profiling of cancer-related fatigue involved in cachexia and chemotherapy

Patients with advanced cancer are frequently burdened with a severe sensation of fatigue called cancer-related fatigue (CRF). CRF is induced at various stages and treatments, such as cachexia and chemotherapy, and reduces the overall survival of patients. Objective and quantitative assessment of CRF could contribute to the diagnosis and prediction of treatment efficacy. However, such studies have not been intensively performed, particularly regarding metabolic profiles. Here, we conducted plasma metabolomics of 15 patients with urological cancer. The patients with and without fatigue, including those with cachexia or chemotherapy-induced fatigue, were compared. Significantly lower concentrations of valine and tryptophan were observed in fatigued patients than in non-fatigued patients. In addition, significantly higher concentrations of polyamine pathway metabolites were observed in patients with fatigue and cachexia than in those without cachexia. Patients with exacerbated fatigue due to chemotherapy showed significantly decreased cysteine and methionine metabolism before chemotherapy compared with those without fatigue exacerbation. These findings suggest that plasma metabolic profiles could help improve the diagnosis and monitoring of CRF.

Analysis of Plasma Metabolic Profile in Children with Transfusion-Dependent Thalassemia

To explore the plasma metabolomic characteristics of children with transfusion-dependent thalassemia (TDT), and reveal the changes of metabolic pattern in children with TDT. 23 children with TDT who received regular blood transfusion in Ganzhou Women and Children's Health Care Hospital in 2021 were selected, and 11 healthy children who underwent physical examination during the same period were selected as the control group. The routine indexes between children with TDT and the control group were compared, and then the metabolic composition of plasma samples from children with TDT and the control group was detected by liquid chromatography-mass spectrometry. An OPLS-DA model was established to perform differential analysis on the detected metabolites, and the differential metabolic pathways between the two groups were analyzed based on the differential metabolites. The results of routine testing showed that the indexes of ferritin, bilirubin, total bile acid, glucose and triglycerides in children with TDT were significantly higher than those in healthy controls, while hemoglobin and total cholesterol were significantly lower (all P <0.05). However there was no significant difference in lactate dehydrogenase between the two groups (P >0.05). Compared with the control group, 190 differential metabolites (VIP>1) were identified in TDT children. Among them, 168 compounds such as arginine, proline and glycocholic acid were significantly increased, while the other 22 compounds such as myristic acid, eleostearic acid, palmitic acid and linoleic acid were significantly decreased. The metabolic pathway analysis showed that the metabolic impact of TDT on children mainly focused on the upregulation of amino acid metabolism and downregulation of lipid metabolism. The amino acid and lipid metabolism in children with TDT were significantly changed compared with the healthy control group. This finding is helpful to optimize the treatment choice for children with TDT, and provides a new idea for clinical treatment.

Plasma Metabolic Profiling and Multiclass Diagnostic Model Development for Stable Angina Pectoris and Acute Myocardial Infarction.

Coronary heart disease remains a major global health challenge, with a clear need for enhanced early risk assessment. This study aimed to elucidate metabolic signatures across various stages of coronary heart disease and develop an effective multiclass diagnostic model. Using metabolomic approaches, gas chromatography-mass and liquid chromatography-tandem mass spectrometry were used to analyze plasma samples from healthy controls, patients with stable angina pectoris, and those with acute myocardial infarction. Pathway enrichment analysis was conducted on metabolites exhibiting significant differences. The key metabolites were identified using Random Forest and Recursive Feature Elimination strategies to construct a multiclass diagnostic model. The performance of the model was validated through 10-fold cross-validation and evaluated using confusion matrices, receiver operating characteristic curves, and calibration curves. Metabolomics was used to identify 1491 metabolites, with 216, 567, and 295 distinctly present among the healthy controls, patients with stable angina pectoris, and those with acute myocardial infarction, respectively. This implicated pathways such as the glucagon signaling pathway, d-amino acid metabolism, pyruvate metabolism, and amoebiasis across various stages of coronary heart disease. After selection, testosterone isobutyrate, N-acetyl-tryptophan, d-fructose, l-glutamic acid, erythritol, and gluconic acid were identified as core metabolites in the multiclass diagnostic model. Evaluating the diagnostic model demonstrated its high discriminative ability and accuracy. This study revealed metabolic pathway perturbations at different stages of coronary heart disease, and a precise multiclass diagnostic model was established based on these findings. This study provides new insights and tools for the early diagnosis and treatment of coronary heart disease.

Dietary Methionine Restriction Improves Gut Health and Alters the Plasma Metabolomic Profile in Rats by Modulating the Composition of the Gut Microbiota.

Dietary methionine restriction (MetR) offers an integrated set of beneficial health effects, including delaying aging, extending health span, preventing fat accumulation, and reducing oxidative stress. This study aimed to investigate whether MetR exerts entero-protective effects by modulating intestinal flora, and the effect of MetR on plasma metabolites in rats. Rats were fed diets containing 0.86% methionine (CON group) and 0.17% methionine (MetR group) for 6 weeks. Several indicators of inflammation, gut microbiota, plasma metabolites, and intestinal barrier function were measured. 16S rRNA gene sequencing was used to analyze the cecal microbiota. The MetR diet reduced the plasma and colonic inflammatory factor levels. The MetR diet significantly improved intestinal barrier function by increasing the mRNA expression of tight junction proteins, such as zonula occludens (ZO)-1, claudin-3, and claudin-5. In addition, MetR significantly increased the levels of short-chain fatty acids (SCFAs) by increasing the abundance of SCFAs-producing Erysipclotxichaceae and Clostridium_sensu_stricto_1 and decreasing the abundance of pro-inflammatory bacteria Proteobacteria and Escherichia-Shigella. Furthermore, MetR reduced the plasma levels of taurochenodeoxycholate-7-sulfate, taurocholic acid, and tauro-ursodeoxycholic acid. Correlation analysis identified that colonic acetate, total colonic SCFAs, 8-acetylegelolide, collettiside I, 6-methyladenine, and cholic acid glucuronide showed a significant positive correlation with Clostridium_sensu_stricto_1 abundance but a significant negative correlation with Escherichia-Shigella and Enterococcus abundance. MetR improved gut health and altered the plasma metabolic profile by regulating the gut microbiota in rats.

VLDL and LDL Subfractions Enhance the Risk Stratification of Individuals Who Underwent Epstein-Barr Virus-Based Screening for Nasopharyngeal Carcinoma: A Multicenter Cohort Study.

Serological tests for Epstein-Barr virus (EBV) antibodies have been widely conducted for the screening of nasopharyngeal carcinoma (NPC) in endemic areas. Further risk stratification of NPC can be achieved through plasma lipoprotein and metabolic profiles. A total of 297 NPC patients and 149 EBV-positive participants are enrolled from the NCT03919552 and NCT05682703 cohorts for plasma nuclear magnetic resonance (NMR) metabolomic analysis. Small, dense very low density lipoprotein particles (VLDL-5) and large, buoyant low density lipoprotein particles (LDL-1) are found to be closely associated with nasopharyngeal carcinogenesis. Herein, an NMR-based risk score (NRS), which combines lipoprotein subfractions and metabolic biomarkers relevant to NPC, is developed and well validated within a multicenter cohort. Combining the median cutoff value of the NRS (N50) with that of the serological test for EBV antibodies, the risk stratification model achieves a satisfactory performance in which the area under the curve (AUC) is 0.841 (95% confidence interval: 0.811-0.871), and the positive predictive value (PPV) reaches 70.08% in the combined cohort. These findings not only suggest that VLDL-5 and LDL-1 particles can serve as novel risk factors for NPC but also indicate that the NRS has significant potential in personalized risk prediction for NPC.

Abstract 4429: Plasma metabolic profiles in association with subsequent risk of colorectal cancer in the UK Biobank cohort

Abstract Background: Dysregulation of metabolic processes contributes to colorectal cancer (CRC) etiology. We aimed to comprehensively evaluate the prospective associations between pre-diagnostic metabolic biomarkers and CRC risk in 230,420 UK Biobank participants. Methods: A total of 249 metabolic biomarkers were measured by nuclear magnetic resonance spectroscopy from baseline plasma samples. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of metabolic biomarkers with CRC risk after adjusting for potential confounders. Subgroup analyses were performed by sex and CRC subsites (i.e., proximal colon, distal colon, rectum). We also conducted factor analyses to identify latent factors and examined their associations with CRC risk. Results: During a median follow-up time of 9.7 years, 2,410 incident primary CRC cases were identified after excluding participants diagnosed with CRC within two years after blood collection. After correcting for multiple testing, 50 metabolic biomarkers, including lipids and lipoproteins, fatty acids, ketone bodies, and inflammation, were significantly associated with incident CRC risk. No statistically significant differences were observed for the biomarker-CRC associations by sex and CRC subsite. In the sensitivity analysis, excluding cholesterol-lowering medication users did not alter the main findings. In factor analyses, we identified a significant association of CRC risk (HR = 1.08; 95% CI = 1.04-1.13; P-value = 6.89×10-5) with a metabolite pattern which was positively correlated with triglycerides and inversely correlated with relative concentrations of omega-6 fatty acids and polyunsaturated fatty acids. Conclusion: We identified multiple metabolic biomarkers and a metabolite pattern associated with CRC risk in a large prospective cohort. These findings suggest lipid metabolism may contribute to carcinogenesis of the colorectum. Citation Format: Fangcheng Yuan, Guochong Jia, Wanqing Wen, Wei Zheng. Plasma metabolic profiles in association with subsequent risk of colorectal cancer in the UK Biobank cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4429.

Comprehensive blood metabolomics profiling of Parkinson’s disease reveals coordinated alterations in xanthine metabolism

Parkinson’s disease (PD) is a highly heterogeneous disorder influenced by several environmental and genetic factors. Effective disease-modifying therapies and robust early-stage biomarkers are still lacking, and an improved understanding of the molecular changes in PD could help to reveal new diagnostic markers and pharmaceutical targets. Here, we report results from a cohort-wide blood plasma metabolic profiling of PD patients and controls in the Luxembourg Parkinson’s Study to detect disease-associated alterations at the level of systemic cellular process and network alterations. We identified statistically significant changes in both individual metabolite levels and global pathway activities in PD vs. controls and significant correlations with motor impairment scores. As a primary observation when investigating shared molecular sub-network alterations, we detect pronounced and coordinated increased metabolite abundances in xanthine metabolism in de novo patients, which are consistent with previous PD case/control transcriptomics data from an independent cohort in terms of known enzyme-metabolite network relationships. From the integrated metabolomics and transcriptomics network analysis, the enzyme hypoxanthine phosphoribosyltransferase 1 (HPRT1) is determined as a potential key regulator controlling the shared changes in xanthine metabolism and linking them to a mechanism that may contribute to pathological loss of cellular adenosine triphosphate (ATP) in PD. Overall, the investigations revealed significant PD-associated metabolome alterations, including pronounced changes in xanthine metabolism that are mechanistically congruent with alterations observed in independent transcriptomics data. The enzyme HPRT1 may merit further investigation as a main regulator of these network alterations and as a potential therapeutic target to address downstream molecular pathology in PD.

Untargeted metabolomics identifies indole-3-propionic acid to relieve Ang II-induced endothelial dysfunction in aortic dissection.

Indole-3-propionic acid (IPA), a gut microbiota-derived metabolite of tryptophan, has been proven to fulfill an essential function in cardiovascular disease (CVD) and nerve regeneration disease. However, the role of IPA in aortic dissection (AD) has not been revealed. We aimed to investigate the role of IPA in the pathogenesis of AD and the underlying mechanisms of IPA in endothelial dysfunction. Untargeted metabolomics has been employed to screen the plasma metabolic profile of AD patients in comparison with healthy individuals. Network pharmacology provides insights into the potential molecular mechanisms underlying IPA. 3-aminopropionitrile fumarate (BAPN) and angiotensin II (Ang II) were administered to induce AD in mice, while human umbilical vein endothelial cells (HUVECs) were employed for in vitro validation of the signaling pathways predicted by network pharmacology. A total of 224 potentially differential plasma metabolites were identified in the AD patients, with 110 up-regulated metabolites and 114 down-regulated metabolites. IPA was the most significantly decreased metabolite involved in tryptophan metabolism. Bcl2, caspase3, and AKT1 were predicted as the target genes of IPA by network pharmacology and molecular docking. IPA suppressed Ang II-induced apoptosis, intracellular ROS generation, inflammation, and endothelial tight junction (TJ) loss. Animal experiments demonstrated that administration of IPA alleviated the occurrence and severity of AD in mice. Taken together, we identified a previously unexplored association between tryptophan metabolite IPA and AD, providing a novel perspective on the underlying mechanism through which IPA mitigates endothelial dysfunction to protect against AD.

Plasma metabolomics identifies S-adenosylmethionine as a biomarker and potential therapeutic target for vascular aging in older adult males

Brachial-ankle pulse wave velocity (baPWV) is a noninvasive index of vascular aging. However, the metabolic profile underlying vascular aging has not yet been fully elucidated. The current study aimed to identify circulating markers of vascular aging as assessed by baPWV and to elucidate its mechanism from a metabolomic perspective in older adults. A total of 60 and 61 Chinese male participants aged ≥80 years were recruited to the metabolome and validation cohorts, respectively. The baPWV of participants was measured using an automatic waveform analyzer. Plasma metabolic profile was investigated using ultra-performance liquid chromatography coupled with triple quadrupole linear ion trap tandem mass spectrometry. Orthogonal partial least squares (OPLS) regression modeling established the association between metabolic profile and baPWV to determine important metabolites predictive of vascular aging. Additionally, an enzyme-linked immunosorbent assay was employed to validate the metabolites in plasma and culture media of vascular smooth muscle cells in vitro. OPLS modeling identified 14 and 22 metabolites inversely and positively associated with baPWV, respectively. These 36 biomarkers were significantly enriched in seven metabolite sets, especially in cysteine and methionine metabolism (p <0.05). Notably, among metabolites involved in cysteine and methionine metabolism, S-adenosylmethionine (SAM) level was inversely related to baPWV, with a significant correlation coefficient in the OPLS model (p <0.05). Furthermore, the relationship between SAM and vascular aging was reconfirmed in an independent cohort and at the cellular level in vitro. SAM was independently associated with baPWV after adjustments for clinical covariates (β = −0.448, p <0.001) in the validation cohort. In summary, plasma metabolomics identified an inverse correlation between SAM and baPWV in older males. SAM has the potential to be a novel biomarker and therapeutic target for vascular aging.

UHPLC-qTOF-MS-Based Nontargeted Metabolomics to Characterize the Effects of Capsaicin on Plasma and Skin Metabolic Profiles of C57BL/6 Mice-An In vivo Experimental Study.

Capsaicin is the main compound found in chili pepper and has complex pharmacologic effects. This study aimed to elucidate the mechanism of the effect of capsaicin on physiological processes by analyzing changes in metabolites and metabolic pathways. Female C57BL/6 mice were divided into two groups(n = 10/group) and fed with capsaicin-soybean oil solution(group T) or soybean oil(group C) for 6 weeks. Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-qTOF-MS) based metabolomics was undertaken to assess plasma and skin metabolic profile changes and identify differential metabolites through multivariate analysis. According to the OPLS-DA score plots, the plasma and skin metabolic profiles in the group T and group C were significantly separated. In plasma, 38 significant differential metabolites were identified. KEGG pathway enrichment analysis revealed that the most significant plasma metabolic pathways included pyruvate metabolism and ABC transporters. In skin, seven significant differential metabolites were found. Four metabolic pathways with p values < 0.05 were detected, including sphingolipid metabolism, sphingolipid signaling pathway, apoptosis, and necroptosis. These findings will provide metabolomic insights to assess the physiological functions of capsaicin and contribute to a better understanding of the potential effects of a capsaicin-rich diet on health.

Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

IntroductionThe chromosome 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with a wide range of brain-related phenotypes including schizophrenia spectrum disorders (SCZ), autism spectrum disorders (ASD), anxiety disorders and attention deficit disorders (ADHD). The typically deleted region in 22q11.2DS contains multiple genes which haploinsufficiency has the potential of altering the protein and the metabolic profiles.Objectives Alteration in metabolic processes and downstream protein pathways during the early brain development may help to explain the increased prevalence of the observed neurodevelopmental phenotypes in 22q11.2DS. However, relatively little is known about the correlation of dysregulated protein/metabolite expression and neurobehavioral impairments in individuals who developed them over time.Methods In this study, we performed untargeted metabolic and proteomic analysis in plasma samples derived from 30 subjects including 16 participants with 22q11.2DS and 14 healthy controls (TD) enrolled in a longitudinal study, aiming to identify a metabolic and protein signature informing about the underlying mechanisms involved in disease development and progression. The metabolic and proteomic profiles were also compared between the participants with 22q11.2DS with and without various comorbidities, such as medical involvement, psychiatric conditions, and autism spectrum disorder (ASD) to detect potential changes among multiple specimens, collected overtime, with the aim to understand the basic underlying mechanisms involved in disease development and progression.ResultsWe observed a large number of statistically significant differences in metabolites between the two groups. Among them, the levels of taurine and arachidonic acid were significantly lower in 22q11.2DS compared to the TD group. In addition, we identified 16 proteins that showed significant changes in expression levels (adjusted P < 0.05) in 22q11.2DS as compared to TD, including those involved in 70 pathways such as gene expression, the PI3K-Akt signaling pathway and the complement system. Within participants with 22q11.2DS, no significant changes in those with and without medical or psychiatric conditions were observed.ConclusionTo our knowledge, this is the first report on plasma metabolic and proteomic profiling and on the identification of unique biomarkers in 22q11.2DS. These findings may suggest the potential role of the identified metabolites and proteins as biomarkers for the onset of comorbid conditions in 22q11.2DS. Ultimately, the altered protein pathways in 22q11.2DS may provide insights of the biological mechanisms underlying the neurodevelopmental phenotype and may provide missing molecular outcome measures in future clinical trials to assess early-diagnosis treatment and the efficacy of response to targeted treatment.

Impact of Bariatric Surgery on Circulating Metabolites and Cognitive Performance.

Bariatric surgery is an effective intervention to reduce obesity and improve associated comorbidities. However, its effects on cognitive function are still the subject of debate. Given that the bioavailability of circulating metabolites can influence brain metabolism and cognitive performance, we aimed to assess the effects of bariatric surgery on plasma metabolic profiles and cognitive performance. We recruited 26 women undergoing gastric bypass surgery. We conducted anthropometric assessments and collected plasma samples for metabolomic analysis. A set of 4 cognitive tests were used to evaluate cognitive performance. Participants were reevaluated 1year post-surgery. After surgery, attention capacity and executive function were improved, while immediate memory had deteriorated. Regarding metabolic profile, reduction of beta-tocopherol and increase of serine, glutamic acid, butanoic acid, and glycolic acid were observed. To better understand the relationship between cognitive function and metabolites, a cluster analysis was conducted to identify more homogeneous subgroups based on the cognitive performance. We identified cluster 1, which did not show changes in cognitive performance after surgery, and cluster 2, which showed improved attention and executive function, but reduced performance in the immediate memory test. Thus, cluster 2 was more homogeneous group that replicated the results of non-clustered subjects. Analysis of the metabolic profile of cluster 2 confirmed serine, glutamic acid, and glycolic acid as potential metabolites associated with cognitive performance. Metabolites identified in this study have potential for biomarkers and alternative therapeutic target to prevent obesity-related cognitive decline. • Attention capacity and executive function were improved 12 months post bariatric surgery. • Immediate memory was worsened 12 months post bariatric surgery. • Serine, glutamic acid, and glycolic acid are potential metabolites linked to the alteration of cognitive performance.

Association between altered tryptophan metabolism, plasma aryl hydrocarbon receptor agonists, and inflammatory Chagas disease.

Chagas disease causes a cardiac illness characterized by immunoinflammatory reactions leading to myocardial fibrosis and remodeling. The development of Chronic Chagas Cardiomyopathy (CCC) in some patients while others remain asymptomatic is not fully understood, but dysregulated inflammatory responses are implicated. The Aryl hydrocarbon receptor (AhR) plays a crucial role in regulating inflammation. Certain tryptophan (Trp) metabolites have been identified as AhR ligands with regulatory functions. We investigated AhR expression, agonist response, ligand production, and AhR-dependent responses, such as IDO activation and regulatory T (Treg) cells induction, in two T. cruzi-infected mouse strains (B6 and Balb/c) showing different polymorphisms in AhR. Furthermore, we assessed the metabolic profile of Trp catabolites and AhR agonistic activity levels in plasma samples from patients with chronic Chagas disease (CCD) and healthy donors (HD) using a luciferase reporter assay and liquid chromatography-mass spectrophotometry (LC-MS) analysis. T. cruzi-infected B6 mice showed impaired AhR-dependent responses compared to Balb/c mice, including reduced IDO activity, kynurenine levels, Treg cell induction, CYP1A1 up-regulation, and AhR expression following agonist activation. Additionally, B6 mice exhibited no detectable AhR agonist activity in plasma and displayed lower CYP1A1 up-regulation and AhR expression upon agonist activation. Similarly, CCC patients had decreased AhR agonistic activity in plasma compared to HD patients and exhibited dysregulation in Trp metabolic pathways, resulting in altered plasma metabolite profiles. Notably, patients with severe CCC specifically showed increased N-acetylserotonin levels in their plasma. The methods and findings presented here contribute to a better understanding of CCC development mechanisms and may identify potential specific biomarkers for T. cruzi infection and the severity of associated heart disease. These insights could be valuable in designing new therapeutic strategies. Ultimately, this research aims to establish the AhR agonistic activity and Trp metabolic profile in plasma as an innovative, non-invasive predictor of prognosis for chronic Chagas disease.

Adaptive metabolic response to short-term intensive fasting

Short-term intensive fasting (STIF), known as beego in Chinese phonetic articulation, has been practiced for more than two thousand years. However, the potential risk of STIF and the body's response to the risk have not been adequately evaluated. This study aims to address this issue, focusing on the STIF-triggered metabolic response of the liver and kidney. The STIF procedure in the clinical trial includes a 7-day water-only intensive fasting phase and a 7-day gradual refeeding phase followed by a regular diet. The intensive fasting in humans was assisted with psychological induction. To gain insights not available in the clinical trial, we designed a STIF program for mice that resulted in similar phenotypes seen in humans. Plasma metabolic profiling and examination of gene expression as well as liver and kidney function were performed by omics, molecular, biochemical and flow cytometric analyses. A human cell line model was also used for mechanistic study. Clinically significant metabolites of fat and protein were found to accumulate during the fasting phase, but they were relieved after gradual refeeding. Metabolomics profiling revealed a universal pattern in the consumption of metabolic intermediates, in which pyruvate and succinate are the two key metabolites during STIF. In the STIF mouse model, the accumulation of metabolites was mostly counteracted by the upregulation of catabolic enzymes in the liver, which was validated in a human cell model. Kidney filtration function was partially affected by STIF but could be recovered by refeeding. STIF also reduced oxidative and inflammatory levels in the liver and kidney. Moreover, STIF improved lipid metabolism in mice with fatty liver without causing accumulation of metabolites after STIF. The accumulation of metabolites induced by STIF can be relieved by spontaneous upregulation of catabolic enzymes, suggesting an adaptive and protective metabolic response to STIF stress in the mammalian body.

Integrated metabolomics and transcriptomics to reveal biomarkers and mitochondrial metabolic dysregulation of premature ovarian insufficiency.

The metabolic characteristics of premature ovarian insufficiency (POI), a reproductive endocrine disease characterized by abnormal sex hormone metabolism and follicle depletion, remain unclear. Metabolomics is a powerful tool for exploring disease phenotypes and biomarkers. This study aims to identify metabolic markers and construct diagnostic models, and elucidate the underlying pathological mechanisms for POI. Non-targeted metabolomics was utilized to characterize the plasma metabolic profile of 40 patients. The metabolic markers were identified through bioinformatics and machine learning, and constructed an optimal diagnostic model by classified multi-model analysis. Enzyme-linked immunosorbent assay (ELISA) was used to verify antioxidant indexes, mitochondrial enzyme complexes, and ATP levels. Finally, integrated transcriptomics and metabolomics were used to reveal the dysregulated pathways and molecular regulatory mechanisms of POI. The study identified eight metabolic markers significantly correlated with ovarian reserve function. The XGBoost diagnostic model was developed based on six machine learning models, demonstrating its robust diagnostic performance and clinical applicability through the evaluation of receiver operating characteristic (ROC) curve, decision curve analysis (DCA), calibration curve, and precise recall (PR) curve. Multi-omics analysis showed that mitochondrial respiratory chain electron carrier (CoQ10) and enzyme complex subunits were down-regulated in POI. ELISA validation revealed an elevation in oxidative stress markers and a reduction in the activities of antioxidant enzymes, CoQ10, and mitochondrial enzyme complexes in POI. Our findings highlight that mitochondrial dysfunction and energy metabolism disorders are closely related to the pathogenesis of POI. The identification of metabolic markers and predictive models holds significant implications for the diagnosis, treatment, and monitoring of POI.

Comparing plasma and skin imprint metabolic profiles in COVID-19 diagnosis and severity assessment.

As SARS-CoV-2 continues to produce new variants, the demand for diagnostics and a better understanding of COVID-19 remain key topics in healthcare. Skin manifestations have been widely reported in cases of COVID-19, but the mechanisms and markers of these symptoms are poorly described. In this cross-sectional study, 101 patients (64 COVID-19 positive patients and 37 controls) were enrolled between April and June 2020, during the first wave of COVID-19, in São Paulo, Brazil. Enrolled patients had skin imprints sampled non-invasively using silica plates; plasma samples were also collected. Samples were used for untargeted lipidomics/metabolomics through high-resolution mass spectrometry. We identified 558 molecular ions, with lipids comprising most of them. We found 245 plasma ions that were significant for COVID-19 diagnosis, compared to 61 from the skin imprints. Plasma samples outperformed skin imprints in distinguishing patients with COVID-19 from controls, with F1-scores of 91.9% and 84.3%, respectively. Skin imprints were excellent for assessing disease severity, exhibiting an F1-score of 93.5% when discriminating between patient hospitalization and home care statuses. Specifically, oleamide and linoleamide were the most discriminative biomarkers for identifying hospitalized patients through skin imprinting, and palmitic amides and N-acylethanolamine 18:0 were also identified as significant biomarkers. These observations underscore the importance of primary fatty acid amides and N-acylethanolamines in immunomodulatory processes and metabolic disorders. These findings confirm the potential utility of skin imprinting as a valuable non-invasive sampling method for COVID-19 screening; a method that may also be applied in the evaluation of other medical conditions. KEY MESSAGES: Skin imprints complement plasma in disease metabolomics. The annotated markers have a role in immunomodulation and metabolic diseases. Skin imprints outperformed plasma samples at assessing disease severity. Skin imprints have potential as non-invasive sampling strategy for COVID-19.

322 Metabolic Pathway and Rumen Bacterial Taxa Associated with Divergent Residual Body Weight Gain Phenotypes in Beef Cattle

Abstract We applied metabolomics and 16S rRNA gene sequencing to determine the metabolic pathway and ruminal bacterial taxa associated with divergent residual body weight (BW) gain phenotype in crossbred beef steers. A group of 108 crossbred growing beef steers (average BW = 282.87 ± 30 kg) were fed a forage-based diet for a period of 56 d in a confinement dry lot equipped with GrowSafe intake nodes to determine their residual body weight gain (RADG) phenotype. After RADG identification, blood and rumen fluid samples were collected from beef steers with the greatest RADG (most efficient; n = 20; 0.76 kg/d) and least RADG (least efficient; n = 20; -0.65 kg/d). Metabolome analysis of the plasma and rumen fluid samples was conducted using chemical isotope labelling/liquid chromatography–mass spectrometry. Differentially abundant metabolites in each of the plasma and rumen fluid samples between the two groups of beef steers were determined using a false discovery rate (FDR)-adjusted P-values ≤ 0.05 and area under the curve (AUC) &amp;gt; 0.80. Rumen and plasma metabolic pathways that were differentially enriched or depleted (P ≤ 0.05) in beef steers with positive RADG compared with those with negative RADG were determined by the quantitative pathway enrichment analysis. A total of 1,629 metabolites were detected and identified in the plasma of the beef steers; eight metabolites including alanyl-phenylalanine, 8-hydroxyguanosine, and slaframine were differentially abundant (FDR ≤ 0.05; AUC &amp;gt; 0.80) in beef steers with divergent RADG; five metabolic pathways including steroid hormone biosynthesis, thiamine metabolism, propanoate metabolism, pentose phosphate pathway, and butanoate metabolism were enriched (P ≤ 0.05) in beef steers with positive RADG, relative to negative RADG steers. A total of 1908 metabolites were detected and identified in the rumen of the beef steers; results of the pathway enrichment analysis of all the metabolites revealed no metabolic pathways in the rumen were altered (P ≥ 0.05). The rumen fluid samples were also analyzed using 16S rRNA gene sequencing to assess the bacterial community composition. We compared the rumen bacterial community composition at the genus level using a linear discriminant analysis effect size (LEfSe) to identify the differentially abundant taxa between the two groups of beef steers. The LEfSe results showed greater relative abundance of Bacteroidetes_vadinHA17 and Anaerovibrio in steers with positive RADG compared with the negative RADG group, while steers in the negative RADG group had greater relative abundance of Candidatus_Amoebophilus, Clostridium_sensu_stricto_1, Pseudomonas, Empedobacter, Enterobacter, and Klebsiella compared with the positive RADG group. Our results demonstrate that beef steers with positive or negative RADG exhibit differences in plasma metabolic profiles and some ruminal bacterial taxa which probably explain their divergent feed efficiency phenotypes.

Plasma metabolomics and proteomics reveal novel molecular insights and biomarker panel for cholelithiasis

BackgroundCholelithiasis is a gastrointestinal disease that is associated with the highest socioeconomic cost. A diagnosis of cholelithiasis based on clinical features is significantly limited, and direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters are unclear. ObjectivesUncovering direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters. Identifying sensitive and specific biomarkers for this disease. MethodsParallel metabolomic and proteomic analyses of plasma from cholelithiasis patients (CPs) and healthy control individuals (HCs) without cholelithiasis were performed using ultrahigh-performance liquid chromatography-tandem mass spectrometry. A multimodule coexpression network analysis and integrated machine learning methods, including least absolute shrinkage and selection operator, random forest, and support vector machine, were used for bioinformatic analyses. An independent cohort and the cross-validation of the combination of two cohorts were used to evaluate the diagnostic performance of the panel. ResultsArachidonic acid metabolism was significantly different between the CP and HC groups. Glyceraldehyde-3-phosphate dehydrogenase, actin beta, phosphoglycerate mutase 1, Enolase 1, Myeloperoxidase, and actin alpha 1 were identified as potential proteins related to cholelithiasis. The correlation between the merged modules and clinical biochemical tests was calculated. A diagnostic panel composed of four candidate biomarkers, including 3-oxotetradecanoic acid, 12-hydroxydodecanoic acid, hemoglobin subunit delta (HBD), and fibrinogen beta chain (FGB), was proposed based on three modules that were significantly associated with cholelithiasis. The classification according to the diagnostic panel detected CPs with an area under the curve (AUC) of 0.955. External validation in an independent cohort resulted in similar accuracy (AUC=0.995). ConclusionsThis study provided some direct molecular insights into cholelithiasis by showing the differences in plasma metabolic and protein profiles between CPs and HCs and presented a potential biomarker panel with two metabolites (3-oxotetradecanoic acid, 12-hydroxydodecanoic acid) and two proteins (HBD, FGB) for predicting cholelithiasis. We also explored the potential correlation of clinical biochemical parameters with combined modules. These findings may provide some reference for the diagnosis of cholelithiasis in clinical practice.

Acute repeated cage exchange stress modifies urinary stress and plasma metabolic profiles in male mice.

Exposure to a novel environment is psychologically and physically stressful for humans and animals. The response has been reported to involve enhanced sympathetic nervous system activity, but changes in nutrient levels under stress are not fully understood. As a form of exposure to a novel environment, repeated cage exchange (CE, four times at 2-h intervals for 8 h from 08:00 h) during the light phase with no restraint on movement was applied to A/J mice, a strain particularly prone to stress. Body temperature was measured with a temperature-sensing microchip implanted in the interscapular region. The stress conditions and anxiety level were evaluated by measuring urinary catecholamines and corticosterone and by performing an anxiety-like behavior test, respectively. Major nutrients such as glucose, fatty acids, and amino acids in the plasma were also examined. CE mice showed a significant increase in body temperature with each CE. They also showed a significantly greater reduction of body weight change, more water intake, and higher levels of urinary catecholamines and corticosterone and anxiety-like behavior score than control mice. The model revealed a significantly lower plasma glucose level and higher levels of several essential amino acids, such as branched-chain amino acids and phenylalanine, than those of control mice. Meanwhile, free fatty acids and several amino acids such as arginine, aspartic acid, proline, threonine, and tryptophan in both sets of mice were significantly decreased from the corresponding levels at 08:00 h, while similar plasma levels were exhibited between mice with and without CE. In conclusion, repeated CE stress was associated with changes in glucose and amino acids in plasma. Although further study is needed to clarify how these changes are specifically linked to anxiety-like behavior, this study suggests the potential for nutritional intervention to counter stress in humans exposed to novel environments.