Serum proteomic analysis of major depressive disorder patients and their remission status: Novel biomarker set of zinc-alpha-2-glycoprotein and keratin type II cytoskeletal 1.

Major depressive disorder (MDD) is the most common mood disorder, and causes various mental, physical and cognitive symptoms. Clinicians diagnose MDD using multiple interviews and overall impression during the interviews, which makes MDD diagnosis highly subjective. To overcome this, we investigated novel protein biomarker for MDD. Serum from each subject were analyzed using nano liquid chromatography-triple time-of-flight mass spectrometry. We identified two proteins, zinc-alpha-2-glycoprotein (ZA2G) and keratin type II cytoskeletal 1 (K2C1), as final biomarkers. These biomarkers were downregulated during depression (p < 0.05, AUC of ROC >0.7). ZA2G is related to tryptophan metabolism, which is a main serotonin synthesis pathway. K2C1 is involved in the kinin-kallikrein system, which produces bradykinin, an anti-inflammatory mediator in the brain. Our results suggest that the two protein candidates are related to inflammation and that MDD is highly associated with inflammation. Finally, since all subjects in the two groups were taking antidepressants, our results suggest that the identified biomarkers could determine the presence or absence of illness and could be used to monitor therapeutic effects.

iTRAQ­based proteomic analysis reveals potential regulatory networks in dust mite­related asthma treated with subcutaneous allergen immunotherapy.

Asthma is one of the most common childhood chronic diseases worldwide. Subcutaneous immunotherapy (SCIT) is commonly used in the treatment of house dust mite (HDM)­related asthma in children. However, the therapeutic mechanism of SCIT in asthma remains unclear. The present study aimed to investigate the molecular biomarkers associated with HDM­related asthma in asthmatic children prior and subsequent to SCIT treatment compared with those in healthy children via proteomic analysis. The study included a control group (30 healthy children), ­Treatment group (30 children with HDM­related allergic asthma) and +Treatment group (30 children with HDM­related allergic asthma treated with SCIT). An isobaric labeling with relative and absolute quantification­based method was used to analyze serum proteome changes to detect differentially expressed proteins, while functional enrichment and protein­protein interaction network analysis were used to select candidate biomarkers. A total of 72 differentially expressed proteins were detected in the ­Treatment, +Treatment and control groups. A total of 33 and 57 differentially expressed proteins were observed in the ­Treatment vs. control and +Treatment vs. control groups, respectively. Through bioinformatics analysis, 5 candidate proteins [keratin 1 (KRT1), apolipoprotein B (APOB), fibronectin 1, antithrombin III (SERPINC1) and α­1­antitrypsin (SERPINA1)] were selected for validation by western blotting; among them, 4 proteins (KRT1, APOB, SERPINC1 and SERPINA1) showed robust reproducibility in asthma and control samples. This study illustrated the changes in proteome regulation following SCIT treatment for asthma. The 4 identified proteins may serve as potential biomarkers prior and subsequent to SCIT treatment, and help elucidate the molecular regulation mechanisms of SCIT to treat HDM­related asthma.

Proteomic analysis of differentially expressed proteins in the serum of patients with acute renal allograft rejection using iTRAQ labelling technology.

Transplantation is currently the best treatment for patients with end­stage renal disease. However, acute rejection (AR) is the major source of failure in renal transplantation. The current best practice for the diagnosis of AR involves renal biopsy, but it is invasive, time­consuming, costly and inconvenient. Sensitive and less invasive detection of AR episodes in renal transplant patients is essential to preserve allograft function. The present study applied isobaric tags for relative and absolute quantitation (iTRAQ) mass spectrometry to analyze serum protein expression in patients with AR and healthy controls. Overall, 1,399 proteins were identified. Using a cut­off of Q<0.05 and a fold change of >1.2 for the variation in expression, 109 proteins were identified to be differentially expressed between the AR and control groups, 72 of which were upregulated and 37 were downregulated. Several proteins, including properdin, keratin 1, lipoprotein(a) and vitamin D­binding protein, may have roles in the pathogenesis of AR. The present study focused on iTRAQ­based proteomic profiling of serum samples in AR. Insight from the present study may help advance the understanding of the molecular mechanisms of AR and identify potential novel biomarkers of AR for further characterization.

Clinical value of a diagnostic score for colon cancer based on serum CEA, CA19-9, cytokeratin-1 and mucin-1.

BACKGROUND: Although established markers such as CEA and CA19-9 are important for diagnosing early stages of colon cancer, they are not ideal. Developing promising markers include cytokeratin 1 (CK1) and mucin-1 (MUC1), but the combined value of each of these markers is unclear. We therefore evaluated the value of a combined laboratory-based score of these four markers in the diagnosis of colon cancer. METHODS: Two hundred patients who had undergone colonoscopic examination (150 colon cancer, 50 benign growths) were recruited. The study was controlled by 35 healthy subjects. CEA, CA19-9, CK1 and MUC1 were measured by ELISA and evaluated for cancer diagnosis using area under the receiver operating characteristic curve (AUC). RESULTS: Serum levels of all four markers were increased in the order colon cancer > benign disease > healthy controls (p < 0.001). In multivariate analysis, CA19.9 (p = 0.025), CK1 (p < 0.001) and MUC1 (p = 0.009) were significant independent predictors of colon cancer. A score that gave the greatest power of discrimination for colon cancer was defined as 1.06 + [0.001 × CA19.9 result] + [0.003 × CEA result] + [0.03 × CK1 result] + [0.05 × MUC1 result]. The colon score provided superior discrimination, AUC, and sensitivity and specificity for colon cancer versus benign growth than each of the individual markers. Similarly, the colon score provided superior AUC, and sensitivity and specificity that each individual marker for tumour stage, lymph node invasion and distant organ metastases than each individual marker. CONCLUSION: A colon score derived from serum CEA, CA19-9, CK1 and MUC1 is a potential valuable non-invasive index that could be used for detection and screening early stage colon cancer patients.

Analysis of Sera of Recipients with Allograft Rejection Indicates That Keratin 1 Is the Target of Anti-Endothelial Antibodies.

Anti-endothelial cell antibodies (AECAs) are usually directed against the surface antigens on the vascular endothelial cells. Clinical studies suggest a pathogenic role for nonhuman leukocyte antigen in antibody-mediated rejection; however, the antigens on the donor vascular endothelium that serve as the first-line targets for an immune response during allograft rejection have not been fully identified. Here, we used immunoprecipitation and mass spectrometry to identify antigens from the sera of kidney transplant recipients who were experiencing antibody-mediated rejection. Keratin 1 (KRT1) was identified as a novel antigenic target expressed on endothelial cells. To validate our finding, we produced recombinant proteins representing the three most common alleles of KRT1. The serum used for immunoprecipitation showed a strong reaction to KRT1 recombinants in western blot and ELISA. In the kidney transplant cohort, more AECA-positive recipients than AECA-negative recipients had KRT1 antibodies (32.2% versus 11.9%, p = 0.002). Sera from 255 renal recipients were tested by ELISA. Of the 77 recipients with deteriorating graft function (serum creatinine > 120 µmol/L), 23 had anti-KRT1 antibodies. KRT1-IgG positivity was, therefore, associated with a higher risk of kidney transplant rejection (29.9% (23/77) versus 16.9% (30/178), p = 0.0187). A better understanding of this antigenic target will improve long-term allograft survival.