Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*

Sjogren's syndrome (SS) is a common autoimmune disorder that primarily targets exocrine glands, leading to hallmark manifestations of xerostomia and xerophthalmia, with potential progression to multisystem involvement. The rapid advances in omics technologies-including metabolomics, proteomics, and transcriptomics-have yielded substantial insights into SS pathophysiology. This review consolidates current evidence on omics-derived biomarkers in SS. Studies consistently implicate aberrant glucose metabolism, neutrophil-derived enzyme activity, mitochondrial bioenergetic impairment, ferroptosis, and apoptotic pathways as central to SS development. These findings refine our understanding of disease mechanisms and the heterogeneity of therapeutic responses. Hydroxyproline has emerged as a candidate marker for distinguishing SS from IgG4-related disease, whereas distinct cytokine and chemokine signatures may enable earlier diagnosis. Genomic analyses demonstrate a robust association between expression of the rs11797 locus and SS-related lymphomagenesis, and several genes controlling DNA methylation represent promising therapeutic targets. Collectively, these findings lay the groundwork for personalized risk stratification and intervention in SS. The review concludes by summarizing existing progress and outlining priorities for future omics-based investigations.
Humans ; Sjogren's Syndrome/diagnosis* ; Biomarkers/analysis* ; Metabolomics/methods* ; Proteomics/methods* ; Genomics ; Multiomics

OBJECTIVES: To investigate the targets and mechanisms of 7-hydroxyethyl chrysin (7-HEC) in prevention and treatment of high-altitude cerebral edema (HACE) in rats. METHODS: Fifty-four male Wistar rats were randomly divided into normal control group, HACE model group, and 7-HEC-treated group (18 rats in each group). Except for the normal control group, rats in the two other groups were exposed to a hypobaric hypoxic chamber simulating a 7000 m altitude for 72 h to establish the HACE model. The 7-HEC-treated group was intraperitoneally injected with 7-HEC (150 mg·kg^－¹·d^－¹) for 3 consecutive days before modeling, while the model group received equivalent isotonic sodium chloride solution. Tandem Mass Tag (TMT) proteomics technology was used to detect differentially expressed proteins (DEPs) with screening criteria set at a fold change >1.2 and P<0.05. Western blotting was used to verify the expression levels of target proteins. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. RESULTS: Compared with the normal control group, 256 DEPs were identified in the HACE model group. Compared with the HACE model group, 87 DEPs were identified in the 7-HEC-treated group. Among them, 19 DEPs that were dysregulated in the HACE model group were restored after 7-HEC intervention, of which seven (HSPA4, Arhgap20, SERT, HACL1, CCDC43, POLR3A, and PCBD1) were confirmed by Western blotting. GO enrichment analysis of the DEPs between the HACE model and 7-HEC-treated groups revealed their involvement in 13 biological processes, five cellular components, and two molecular functions. KEGG pathway analysis indicated associations with the mRNA surveillance pathway, Th17 cell differentiation, serotonergic synapse, RNA polymerase, protein processing in the endoplasmic reticulum, peroxisome, neuroactive ligand-receptor interaction, folate biosynthesis. PPI network analysis demonstrated that HSPA4, POLR3A, and HACL1, which were validated by Western blotting, interacted with multiple signaling pathways and ranked among the top 20 hub proteins by degree value, suggesting their potential role as core regulatory factors. Arhgap20, SERT and PCBD1 also exhibited interactions with several proteins, suggesting their potential as key regulatory proteins, whereas no interactions for CCDC43 were identified. CONCLUSIONS This study applied TMT proteomics to identify seven potential therapeutic targets of 7-HEC for the prevention and treatment of HACE. These targets may be involved in the pathogenesis of HACE through multiple pathways, including maintaining cellular homeostasis, ameliorating oxidative stress, regulating energy metabolism, and reducing vascular permeability.
Animals ; Male ; Proteomics/methods* ; Rats, Wistar ; Flavonoids/therapeutic use* ; Rats ; Brain Edema/etiology* ; Altitude Sickness/metabolism* ; Protein Interaction Maps

Saliva is an important body fluid in the oral cavity containing lots of biomarkers, whose inherent micro-ecosystem holds significant value for early diagnosis and monitoring of oral diseases. Simultaneously, saliva has particular advantages, such as ease of sampling, painless and non-invasive collection, and suitability for repeated sampling, making it highly appropriate for surveillance and follow-up of diseases. In a series of studies conducted by the research group for preventive dentistry in Peking University School and Hospital of Stomatology, we compared different segments of saliva and those samples collected via different sampling methods using proteomic/peptidomic and microbiomic technologies to explore the stability of saliva samples. Besides, the significance of applying representative salivary biomarkers in early prevention and control of representative oral diseases (e.g. dental caries, periodontal diseases) and systemic conditions (e.g. type 2 diabetes mellitus, chronic kidney disease) was confirmed as well.
Humans ; Saliva/chemistry* ; Dental Caries/diagnosis* ; Biomarkers/analysis* ; Periodontal Diseases/diagnosis* ; Mouth Diseases/diagnosis* ; Proteomics/methods* ; Diabetes Mellitus, Type 2/diagnosis* ; Microbiota ; Renal Insufficiency, Chronic/prevention & control*

Sini Decoction (SNT) is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold. However, elucidating the mechanism of action of SNT remains challenging due to its complex multiple components. This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE)-based drug affinity responsive target stability (DARTS) with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction. The analysis identified 590 proteins, with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group. Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments, the findings indicate that protein disulfide-isomerase A3 (PDIA3) may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
Myocardial Infarction/genetics* ; Proteomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Animals ; Protein Disulfide-Isomerases/genetics* ; Male ; Two-Dimensional Difference Gel Electrophoresis/methods* ; Humans ; Rats ; Rats, Sprague-Dawley ; Electrophoresis, Gel, Two-Dimensional

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recruited, and the high-quality serum proteome of the AYAs with tuberculosis was profiled by quantitative proteomics. The data of serum proteomics indicated that the relative abundance of hemoglobin and apolipoprotein was significantly reduced in the patients with active tuberculosis (ATB). The pathway enrichment analysis showed that the downregulated proteins in the ATB group were mainly involved in the antioxidant and cell detoxification pathways, indicating extensive oxidative stress damage. Random forest (RF) and extreme gradient boosting (XGBoost) were employed to evaluate protein importance, which yielded a set of candidate proteins that can distinguish between ATB and non-ATB. The analysis with the support vector machine algorithm (recursive feature elimination) suggested that the combination of apolipoprotein A-I (APOA1), hemoglobin subunit beta (HBB), and hemoglobin subunit alpha-1 (HBA1) had the highest accuracy and sensitivity in diagnosing ATB. Meanwhile, the levels of hemoglobin (HGB) and albumin (ALB) can be used as blood biochemical indicators to evaluate changes in the protein levels of APOA1 and HBB. This study established the serum proteome landscape of AYAs with tuberculosis and identified new biomarkers for the diagnosis of tuberculosis in this population.
Humans ; Proteomics/methods* ; Biomarkers/blood* ; Adolescent ; Young Adult ; Apolipoprotein A-I/blood* ; Machine Learning ; Tuberculosis/blood* ; Proteome/analysis* ; Male ; Hemoglobins/analysis* ; Female ; Blood Proteins/analysis* ; Adult

Schizophrenia is a severe psychiatric disorder with an unclear etiology and various clinical manifestations. The diagnosis and consequent treatment of schizophrenia mainly rely on clinical symptoms. Multiple risk sites associated with schizophrenia have been identified, yet objective indicators have not been found to facilitate clinical diagnosis and treatment of schizophrenia. The development of omics technology provides different perspectives on the etiology of schizophrenia and make the early identification, diagnosis and treatment of the disorder possible. This article summarizes the prevalence of schizophrenia, reviews the research results and shortcomings of transcriptomics and proteomics, as well as the latest achievements and prospects of multi-omics, aiming to reveal the use of omics in SZ, provide more comprehensive biological evidence to reveal the complex pathogenesis of schizophrenia and provide a theoretical basis for the early identification, accurate diagnosis, disease progression control, and prognosis improvement of schizophrenia.
Humans ; Proteomics/methods* ; Transcriptome ; Schizophrenia/genetics*

OBJECTIVES: To study the changes of protein levels in peripheral blood after it dried. METHODS: The proteins from whole blood and bloodstains were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and normalized by the label-free quantification (LFQ) method. The differential proteins were analyzed by using R 4.2.1 software, limma and edgeR package. The analysis of biological function, signaling pathway and subcellular localization for the differential proteins was then performed. RESULTS: A total of 623 and 596 proteins were detected in whole blood and bloodstains, respectively, of which 31 were statistically significant in the quantitative results, including 10 up-regulated and 21 down-regulated proteins in bloodstains. CONCLUSIONS The protein abundances in whole blood and bloodstains are highly correlated, and the variation of protein abundances may be related to the changes of endogenous and structural proteins in cells. The application of proteomics technology can assist the screening and identification of protein biomarkers, thereby introducing new biomarkers for forensic research.
Chromatography, Liquid/methods* ; Tandem Mass Spectrometry/methods* ; Proteomics/methods* ; Blood Stains ; Biomarkers

Schizophrenia is a severe psychiatric disorder with an unclear etiology and various clinical manifestations. The diagnosis and consequent treatment of schizophrenia mainly rely on clinical symptoms. Multiple risk sites associated with schizophrenia have been identified, yet objective indicators have not been found to facilitate clinical diagnosis and treatment of schizophrenia. The development of omics technology provides different perspectives on the etiology of schizophrenia and make the early identification, diagnosis and treatment of the disorder possible. This article summarizes the prevalence of schizophrenia, reviews the research results and shortcomings of transcriptomics and proteomics, as well as the latest achievements and prospects of multi-omics, aiming to reveal the use of omics in SZ, provide more comprehensive biological evidence to reveal the complex pathogenesis of schizophrenia and provide a theoretical basis for the early identification, accurate diagnosis, disease progression control, and prognosis improvement of schizophrenia.
Humans ; Proteomics/methods* ; Transcriptome ; Schizophrenia/genetics*