Serum metabolism alteration behind different etiology, diagnosis, and prognosis of disorders of consciousness.

BACKGROUND: Patients with disorders of consciousness (DoC) exhibit varied revival outcomes based on different etiologies and diagnoses, the mechanisms of which remain largely unknown. The fluctuating clinical presentations in DoC pose challenges in accurately assessing consciousness levels and prognoses, often leading to misdiagnoses. There is an urgent need for a deeper understanding of the physiological changes in DoC and the development of objective diagnostic and prognostic biomarkers to improve treatment guidance. METHODS: To explore biomarkers and understand the biological processes, we conducted a comprehensive untargeted metabolomic analysis on serum samples from 48 patients with DoC. Patients were categorized based on etiology (TBI vs. non-TBI), CRS-R scores, and prognosis. Advanced analytical techniques, including PCA and OPLS-DA models, were employed to identify differential metabolites. RESULTS: Our analysis revealed a distinct separation in metabolomic profiles among the different groups. The primary differential metabolites distinguishing patients with varying etiologies were predominantly phospholipids, with a notable decrease in glycerophospholipids observed in the TBI group. Patients with higher CRS-R scores exhibited a pattern of impaired carbohydrate metabolism coupled with enhanced lipid metabolism. Notably, serum concentrations of both LysoPE and PE were reduced in patients with improved outcomes, suggesting their potential as prognostic biomarkers. CONCLUSIONS: Our study underscores the critical role of phospholipid metabolism in the brain's metabolic alterations in patients with DoC. It identifies key biomarkers for diagnosis and prognosis, offering insights that could lead to novel therapeutic targets. These findings highlight the value of metabolomic profiling in understanding and potentially treating DoC.

Characterization of the proteome of stable and unstable carotid atherosclerotic plaques using data-independent acquisition mass spectrometry.

BACKGROUND: Currently, noninvasive imaging techniques and circulating biomarkers are still insufficient to accurately assess carotid plaque stability, and an in-depth understanding of the molecular mechanisms that contribute to plaque instability is still lacking. METHODS: We established a clinical study cohort containing 182 patients with carotid artery stenosis. After screening, 39 stable and 49 unstable plaques were included in the discovery group, and quantitative proteomics analysis based on data independent acquisition was performed for these plaque samples. Additionally, 35 plaques were included in the validation group to validate the proteomics results by immunohistochemistry analysis. RESULTS: A total of 397 differentially expressed proteins were identified in stable and unstable plaques. These proteins are primarily involved in ferroptosis and lipid metabolism-related functions and pathways. Plaque validation results showed that ferroptosis- and lipid metabolism-related proteins had different expression trends in stable plaques versus unstable fibrous cap regions and lipid core regions. Ferroptosis- and lipid metabolism-related mechanisms in plaque stability were discussed. CONCLUSIONS: Our results may provide a valuable strategy for revealing the mechanisms affecting plaque stability and will facilitate the discovery of specific biomarkers to broaden the therapeutic scope.

LC-MS-based urine metabolomics analysis of chronic subdural hematoma for biomarker discovery.

BACKGROUND: Chronic subdural hematoma (CSDH) is one of the most common neurosurgical diseases with atypical manifestations. The aim of this study was to utilize urine metabolomics to explore potential biomarkers for the diagnosis and prognosis of CSDH. METHODS: Seventy-seven healthy controls and ninety-two patients with CSDH were enrolled in our study. In total, 261 urine samples divided into the discovery group and validation group were analyzed by LC-MS. The statistical analysis and functional annotation were applied to discover potential biomarker panels and altered metabolic pathways. RESULTS: A total of 53 differential metabolites were identified in this study. And the urinary metabolic profiles showed apparent separation between patients and controls. Further functional annotation showed that the differential metabolites were associated with lipid metabolism, fatty acid metabolism, amino acid metabolism, biotin metabolism, steroid hormone biosynthesis, and pentose and glucuronate interconversions. Moreover, one panel of Capryloylglycine, cis-5-Octenoic acid, Ethisterone, and 5,6-DiHETE showed good predictive performance in the diagnosis of CSDH, with an AUC of 0.89 in discovery group and an AUC of 0.822 in validation group. Another five metabolites (Trilobinol, 3'-Hydroxyropivacaine, Ethisterone, Arginyl-Proline, 5-alpha-Dihydrotestosterone glucuronide) showed the levels of them returned to a healthy state after surgery, showing good possibility to monitor the recovery of CSDH patients. CONCLUSION AND CLINICAL RELEVANCE: The findings of the study revealed urine metabolomic differences between CSDH and controls. The potentially diagnostic and prognostic biomarker panels of urine metabolites were established, and functional analysis demonstrated deeper metabolic disorders of CSDH, which might conduce to improve early diagnose of CSDH clinically.

Untargeted Metabolomic Analyses of Body Fluids to Differentiate TBI DOC and NTBI DOC.

OBJECTIVE: To investigate the metabolomic differences between Traumatic brain injury (TBI) disorder of consciousness (DOC) patients and non-traumatic brain injury (NTBI) DOC patients by using cerebrospinal fluid (CSF), serum and urine samples beneficial to understand the pathological mechanism differences between the two etiologies, provide potential clues for the subsequent treatment and prognosis, and investigate the metabolome differences and similarities between TBI and NTBI among three different body fluids. METHODS: In total, 24 TBI DOC subjects and 29 NTBI DOC subjects were enrolled. CSF, serum and urine samples from TBI DOC and NTBI DOC patients were collected and analyzed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarkers and altered metabolic functions. RESULTS: When comparing TBI DOC and NTBI DOC, 36, 31 and 52 differential metabolites were obtained in CSF, serum and urine, respectively. The functional analysis of differential metabolites obtained in CSF, serum and urine were all related to amino acid metabolism. Except for amino acid metabolism, metabolic biomarkers in CSF, serum and urine mainly focus on central function, cognitive function, necrosis and apoptosis and neurological function, respectively. In CSF, the highest AUC was 0.864 (Isoproturon) and 0.816 (Proline betaine). Then, the AUC of NFurfurylformamide in serum was 0.941, while the AUC of Dihydronepetalactone and Doxepin N-oxide glucuronide were 1.0 in urine. CONCLUSION: CSF, serum and urine metabolomic analyses could differentiate TBI DOC from NTBI DOC and functional analyses showed a metabolic change difference between TBI DOC and NTBI DOC.

Cerebrospinal fluid metabolite alterations in patients with different etiologies, diagnoses, and prognoses of disorders of consciousness.

INTRODUCTION: Medical management of disorders of consciousness (DoC) is a growing issue imposing a major burden on families and societies. Recovery rates vary widely among patients with DoC, and recovery predictions strongly influence decisions on medical care. However, the specific mechanisms underlying different etiologies, consciousness levels, and prognoses are still unclear. METHODS: We analyzed the comprehensive cerebrospinal fluid (CSF) metabolome through liquid chromatography-mass spectrometry. Metabolomic analyses were used to identify the metabolic differences between patients with different etiologies, diagnoses, and prognoses. RESULTS: We found that the CSF levels of multiple acylcarnitines were lower in patients with traumatic DoC, suggesting mitochondrial function preservation in the CNS, which might contribute to the better consciousness outcomes of these patients. Metabolites related to glutamate and GABA metabolism were altered and showed a good ability to distinguish the patients in the minimally conscious state and the vegetative state. Moreover, we identified 8 phospholipids as potential biomarkers to predict the recovery of consciousness. CONCLUSIONS: Our findings shed light on the differences in physiological activities underlying DoC with different etiologies and identified some potential biomarkers used for DoC diagnosis and prognosis.

Susceptibility to preoperative seizures in glioma patients with elevated homocysteine levels.

OBJECTIVE: Seizures are a common clinical presentation in patients with glioma and substantially impact patients' quality of life. Hyperhomocysteinemia is defined as abnormally high serum levels of homocysteine (Hcy) and is reportedly linked to susceptibility to various nervous system diseases. However, it remains unclear whether and how hyperhomocysteinemia and its associated genetic polymorphisms promote seizures in glioma patients. METHODS: We retrospectively reviewed all medical data from 127 patients with malignant gliomas, who underwent initial tumor resection by our team between July 2019 and June 2021 and had preoperative measurements of serum Hcy levels. According to whether they had at least one seizure before surgery, they were divided into the seizure and nonseizure groups. We also detected polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene and measured intratumoral Hcy levels in these patients. RESULTS: Hyperhomocysteinemia was a susceptibility factor for preoperative seizures in glioma patients according to both univariate analyses (P < 0.001) and multivariate logistic regression analyses (OR 1.239, 95% CI 1.062-1.445, P = 0.007). Patients with the MTHFR C677T variant exhibited elevated serum Hcy levels (P = 0.027) and an increased prevalence of preoperative seizures (P = 0.019). Intratumoral Hcy levels were positively correlated with serum Hcy levels (R = 0.231, P = 0.046) and were elevated in patients with hyperhomocysteinemia (P = 0.031), the MTHFR C677T variant (P = 0.002) and preoperative seizures (P = 0.003). High intratumoral Hcy levels, rather than hyperhomocysteinemia or the MTHFR C677T variant, emerged as an independent risk factor for preoperative seizures (OR 1.303, 95% CI 1.015-1.673, P = 0.038). Furthermore, the effects of hyperhomocysteinemia on epileptic susceptibility were reduced to nonsignificance when intratumoral Hcy was controlled to the same level between groups. SIGNIFICANCE: Glioma patients with hyperhomocysteinemia and the MTHFR C677T variant were susceptible to preoperative seizures, suggesting their potential as biomarkers for the management of seizures in glioma patients. The elevation of intratumoral Hcy is a possible mechanism underlying this susceptibility.

Metaproteomics Characterizes the Human Gingival Crevicular Fluid Microbiome Function in Periodontitis.

Periodontitis is the leading cause of tooth loss in adults worldwide. The human proteome and metaproteome characterization of periodontitis is not clearly understood. Gingival crevicular fluid samples were collected from eight periodontitis and eight healthy subjects. Both the human and microbial proteins were characterized by liquid chromatography coupled with high-resolution mass spectrometry. A total of 570 human proteins were found differentially expressed, which were primarily associated with inflammatory response, cell death, cellular junction, and fatty acid metabolism. For the metaproteome, 51 genera were identified, and 10 genera were found highly expressed in periodontitis, while 11 genera were downregulated. The analysis showed that microbial proteins related to butyrate metabolism were upregulated in periodontitis cases. In particular, correlation analysis showed that the expression of host proteins related to inflammatory response, cell death, cellular junction, and lipid metabolism correlates with the alteration of metaproteins, which reflect the changes of molecular function during the occurrence of periodontitis. This study showed that the gingival crevicular fluid human proteome and metaproteome could reflect the characteristics of periodontitis. This might benefit the understanding of the periodontitis mechanism.

Blood- and Urine-Based Liquid Biopsy for Early-Stage Cancer Investigation: Taken Clear Renal Cell Carcinoma as a Model.

Liquid biopsy is a noninvasive technique that can provide valuable information for disease characterization by using biofluids as a source of biomarkers. Proteins found in biofluids can offer a wealth of information for understanding pathological processes. In this study, we used early-stage clear cell renal cell carcinoma (ccRCC) as a model to explore the proteomic relationships among tissue, plasma, and urine. We analyzed samples of tumor tissue, plasma, and urine from a cohort of 27 ccRCC patients with T1-2 stage and 27 matched healthy controls, using liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis. We integrated the differential proteins found in the three types of samples to explore ccRCC-associated molecular changes. Our results showed that both plasma and urine proteomes could reflect functional changes in tumor tissue. In plasma, cytoskeletal proteins and metabolic enzymes were differentially expressed, while in urine, adhesion molecules and defense proteins showed differential levels. The differential proteins found in plasma and urine both reflect the binding and catalytic activity of tumor tissue. Additionally, proteins only changed in biofluids could reflect body immune response changes, with plasma proteins involved in actin cytoskeleton and oxidative stress, and urine proteins involved in granulocyte adhesion and leukocyte extravasation signaling. Plasma and urine proteins could effectively distinguish RCC from control, with good performances (plasma/urine: 92.6%/92.6% specificity, 96.3%/92.6% sensitivity, and an area under the curve of 0.981/0.97). In conclusion, biofluids could not only reflect functional changes in tumor tissue but also reflect changes in the body's immune response. These findings will benefit the understanding of body biomarkers in tumors and the discovery of potential disease biomarkers.

Clinical and Proteomic-Based Molecular Characterizations of Invasive and Noninvasive Somatotroph PitNETs.

INTRODUCTION: Somatotroph pituitary neuroendocrine tumours (PitNETs) are characterized by complex and variable biological behaviours with unpredictable patterns of growth and invasiveness. The molecular mechanisms and reliable predictors of biological markers of invasiveness remain unknown. METHODS: Seventy-two acromegaly patients were consecutively enrolled. Data-independent acquisition-based proteomics and ingenuity pathway analysis were conducted between invasive and noninvasive somatotroph PitNETs. The expression of selected biomarkers was verified in PitNET tissue, and its correlation with various clinical indicators and outcomes of these tumours was assessed. The invasive phenotypes of GH3 cells were validated in vitro. RESULTS: Patients with invasive somatotroph PitNETs were significantly younger at onset and diagnosis, with significantly higher secretion and faster growth and a lower long-term biochemical response rate than patients with noninvasive somatotroph PitNETs. Proteomic data were evaluated in a consecutively collected sample of 19 (10 invasive and 9 noninvasive somatotroph PitNETs) tumours and indicated a distinct proteomic pattern. The enriched and important pathways included IL-4, PDGF, PTEN, VEGF, PI3K/AKT, FAK, and other pathways that were significantly associated with tumour proliferation, migration, and invasion. High cathepsin Z (CTSZ) expression was found in invasive somatotroph PitNETs and significantly positively correlated with parameters of tumour invasion and growth. In Ctsz-overexpressing GH3 cells, cell proliferation, invasion, and migration were consequently increased. CONCLUSION: It is more difficult for patients with invasive somatotroph PitNETs to achieve remission than those with noninvasive somatotroph PitNETs, and proteomic data analysis has revealed the high expression of CTSZ as a contributing factor to invasive transformation and poor prognosis in somatotroph PitNETs for the first time.

Urinary complement proteins in IgA nephropathy progression from a relative quantitative proteomic analysis.

Aim: IgA nephropathy (IgAN) is one of the leading causes of end-stage renal disease (ESRD). Urine testing is a non-invasive way to track the biomarkers used for measuring renal injury. This study aimed to analyse urinary complement proteins during IgAN progression using quantitative proteomics. Methods: In the discovery phase, we analysed 22 IgAN patients who were divided into three groups (IgAN 1-3) according to their estimated glomerular filtration rate (eGFR). Eight patients with primary membranous nephropathy (pMN) were used as controls. Isobaric tags for relative and absolute quantitation (iTRAQ) labelling, coupled with liquid chromatography-tandem mass spectrometry, was used to analyse global urinary protein expression. In the validation phase, western blotting and parallel reaction monitoring (PRM) were used to verify the iTRAQ results in an independent cohort (N = 64). Results: In the discovery phase, 747 proteins were identified in the urine of IgAN and pMN patients. There were different urine protein profiles in IgAN and pMN patients, and the bioinformatics analysis revealed that the complement and coagulation pathways were most activated. We identified a total of 27 urinary complement proteins related to IgAN. The relative abundance of C3, the membrane attack complex (MAC), the complement regulatory proteins of the alternative pathway (AP), and MBL (mannose-binding lectin) and MASP1 (MBL associated serine protease 2) in the lectin pathway (LP) increased during IgAN progression. This was especially true for MAC, which was found to be involved prominently in disease progression. Alpha-N-acetylglucosaminidase (NAGLU) and α-galactosidase A (GLA) were validated by western blot and the results were consistent with the iTRAQ results. Ten proteins were validated in a PRM analysis, and these results were also consistent with the iTRAQ results. Complement factor B (CFB) and complement component C8 alpha chain (C8A) both increased with the progression of IgAN. The combination of CFB and mucosal addressin cell adhesion molecule-1 (MAdCAM-1) also showed potential as a urinary biomarker for monitoring IgAN development. Conclusion: There were abundant complement components in the urine of IgAN patients, indicating that the activation of AP and LP is involved in IgAN progression. Urinary complement proteins may be used as biomarkers for evaluating IgAN progression in the future.

A Comprehensive 2D-LC/MS/MS Profile of the Normal Human Urinary Metabolome.

Profiling bodily fluids is crucial for monitoring and discovering metabolic markers of disease. In this study, a comprehensive analysis approach based on 1D-LC-MS/MS and 2D-LC-MS/MS was applied to profile normal human urine metabolites from 348 children and 315 adults. A total of 2357 metabolites were identified, including 1831 endogenous metabolites and 526 exogenous ones. In total, 1005 metabolites were identified in urine for the first time. The urinary metabolites were mainly involved in amino acid metabolism, small molecule biochemistry, lipid metabolism and cellular compromise. The comparison of adult's and children's urine metabolomes showed adults urine had more metabolites involved in immune response than children's, but the function of binding of melatonin, which belongs to the endocrine system, showed a higher expression in children. The urine metabolites detected by the 1D-LC-MS/MS method were mainly related to amino acid metabolism and lipid metabolism, and the 2D-LC-MS/MS method not only explored metabolites from 1D-LC-MS/MS but also metabolites related to cell signaling, cell function and maintenance, etc. Our analysis comprehensively profiled and functionally annotated the metabolome of normal human urine, which would benefit the application of urinary metabolome to clinical research.

Urinary proteomic analysis during pregnancy and its potential application in early prediction of gestational diabetes mellitus and spontaneous abortion.

Background: The maternal physiological changes which occur during gestation are complex and affect diverse systems in the body. Elucidating the various changes that occur during pregnancy may assist with understanding maternal health and the factors affecting pregnancy outcomes. Methods: A longitudinal cohort of 84 pregnant women was established. The urinary proteomes of women in different trimesters of pregnancy (6-8, 22-24, and 32-34 weeks) were characterized using data-independent acquisition tandem mass spectrometry. Gestational diabetes mellitus (GDM) was diagnosed at 24 to 28 weeks. Functional analysis of serial changed proteins was performed. Results: Fifteen women had GDM, 50 were healthy, and 19 experienced spontaneous abortion (SA). Functional analysis showed that the urinary proteome reflected physiological and pathological changes during pregnancy. Compared to those of women with a normal pregnancy, the urinary proteomes of women with GDM and SA showed significant disease-related changes in insulin secretion and estrogen receptor activity, respectively, during the first trimester. Urinary protein during the first trimester of pregnancy achieved an area under the curve of 0.91 and 0.81 for GDM and SA, respectively. Conclusions: The urinary proteome has the potential to reflect serial changes of pregnancy progression; therefore, its use might facilitate early diagnosis of pregnancy complications.

Proteomic and Metabolomic Analyses of Right Ventricular Failure due to Pulmonary Arterial Hypertension.

Right ventricular failure (RVF) is the independent and strongest predictor of mortality in pulmonary arterial hypertension (PAH), but, at present, there are no preventive and therapeutic strategies directly targeting the failing right ventricle (RV). The underlying mechanism of RV hypertrophy (RVH) and dysfunction needs to be explored in depth. In this study, we used myocardial proteomics combined with metabolomics to elucidate potential pathophysiological changes of RV remodeling in a monocrotaline (MCT)-induced PAH rat model. The proteins and metabolites extracted from the RV myocardium were identified using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). The bioinformatic analysis indicated that elevated intracellular Ca2+ concentrations and inflammation may contribute to myocardial proliferation and contraction, which may be beneficial for maintaining the compensated state of the RV. In the RVF stage, ferroptosis, mitochondrial metabolic shift, and insulin resistance are significantly involved. Dysregulated iron homeostasis, glutathione metabolism, and lipid peroxidation related to ferroptosis may contribute to RV decompensation. In conclusion, we depicted a proteomic and metabolomic profile of the RV myocardium during the progression of MCT-induced PAH, and also provided the insights for potential therapeutic targets facilitating the retardation or reversal of RV dysfunction in PAH.

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD).

Objectives: Knowledge of the urinary metabolomic profiles of healthy children and adolescents plays a promising role in the field of pediatrics. Metabolomics has also been used to diagnose disease, discover novel biomarkers, and elucidate pathophysiological pathways. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. However, large-sample urinary metabolomic studies in children with ADHD are relatively rare. In this study, we aimed to identify specific biomarkers for ADHD diagnosis in children and adolescents by urinary metabolomic profiling. Methods: We explored the urine metabolome in 363 healthy children aged 1-18 years and 76 patients with ADHD using high-resolution mass spectrometry. Results: Metabolic pathways, such as arachidonic acid metabolism, steroid hormone biosynthesis, and catecholamine biosynthesis, were found to be related to sex and age in healthy children. The urinary metabolites displaying the largest differences between patients with ADHD and healthy controls belonged to the tyrosine, leucine, and fatty acid metabolic pathways. A metabolite panel consisting of FAPy-adenine, 3-methylazelaic acid, and phenylacetylglutamine was discovered to have good predictive ability for ADHD, with a receiver operating characteristic area under the curve (ROC-AUC) of 0.918. A panel of FAPy-adenine, N-acetylaspartylglutamic acid, dopamine 4-sulfate, aminocaproic acid, and asparaginyl-leucine was used to establish a robust model for ADHD comorbid tic disorders and controls with an AUC of 0.918.

Characterization of LC-MS based urine metabolomics in healthy children and adults.

Previous studies reported that sex and age could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive lifespan characterization of urine metabolomics in a cohort of 348 healthy children and 315 adults, aged 1 to 78 years, using liquid chromatography coupled with high resolution mass spectrometry. Our results suggest that sex-dependent urine metabolites are much greater in adults than in children. The pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the geriatric stage. Based on the above analysis, metabolomic characteristics of each age stage were provided. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery.

Noninvasive urinary protein signatures associated with colorectal cancer diagnosis and metastasis.

Currently, imaging, fecal immunochemical tests (FITs) and serum carcinoembryonic antigen (CEA) tests are not adequate for the early detection and evaluation of metastasis and recurrence in colorectal cancer (CRC). To comprehensively identify and validate more accurate noninvasive biomarkers in urine, we implement a staged discovery-verification-validation pipeline in 657 urine and 993 tissue samples from healthy controls and CRC patients with a distinct metastatic risk. The generated diagnostic signature combined with the FIT test reveals a significantly increased sensitivity (+21.2% in the training set, +43.7% in the validation set) compared to FIT alone. Moreover, the generated metastatic signature for risk stratification correctly predicts over 50% of CEA-negative metastatic patients. The tissue validation shows that elevated urinary protein biomarkers reflect their alterations in tissue. Here, we show promising urinary protein signatures and provide potential interventional targets to reliably detect CRC, although further multi-center external validation is needed to generalize the findings.

Diagnostic Potential of Plasma IgA1 O-Glycans in Discriminating IgA Nephropathy From Other Glomerular Diseases and Healthy Participants.

Background: Aberrant O-glycosylation of IgA1 plays an important role in IgA nephropathy pathogenesis. Previous proteomic studies analyzed O-glycans of the circulating IgA1 hinge region and found that the N-acetylgalactosamine (GalNAc) and galactose numbers in the hinge region of IgA1 of patients with IgA nephropathy were lower than those in healthy participants. However, the diagnostic performance of the O-glycosylation traits in the hinge region of plasma IgA1 for IgA nephropathy remains unelucidated. The present study aimed to determine the difference in plasma IgA1 hinge region O-glycoforms among IgA nephropathy, non-IgA nephropathy disease controls, and healthy participants, and to further evaluate the diagnostic performance of plasma IgA1 glycosylation traits. Methods: Sixty-two patients with biopsy-proven primary IgA nephropathy, 30 age- and sex-matched non-IgA nephropathy disease controls (10 patients with membranous nephropathy, 10 with focal segmental glomerulosclerosis, and 10 with minimal change disease), and 30 healthy participants were prospectively recruited. Plasma galactose deficient-IgA1 levels were measured using a KM55 kit. Plasma IgA was extracted using IgA immunoaffinity beads. After de-N-glycosylation, reduction, alkylation, trypsin digestion, and O-glycopeptide enrichment via hydrophilic interaction liquid chromatography, liquid chromatography tandem mass spectrometry (LC-MS/MS) was applied to analyze the IgA1 O-glycosylation patterns and we derived the plasma IgA1 O-glycosylation traits. Results: Plasma IgA1 O-glycosylation patterns were significantly changed in IgA nephropathy patients compared to those with non-IgA nephropathy disease controls and healthy participants. The GalNAc number was lowest in IgA nephropathy patients. In addition, a similar result was observed for the galactose number in the IgA1 hinge region. These values showed moderate potential for discriminating between IgA nephropathy and the controls. When these values were combined, the area under the curve increased compared to when they were considered individually. When further adding a clinical indicator, the area under the curve of the GalNAc-galactose-IgA panel exceed 0.9 in discriminating IgA nephropathy from the controls. Conclusion: The amount of GalNAc and galactose in plasma IgA1 hinge region identified by glycoproteomics could be used as a diagnostic biomarker for IgA nephropathy. The panel containing GalNAc, galactose, and circulating IgA displayed excellent diagnostic performance and is promising for practical clinical applications.

Evaluation of machine learning models on protein level inference from prioritized RNA features.

The parallel measurement of transcriptome and proteome revealed unmatched profiles. Since proteomic analysis is more expensive and challenging than transcriptomic analysis, the question of how to use messenger RNA (mRNA) expression data to predict protein level is extremely important. Here, we comprehensively evaluated 13 machine learning models on inferring protein expression levels using RNA expression profile. A total of 20 proteogenomic datasets from three mainstream proteomic platforms with >2500 samples of 13 human tissues were collected for model evaluation. Our results highlighted that the appropriate feature selection methods combined with classical machine learning models could achieve excellent predictive performance. The voting ensemble model outperformed other candidate models across datasets. Adding the mRNA proxy model to the regression model further improved the prediction performance. The dataset and gene characteristics could affect the prediction performance. Finally, we applied the model to the brain transcriptome of cerebral cortex regions to infer the protein profile for better understanding the functional characteristics of the brain regions. This benchmarking work not only provides useful hints on the inherent correlation between transcriptome and proteome, but also has practical value of the transcriptome-based prediction of protein expression levels.

A Probe into the Intervention Mechanism of Yiqi Huayu Jiedu Decoction on TLR4/NLRP3 Signal Pathway in Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome (ARDS) Rats.

BACKGROUND: This study discusses the anti-inflammatory mechanism of Yiqi Huayu Jiedu decoction (YQHYJD) and studies the intervening effect of YQHYJD on the inflammatory cytokines in acute respiratory distress syndrome (ARDS) rats by inhibiting the TLR4/NLRP3 signal pathway. The aim of the probe is to provide evidence to support the identification of therapeutic targets in Chinese medicine treatment, which broadens the alternatives for the treatment of ARDS. METHOD: A lipopolysaccharide (LPS)-induced ARDS model group is established on rats by tail vein injection. A medicine group is established on ARDS rats by prophylactic administration using YQHYJD. Materials are collected, and tests are conducted according to experimental processes. RESULT: The rats in the medicine group gained weight compared with those in the ARDS model group. Pathological sections from the medicine group indicated improved condition in terms of pulmonary and interstitial edema in the lung tissues of rats compared with that from the ARDS model group. The percentage of neutrophil of the medicine group was significantly brought down compared with that of the ARDS model group (P < 0.001). Enzyme-linked immunosorbent assay (ELISA) was used to detect the changes in the level of inflammatory cytokines. It was observed that the levels of IL-1ß and IL-18 in serum of the medicine group significantly decreased (P < 0.001 and P < 0.01), the contents of TLR4 and NLRP3 in bronchoalveolar lavage fluid (BALF) of the medicine group decreased, and the contents of TLR4 and NLRP3 in lung tissue homogenate of the medicine group significantly decreased (P < 0.05, P < 0.001, P < 0.01, and P < 0.05). In further mass spectrum identification of the proteins from the same animal groups, it was observed that the expressions of inflammatory proteins TNFRSF1, LBP, and NOS2 of the medicine group were reduced. The differences were statistically significant. CONCLUSIONS: The pharmacological action of YQHYJD's anti-inflammatory mechanism is closely associated with the regulation of inflammatory cytokines TLR4, NLRP3, IL-1ß, IL-18, TNFRSF1, LBP, and NOS2 on the TLR4/NLRP3 signal pathway.

96DRA-Urine: A high throughput sample preparation method for urinary proteome analysis.

Mass spectrometry (MS)-based urinary proteomics is increasingly used for clinical research. A critical step in urinary proteomic analysis comprises the implementation of a reliable sample preparation method with high yields of peptides and proteins. In this study, we developed a urinary sample preparation method, DRA-Urine (Direct reduction/alkylation in urine), which urinary proteins were directly reduced/alkylated in urine, and then precipitated by acetone, washed and digestion on an ultrafilter unit. The qualitative and quantitative comparison of different urinary sample preparation methods (in-solution methods and ultrafilter-assisted methods) showed that DRA-Urine could achieve better results. Adapting DRA-Urine protocol to a 96-well format, namely 96DRA-Urine, shortened the time for buffer change and improved sample preparation throughput. The results showed that 96DRA-Urine displayed similar proteomic performance to DRA-Urine. Finally, the 96DRA-Urine method was used in a label-free, small pilot biomarker discovery analysis for differential urinary proteome analysisof bladder cancer urine. The results showed that urinary proteins could differentiate bladder cancer (BCa) patients from healthy controls and distinguish high-grade BCa from low-grade BCa with area under the curve (AUC) values of 0.972 and 0.847, respectively. Consequently, the 96DRA-Urine method might be a high-throughput method for preparing body fluid samples used in clinical research but needs to be further verified.