scholarly journals Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

2010 ◽  
Vol 6 (9) ◽  
pp. e1000940 ◽  
Author(s):  
Rong Chen ◽  
Tara K. Sigdel ◽  
Li Li ◽  
Neeraja Kambham ◽  
Joel T. Dudley ◽  
...  
2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 891-892
Author(s):  
D. Galbraith ◽  
M. Caliskan ◽  
O. Jabado ◽  
S. Hu ◽  
R. Fleischmann ◽  
...  

Background:RA is a systemic autoimmune disease with heterogeneous manifestation. Recent advances in serum proteomics, such as the SomaScan®platform (SomaLogic, Inc., Boulder, USA), allow for a deeper exploration of the protein biomarkers associated with RA and a better understanding of the molecular aetiology of the disease.Objectives:To characterise the differences in baseline serum proteome of patients with RA (enrolled in the Phase IIIb Abatacept vs adaliMumab comParison in bioLogic-naïvERA subjects with background MTX [AMPLE] study)1compared with a healthy population, and to identify serum protein biomarkers associated with disease severity and radiographic progression.Methods:Patients in the AMPLE study had an inadequate response to MTX and were naïve to biologic DMARDs. Protein abundance was assessed in baseline serum samples from 440 AMPLE study patients and 123 healthy individuals with matching demographics using the SomaScan®platform, with 5000+ slow off-rate modified aptamers and up to 8 log of dynamic range.2Differential abundance testing was performed using linear models to identify differences in protein abundance in patients with RA vs healthy individuals. A separate analysis using a linear model was conducted in only the patients with RA to identify the proteins associated with DAS28 (CRP) and TSS. Pathway analyses were performed for proteins significantly (false discovery rate-adjusted p value <0.05) associated with RA and the disease severity measurements to identify over-representation of the molecular pathways.Results:Compared with healthy individuals, >2000 serum proteins were significantly differentially expressed in patients with RA, including many proteins that have been associated with RA (e.g. serum amyloid A [SAA], CRP) and complement. Most of the protein expression differences were of small magnitude (fold change <2). Proteins that were differentially expressed between patients with RA and healthy individuals were enriched in interleukin signalling, neutrophil degranulation, platelet activation/degranulation and extracellular matrix organisation pathways. DAS28 (CRP) was significantly associated with several biomarkers, including SAA, fibrinogen and CRP; in general, proteins associated with DAS28 (CRP) were most strongly enriched in the platelet activation/degranulation pathways (Figure 1), also seen in patients with RA vs healthy individuals. Additionally, many proteins were significantly associated with TSS, including SAA, matrix metalloproteinase-3 and cartilage acidic protein 1. Here, the proteins were most strongly enriched in the extracellular matrix remodelling pathways (Figure 2).Conclusion:Our study revealed that thousands of serum proteins are differentially expressed and several pathways are dysregulated between patients with RA and healthy individuals. Additional pathways were identified that reflect disease severity, including joint damage, distinct from those pathways associated with the disease. The SomaScan®platform provides a unique proteomic tool with a wide dynamic range for the identification of serum protein biomarkers associated with RA and disease severity. Proteomic signatures should be considered in clinical trials to better understand disease pathogenesis and predict risk in response to treatment.References:[1]Schiff M, et al.Ann Rheum Dis2014;73:86–94.[2]Gold L, et al.PLoS One2010;5:e15004.Acknowledgments:Rachel Rankin (medical writing, Caudex; funding: Bristol-Myers Squibb)Disclosure of Interests:David Galbraith Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Minal Caliskan Employee of: Bristol-Myers Squibb, Omar Jabado Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Sarah Hu Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Roy Fleischmann Grant/research support from: AbbVie, Akros, Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer, IngelhCentrexion, Eli Lilly, EMD Serono, Genentech, Gilead, Janssen, Merck, Nektar, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Roche, Samsung, Sandoz, Sanofi Genzyme, Selecta, Taiho, UCB, Consultant of: AbbVie, ACEA, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Novartis, Pfizer, Sanofi Genzyme, UCB, Michael Weinblatt Grant/research support from: Amgen, Bristol-Myers Squibb, Crescendo, Lily, Sanofi/Regeneron, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Crescendo, Gilead, Horizon, Lily, Pfizer, Roche, Sean Connolly Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Michael A Maldonado Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Sheng Gao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb


2019 ◽  
Vol 17 ◽  
Author(s):  
Xiaoli Yu ◽  
Lu Zhang ◽  
Na Li ◽  
Peng Hu ◽  
Zhaoqin Zhu ◽  
...  

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary tuberculosis. Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of Pulmonary tuberculosis were still lacked. Objective: This study focused on construct a label-free LC-MS/MS based comparative proteomics between six tuberculosis patients and six healthy controls to identify differentially expressed proteins (DEPs) in plasma. Method: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by general discriminant analysis (GDA), with leave-one-out cross-validation. Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for differentially expressed protein was set as adjusted p-value < 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for pulmonary tuberculosis, and be worthy of further validation.


Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1480
Author(s):  
Hiresh Ayoubian ◽  
Joana Heinzelmann ◽  
Sebastian Hölters ◽  
Oybek Khalmurzaev ◽  
Alexey Pryalukhin ◽  
...  

Although microRNAs are described as promising biomarkers in many tumor types, little is known about their role in PSCC. Thus, we attempted to identify miRNAs involved in tumor development and metastasis in distinct histological subtypes considering the impact of HPV infection. In a first step, microarray analyses were performed on RNA from formalin-fixed, paraffin-embedded tumor (22), and normal (8) tissue samples. Microarray data were validated for selected miRNAs by qRT-PCR on an enlarged cohort, including 27 tumor and 18 normal tissues. We found 876 significantly differentially expressed miRNAs (p ≤ 0.01) between HPV-positive and HPV-negative tumor samples by microarray analysis. Although no significant differences were detected between normal and tumor tissue in the whole cohort, specific expression patterns occurred in distinct histological subtypes, such as HPV-negative usual PSCC (95 differentially expressed miRNAs, p ≤ 0.05) and HPV-positive basaloid/warty subtypes (247 differentially expressed miRNAs, p ≤ 0.05). Selected miRNAs were confirmed by qRT-PCR. Furthermore, microarray data revealed 118 miRNAs (p ≤ 0.01) that were significantly differentially expressed in metastatic versus non-metastatic usual PSCC. The lower expression levels for miR-137 and miR-328-3p in metastatic usual PSCC were validated by qRT-PCR. The results of this study confirmed that specific miRNAs could serve as potential diagnostic and prognostic markers in single PSCC subtypes and are associated with HPV-dependent pathways.


2010 ◽  
Vol 136 (8) ◽  
pp. 1151-1159 ◽  
Author(s):  
Xiaonan Kang ◽  
Lu Sun ◽  
Kun Guo ◽  
Hong Shu ◽  
Jun Yao ◽  
...  

2017 ◽  
Vol 16 (6) ◽  
pp. 8427-8433 ◽  
Author(s):  
Long Wang ◽  
Ya-Qian Hu ◽  
Zhuo-Jie Zhao ◽  
Hong-Yang Zhang ◽  
Bo Gao ◽  
...  

2020 ◽  
Author(s):  
Angela Mc Ardle ◽  
Anna Kwasnik ◽  
Agnes Szenpetery ◽  
Melissa Jones ◽  
Belinda Hernandez ◽  
...  

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8682
Author(s):  
Yi-Shian Peng ◽  
Chia-Wei Tang ◽  
Yi-Yun Peng ◽  
Hung Chang ◽  
Chien-Lung Chen ◽  
...  

Background Alzheimer’s disease (AD) is a prevalent progressive neurodegenerative human disease whose cause remains unclear. Numerous initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests. Natural aging (AG) is a high-risk factor for AD. Here, we aim to gain insights in AD that may lead to its novel therapeutic treatment through conducting meta-analyses of gene expression microarray data from AG and AD-affected brain. Methods Five sets of gene expression microarray data from different regions of AD (hereafter, ALZ when referring to data)-affected brain, and one set from AG, were analyzed by means of the application of the methods of differentially expressed genes and differentially co-expressed gene pairs for the identification of putatively disrupted biological pathways and associated abnormal molecular contents. Results Brain-region specificity among ALZ cases and AG-ALZ differences in gene expression and in KEGG pathway disruption were identified. Strong heterogeneity in AD signatures among the five brain regions was observed: HC/PC/SFG showed clear and pronounced AD signatures, MTG moderately so, and EC showed essentially none. There were stark differences between ALZ and AG. OXPHOS and Proteasome were the most disrupted pathways in HC/PC/SFG, while AG showed no OXPHOS disruption and relatively weak Proteasome disruption in AG. Metabolic related pathways including TCA cycle and Pyruvate metabolism were disrupted in ALZ but not in AG. Three pathogenic infection related pathways were disrupted in ALZ. Many cancer and signaling related pathways were shown to be disrupted AG but far less so in ALZ, and not at all in HC. We identified 54 “ALZ-only” differentially expressed genes, all down-regulated and which, when used to augment the gene list of the KEGG AD pathway, made it significantly more AD-specific.


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