Plasma Metabolic Profiles Research Articles

Plasma metabolic profile reveals signatures of maternal health during gestational hypertension and preeclampsia without and with severe features.

Preeclampsia, a pregnancy-specific syndrome, poses substantial risks to maternal and neonatal health, particularly in cases with severe features. Our study focuses on evaluating the impact of low molecular weight metabolites on the intricate mechanisms and pathways involved in the pathophysiology of preeclampsia when severe features are present. We aim to pinpoint the distinct metabolomic profile in maternal plasma during pregnancies affected by hypertensive disorders and to correlate the metabolite levels with the clinical characteristics of the study cohort. A total of 173 plasma samples were collected, comprising 36 healthy pregnant women (HP), 52 patients with gestational hypertension (GH), 43 with preeclampsia without (PE-), and 42 with severe features (PE+). Nuclear magnetic resonance spectroscopy and metabolite identification were conducted to establish the metabolomic profiles. Univariate and chemometric analyses were conducted using MetaboAnalyst, and correlations were performed using GraphPad Prism. Our study unveils distinct metabolomic profiles differentiating HP women, patients featuring GH, and patients with PE-and PE+. Our analysis highlights an increase in acetate, N,N-dimethylglycine, glutamine, alanine, valine, and creatine levels in the PE+ group compared to the HP and GH groups. The PE+ group exhibited higher concentrations of N,N-dimethylglycine, glutamine, alanine, and valine compared to the PE-group. Moreover, elevated levels of specific metabolites, including N,N-dimethylglycine, alanine, and valine, were associated with increased blood pressure, worse obstetric outcomes, and poorer end-organ function, particularly renal and hepatic damage. Metabolomic analysis of PE+ individuals indicates heightened disturbances in nitrogen metabolism, methionine, and urea cycles. Additionally, the exacerbated metabolic disturbance may have disclosed renal impairment and hepatic dysfunction, evidenced by elevated levels of creatine and alanine. These findings not only contribute novel insights but also provide a more comprehensive understanding of the pathophysiological mechanisms at play in cases of PE+.

Untargeted metabolomics to detect and identify plasma metabolic signatures associated with intracranial aneurysm and its rupture.

The biological basis for metabolic differences between unruptured and ruptured intracranial aneurysm (UIA and RIA) populations and their potential role in triggering IA rupture remain unclear. The aim of this study was to analyze the plasma metabolic profiles of patients with UIA and RIA using an untargeted metabolomic approach and to develop a model for early rupture classification. Plasma samples were analyzed using an ultra-high-performance liquid chromatography high-resolution tandem mass spectrometry-based platform. Least absolute shrinkage and selection operator regression and random forest machine learning methods were employed for metabolite feature selection and predictive model construction. Among 49 differential plasma metabolites identified, 31 were increased and 18 were decreased in the plasma of RIA patients. Five key metabolites-canrenone, piperine, 1-methyladenosine, betaine, and trigonelline-were identified as having strong potential to discriminate between UIA and RIA patients. This combination of metabolites demonstrated high diagnostic accuracy, with an area under the curve exceeding 0.95 in both the training and validation datasets. Our finding highlights the significance of plasma metabolites as potential biomarkers for early detection of IA rupture risk, offering new insights for clinical practice and future research on IA management.

Circulating metabolites in patients with chronic heart failure are related to increased lipid utilisation but not to gut microbiota alterations

Abstract Background The gut microbiota produces numerous metabolites that can enter the circulation and exert their effects outside the gut. Some have been implicated in the pathogenesis of chronic heart failure (HF). Several studies have reported altered gut microbiota composition and circulating metabolites in patients with chronic HF compared to healthy controls (HC). However, limited data is available on the potential interplay between the dysbiotic features of the gut microbiota and the altered circulating metabolome in these patients. Purpose To examine differences in circulating metabolites between patients with chronic HF and HC, and their association with cardiac function and gut dysbiosis. Methods We included 123 patients, aged 18-75 years, with stable chronic HF and left ventricular ejection fraction (LVEF) <40%, and 51 HC. We collected fasting blood samples for metabolomic and lipidomic analyses, which were performed using liquid chromatography tandem mass spectrometry. A web-based platform was utilised for data preprocessing, filtering, pathway analysis, and metabolite annotation. Principal component analysis and orthogonal partial least squares discriminant analysis were used to explore differences in plasma metabolic profiles. Over-representation analysis was performed to identify the pathways in which relevant metabolites were involved. Stool samples were sequenced using 16S ribosomal RNA gene amplification. We calculated a dysbiosis index for each sample based on different abundances of microbial taxa in patients vs. controls. Results After adjusting for age and sex, we identified 73 enriched metabolites and 27 enriched lipids (odds ratio≥2 and p<0.05), and 124 depleted metabolites and 6 depleted lipids (odds ratio≤0.5 and p<0.05) in HF patients compared to HC. The enriched metabolites were involved in pathways related to lipid metabolism (beta oxidation, glycerolipid, sex hormone, and fatty acid metabolism), pyrimidine metabolism, Warburg effect, citric acid cycle, and pentose phosphate pathway. The depleted metabolites were involved in pathways related to lipid biosynthesis (fatty acids, steroids, bile acids), amino acid metabolism (glycine, serine, taurine, hypotaurine, cysteine, selenoamino acids), polyamine biosynthesis (spermidine, spermine), sulphate/sulphite metabolism, propanoate and pyruvate metabolism, carbohydrate metabolism (galactose, amino sugars, glycolysis), transfer of acetyl groups into mitochondria, urea cycle, and beta oxidation of very long chain fatty acids (Figure 1). LVEF, N-terminal pro B-type natriuretic peptide, and the dysbiosis index were not significantly related to any metabolite. Conclusions In patients with chronic HF, energy metabolism is significantly altered compared to HC, with a notable shift towards lipid utilisation. However, the alterations in circulating metabolites were not related to markers of cardiac function and appear to be unrelated to gut dysbiosis.Figure 1

P08.06.B TARGETED PLASMA METABOLOMICS DETECTS A METABOLIC SIGNATURE POTENTIALLY RELEVANT FOR DIAGNOSIS AND PROGNOSIS IN PATIENTS WITH GLIOBLASTOMA

Abstract BACKGROUND Glioblastoma diagnosis is made initially with radiological examination and pathological examination of the resected tumor. Debut symptoms may vary and be mild in the beginning therefore diagnosis can be delayed. Additional un-invasive diagnostic strategies can be useful for diagnosis and clinical follow up. Moreover, despite glioblastoma being almost invariably fatal, there are no clinically established plasma biomarkers to define prognosis in patients with glioblastoma. MATERIAL AND METHODS In this study we employed flow injection analysis tandem mass spectrometry to compare the plasma metabolic profile of patients with GBM (n=51) and healthy controls (n=24). RESULTS Principal Component Analysis (PCA) and Partial Least Discriminant Analysis (PLS-DA) highlighted a distinctive glioblastoma signature. The best confusion matrix from the ROC curve built on two metabolites, GLU and GLN-LYS, provided specificity of 87% and sensitivity of 92%, with positive and negative predictive values of 95% and 88%, respectively. Multivariate survival analyses revealed that higher levels of ALA, MET, ORN, PHE, TYR were to be associated with a shorter overall survival. CONCLUSION These results are currently being evaluated prospectively and at different stages of disease in a larger cohort of patients with glioblastoma to identify plasma metabolic markers relevant for recurrence development.

Lifelong impacts of puberty timing on human plasma metabolic profiles: A metabolome-wide Mendelian randomization study.

The aim was to investigate the causal relationship between puberty timing and plasma metabolites, accounting for birth weight, childhood and adulthood adiposity. The meta-analysis of genome-wide association studies (GWAS) for puberty timing was extracted from the ReproGen Consortium, involving 329 345 women of European ancestry. Summary data for 174 plasma metabolites were retrieved from a recently conducted cross-platform GWAS that involved a meta-analysis of three cohort studies (i.e. the Fenland, European Prospective Investigation into Cancer-Norfolk and INTERVAL studies) and three publicly available studies and included up to 86 507 participants. We conducted a two-sample Mendelian randomization (MR) analysis to infer the causal relationship of puberty timing on 174 plasma metabolites, complemented by a two-step and multivariable Mendelian randomization (MVMR) analysis to assess direct and indirect effects. Additionally, summary-level data from the UK Biobank were used for our replication analysis. The results of the two-sample MR provide moderate evidence supporting a causal relationship between puberty timing and 23 of 174 plasma metabolites (i.e. 7 acylcarnitines, 8 amino acids, 2 biogenic amines and 6 lysophosphatidylcholines). Even after single-nucleotide polymorphisms associated with birth weight and childhood adiposity were excluded, causal effects persisted for 16 metabolites (i.e. 8 acylcarnitines, 4 amino acids, 2 biogenic amines and 2 lysophosphatidylcholines). The two-step MR analysis provided evidence that the relationship between puberty timing and plasma metabolites was mediated by adulthood adiposity. Additionally, moderate evidence emerged for an independent causal effect of puberty timing on 10 metabolites through an MVMR analysis (i.e. 5 acylcarnitines, 2 amino acids, 1 biogenic amine, 1 lysophosphatidylcholine and 1 phosphatidylcholine). Furthermore, the replication analysis suggested the robustness of our results. In summary, our study provides compelling evidence that puberty timing has a causal influence on certain plasma metabolites, although this influence is largely mediated by adulthood adiposity.

Dynamic variations of plasma and urine metabolic profiles in left anterior descending coronary artery ligation-induced myocardial infarction rats and the regulatory effects of Chinese patent medicine Xin-Ke-Shu

Myocardial infarction (MI) is one of the most severe cardiovascular diseases (CVD). Traditional Chinese medicines have unique advantages in the treatment of CVD, with Xin-Ke-Shu (XKS) being a commonly used Chinese patent medicine for the prevention and treatment of MI patients. This study aimed to investigate the dynamic metabolic profiles of plasma and urine in left anterior descending coronary artery ligation (LAD) -induced MI rats at days 3, 12, and 21 after surgery, and to evaluate the regulatory effects of XKS at these time points using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) metabolomics. The metabolic profiles of plasma and urine in the LAD-induced MI rats showed significant variations at days 3, 12, and 21 after MI. We identified a total of 23 plasma metabolites and 12 urine metabolites as potential pathological markers related to MI progression. These metabolites were mainly involved in pathways such as TCA cycle, arachidonic acid metabolism, glutathione metabolism, glycerophospholipid metabolism, sphingolipid metabolism, and fatty acid metabolism, all of which were associated with imbalance of myocardial energy metabolism, oxidative stress, and calcium overload. Disturbances in the TCA cycle, arachidonic acid metabolism, glutathione metabolism, and purine metabolism in plasma and urine were observed as early as day 3 after MI. By day 12, we noted significant changes in fatty acid metabolism in plasma and urine, along with notable alterations in sphingolipid metabolism in plasma. Disorders in plasma glycerophospholipid metabolism were first evident at day 12 and reached their peak severity by day 21. Treatments with XKS significantly regulated the disturbances in the plasma and urine metabolic profiles of MI rats at days 3, 12, and 21, with medium dose of XKS displaying a particularly strong regulatory effect, especially at day 12. Our study demonstrates that host metabolism undergoes dynamical changes following MI with most metabolic disorders manifesting in the early stage of MI. XKS effectively regulates nearly all of these disturbances and can be administered as soon as possible after MI. These findings provide valuable insights into the metabolic progression of MI and highlight the therapeutic potential of XKS in the treatment of MI.

6-Gingerol improves lipid metabolism disorders in skeletal muscle by regulating AdipoR1/AMPK signaling pathway

BackgroundTo delve into the precise mechanisms by which 6-gingerol ameliorates lipid metabolism disorders in skeletal muscle. MethodsThe level of triglycerides (TG) was used to evaluate lipid deposition. In skeletal muscle, transmission electron microscopy (TEM) was employed to observe mitochondrial morphology. Additionally, PCR was applied to detect mitochondrial biogenesis, and levels of malondialdehyde (MDA), catalase (CAT), glutathione, r-glutamyl cysteingl+glycine (GSH) and nicotinamide adenine dinucleotide (NADH) were measured to assess mitochondrial oxidative stress levels. In vivo, flow cytometry and immunofluorescence assays were conducted to quantify reactive oxygen species (ROS) and mitochondrial membrane potential (MMP). Furthermore, the Seahorse XF assays was utilized to assess mitochondrial respiratory capacity. Fluorescence confocal microscopy and molecular docking were applied to analyze the binding of 6-gingerol and adiponectin receptor 1 (AdipoR1). The expression of AdipoR1, AMPK, PGC-1α and SIRT1 were detected by Western Blot. ResultsIn vivo, 6-gingerol could reduce body weight in mice induced by a high-fat diet, enhance metabolic profiles in plasma, decrease lipid accumulation in skeletal muscle and liver, and elevate adiponectin levels. In skeletal muscle, it could restore mitochondrial morphology, boost mitochondrial copy number and biogenesis, and mitigate oxidative stress. In vitro, 6-gingerol may directly interact with AdipoR1 to upregulate the expression of downstream proteins p-AMPK, SIRT1, and PGC-1α, leading to a reduction in lipid deposition, a decrease in ROS production, an increase in mitochondrial membrane potential, and an enhancement of mitochondrial respiratory capacity in C2C12 myotubes. Conclusion6-Gingerol ameliorated lipid metabolism in skeletal muscle by regulating the AdipoR1/AMPK signaling pathway.

New insight into primary hyperparathyroidism using untargeted metabolomics

Primary Hyperparathyroidism (PHPT) is characterized by excessive parathormone (PTH) secretion and disrupted calcium homeostasis. Untargeted metabolomics offers a valuable approach to understanding the complex metabolic alterations associated with different diseases, including PHPT. Plasma untargeted metabolomics was applied to investigate the metabolic profiles of PHPT patients compared to a control group. Two complementary liquid-phase separation techniques were employed to comprehensively explore the metabolic landscape in this retrospective, single-center study. The study comprised 28 female patients diagnosed following the current guidelines of PHPT diagnosis and a group of 30 healthy females as a control group. To evaluate their association with PHPT, we identified changes in plasma metabolic profiles in patients with PHPT compared to the control group. The primary outcome measure included detecting plasma metabolites and discriminating PHPT patients from controls. The study unveiled specific metabolic imbalances that may link l-amino acids with peptic ulcer disease, gamma-glutamyls with oxidative stress, and asymmetric dimethylarginine (ADMA) with cardiovascular complications. Several metabolites, such as gamma-glutamyls, caffeine, sex hormones, carnitine, sphingosine-1-phosphate (S-1-P), and steroids, were connected with reduced bone mineral density (BMD). Metabolic profiling identified distinct metabolic patterns between patients with PHPT and healthy controls. These findings provided valuable insights into the pathophysiology of PHPT.

Plasma metabolic profiling reveals that crude and processed Polygonatum cyrtonema hua extract ameliorates myocardial ischemia-induced damage by regulating branched-chain amino acid and energy metabolism

Polygonatum cyrtonema Hua and its processed products have demonstrated cardio-protective effects, though the underlying mechanisms remain unclear. In this study, plasma metabolic profiling and pattern recognition were employed to explore the cardio-protective mechanisms of both crude and processed P. cyrtonema in a myocardial ischemia model induced by ligation, using gas chromatography-mass spectrometry. Post-modeling, plasma levels of creatine kinase-MB, lactate dehydrogenase, troponin T, and malondialdehyde were significantly elevated but were notably reduced after treatment. Conversely, plasma levels of glutathione peroxidase and superoxide dismutase, which were significantly decreased post-modeling, were restored following treatment. Hematoxylin-eosin (HE) and Masson staining revealed that both crude and processed P. cyrtonema effectively reduced inflammatory infiltration and fibrosis in cardiac tissue. Metabolic profiling identified 34 differential endogenous metabolites in the treatment groups, with 19 confirmed using standard compounds. The linear correlation coefficients (R2) for these standards ranged from 0.9960 to 0.9996, indicating high accuracy. The method exhibited excellent precision and repeatability, with relative standard deviation (RSD) values below 8.57%. Recovery rates were between 95.02% and 105.15%, and the stability of the standard compounds was confirmed after three freeze–thaw cycles, with RSD values under 4.42%. Both crude and processed P. cyrtonema were found to alleviate myocardial ischemia symptoms by regulating branched-chain amino acid metabolism and energy metabolism. These findings provide a solid foundation for the potential clinical use of this herb and its processed products in treating heart disease.

2837: Metabolic profiling of plasma and tissue in breast cancer patients: uncovering therapeutic response

2837: Metabolic profiling of plasma and tissue in breast cancer patients: uncovering therapeutic response

Study of plasma metabolic markers in unexplained recurrent spontaneous abortion based on non-target metabolomics approach

Objective: To screen plasma metabolic markers in patients with unexplained recurrent spontaneous abortion (URSA) by non-target metabolomics approach. Methods: From September 2022 to May 2023, the plasma of 23 URSA pregnant women with threatened abortion who visited the outpatient clinic of Gansu Provincial Maternity and Child-care Hospital in the first trimester (URSA group) was collected, and the plasma of 22 healthy pregnant women in the first trimester who underwent prenatal examination during the same period (normal control group) was collected. Plasma metabolomics was analyzed by ultra performance liquid chromatography (UPLC) coupled with mass spectrometry (MS), fold change analysis, principal component analysis and partial least square discriminant analysis were applied to screen for differential metabolites, and the metabolites and their pathways associated with URSA were screened using receiver operating characteristic (ROC) curve and pathway enrichment analysis. Results: There were no significant differences in age, body mass index and gestational weeks between URSA and normal control group(all P<0.05). Metabolomics analysis using UPLC-MS showed that a total of 526 metabolites were detected from plasma, of which 33 were found to be differential metabolites associated with URSA based on the screening standards. Six potential metabolites with large area under the curve (AUC) were identified by ROC curve analysis, including phosphatidylethanolamine (AUC=0.972, 95%CI: 0.920-1.000), santene hydrate (AUC=0.902, 95%CI: 0.786-0.982), L-leucine (AUC=0.884, 95%CI: 0.772-0.960), cembrene (AUC=0.881, 95%CI: 0.758-0.956), caffeine (AUC=0.875, 95%CI: 0.756-0.962), and 4-hydroxybenzoic acid propyl ester (AUC=0.864, 95%CI: 0.732-0.946). The AUC for the combined diagnosis of URSA by the six metabolites was 0.983 (95%CI: 0.929-1.000). Pathway enrichment analysis of the differential metabolites showed that the pathogenesis of URSA was associated with a variety of metabolic pathways including caffeine metabolism, glycerophospholipid metabolism, and unsaturated fatty acid biosynthesis. Conclusion: The plasma metabolic profiles of pregnant women with normal pregnancies versus URSA differ in early pregnancy, and six potential metabolites such as phosphatidylethanolamine, santene hydrate, L-leucine, cembrene, caffeine, 4-hydroxybenzoic acid propyl ester, and their metabolic pathways may be involved in the pathogenesis of URSA.

Physical performance and plasma metabolic profile as potential prognostic factors in metastatic lung cancer patients.

Low physical performance is associated with higher mortality rate in multiple pathological conditions. Here, we aimed to determine whether body composition and physical performance could be prognostic factors in non-small cell lung cancer (NSCLC) patients. Moreover, we performed an exploratory approach to determine whether plasma samples from NSCLC patients could directly affect metabolic and structural phenotypes in primary muscle cells. This prospective cohort study included 55 metastatic NSCLC patients and seven age-matched control subjects. Assessments included physical performance, body composition, quality of life and overall survival rate. Plasma samples from a sub cohort of 18 patients were collected for exploratory studies in cell culture and metabolomic analysis. We observed a higher survival rate in NSCLC patients with high performance in the timed up-and-go (+320%; p = .007), sit-to-stand (+256%; p = .01) and six-minute walking (+323%; p = .002) tests when compared to NSCLC patients with low physical performance. There was no significant association for similar analysis with body composition measurements (p > .05). Primary human myotubes incubated with plasma from NSCLC patients with low physical performance had impaired oxygen consumption rate (-54.2%; p < .0001) and cell proliferation (-44.9%; p = .007). An unbiased metabolomic analysis revealed a list of specific metabolites differentially expressed in the plasma of NSCLC patients with low physical performance. These novel findings indicate that physical performance is a prognostic factor for overall survival in NSCLC patients and provide novel insights into circulating factors that could impair skeletal muscle metabolism.

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy.

Non-small cell lung cancer (NSCLC) is the primary form of lung cancer, and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease. However, the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies. Consequently, it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments. To identify the metabolic signatures associated with neutrophil extracellular traps (NETs) and chemoimmunotherapy efficacy in NSCLC patients. In total, 159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled. We first investigated the characteristics influencing clinical efficacy. Circulating levels of NETs and cytokines were measured by commercial kits. Liquid chromatography tandem mass spectrometry quantified plasma metabolites, and differential metabolites were identified. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest algorithms were employed. By using plasma metabolic profiles and machine learning algorithms, predictive metabolic signatures were established. First, the levels of circulating interleukin-8, neutrophil-to-lymphocyte ratio, and NETs were closely related to poor efficacy of first-line chemoimmunotherapy. Patients were classed into a low NET group or a high NET group. A total of 54 differential plasma metabolites were identified. These metabolites were primarily involved in arachidonic acid and purine metabolism. Three key metabolites were identified as crucial variables, including 8,9-epoxyeicosatrienoic acid, L-malate, and bis(monoacylglycerol)phosphate (18:1/16:0). Using metabolomic sequencing data and machine learning methods, key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy. The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

Metabolic plasma signatures in thoracic aortic aneurysm associated to tricuspid and bicuspid aortic valves

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Instituto de Salud Carlos III with co-funding from the ERDF and Comunidad de Madrid Background/Introduction Thoracic aortic aneurysm (TAA) develops asymptomatic with life-threatening consequences and its diagnosis is usually fortuitous. TAA is mostly idiopathic, although its prevalence is significantly higher in subjects with bicuspid aortic valve (BAV) for unknown reasons. We hypothesize that it is essential to investigate idiopathic TAA by differentiating between BAV and tricuspid aortic valve (TAV) patients for personalized diagnosis and treatment. Purpose We aimed to identify plasma metabolic profiles of aortic dilatation in idiopathic TAA, differentiating between subjects with BAV or TAV. Methods Plasma samples from 41 idiopathic TAA patients and 57 subjects without aortic dilatation (control, C) were collected and classified according to aortic valve type (BAV or TAV). Full metabolomics coverage was carried out by 1H RMN and LC-MS/MS untargeted analysis, including reverse phase and hydrophilic interaction chromatography and positive and negative electrospray ionization modes. Significant variation in metabolite levels were considered if FDR-adjusted p-value &amp;lt;0.05. Results Our analyses highlighted a metabolic signature specific for BAV and TAV subjects. BAV patients presented a marked glycerophospholipid metabolism alteration involving different lysophospholipids (LPAs, LPCs and LPEs) and phospholipids (PCs, PEs, PAs and PIs). Particularly, LPCs and LPEs were increased in BAV-TAA vs BAV-C, being an indicator of stimulation of glucose utilization through glycolysis and suppression of fatty acid biosynthesis. In contrast, carnitine-related metabolism was the most altered pathway observed in TAV subjects. In particular, we detected an increment in plasma acylcarnitines in TAV-TAA compared to TAV-C suggesting an altered β-oxidation of fatty acids and mitochondrial overload. Conclusions Idiopathic TAA development is differentially reflected in plasma from BAV and TAV patients, supporting an individualized diagnosis valve-dependent and suggesting also differential therapeutic targets.

Metabolomic and biochemical changes in the plasma and liver of toxic milk mice model of Wilson disease

Wilson disease (WD) is an inherited disorder characterized by abnormal copper metabolism with complex pathological features. Currently, this mechanism of copper overload-induced hepatic injury remains unclear. In this study, male toxic milk (TX) mice were selected as experimental subjects. Copper levels and biochemical indices were measured by atomic absorption spectroscopy (AAS) and kits. Liver tissue ultrastructure was observed by hematoxylin-eosin (H&E), sirius red staining and transmission electron microscopy. Plasma and liver metabolic profiles of TX mice were characterized by untargeted metabolomics. In addition, the expression of enzymes related to arachidonic acid metabolism in liver tissue was detected by Western blotting. The results showed the excessive copper content, concomitant oxidative stress, and hepatic tissue structural damage in TX mice. Seventy-eight metabolites were significantly different in WD, mainly involved in the metabolism of arachidonic acid, glycerophospholipids, sphingolipids, niacin and nicotinamide, and phenylalanine. Furthermore, the arachidonic acid metabolic pathway is an important pathway involved in WD metabolism. The level of arachidonic acid in the liver of TX mice was significantly lower (p < 0.01) compared to the control group. The expression of cytoplasmic phospholipase A2 (cPLA2) and arachidonic acid 12-lipoxygenase (ALOX12), related to the arachidonic acid metabolic pathway, was significantly different in the liver of TX mice (p < 0.01). Modulation of the arachidonic acid metabolic pathway could be a potential therapeutic strategy to alleviate WD symptoms.

Human-derived fecal microbiota transplantation alleviates social deficits of the BTBR mouse model of autism through a potential mechanism involving vitamin B6 metabolism.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by social communication deficiencies and stereotypic behaviors influenced by hereditary and/or environmental risk factors. There are currently no approved medications for treating the core symptoms of ASD. Human fecal microbiota transplantation (FMT) has emerged as a potential intervention to improve autistic symptoms, but the underlying mechanisms are not fully understood. In this study, we evaluated the effects of human-derived FMT on behavioral and multi-omics profiles of the BTBR mice, an established model for ASD. FMT effectively alleviated the social deficits in the BTBR mice and normalized their distinct plasma metabolic profile, notably reducing the elevated long-chain acylcarnitines. Integrative analysis linked these phenotypic changes to specific Bacteroides species and vitamin B6 metabolism. Indeed, vitamin B6 supplementation improved the social behaviors in BTBR mice. Collectively, these findings shed new light on the interplay between FMT and vitamin B6 metabolism and revealed a potential mechanism underlying the therapeutic role of FMT in ASD.IMPORTANCEAccumulating evidence supports the beneficial effects of human fecal microbiota transplantation (FMT) on symptoms associated with autism spectrum disorder (ASD). However, the precise mechanism by which FMT induces a shift in the microbiota and leads to symptom improvement remains incompletely understood. This study integrated data from colon-content metagenomics, colon-content metabolomics, and plasma metabolomics to investigate the effects of FMT treatment on the BTBR mouse model for ASD. The analysis linked the amelioration of social deficits following FMT treatment to the restoration of mitochondrial function and the modulation of vitamin B6 metabolism. Bacterial species and compounds with beneficial roles in vitamin B6 metabolism and mitochondrial function may further contribute to improving FMT products and designing novel therapies for ASD treatment.

Metabolic features of adolescent major depressive disorder: A comparative study between treatment-resistant depression and first-episode drug-naive depression

Major depressive disorder (MDD) is a psychiatric illness that can jeopardize the normal growth and development of adolescents. Approximately 40% of adolescent patients with MDD exhibit resistance to conventional antidepressants, leading to the development of Treatment-Resistant Depression (TRD). TRD is associated with severe impairments in social functioning and learning ability and an elevated risk of suicide, thereby imposing an additional societal burden. In this study, we conducted plasma metabolomic analysis on 53 adolescents diagnosed with first-episode drug-naïve MDD (FEDN-MDD), 53 adolescents with TRD, and 56 healthy controls (HCs) using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) and reversed-phase liquid chromatography-mass spectrometry (RPLC-MS). We established a diagnostic model by identifying differentially expressed metabolites and applying cluster analysis, metabolic pathway analysis, and multivariate linear support vector machine (SVM) algorithms. Our findings suggest that adolescent TRD shares similarities with FEDN-MDD in five amino acid metabolic pathways and exhibits distinct metabolic characteristics, particularly tyrosine and glycerophospholipid metabolism. Furthermore, through multivariate receiver operating characteristic (ROC) analysis, we optimized the area under the curve (AUC) and achieved the highest predictive accuracy, obtaining an AUC of 0.903 when comparing FEDN-MDD patients with HCs and an AUC of 0.968 when comparing TRD patients with HCs. This study provides new evidence for the identification of adolescent TRD and sheds light on different pathophysiologies by delineating the distinct plasma metabolic profiles of adolescent TRD and FEDN-MDD.

Study on plasma metabolomics profiling of depression in Chinese community-dwelling older adults based on untargeted LC/GC‒MS

Depression is a serious psychiatric illness that causes great inconvenience to the lives of elderly individuals. However, the diagnosis of depression is somewhat subjective. Nontargeted gas chromatography (GC)/liquid chromatography (LC)–mass spectrometry (MS) was used to study the plasma metabolic profile and identify objective markers for depression and metabolic pathway variation. We recruited 379 Chinese community-dwelling individuals aged ≥ 65. Plasma samples were collected and detected by GC/LC‒MS. Orthogonal partial least squares discriminant analysis and a heatmap were utilized to distinguish the metabolites. Receiver operating characteristic curves were constructed to evaluate the diagnostic value of these differential metabolites. Additionally, metabolic pathway enrichment was performed to reveal metabolic pathway variation. According to our standard, 49 people were included in the depression cohort (DC), and 49 people age- and sex-matched individuals were included in the non-depression cohort (NDC). 64 metabolites identified via GC‒MS and 73 metabolites identified via LC‒MS had significant contributions to the differentiation between the DC and NDC, with VIP values > 1 and p values < 0.05. Three substances were detected by both methods: hypoxanthine, phytosphingosine, and xanthine. Furthermore, 1-(sn-glycero-3-phospho)-1D-myo-inositol had the largest area under the curve (AUC) value (AUC = 0.842). The purine metabolic pathway is the most important change in metabolic pathways. These findings show that there were differences in plasma metabolites between the depression cohort and the non-depression cohort. These identified differential metabolites may be markers of depression and can be used to study the changes in depression metabolic pathways.

Abstract PO3-14-05: Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ Breast Cancer

Abstract Background: Neoadjuvant therapy (NAT) has become the standard treatment for early human epidermal growth factor receptor 2 positive (HER2+) breast cancer. For patients with HER2+ breast cancer, achieving a pathologic complete response (pCR) is highly indicative of their prognosis. However, not all HER2+ breast cancer patients could benefit from the NAT, about 40%-50% patients could not achieve pCR at surgery, even if they used the present standard neoadjuvant regime of TCbHP (taxane, carboplatin, trastuzumab and pertuzumab). This study was conducted to explore potential indicators associated with neoadjuvant efficacy of TCbHP in HER2+ breast cancer. Methods: Consecutive HER2+ breast cancer patients, who received and completed NAT with TCbHP regime and subsequent surgery at Chongqing University Cancer Hospital were prospectively enrolled. LC-MS and GC-MS platform-based untargeted metabolomics were performed to determine the metabolic profiles of plasma samples from these patients at different time points during treatment period. Random forest (RF) was used to establish predictive models based on pre-therapeutic metabolic traits. The potential monitors for the treatment response were obtained by time series analysis. Transcriptome analysis was performed in available samples to identify differentially expressed genes (DEGs) before treatment. qRT-pCR was used to detect DEGs in tastuzumab-sensitive and -resistant cell lines. Metabolic and transcriptomic data were integrated to explore substantially altered pathways that might be responsible for drug resistance. Results: From July 20, 2020 to May 28, 2021, a total of 40 HER2+ breast cancer patients with 120 plasma samples were eligible and recruited for this study. Of whom 21 (52.5%) patients achieved pCR and 19 (47.5%) achieved non-pCR, there are no significant difference in baseline clinicopathological features between pCR and non-pCR patients. There were significant differences in plasma metabolic profiles between non-pCR and pCR groups before and during treatment. A total of 100 differential metabolites were identified between pCR and non-pCR patients at pre-therapeutic period, which were markedly enriched in 40 metabolic pathways. Four key metabolites [sophorose, N-(2-acetamido)iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] were selected by RF analysis. The AUC value to discriminate pCR and non-PCR group to NAT of the single potential metabolite or combined panel of these metabolites were more than 0.910. 18 metabolites exhibit a potential for monitoring efficacy. Among 163 DEGs identified by RNA-seq, some genes might associate with trastuzumab resistance detected by qRT-PCR in cell lines. 39 altered pathways were found abnormally expressed at both the transcriptional and metabolic levels, including ABC transporters, protein digestion and absorption, mineral absorption, et al. Conclusion: By metabolomics analysis, we have both offered a road map of the molecular alterations underlying NAT of TCbHP regime in HER2+ breast cancer and a preliminary analysis of a unique metabolic signature that might be used to distinguish non-pCR from pCR patients. Metabolomics integrated with transcriptomics analysis could assist for gaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients. Citation Format: Ningning Zhang, Yuxin Huang, Guanwen Wang, Yimei Xiang, Zhouhong Jing, Junjie Zeng, Feng Yu, Xianjun Pan, Wenqi Zhou, Xiaohua Zeng. Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-05.

Comprehensive characterization of Epimedium-Rhizoma drynariae herb pair in rat plasma, urine, and feces metabolic profiles by UHPLC-Q-Orbitrap HRMS combined with diagnostic extraction strategy and multicomponent pharmacokinetic study by UHPLC-MS/MS.

Epimedium-Rhizoma drynariae (EP-RD) was a well-known herb commonly used to treat bone diseases in traditional Chinese medicine. Nevertheless, there was incomplete pharmacokinetic behavior, metabolic conversion and chemical characterization of EP-RD in vivo. Therefore, this study aimed to establish metabolic profiles combined with multicomponent pharmacokinetics to reveal the in vivo behavior of EP-RD. Firstly, the diagnostic product ions (DPIs) and neutral losses (NLs) filtering strategy combined with UHPLC-Q-Orbitrap HRMS for the in vitro chemical composition of EP-RD and metabolic profiles of plasma, urine, and feces after oral administration of EP-RD to rats were proposed to comprehensively characterize the 47 chemical compounds and the 97 exogenous in vivo (35 prototypes and 62 metabolites), and possible biotransformation pathways of EP-RD were proposed, which included phase I reactions such as hydrolysis, hydrogenation, dehydrogenation, hydroxylation, dehydroxylation, isomerization, and demethylation and phase II reactions such as glucuronidation, acetylation, methylation, and sulfation. Moreover, a UHPLC-MS/MS quantitative approach was established for the pharmacokinetic analysis of seven active components: magnoflorine, epimedin A, epimedin B, epimedin C, icariin, baohuoside II, and icariin II. Results indicated that the established method was reliably used for the quantitative study of plasma active ingredients after oral administration of EP-RD in rats. Compared to oral EP alone, the increase in area under curves and maximum plasma drug concentration (P < 0.05). This study increased the understanding of the material basis and biotransformation profiles of EP-RD in vivo, which was of great significance in exploring the pharmacological effects of EP-RD.