Inter-alpha-trypsin Inhibitor Heavy Chain H4 Research Articles

Inter-alpha-trypsin inhibitor heavy chain H3 is a potential biomarker for disease activity in myasthenia gravis

Myasthenia gravis is a chronic antibody-mediated autoimmune disease disrupting neuromuscular synaptic transmission. Informative biomarkers remain an unmet need to stratify patients with active disease requiring intensified monitoring and therapy; their identification is the primary objective of this study. We applied mass spectrometry-based proteomic serum profiling for biomarker discovery. We studied an exploration and a prospective validation cohort consisting of 114 and 140 anti-acetylcholine receptor antibody (AChR-Ab)-positive myasthenia gravis patients, respectively. For downstream analysis, we applied a machine learning approach. Protein expression levels were confirmed by ELISA and compared to other myasthenic cohorts, in addition to myositis and neuropathy patients. Anti-AChR-Ab levels were determined by a radio receptor assay. Immunohistochemistry and immunofluorescence of intercostal muscle biopsies were employed for validation in addition to interactome studies of inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3). Machine learning identified ITIH3 as potential serum biomarker reflective of disease activity. Serum levels correlated with disease activity scores in the exploration and validation cohort and were confirmed by ELISA. Lack of correlation between anti-AChR-Ab levels and clinical scores underlined the need for biomarkers. In a subgroup analysis, ITIH3 was indicative of treatment responses. Immunostaining of muscle specimens from these patients demonstrated ITIH3 localization at the neuromuscular endplates in myasthenia gravis but not in controls, thus providing a structural equivalent for our serological findings. Immunoprecipitation of ITIH3 and subsequent proteomics lead to identification of its interaction partners playing crucial roles in neuromuscular transmission. This study provides data on ITIH3 as a potential pathophysiological-relevant biomarker of disease activity in myasthenia gravis. Future studies are required to facilitate translation into clinical practice.

SERPINA3, FGA, AGP1, ITIH3 and SAA1 as novel biomarkers for eosinophilic granulomatosis with polyangiitis diagnosis and activity assessment.

To identify novel biomarkers for diagnosis and prediction of active eosinophilic granulomatosis with polyangiitis (EGPA) through data-independent acquisition (DIA) analysis. Plasma from 11 EGPA patients and 10 healthy controls (HCs) were analyzed through DIA to identify potential biomarkers. The results were validated in 32 EGPA patients, 24 disease controls (DCs), and 20 HCs using enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve was used to assess the diagnostic value of candidate biomarkers. Thirty-five differentially expressed proteins (DEPs) (24 upregulated and 11 downregulated) were screened between EGPA and HC groups. Five proteins, including serine proteinase inhibitor A3 (SERPINA3), alpha-fibrinogen (FGA), alpha-1 acid glycoprotein 1(AGP1), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), and serum amyloid A1 (SAA1), were significantly upregulated in EGPA compared with HCs. Apart from SAA1, all proteins were also higher in EGPA patients compared with DCs. Furthermore, a panel of SERPINA3 and SAA1 exhibited potential diagnostic value for EGPA with an area under the curve (AUC) of 0.953, while a panel of SERPINA3, FGA, AGP1, and ITIH3 showed good discriminative power to differentiate EGPA from DCs with AUC of 0.926. Moreover, SERPINA3, FGA, and AGP levels were significantly higher in active EGPA and correlated well with disease activity. A combination of SERPINA3 and AGP1 exhibited an excellent AUC of 0.918 for disease activity assessment. SERPINA3, FGA, AGP1, ITIH3 and SAA1 were identified as potential biomarkers for EGPA diagnosis and disease activity assessment. Among them, as a single biomarker, SERPINA3 has the best diagnostic performance.

Secreted proteins in plasma and placenta as novel non-invasive biomarkers for intrahepatic cholestasis of pregnancy: A case-control study

BackgroundIntrahepatic cholestasis of pregnancy (ICP) is likely to lead to unfavorable consequences. Total bile acid (TBA) is thought to be the sole ICP indicator available as of now, but it comes with some kind of restrictions in terms of sensitivity and specificity. We were endeavoring to find potential diagnostic biomarkers for ICP in this investigation. MethodsThis case-control study with a prospective nature included 40 females in the stage of pregnancy who were diagnosed with ICP. It also included another 20 females who were also pregnant but with sound physical condition(control). Placental and plasma samples were collected from all females that were in the stage of pregnancy, except for 20 ICP patients, in which only plasma was collected. We used four-dimensional data-independent acquisition followed by enzyme-linked immunosorbent assay and immunohistochemistry to identify and validate plasma and placental profiles in ICP patients and controls. Bioinformatics was adopted in an effort to demonstrate the relevant biological processes and signalling pathways. Correlation analysis was used to analyse the consistency of tissue and plasma protein expression and the correlation between sequencing and experimental results. ResultsThe expression levels of nectin-1 (NECTIN1), Kunitz-type protease inhibitor 1 (SPINT1), and inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) were remarkably higher in ICP patients than in controls. However, heparin cofactor 2 (SERPIND1) expression levels in female participants in the stage of pregnancy who were diagnosed with ICP were remarkably lower than those pregnant females with good physical fitness. In addition to the negative correlation between SERPIND1 and TBA, NECTIN1, SPINT1, and ITIH3 expression positively correlated with TBA. Area under the receiver operating characteristic curve (AUC) values of 0.7925, 0.8313, 0.8163, and 0.9025, respectively, were used to assess the diagnostic accuracies of NECTIN1, SPINT1, ITIH3, and SERPIND1. AUC (0.9438) was considerably greater when NECTIN1, SPINT1, and SERPIND1 were integrated, according to binary logistic regression. The AUC of the ROC curve for various combinations of SERPIND1 and other indicators was higher than itself, thus providing a more reliable ICP diagnosis. Furthermore, according to the bioinformatics analysis, the NECTIN1, SPINT1, ITIH3, and SERPIND1 were identified as secreted proteins because they were localized in the extracellular region. ConclusionsThis research discovered new non-invasive ICP indicators. On top of this, it sheds new light on the crucial diagnostic function of secreted proteins in ICP.

Longitudinal change of serum inter-alpha-trypsin inhibitor heavy chain H4, and its correlation with inflammation, multiorgan injury, and death risk in sepsis.

Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) inhibits infection-induced inflammation and multiorgan injury through several methods. The present study aimed to estimate the association of serum ITIH4 with inflammatory cytokines, multiorgan injury, and death risk in sepsis patients. Serum samples were collected to detect ITIH4 by enzyme-linked immunosorbent assay in 127 sepsis patients at admission (baseline), day (D)1, D3, and D7 after admission, as well as in 30 healthy controls (HCs). Additionally, 28-day mortality was recorded in sepsis patients. ITIH4 was reduced in sepsis patients versus HCs (median [interquartile range]: 147.9 [78.2-208.8] vs. 318.8 [237.2-511.4] ng/ml) (p < 0.001). In sepsis patients, ITIH4 was associated with the absence of cardiovascular and cerebrovascular disease history (p=0.021). Additionally, ITIH4 was negatively correlated with tumor necrosis factor-α (p < 0.001), interleukin (IL)-1β (p < 0.001), IL-6 (p=0.019), IL-17A (p=0.002), and C-reactive protein (p=0.001), but positively related to IL-10 (p=0.007). Moreover, ITIH4 was also inversely associated with Acute Physiology and Chronic Health Evaluation II score (p=0.002), Sequential Organ Failure Assessment (SOFA) score (p < 0.001), SOFA-respiratory system score (p=0.023), and SOFA-renal system score (p=0.007). Interestingly, ITIH4 gradually increased from baseline to D7 (p < 0.001); besides, ITIH4 at baseline (p=0.009), D1 (p=0.002), D3 (p < 0.001), and D7 (p=0.015) were all decreased in sepsis deaths versus sepsis survivors. Serum ITIH4 is raised from baseline to D7 after disease onset, and it reflects the reduction of systemic inflammation, disease severity, and 28-day mortality for sepsis. However, further verification is required.

Alterations of plasma exosomal proteins and motabolies are associated with the progression of castration-resistant prostate cancer

BackgroundCurrent diagnosis tools for prostate cancer (PCa) such as serum PSA detection and prostate biopsy cannot distinguish dormant tumors from invasive malignancies, either be used as prognosis marker for castration resistant prostate cancer (CRPC), the lethal stage of PCa patients. Exosomes have been widely investigated as promising biomarkers for various diseases. We aim to characterize the proteomic and metabolomic profile of exosomes and to evaluate their potential value for the diagnosis of PCa, especially CRPC. We also investigate the functions of some specific exosome biomarkers in the progression of CRPC.MethodsIntegrated proteomics and metabolomics analysis were performed for plasma-derived exosomes collected from tumor-free controls (TFC), PCa and CRPC patients. Expression of specific exosomal proteins were further validated by targeted 4D-parallel reaction monitoring (PRM) mass spectrometry among the three cohorts. Tissue distribution and functional role of exosomal protein LRG1 was studied in clinical PCa tissue samples and cell line models.ResultsThree potential exosomal protein markers were identified. The apolipoprotein E level in PCa samples was 1.7-fold higher than that in TFC (receiver operating characteristic value, 0.74). Similarly, the levels of exosome-derived leucine-rich alpha2-glycoprotein 1 (LRG1) and inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) in the CRPC group were 1.7 and 2.04 times, respectively, higher than those in the PCa group (ROC values, 0.84 and 0.85, respectively), indicating that LRG1 and ITIH3 could serve as predictive markers for CRPC. For metabolomic evaluation of exosomes, a series of differentially expressed metabolites were identified, and a combined metabolite panel showed ROC value of 0.94 for distinguishing PCa from TFC and 0.97 for distinguishing CRPC from PCa. Immunohistochemistry of tissue microarray showed that LRG1 protein was significantly upregulated in advanced prostate cancer and functional assay revealed that ectopic expression of LRG1 can significantly enhance the malignant phenotype of prostate cancer cells. More importantly, PCa cell derived LRG1-overexpressed exosomes remarkably promoted angiogenesis.ConclusionIntegration of proteomics and metabolomics data generated proteomic and metabolic signatures of plasma exosomes that may facilitate discrimination of CRPC from PCa and TFC patients, suggesting the potential of exosomal proteins and metabolites as CRPC markers. The study also confirmed the important role of exosomal protein LRG1 in PCa malignant progression.

Serum peptidomic screening identified circulating peptide biomarkers predictive for preeclampsia.

BackgroundReliable biomarkers are needed to improve preeclampsia (PE) prediction accuracy. With the investigational tool of peptidomics, we aimed to identify and validate potential serum peptide biomarkers in cohorts suspected for PE development in middle or late pregnancy.MethodsTotally 195 serum samples were prospectively collected from pregnant women with PE-related syndromes who were followed up for PE development until delivery. Serum peptidomic analysis was performed in the discovery cohort of 115 samples using matrix-assisted laser desorption ionization-time of flight coupled with Linear Trap Quadropole Orbitrap mass spectrometry. The candidate biomarkers were further validated using an in-house developed liquid chromatography tandem mass spectrometry (LC-MS/MS) method in an independent validation cohort of 80 serum samples.ResultsWe identified 8 peptides that were differentially expressed and originated from fibrinogen alpha chain (FGA), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and complement component 3. In the subsequent LC-MS/MS quantitation analysis, the levels of the three peptides (FGA-1033.4, ITIH4-2026.9, ITIH4-2051.1) exhibited a significant difference between the PE-positive and PE-negative groups. Further, the three-peptide panel yielded an area under the ROC curve (AUC) of 0.985 [95% confidence interval (CI) 0.965–1.000] and 0.923 (95% CI 0.845–1.000) in the discovery and validation cohorts respectively, with negative predictive values of 98.1–98.8% and positive predictive values of 73.1–85.3% that were much improved when compared with that of soluble fms-like tyrosine kinase-1/placental growth factor (sFlt-1/PlGF) ratio.ConclusionsWe have discovered and validated a novel three-peptide biomarker panel predictive for the occurrence PE in pregnant women.

Quantitative label-free proteomic analysis of human follicle fluid to identify novel candidate protein biomarker for endometriosis-associated infertility

BackgroundEndometriosis (EM) leads to a decline in fertility, which is characterized by a decrease in the number and quality of follicles, and thus has a negative impact on in vitro fertilization (IVF) outcomes. However, the mechanism of how EM affects oocytes and leads to infertility remains unclear. As a potentially available sample directly related to oocyte growth, follicular fluid (FF) has important research value. Evaluating the association of FF content and EM-associated infertility through proteomics may helpful to explore the possible pathogenesis of EM-associated infertility. MethodsIn the present experimental study, from August 2019 to June 2020, FF samples were obtained as control group (CON-G; n = 10) from women with no one female factor of infertility and were undergoing IVF due to other reasons, 20 women with EM-associated infertility undergoing IVF with no other female factors were distributed into the EM group according to the time for IVF: (i) EM-group 1 (EM-G1, Stage I to Stage III, n = 10); (ii) EM-group 2 (EM-G2, Stage I to Stage III, n = 10). label-free quantitative proteomics (LFQP) technology and parallel reaction monitoring (PRM) approach were combined to aid in identifying and validating FF protein biomarkers for EM-associated infertility. In PRM analysis, another 20 subjects were enrolled as EM-associated infertility group (EM,Stage I to Stage III, n = 10) and controls (CON, n = 10) within the same time and inclusion criteria are the same as previously described. Finally, a potential protein biomarker panel of FF differential expressed proteins to EM-associated infertility was also evaluated by t-test and receiver operating characteristic (ROC) curve and binary Logistic regression models. Results7 significant differential expressed proteins which closely related to EM-associated infertility were found by LFQP technology, among which immunoglobulin lambda variable 7–46 (IGLV7–46), Immunoglobulin heavy constant gamma 2 (IGHG2), glia-derived nexin (GDN) and Inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) were significantly up-regulated (p < 0.05), while corticosteroid-binding globulin (CBG), angiotensinogen (AGT) and Fetuin-B (FETUB) were significantly down regulated (p < 0.05). Additionally, GDN and AGT was identified as a potential protein biomarker by further PRM analysis for EM-associated infertility according to ROC curve analysis and t-test (p < 0.05), the area under the curve (AUC) for GDN and AGT was 0.78 and 0.69 with optimum sensitivity of 50%, 70% and specificity of 100%, 90%, respectively. According to binary logistic regression and evaluated ROC analysis, the AUC for the combination of GDN and AGT was 0.80. ConclusionsTo the best of our knowledge, this is the first time that elevated GDN protein levels have been found in the FF of patients with EM-associated infertility. Combining LFQP technology and PRM method we found the abnormal of GDN and AGT in FF may be the potential cause of EM-associated infertility which may help to better understand the physiological and pathological mechanism of EM-associated infertility. Further experimental studies are required to confirm their mechanism in EM-associated infertility. The results of this study are also consistent with the previous conclusion that EM is a chronic inflammatory disease. SignificanceTo the best of our knowledge, this is the first time that elevated GDN protein levels have been found in the follicular fluid of patients with EM-associated infertility. Combining LFQP technology and PRM methods we found the abnormal of GDN and AGT protein in FF may be the potential cause of EM-associated infertility which may help to better understand the physiological and pathological mechanism of EM-associated infertility.Clinically, it has been recognized that EM is related to infertility, but the mechanism remains unclear. Our study combines label-free quantitative proteomics technology and parallel reaction monitoring methods to identify and verify the FF protein biomarkers of EM-associated infertility, which provides a good research method for follow-up research.

HDL proteome remodeling associates with COVID-19 severity

BackgroundBesides the well-accepted role in lipid metabolism, high-density lipoprotein (HDL) also seems to participate in host immune response against infectious diseases.Objective: We used a quantitative proteomic approach to test the hypothesis that alterations in HDL proteome associate with severity of Coronavirus disease 2019 (COVID-19).MethodsBased on clinical criteria, subjects (n=41) diagnosed with COVID-19 were divided into two groups: a group of subjects presenting mild symptoms and a second group displaying severe symptoms and requiring hospitalization. Using a proteomic approach, we quantified the levels of 29 proteins in HDL particles derived from these subjects.ResultsWe showed that the levels of serum amyloid A 1 and 2 (SAA1 and SAA2, respectively), pulmonary surfactant-associated protein B (SFTPB), apolipoprotein F (APOF), and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) were increased by more than 50% in hospitalized patients, independently of sex, HDL-C or triglycerides when comparing with subjects presenting only mild symptoms. Altered HDL proteins were able to classify COVID-19 subjects according to the severity of the disease (error rate 4.9%). Moreover, apolipoprotein M (APOM) in HDL was inversely associated with odds of death due to COVID-19 complications (odds ratio [OR] per 1-SD increase in APOM was 0.27, with 95% confidence interval [CI] of 0.07 to 0.72, P=0.007).ConclusionOur results point to a profound inflammatory remodeling of HDL proteome tracking with severity of COVID-19 infection. They also raise the possibility that HDL particles could play an important role in infectious diseases.

Quantitative proteomics by iTRAQ-PRM based reveals the new characterization for gout

BackgroundGout is a common and complex form of immunoreactive arthritis based on hyperuricemia, while the symptoms would turn to remission or even got worse. So, it is hard to early identify whether an asymptomatic hyperuricemia (AHU) patient will be susceptible to get acute gout attack and it is also hard to predict the process of gout remission to flare. Here, we report that the plasma proteins profile can distinguish among acute gout (AG), remission of gout (RG), AHU patients, and healthy controls.MethodsWe established an isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM) based method to measure the plasma proteins for AG group (n = 8), RG group (n = 7), AHU group (n = 7) and healthy controls (n = 8).ResultsEleven differentially expressed proteins such as Histone H2A, Histone H2B, Thrombospondin-1 (THBS1), Myeloperoxidase (MPO), Complement C2, Complement component C8 beta chain (C8B), Alpha-1-acid glycoprotein 1 (ORM1), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Carbonic anhydrase 1 (CA1), Serum albumin (ALB) and Multimerin-1 (MMRN1) were identified. Histone H2A, Histone H2B and THBS1 might be the strongest influential regulator to maintain the balance and stability of the gout process. The complement and coagulation cascades is one of the main functional pathways in the mechanism of gout process.ConclusionsHistone H2A, Histone H2B and THBS1 are potential candidate genes for novel biomarkers in discriminating gout attack from AHU or RG, providing new theoretical insights for the prognosis, treatment, and management of gout process.Trial registrationThis study is not a clinical trial.

Levels of inter-alpha-trypsin inhibitor heavy chain H4 urinary polypeptide in gestational diabetes mellitus

ABSTRACT Gestational diabetes mellitus (GDM) can cause a variety of adverse maternal and fetal complications. The purpose of this study was to screen and identify the urinary polypeptides related to the severity of GDM and to analyze the correlation between urinary peptide levels and neonatal metabolic indices. A total of 31 normal pregnant women (N group) and 74 patients with GDM (GDM group) were randomly selected between February 2018 and August 2019. Patients with GDM were divided into two groups according to their fasting plasma glucose (FPG) levels. The urine samples were enriched using weak cation-exchange magnetic beads (MB-WCX), and eight different urine polypeptides were screened and analyzed. The peptide spectra were obtained using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). The urinary peptide signatures of the two groups were compared using the BioExplorer software. The difference analysis of the eight urinary polypeptides between the normal pregnant (N) group and GDM group showed that two polypeptides with mass-to- charge ratios (m/z) of 2175.7 and 2318.8, respectively, were significantly different between the two groups (P < 0.01). The m/z 2175.7 polypeptide was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS), and the corresponding name of the molecule was inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4). The changes in ITIH4 levels correlated with those in the neonatal metabolic indices. By establishing the Fisher discriminant function equation for the GDM group, the difference in sample distribution and mean value of the two groups could be observed directly. Abbreviations: GDM: gestational diabetes mellitus; FPG: fasting plasma glucose; MB-WCX: weak cation exchange magnetic beads; MALDI-TOF MS: matrix-assisted laser desorption ionization time-of-flight mass spectrometry; m/z: mass charge ratio; LC-MS: liquid chromatography-tandem mass spectrometry; glycosylated hemoglobin (HbA1c); PPG: postprandial plasma glucose; ITIH4: inter-alpha-trypsin inhibitor heavy chain H4; IR: insulin resistance; NFPG: neonatal fasting plasma glucose; NH: neonatal height; NW: neonatal weight; BMI: body mass index; RPL: recurrent pregnancy loss; OGTT: oral glucose tolerance test; ADA: American Diabetes Association; LIS: Laboratory Information System

Preliminary exploration on the serum biomarkers of bloodstream infection with carbapenem-resistant Klebsiella pneumoniae based on mass spectrometry.

BackgroundCarbapenem‐resistant K. pneumoniae (CRKP) bloodstream infections (BSI) must be rapidly identified to improve patient survival rates. This study investigated a new mass spectrometry‐based method for improving the identification of CRKP BSI and explored potential biomarkers that could differentiate CRKP BSI from sensitive.MethodsMouse models of BSI were first established. MALDI‐TOF MS was then used to profile serum peptides in CRKP BSI versus normal samples before applying BioExplorer software to establish a diagnostic model to distinguish CRKP from normal. The diagnostic value of the model was then tested against 32 clinical CRKP BSI and 27 healthy serum samples. Finally, the identities of the polypeptides used to establish the diagnostic model were determined by secondary mass spectrometry.Results107 peptide peaks were shared between the CRKP and normal groups, with 18 peaks found to be differentially expressed. Five highly expressed peptides in the CRKP group (m/z 1349.8, 2091.3, 2908.2, 4102.1, and 8129.5) were chosen to establish a diagnostic model. The accuracy, specificity and sensitivity of the model were determined as 79.66%, 81.48%, and 78.12%, respectively. Secondary mass spectrometry identified the Fibrinogen alpha chain (FGA), Inter‐alpha‐trypsin inhibitor heavy chain H4 (ITIH4) and Serum amyloid A‐2 protein (SAA2) as the source of the 5 serum peptides.ConclusionsWe successfully established a serum peptide‐based diagnostic model that distinguished clinical CRKP BSI samples from normal healthy controls. The application of MALDI‐TOF MS to measure serum peptides, therefore, represents a promising approach for early BSI diagnosis of BSI, especially for multidrug‐resistant bacteria where identification is urgent.

The Alterations in Methylene Blue/Light-Treated Frozen Plasma Proteins Revealed by Proteomics

Introduction: The aim of this study was to investigate the modified proteins in methylene blue/light-treated frozen plasma (MB-FP) compared with fresh frozen plasma (FFP) in order to gain a better application of MB/light-treated plasma in clinic transfusion. Methods: MB-FP and FFP were collected from Changchun central blood station, and a trichloroacetic acid/acetone precipitation method was used to remove albumin for the enrichment of lower abundance proteins. The plasma protein in MB-FP and FFP were separated using two-dimensional gel electrophoresis (2-DE) and the differentially expressed protein spots were analyzed using mass spectrometry. Finally, the differentially expressed proteins were tested using Western blot and enzyme-linked immunosorbent assay (ELISA). Results: Approximately 14 differentially expressed protein spots were detected in the MB-FP, and FFP was chosen as the control. After 2-DE comparison analysis and mass spectrometry, 8 significantly differentially expressed protein spots were identified, corresponding to 6 different proteins, including complement C1r subcomponent (C1R), inter-alpha-trypsin inhibitor heavy chain H4 (ITI-H4), keratin, type II cytoskeletal 1 (KRT1), hemopexin (HPX), fibrinogen gamma chain (FGG), and transthyretin (TTR). Western blot showed no significant difference in the expression level of KRT1 between MB-FP and FFP (p > 0.05). Both Western blot and ELISA indicated that the level of HPX was significantly higher in FFP than in MB-FP (p < 0.05). Conclusion: This comparative proteomics study revealed that some significantly modified proteins occur in MB-FP, such as C1R, ITI-H4, KRT1, HPX, FGG, and TTR. Our findings provide more theoretical data for using MB-FP in transfusion medicine. However, the relevance of the data for the transfusion of methylene blue/light-treated plasma remains unclear. The exact modification of these proteins and the effects of these modified proteins on their functions and their effects in clinical plasma infusion need to be further studied.

Chronic Periodontitis and Alzheimer Disease: A Putative Link of Serum Proteins Identification by 2D-DIGE Proteomics.

Increasing evidence indicates Chronic Periodontitis (CP) is a comorbidity of Alzheimer’s disease (AD), which is the most common form of age-related dementia, and for the latter, effective diagnostic and treatment strategies are lacking. Although inflammation is present in both diseases, the exact mechanisms and cross-links between CP and AD are poorly understood; and a direct association between the two has not been reported. This study aimed to identify a direct serum proteins link between AD and CP. Two-dimensional differential in-gel electrophoresis was employed to analyze serum samples from 12 CP patients and 12 age-matched controls. Furthermore, to determine the molecular link between CP and AD, neuroblastoma SK-N-SH APPwt cells were treated with 1 μg/ml of lipopolysaccharide from Porphyromonas gingivalis (P.g-LPS). Ten differentially expressed proteins were identified in CP patients. Among them, nine proteins were up-regulated, and one protein was down-regulated. Of the 10 differentially expressed proteins, five proteins were reportedly involved in the pathology of AD: Cofilin-2, Cathepsin B, Clusterin, Triosephosphate isomerase, and inter-alpha-trypsin inhibitor heavy chain H4 (ITI-H4). Western blotting indicated significantly higher expression of Cofilin-2, Cathepsin B, and Clusterin and lower expression of ITI-H4 in the CP group than in the Control group. The serum concentration of Cathepsin B has a good correlation with MMSE scores. Moreover, the protein level of Cathepsin B (but not that of ADAM10 and BACE1) increased significantly along with a prominent increase in Aβ1–40 and Aβ1–42 in the cell lysates of P.g-LPS-treated SK-N-SH APPwt cells. Cathepsin B inhibition resulted in a sharp decrease in Aβ1–40 and Aβ1–42 in the cell lysates. Furthermore, TNF-α was one of the most important inflammatory cytokines for the P.g-LPS-induced Cathepsin B upregulation in SK-N-SH APPwt cells. These results show that CP and AD share an association, while Cathepsin B could be a key link between the two diseases. The discovery of the identical serum proteins provides a potential mechanism underlying the increased risk of AD in CP patients, which could be critical for elucidating the pathophysiology of AD.

Systemic Proteome Alterations Linked to Early Stage Pancreatic Cancer in Diabetic Patients.

Background: Diabetes is a risk factor associated with pancreatic ductal adenocarcinoma (PDAC), and new adult-onset diabetes can be an early sign of pancreatic malignancy. Development of blood-based biomarkers to identify diabetic patients who warrant imaging tests for cancer detection may represent a realistic approach to facilitate earlier diagnosis of PDAC in a risk population. Methods: A spectral library-based proteomic platform was applied to interrogate biomarker candidates in plasma samples from clinically well-defined diabetic cohorts with and without PDAC. Random forest algorithm was used for prediction model building and receiver operating characteristic (ROC) curve analysis was applied to evaluate the prediction probability of potential biomarker panels. Results: Several biomarker panels were cross-validated in the context of detection of PDAC within a diabetic background. In combination with carbohydrate antigen 19-9 (CA19-9), the panel, which consisted of apolipoprotein A-IV (APOA4), monocyte differentiation antigen CD14 (CD14), tetranectin (CLEC3B), gelsolin (GSN), histidine-rich glycoprotein (HRG), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), plasma kallikrein (KLKB1), leucine-rich alpha-2-glycoprotein (LRG1), pigment epithelium-derived factor (SERPINF1), plasma protease C1 inhibitor (SERPING1), and metalloproteinase inhibitor 1 (TIMP1), demonstrated an area under curve (AUC) of 0.85 and a two-fold increase in detection accuracy compared to CA19-9 alone. The study further evaluated the correlations of protein candidates and their influences on the performance of biomarker panels. Conclusions: Proteomics-based multiplex biomarker panels improved the detection accuracy for diagnosis of early stage PDAC in diabetic patients.

Plasma Inter-Alpha-Trypsin Inhibitor Heavy Chains H3 and H4 Serve as Novel Diagnostic Biomarkers in Human Colorectal Cancer.

Objective Inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) are heavy chains of protein members belonging to the ITI family, which was associated with inflammation and carcinogenesis. However, the diagnostic value of ITIH3 and ITIH4 in human colorectal cancer (CRC) remains unknown. Methods In total, 101 CRC patients and 156 healthy controls were enrolled. The concentrations of ITIH3 and ITIH4 proteins in plasma samples of participants were assessed using enzyme-linked immunosorbent assay. ITIH3 and ITIH4 expressions in human CRC tissues were additionally assessed via immunohistochemical staining (IHC). Receiver operating characteristic (ROC) was applied to estimate the diagnostic power of the two proteins, and the net reclassification improvement (NRI) was adopted to evaluate the incremental predictive ability of ITIH3/ITIH4 when added to the tissue inhibitor of metalloproteinase-1 (TIMP-1). Results The plasma concentration of ITIH3 in CRC patients (median: 4.370 μg/mL; range: 2.152–8.170 μg/mL) was significantly lower than that in healthy subjects (median: 4.715 μg/mL; range: 2.665–10.257 μg/mL; p < 0.001), while the ITIH4 plasma level in subjects with CRC (median: 0.211 μg/mL; range: 0.099–0.592 μg/mL) was markedly increased relative to that in the control group (median: 0.134 μg/mL; range: 0.094–0.460 μg/mL, p < 0.001). Consistently, IHC score assessment showed a dramatic reduction in ITIH3 expression and, conversely, upregulation of ITIH4 in colorectal carcinoma specimens relative to adjacent normal colorectal tissues (p < 0.001 in both cases). The area under the curve (AUC) of the ROC for ITIH4 (AUC = 0.801, 95% CI: 0.745–0.857) was higher than that for ITIH3 (AUC = 0.638, 95% CI: 0.571–0.704, both p values < 0.001). The AUC of the ROC for combined ITIH3 and ITIH4 was even higher than that for carcinoembryonic antigen. NRI results showed that combining ITIH3 and ITIH4 with TIMP-1 significantly improved diagnostic accuracy (NRI = 17.12%, p = 0.002) for CRC patients compared to TIMP-1 alone. Conclusions Circulating ITIH3 and ITIH4 levels are associated with carcinogenesis in CRC, supporting their potential diagnostic utility as surrogate biomarkers for colorectal cancer detection.

Acute Anti-Inflammatory Markers ITIH4 and AHSG in Mice Brain of a Novel Alzheimer's Disease Model.

Alzheimer's disease (AD) is the most common dementia and a progressive neurodegenerative disorder aggravated by chronic hypoperfusion (HP). Since numerous evidence suggests that inflammation is related with AD pathology, we investigated the expression change of two anti-inflammatory markers, inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and alpha-2-HS-glycoprotein (AHSG), in a novel AD model (APP23) with HP at 12 month of age. As compared with wild type (WT, n = 10), immunohistochemical analysis showed a higher ITIH4 and a lower AHSG expressions in the cerebral cortex, hippocampus, and thalamus of the APP23 + HP group (n = 12) than the simple APP23 (n = 10) group (*p < 0.05 and **p < 0.01 versus WT; #p < 0.05 and ##p < 0.01 versus APP23). The present study provides an upregulation of anti-inflammatory ITIH4 and a downregulation of pro-inflammatory TNFα-dependent AHSG in a novel AD plus HP mice model.

Significance of the Differential Peptidome in Multidrug-Resistant Tuberculosis

Most multidrug-resistant tuberculosis (MDR-TB) patients fail to receive a timely diagnosis and treatment. Therefore, we explored the differentially expressed peptides in MDR-TB compared with drug-susceptible tuberculosis (DS-TB) patients using LC-MS/MS and Ingenuity Pathway Analysis (IPA) to analyse the potential significance of these differentially expressed peptides. A total of 301 peptides were differentially expressed between MDR-TB and DS-TB groups. Of these, 24 and 16 peptides exhibited presented high (fold change ≥ 2.0, P < 0.05) and low (fold change ≤ −2.0, P < 0.05) levels in MDR-TB. Significant canonical pathways included the prothrombin activation system, coagulation system, and complement system. In the network of differentially expressed precursor proteins, lipopolysaccharide (LPS) regulates many precursor proteins, including four proteins correlated with organism survival. These four important differentially expressed proteins are prothrombin (F2), complement receptor type 2 (CR2), collagen alpha-2(V) chain (COL5A2), and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4). After addition of CR2 peptide, IL-6 mRNA expression in THP-1 cells decreased significantly in dose- and time-dependent manners. Cumulatively, our study proposes potential biomarkers for MDR-TB diagnosis and enables a better understanding of the pathogenesis of MDR-TB. The functions of differentially expressed peptides, especially CR2, in MDR-TB require further investigation.

A new panel of pancreatic cancer biomarkers discovered using a mass spectrometry-based pipeline

Background:Pancreatic carcinoma (PC) is an aggressive malignancy that lacks strategies for early detection. This study aimed to develop a coherent, high-throughput and non-discriminatory pipeline for the novel clinical biomarker discovery of PC.Methods:We combined mass spectrometry (MS)-intensive methods such as isobaric tags for relative and absolute quantitation with two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS), 1D-targeted LC-MS/MS, prime MRM (P-MRM) and stable isotope dilution-based MRM (SID-MRM) to analyse serum samples from healthy people (normal control, NC), patients with benign diseases (BD) and PC patients to identify novel biomarkers of PC.Results:On the basis of the newly developed pipeline, we identified >1000 proteins, verified 142 differentially expressed proteins and finally targeted four proteins for absolute quantitation in 100 serum samples. The novel biomarker panel of apolipoprotein E (APOE), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), apolipoprotein A-I (APOA1), apolipoprotein L1 (APOL1), combining with CA19-9, statistically-significantly improved the sensitivity (95%) and specificity (94.1%), outperforming CA19-9 alone, for the diagnosis of PC.Conclusions:We developed a highly efficient pipeline for biomarker discovery, verification and validation, with each step systematically informing the next. A panel of proteins that might be clinically relevant biomarkers for PC was found.

Significant changes in ITIH4, AHSG, ORM1, and CD46 content in milk fat globule membrane proteins of ketotic dairy cows.

High concentrations of non-esterified fatty acid (NEFA) and β-hydroxybutyrate (BHBA) in cows' blood caused by ketosis are associated with inflammatory states. We hypothesised that ketosis in postparturient dairy cows would result in altered levels on inflammation-related proteins not only in plasma but also in the milk fat globule membranes (MFGM). Thirty cows were selected from a dairy farm in Heilongjiang, China. Inflammatory milk fat globule membrane proteins were detected using ELISA kits, and a fully automatic biochemical analyser was used to measure the concentrations of BHBA, NEFA, glucose (GLU) and triglyceride (TG) in plasma. MFGM protein from milk of ketotic cows contained significantly different concentrations of acute-phase response proteins (complement C3 (C3), prothrombin (F2), alpha-1-acid glycoprotein (ORM1), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), alpha-2-HS-glycoprotein (AHSG), complement C9 (C9), complement regulatory protein variant 4 (CD46)) in comparison with milk from non-ketotic cows. Blood concentrations of C3, complement C9 (C9), tumour necrosis factor α (TNFα), MFGM C3, monocyte differentiation antigen CD14 (CD14) and ORM1 levels were correlated with energy balance. ITIH4 and CD46 increased, and AHSG and ORM1 decreased before the onset of ketosis. These biomarkers offer potential as predictors and monitors of ketosis in at-risk cows.

Application Value of Mass Spectrometry in the Differentiation of Benign and Malignant Liver Tumors.

BackgroundDifferentiation of malignant from benign liver tumors remains a challenging problem. In recent years, mass spectrometry (MS) technique has emerged as a promising strategy to diagnose a wide range of malignant tumors. The purpose of this study was to establish classification models to distinguish benign and malignant liver tumors and identify the liver cancer-specific peptides by mass spectrometry.Material/MethodsIn our study, serum samples from 43 patients with malignant liver tumors and 52 patients with benign liver tumors were treated with weak cation-exchange chromatography Magnetic Beads (MB-WCX) kits and analyzed by the Matrix-Assisted Laser Desorption Time of Flight Mass Spectrometry (MALDI-TOF-MS). Then we established genetic algorithm (GA), supervised neural networks (SNN), and quick classifier (QC) models to distinguish malignant from benign liver tumors. To confirm the clinical applicability of the established models, the blinded validation test was performed in 50 clinical serum samples. Discriminatory peaks associated with malignant liver tumors were subsequently identified by a qTOF Synapt G2-S system.ResultsA total of 27 discriminant peaks (p<0.05) in mass spectra of serum samples were found by ClinPro Tools software. Recognition capabilities of the established models were 100% (GA), 89.38% (SNN), and 80.84% (QC); cross-validation rates were 81.67% (GA), 81.11% (SNN), and 86.11% (QC). The accuracy rates of the blinded validation test were 78% (GA), 84% (SNN), and 84% (QC). From the 27 discriminatory peptide peaks analyzed, 3 peaks of m/z 2860.34, 2881.54, and 3155.67 were identified as a fragment of fibrinogen alpha chain, fibrinogen beta chain, and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), respectively.ConclusionsOur results demonstrated that MS technique can be helpful in differentiation of benign and malignant liver tumors. Fibrinogen and ITIH4 might be used as biomarkers for the diagnosis of malignant liver tumors.