Identification of Novel Biomarkers for Behcet Disease Diagnosis Using Human Proteome Microarray Approach.

Behcet disease (BD) is a chronic systemic vasculitis and considered as an autoimmune disease. Although rare, BD can be fatal due to ruptured vascular aneurysms or severe neurological complications. To date, no known biomarker has been reported for this disease, making it difficult to diagnosis in the clinics. To undertake this challenge, we employed the HuProt arrays, each comprised of ∼20,000 unique human proteins, to identify BD-specific autoantibodies using a Two-Phase strategy established previously. In Phase I, we profiled the autoimmunity on the HuProt arrays with 75 serum samples collected from 40 BD patients, 15 diagnosed autoimmune patients who suffer from Takayasu arteritis (TA; n = 5)), ANCA associated vasculitis (AAV; n = 5), and Sjogren's syndrome (SS; n = 5), and 20 healthy subjects, and identified 20 candidate autoantigens that were significantly associated with BD. To validate these candidates, in Phase II we constructed a focused array with these 20 candidate BD-associated antigens, and use it to profile a much larger cohort, comprised of serum samples collected from 130 BD patients, 103 autoimmune patients (i.e. 40TA, 40 AAV and 23 SS), and 110 healthy controls. This allowed us to validate CTDP1 (RNA polymerase II subunit A C-terminal domain phosphatase)as a BD-specific autoantigen. The association of anti-CTDP1 with BD patients was further validated using the traditional Western blotting analysis. In conclusion, anti-CTDP1 antibody serves a novel autoantibody for Behcet disease and is expected to help more accurate clinical diagnosis.

Diagnostic efficacy of combining diffusion-weighted magnetic resonance imaging with serum Mucin 1, Mucin 13, and Mucin 16 in distinguishing borderline from malignant epithelial ovarian tumors.

AIMS: To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors. METHODS: A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay. RESULTS: Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670 ± 0.250) × 103 mm2 /s, while MEOTs had a lower ADC mean of (1.332 ± 0.481) × 103 mm2 /s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44 ng/mL vs. 7.77 ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%. CONCLUSION: The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.

The psoas muscle density as a predictor of postoperative complications in elderly patients undergoing rectal cancer resection.

Background: Muscle depletion that impairs normal physiological function in elderly patients leads to poor prognosis. This study aimed to evaluate the association between total abdominal muscle area (TAMA), total psoas area (TPA), psoas muscle density (PMD), and short-term postoperative complications in elderly patients with rectal cancer. Methods: All elderly patients underwent rectal cancer resection with perioperative abdominal computed tomography (CT). Complications were assessed according to the Clavien-Dindo classification. Severe complications were defined as grade III-V following the Clavien-Dindo classification. Univariate and multivariate analyses were performed to evaluate risk factors of short-term severe postoperative complications. Results: The cohort consisted of 191 patients with a mean age of 73.60 ± 8.81 years. Among them, 138 (72.25%) patients had Clavien-Dindo 0- II, 53 (27.75%) patients had severe postoperative complications (Clavien-Dindo III-V), and 1(0.52%) patient died within 30 days of surgery. PMD was significantly higher in the Clavien-Dindo 0-II cohort compared to the Clavien-Dindo III-V cohort (p=0.004). Nevertheless, TAMA and TPA failed to exhibit significant differences. Moreover, the multivariate regression analysis implied that advanced age [OR 1.07 95%CI (1.02-1.13) p=0.013], male [OR 5.03 95%CI (1.76-14.41) p=0.003], high charlson comorbidity index (CCI) score [OR 3.60 95%CI (1.44-9.00) p=0.006], and low PMD [OR 0.94 95%CI (0.88-0.99) p=0.04] were independent risk factors of Clavien-Dindo III-V. Conclusion: Preoperative assessment of the PMD on CT can be a simple and practical method for identifying elderly patients with rectal cancer at risk for severe postoperative complications.

Association Study of a Proliferation-inducing Ligand, Spermatogenesis Associated 8, Platelet-derived Growth Factor Receptor-alpha, and POLB Polymorphisms with Systemic Lupus Erythematosus in Chinese Han Population.

BACKGROUND: Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease with complex genetic inheritance. This study was conducted to examine whether the association of a proliferation-inducing ligand (APRIL), spermatogenesis associated 8 (SPATA8), platelet-derived growth factor receptor-alpha (PDGFRA), and DNA polymerase beta (POLB) with SLE can be replicated in a Chinese Han population. METHODS: Chinese SLE patients (n = 1247) and ethnically and geographically matched healthy controls (n = 1440) were genotyped for the APRIL, SPATA8, PDGFRA, and POLB single-nucleotide polymorphisms (SNPs), rs3803800, rs8023715, rs1364989, and rs12678588 using the Sequenom MassARRAY System. RESULTS: The Chinese Han SLE patients and controls had statistically similar frequencies of alleles and genotypes of four gene polymorphisms. Moreover, no association signal was detected on different genetic models (additive, dominant, and recessive, all, P> 0.05) or in SLE subgroups stratified by various clinical manifestations (all, P> 0.05). CONCLUSIONS: Different genetic backgrounds from different ancestries and various populations may result in different genetic risk factors for SLE. We did not detect any significant association with SNPs of APRIL, SPATA8, PDGFRA, and POLB.