Objective To investigate the differential expression of related proteins in interosseous muscle tissue between patients with familial amyotrophic lateral sclerosis（FALS） and normal individuals in a family using the isobaric tags for relative and absolute quantitation （iTRAQ） technique， to identify the pathogenic proteins for this family， and to provide a basis for treatment. Methods Interosseous muscle tissue samples were collected from all subjects in this family， and the iTRAQ technique was used to perform qualitative and quantitative analyses for all proteins and obtain the expression profile of proteins in the disease group and the normal group. The bioinformatics methods were used to identify the proteins associated with the onset of FALS. A gene ontology（GO）analysis was performed for cell components， and a classification analysis was performed for related proteins. Results A total of 453 proteins were identified by mass spectrometry. The GO analysis obtained 14 differentially expressed proteins between the disease group and the normal group （P<0.05）， and compared with the normal group，the disease group had the low expression of 5 proteins （Ratio<1） and the high expression of 9 proteins （Ratio>1）. Conclusion This study identifies 8 proteins that are highly associated with FALS， i.e.， tripartite motif-containing protein 72， NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 1， annexin A1， decorin， glutathione peroxidase 3， collagen alpha-1 （Ⅻ） chain， collagen alpha-2 （Ⅰ） chain， and collagen type I alpha 1 isoform CRA-a. There are 6 proteins that might be associated with FALS， i.e.，26 S protease regulatory subunit 8， laminin subunit alpha-2，prolargin， fibrillin-1， myosin-8， and dermatopontin.
Proteomics

Objective To identify the differentially expressed proteins associated with cognitive impairment between the high-altitude population and the plain population， and to investigate the biological functions and signaling pathways of the differentially expressed proteins. Methods A total of 30 individuals living in the plain area （with an altitude of 400 m） and 30 individuals living in the high-altitude area （with an altitude of 3 960 m） were enrolled as plain group and high-altitude group， respectively， and general information was collected from all subjects. Montreal Cognitive Assessment （MoCA） was used to assess cognitive function. Blood samples were collected from each group， and the tims TOF Pro mass spectrometer was used to measure the serum levels of proteins after centrifugation. SPSS 25.0 was used for statistical analysis to investigate he association between proteomics and cognitive impairment. Results The results of MoCA assessment for both groups showed that the high-altitude group had a significantly lower MoCA score than the plain group， suggesting that there was significant cognitive impairment in the high-altitude group， with the main manifestation of impairment in visual space/executive ability， attention， delayed memory， and orientation. The proteomic analysis of serum samples from the subjects identified 169 differentially expressed proteins （84 upregulated proteins and 85 downregulated proteins）， among which 39 proteins were associated with cognitive impairment. The enrichment analysis of the differentially expressed proteins showed that these differentially expressed proteins were involved in the regulation of multiple signaling pathways and metabolic pathways. Conclusion Significant cognitive impairment is observed in the high-altitude population， and there are differentially expressed proteins associated with cognitive function between the high-altitude population and the plain population.
Proteomics

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.
Humans ; Proteome/metabolism* ; Proteomics ; Prospective Studies ; Obesity/genetics* ; Genomics ; Genome-Wide Association Study

BACKGROUND: Hair follicles are easily accessible and contain stem cells with different developmental origins, including mesenchymal stem cells (MSCs), that consequently reveal the potential of human hair follicle (hHF)-derived MSCs in repair and regeneration. However, the role of hHF-MSCs in Achilles tendinopathy (AT) remains unclear. The present study investigated the effects of hHF-MSCs on Achilles tendon repair in rabbits. METHODS: First, we extracted and characterized hHF-MSCs. Then, a rabbit tendinopathy model was constructed to analyze the ability of hHF-MSCs to promote repair in vivo . Anatomical observation and pathological and biomechanical analyses were performed to determine the effect of hHF-MSCs on AT, and quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay, and immunohistochemical staining were performed to explore the molecular mechanisms through which hHF-MSCs affects AT. Furthermore, statistical analyses were performed using independent sample t test, one-way analysis of variance (ANOVA), and one-way repeated measures multivariate ANOVA as appropriate. RESULTS: Flow cytometry, a trilineage-induced differentiation test, confirmed that hHF-derived stem cells were derived from MSCs. The effect of hHF-MSCs on AT revealed that the Achilles tendon was anatomically healthy, as well as the maximum load carried by the Achilles tendon and hydroxyproline proteomic levels were increased. Moreover, collagen I and III were upregulated in rabbit AT treated with hHF-MSCs (compared with AT group; P  < 0.05). Analysis of the molecular mechanisms revealed that hHF-MSCs promoted collagen fiber regeneration, possibly through Tenascin-C (TNC) upregulation and matrix metalloproteinase (MMP)-9 downregulation. CONCLUSIONS hHF-MSCs can be a treatment modality to promote AT repair in rabbits by upregulating collagen I and III. Further analysis revealed that treatment of AT using hHF-MSCs promoted the regeneration of collagen fiber, possibly because of upregulation of TNC and downregulation of MMP-9, thus suggesting that hHF-MSCs are more promising for AT.
Animals ; Humans ; Rabbits ; Hair Follicle ; Achilles Tendon/pathology* ; Tendinopathy/pathology* ; Proteomics ; Collagen Type I ; Mesenchymal Stem Cells

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*

Autism spectrum disorder (ASD) is one of the common neurodevelopmental disorders in children. Its etiology and pathogenesis are poorly understood. Previous studies have suggested potential changes in the complement and coagulation pathways in individuals with ASD. In this study, using multiple reactions monitoring proteomic technology, 16 of the 33 proteins involved in this pathway were identified as differentially-expressed proteins in plasma between children with ASD and controls. Among them, CFHR3, C4BPB, C4BPA, CFH, C9, SERPIND1, C8A, F9, and F11 were found to be altered in the plasma of children with ASD for the first time. SERPIND1 expression was positively correlated with the CARS score. Using the machine learning method, we obtained a panel composed of 12 differentially-expressed proteins with diagnostic potential for ASD. We also reviewed the proteins changed in this pathway in the brain and blood of patients with ASD. The complement and coagulation pathways may be activated in the peripheral blood of children with ASD and play a key role in the pathogenesis of ASD.
Child ; Humans ; Autism Spectrum Disorder/metabolism* ; Proteomics ; Brain/metabolism*

Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac®) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC's potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning.
Humans ; COVID-19 Vaccines ; Leukocytes, Mononuclear ; Proteomics ; COVID-19/prevention & control* ; Vaccination ; Antibodies ; Antibodies, Viral ; Antibodies, Neutralizing

BACKGROUND: Steroid receptor-associated and regulated protein (SRARP) suppresses tumor progression and modulates steroid receptor signaling by interacting with estrogen receptors and androgen receptors in breast cancer. In endometrial cancer (EC), progesterone receptor (PR) signaling is crucial for responsiveness to progestin therapy. The aim of this study was to investigate the role of SRARP in tumor progression and PR signaling in EC. METHODS: Ribonucleic acid sequencing data from the Cancer Genome Atlas, Clinical Proteomic Tumor Analysis Consortium, and Gene Expression Omnibus were used to analyze the clinical significance of SRARP and its correlation with PR expression in EC. The correlation between SRARP and PR expression was validated in EC samples obtained from Peking University People's Hospital. SRARP function was investigated by lentivirus-mediated overexpression in Ishikawa and HEC-50B cells. Cell Counting Kit-8 assays, cell cycle analyses, wound healing assays, and Transwell assays were used to evaluate cell proliferation, migration, and invasion. Western blotting and quantitative real-time polymerase chain reaction were used to evaluate gene expression. The effects of SRARP on the regulation of PR signaling were determined by co-immunoprecipitation, PR response element (PRE) luciferase reporter assay, and PR downstream gene detection. RESULTS: Higher SRARP expression was significantly associated with better overall survival and disease-free survival and less aggressive EC types. SRARP overexpression suppressed growth, migration, and invasion in EC cells, increased E-cadherin expression, and decreased N-cadherin and Wnt family member 7A ( WNT7A ) expression. SRARP expression was positively correlated with PR expression in EC tissues. In SRARP -overexpressing cells, PR isoform B (PRB) was upregulated and SRARP bound to PRB. Significant increases in PRE-based luciferase activity and expression levels of PR target genes were observed in response to medroxyprogesterone acetate. CONCLUSIONS This study illustrates that SRARP exerts a tumor-suppressive effect by inhibiting the epithelial-mesenchymal transition via Wnt signaling in EC. In addition, SRARP positively modulates PR expression and interacts with PR to regulate PR downstream target genes.
Female ; Humans ; Receptors, Progesterone/metabolism* ; Proteomics ; Cell Line, Tumor ; Endometrial Neoplasms/metabolism* ; Cell Proliferation/genetics* ; Luciferases/pharmacology* ; Gene Expression Regulation, Neoplastic/genetics*

Data-independent acquisition (DIA) is a high-throughput, unbiased mass spectrometry data acquisition method which has good quantitative reproducibility and is friendly to low-abundance proteins. It becomes the preferred choice for clinical proteomic studies especially for large cohort studies in recent years. The mass-spectrometry (MS)/MS spectra generated by DIA is usually heavily mixed with fragment ion information of multiple peptides, which makes the protein identification and quantification more difficult. Currently, DIA data analysis methods fall into two main categories, namely peptide-centric and spectrum-centric. The peptide-centric strategy is more sensitive for identification and more accurate for quantification. Thus, it has become the mainstream strategy for DIA data analysis, which includes four key steps: building a spectral library, extracting ion chromatogram, feature scoring and statistical quality control. This work reviews the peptide-centric DIA data analysis procedure, introduces the corresponding algorithms and software tools, and summarizes the improvements for the existing algorithms. Finally, the future development directions are discussed.
Humans ; Proteomics/methods* ; Reproducibility of Results ; Peptides/chemistry* ; Software ; Algorithms ; Tandem Mass Spectrometry/methods* ; Proteome/analysis*

Acute mountain sickness (AMS) is a clinical syndrome of multi-system physiological disorder after acute exposure to low pressure and low oxygen at high altitude. Quantitative proteomics can systematically quantify and describe protein composition and dynamic changes. In recent years, quantitative proteomics has been widely used in the prevention, diagnosis, treatment and pathogenesis of many diseases. This review summarizes the progress of quantitative proteomics techniques and its application in the prevention, diagnosis, treatment of AMS and mechanisms of rapidly acclimatizing to plateau, in order to provide a reference for the pathogenesis, early intervention, clinical treatment and proteomic research of AMS.
Humans ; Altitude Sickness/prevention & control* ; Proteomics ; Acute Disease ; Oxygen/metabolism*