FRI0576 IDENTIFICATION OF SERUM PROTEIN BIOMARKERS ASSOCIATED WITH RA DISEASE SEVERITY

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

2021 ◽  
Author(s):  
Juan Chen ◽  
Yaqiong Chen ◽  
Dehao Liu ◽  
Yihua Lin ◽  
Lei Zhu ◽  
...  

Abstract The aim of the study was to identify specific clinical and serum protein biomarkers that are associated with longitudinal outcome of RA-associated interstitial lung disease(RA-ILD). 60 RA patients with clinical and serological profiles were assessed by HRCT and pulmonary function tests (PFTs) at baseline (Year 0) and 5 years post enrollment (Year 5). Progression versus non-progression was defined based on changes in Quantitative Modified HRCT scores and PFTs over time. Specific serum protein biomarkers were assessed in serum samples at baseline and Year 5 by Multiplex enzyme-linked immunosorbent assays (ELISAs). At Year 5, 32% of patients demonstrated progressive RA-ILD, 35% were stable, and 33% improved. Baseline age and rheumatoid factor (RF) were significantly different between RA-ILD outcomes of progression vs. no-progression (p< 0.05). Changes in levels of CXCL11/I-TAC and MMP13 over 5 years also distinguished pulmonary outcomes (p< 0.05). A final binary logistic regression model revealed that baseline age and changes in serum MMP13 were associated with RA-ILD progression at Year 5 (p< 0.05), with an AUC of 0.7569. Collectively, these analyses demonstrated that baseline clinical variables (age, RF) and shifts in levels of selected serum proteins (CXCL11/I-TAC, MMP13) were strongly linked to RA-ILD outcome over time.


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 9571-9571
Author(s):  
Krisztian Homicsko ◽  
Michel A. Cuendet ◽  
Agata Mlynska ◽  
Bianca Moura ◽  
Christine Horak ◽  
...  

9571 Background: Checkpoint inhibitors have revolutionized the treatment of stage IV melanoma patients. Selection of patients for PD-1 monotherapy or CTLA4/PD1 combination remains an important challenge. We set out to perform a discovery study of pretreatment serum protein biomarkers to identify predictors of progression free survival (PFS) for ipilimumab (IPI) or ipilimumab/nivolumab (IPI/NIVO). Methods: We performed an exploratory analysis of baseline serum samples from 135 treatment-naive patients with metastatic melanoma included in the randomized phase II clinical trial, CheckMate 069 (NCT01927419). We used the RayBiotech 440 human cytokine array and evaluated the relationship of serum protein levels with 44 clinical parameters. R, Prism 7.0 and TensorFlow were used for analyses. Results: We focused on correlation of serum protein markers with PFS as a predictor of long-term benefit. In the IPI arm (n = 46), high FGF4 correlated with worse PFS outcome (p = 0.0012). However, FGF4 levels alone were unable to select responsive vs. non-responsive patients. In contrast, a set of three markers consisting of FGF4 ( < 760pg/ml), CCL15 ( > 2.7 ng/ml), and TACE ( > 600pg/ml) separated non-progressing versus progressing patients. Moreover a small group of FGF4-high patients who were concomitantly TIM-3-low also had longer PFS (combined of both: p = 0.0004, HRlogrank: 0.07, 95% CI: 0.03279 to 0.1533). The same markers did not discriminate between IPI/NIVO patients (p = 0.467, HR: 15). In the IPI/NIVO arm, three different markers could select patients. Patients either with low CCL2 ( < 72 pg/ml) or alternatively with high CCL2 combined with high PDGF-AA ( > 8.2 ng/ml) and low GASP-1 ( < 1.3 ng/ml) had longer PFS (p < 0.0001, HR: 0.115, 95% CI: 0.03848 to 0.3408). Conversely, these markers did not predict benefit for IPI-monotherapy. Conclusions: In this study we identified protein signatures in baseline serum that correlate with PFS for therapies with IPI or IPI/NIVO. The markers were exclusive for IPI or IPI/NIVO but not for both. Additional research is warranted to substantiate these results and evaluate the possibility of incorporating into clinical practice.


2016 ◽  
Vol 2016 ◽  
pp. 1-29 ◽  
Author(s):  
Jiankun Yang ◽  
Lichao Yang ◽  
Baixue Li ◽  
Weilong Zhou ◽  
Sen Zhong ◽  
...  

Background.Chronic infection with hepatitis B virus (HBV) is a leading cause of cirrhosis and hepatocellular carcinoma. By traditional Chinese medicine (TCM) pattern classification, damp heat stasis in the middle-jiao (DHSM) and liver Qi stagnation and spleen deficiency (LSSD) are two most common subtypes of CHB.Results.In this study, we employed iTRAQ proteomics technology to identify potential serum protein biomarkers in 30 LSSD-CHB and 30 DHSM-CHB patients. Of the total 842 detected proteins, 273 and 345 were differentially expressed in LSSD-CHB and DHSM-CHB patients compared to healthy controls, respectively. LSSD-CHB and DHSM-CHB shared 142 upregulated and 84 downregulated proteins, of which several proteins have been reported to be candidate biomarkers, including immunoglobulin (Ig) related proteins, complement components, apolipoproteins, heat shock proteins, insulin-like growth factor binding protein, and alpha-2-macroglobulin. In addition, we identified that proteins might be potential biomarkers to distinguish LSSD-CHB from DHSM-CHB, such as A0A0A0MS51_HUMAN (gelsolin), PON3_HUMAN, Q96K68_HUMAN, and TRPM8_HUMAN that were differentially expressed exclusively in LSSD-CHB patients and A0A087WT59_HUMAN (transthyretin), ITIH1_HUMAN, TSP1_HUMAN, CO5_HUMAN, and ALBU_HUMAN that were differentially expressed specifically in DHSM-CHB patients.Conclusion.This is the first time to report serum proteins in CHB subtype patients. Our findings provide potential biomarkers can be used for LSSD-CHB and DHSM-CHB.


Author(s):  
Sandi L. Navarro ◽  
Marta Herrero ◽  
Helena Martinez ◽  
Yuzheng Zhang ◽  
Jon Ladd ◽  
...  

Background: Non-steroidal anti-inflammatory drugs, e.g., celecoxib, are commonly used for inflammatory conditions, but can be associated with adverse effects. Combined glucosamine hydrochloride plus chondroitin sulfate (GH+CS) are commonly used for joint pain and have no known adverse effects. Evidence from in vitro, animal and human studies suggest that GH+CS have anti-inflammatory activity, among other mechanisms of action. Objective: We evaluated the effects of GH+CS versus celecoxib on a panel of 20 serum proteins involved in inflammation and other metabolic pathways. Methods: Samples were from a randomized, parallel, double-blind trial of pharmaceutical grade 1500 mg GH + 1200 mg CS (n=96) versus 200 mg celecoxib daily (n=93) for 6- months in knee osteoarthritis (OA) patients. Linear mixed models adjusted for age, sex, body mass index, baseline serum protein values, and rescue medicine use assessed the intervention effects of each treatment arm adjusting for multiple testing. Results: All serum proteins except WNT16 were lower after treatment with GH+CS, while about half increased after celecoxib. Serum IL-6 was significantly reduced (by 9%, P=0.001) after GH+CS, and satisfied the FDR <0.05 threshold. CCL20, CSF3, and WNT16 increased after celecoxib (by 7%, 9% and 9%, respectively, P<0.05), but these serum proteins were no longer statistically significant after controlling for multiple testing. Conclusion: The results of this study using samples from a previously conducted trial in OA patients, demonstrate that GH+CS reduces circulating IL-6, an inflammatory cytokine, but is otherwise comparable to celecoxib with regard to effects on other circulating protein biomarkers.


2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 13-13
Author(s):  
Meredith C. Henderson ◽  
David Emery Reese ◽  
Sherri Borman ◽  
Susan Yeh ◽  
Alan Hollingsworth

13 Background: The use of protein biomarkers for serum-based detection of invasive breast cancer has been problematic due in large part to intrinsic variability in the population as a whole. The Provista Biomarker Assay (PBA) has been shown previously to be highly sensitive across a wide spectrum of clinical signals. The detection of autoantibodies (AAb) holds great promise due to the inherent specificity these biomarkers provide. However, as a clinical-quality diagnostic, it is necessary to utilize a panel comprised of multiple autoantibodies, as individual sensitivity is general low. Our hypothesis was that combining serum protein and autoantibodies together in a panel would result in an increased ability to correctly identify breast cancer. Methods: To maximize clinical performance (sensitivity and specificity), we utilized the Meso Scale Discovery ELISA-based system to measure AAbs from patient sera. We analyzed 134 prospectively collected patient serum samples for a variety of autoantibody targets. These data, together with serum protein biomarker concentrations, produced an analytically robust test that is also highly specific. Results: Consistent with our hypothesis, the inclusion of autoantibodies with serum proteins in the Provista Biomarker Assay improved test specificity above that observed in serum protein biomarkers alone. Individual protein targets had limited ability to differentiate benign conditions from invasive breast cancer. However, factoring in autoantibody values resulted in improved overall accuracy to differentiate serum from benign and invasive breast cancer patients. Conclusions: In the novel approach of combining these two different classes of analytes, we exploit the specificity of AAbs while maintaining high sensitivity through the inclusion of more generalized cancer-associated protein biomarkers. The combination of these two approaches clearly offers unique performance benefits in the early detection of invasive breast cancer that is greater than either component alone.


2020 ◽  
Vol 14 (Supplement_1) ◽  
pp. S070-S070
Author(s):  
S Verstockt ◽  
N Verplaetse ◽  
D Raimondi ◽  
B Verstockt ◽  
E Glorieus ◽  
...  

Abstract Background The inflammatory bowel diseases (IBD), Crohn’s disease (CD) and ulcerative colitis (UC) are chronic inflammatory conditions with a polygenic and multifactorial pathogenesis. Intensified treatment early in the disease course of IBD results in better outcomes. This is, however, challenged by the diagnostic delay faced in IBD, and especially in CD. Therefore, markers supporting early and differential diagnosis are needed. In this study, we aimed to discriminate IBD patients from non-IBD controls, and CD from UC patients, using serum protein profiles combined with an IBD polygenic risk score. Methods Patients naïve for immunosuppressives and biologicals, and without previous IBD-related surgery were prospectively included within 3 months after diagnosis, across three Belgian IBD referral centres (PANTHER study). We collected serum from 127 patients (88 CD, 39 UC) and 66 age- and gender-matched non-IBD controls. Relative serum levels of 576 unique proteins were quantified (OLINK). Proteins were ranked according to (1) adjusted (adj.) p values obtained from differential expression analysis; (2) importance scores from machine-learning feature-selection algorithms (univariate feature selection, logistic regression with L2 penalty and Random Forest). For all individuals, a weighted IBD polygenic risk score (PRS) was calculated (PRSice 2.0) for the 242 known IBD risk loci. Receiver operating characteristics (ROC) and area under the curve (AUC) analysis were performed to measure the performance of top-ranked proteins and the IBD PRS (R package ROCR). Results Following statistical analysis, 243 serum proteins were found to be differentially expressed (adj. p &lt; 0.05) between IBD patients and controls. Three top-ranked markers were also identified as top 10 ranked proteins by all feature-selection algorithms, and resulted in a significant AUC of 93% (95% CI: 89–97%) to distinguish IBD from controls. While adding the IBD PRS did not further contribute (AUC 93% [95% CI: 89–97%]), the top-ranked protein on its own had a strong discriminative power with an AUC of 87% (95% CI: 82–92%). When comparing UC and CD, we found 15 differentially expressed proteins. Two proteins ranked within the top 10 across all feature-selection algorithms. This two-marker panel could discriminate UC from CD with an accuracy of 88% (95% CI: 82–96%). Adding the IBD PRS did not further improve the prediction model (AUC=88% [95% CI: 81–96%]). Conclusion Machine learning approaches validated top differentially expressed serum proteins with diagnostic potential in IBD. We identified a three-marker panel classifying IBD patients and non-IBD controls, and a two-marker panel discriminating UC from CD.


2012 ◽  
Vol 9 (2) ◽  
pp. 311-321 ◽  
Author(s):  
Baghdad Science Journal

The amount of protein in the serum depends on the balance between the rate of its synthesis, and that of its catabolism or loss. Abnormal metabolism may result from nutritional deficiency, enzyme deficiency, abnormal secretion of hormones, or the actions of drugs and toxins. Renal cancer is the third most common malignancy of the genitourinary system, and accounts for 3% of adult malignancies globally. Total serum proteins were measured in malignant kidney tumor, benign kidney tumors, and non tumoral kidney diseases patient groups, as well as in healthy individuals. A significant decrease (p< 0.001) of total serum protein levels in patients with malignant kidney tumors when compared with those of benign tumors, non tumoral diseases, and healthy individuals. The lowest serum protein levels were found in patients with stage IV, regardless their genders. Analysis of total serum proteins using PAGE revealed clear differences in the number and shape of the bands in patients with different kidney diseases compared with healthy controls.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1302-1302 ◽  
Author(s):  
Susanne Ragg ◽  
Melissa Key ◽  
Fernanda Rankin ◽  
Monica L. Hulbert

Abstract Introduction: Sickle cell disease (SCD) is a multisystem disease, with substantial variation in presentation and clinical course. Many protein biomarkers have been described in serum and plasma of children with homozygous sickle cell disease. In order to understand the effect of hydroxyurea and the hemoglobin SC genotype on serum protein levels, we compared the relative abundance of serum proteins in healthy children and children with SCD. Methods: The relative concentration of 140 different serum proteins was measured using liquid chromatography tandem mass spectrometry. Serum samples of healthy children and of children with SCD were collected at a baseline visit: 30 healthy African American children without sickle cell trait, 30 children with hemoglobin SS genotype, 30 children with hemoglobin SC (HbSC) genotype, and 30 children with hemoglobin SS (HbSS) genotype while adherent to hydroxyurea for at least one year. All groups were matched for age and gender. Type of SCD, hydroxyurea dose, laboratory values prior to starting hydroxyurea and at the time of sample collection were recorded. Disease and control samples were processed in a random block design stratified by disease, sex, and age to minimize the effect of sample preparation and technician processing. Samples were depleted of albumin and immunoglobulins. Tryptic peptides were analyzed on a linear ion-trap (LTQ) mass spectrometer. The acquired data was searched against the Human UniProt database using X!Tandem. Peptide identification and protein assignment were performed using the PeptideProphet and ProteinProphet in the Trans-Proteomic Pipeline. Alignment and quantification were done as described (Lai, X. et. al. 2011). Peptide-level quantitative information was analyzed for each protein using a mixed effects model fit with restricted maximum likelihood estimation to test the differential abundance of each protein. Within each comparison, the false discovery rate was controlled at 5% using the method of Benjamini and Hochberg. Results: Seventy-one serum proteins were significantly different between the children with HbSS disease and the healthy children. In contrast, between children with HbSS disease treated with hydroxyurea and healthy children, only 56 serum proteins were significantly different. Furthermore, in children with HbSC disease, only 25 serum proteins were significantly different compared to healthy children. In assessing the effect of hydroxyurea treatment on serum protein abundance, we found a total of 50 proteins that were significantly different between the 30 children with HbSS disease not prescribed hydroxyurea and the 30 children who were adherent to hydroxyurea (average 24 mg/kg/day) for at least one year (average 3.3 years). We also found a total of 41 proteins that were significantly different in comparing the 30 children with HbSS disease and the 30 children with HbSC disease. Conclusion: Due to the multisystem nature of sickle cell disease, proteins from many pathways are dysregulated, including inflammatory proteins, hemolysis-associated proteins, proteins involved in coagulation and complement regulation and apolipoproteins. Our findings indicate that the increase of HbF might not be the only beneficial effect of hydroxyurea treatment and that some of the clinical improvement might be due to decreased serum protein dysregulation. Disclosures Hulbert: Pfizer, Inc.: Other: spouse employment.


2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Shefa M. Tawalbeh ◽  
Wilfredo Marin ◽  
Gabrielle A. Morgan ◽  
Utkarsh J. Dang ◽  
Yetrib Hathout ◽  
...  

Abstract Background Blood accessible biomarkers to assess disease activity and their response to therapies in Juvenile Dermatomyositis (JDM) are urgently needed. This pilot study aims to identify serum protein biomarkers associated with clinical disease activity in untreated JDM and their response to medical therapy. Methods SomaScan® technology screened JDM patients for 1305 proteins at three points: 1) before start of treatment, 2) while on therapy, and 3) after treatment tapering when patients were clinically inactive. To define disease associated biomarkers, SomaScan® data from untreated JDM patients (n = 8) were compared to SomaScan® data from an independent age-matched healthy control group (n = 12). Longitudinal analysis defined treatment responsive proteins at three time points: untreated (7 samples), treated (7 samples), and clinically inactive (6 samples). To confirm the SomaScan® data, a subset of nine candidate proteins (CXCL11, IL-17B, IL-17D, IL-22, CXCL10, MCP-1, ANGPT2, MIF, IL-23) were tested by ELISA after adding 2 JDM (one untreated, one clinically inactive) serum samples to the same group of JDM girls (8 untreated, 7 treated; 7 clinically inactive) as well as with 17 age, gender, matched healthy controls. Results Comparison of untreated JDM versus healthy controls identified 202 elevated and 49 decreased serum proteins in JDM patients with an adjusted p-value < 0.001. Only 82 out of 251 identified biomarker candidates responded to treatment while 12 out of these 82 proteins returned to their original untreated disease levels upon therapy tapering. The ELISA testing of the untreated samples for nine candidate proteins confirmed previously known biomarkers (CXCL10 or IP-10, CXCL11 or I-TAC and MCP-1) and identified novel biomarkers including IL-22, Angiopoetin-2, and IL-17B in a cross-sectional analysis comparing 8 untreated JDM and 17 age/gender matched controls. The subsequent longitudinal data by ELISA were not concordant for some biomarkers (IL-22 and IL-17B), but the other biomarkers either normalized or rebounded concordantly. Conclusions Blood accessible protein biomarkers reflecting JDM pathophysiology were identified; some of them rebounded after therapy was tapered. Further studies bridging these biomarkers to specific clinical features of JDM are required to confirm the clinical utility of these serum protein biomarkers.


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