Investigation of serum biomarkers in Rheumatoid and Psoriatic arthritis patients for disease-specific signatures

Investigation of serum biomarkers in Rheumatoid and Psoriatic arthritis patients for disease-specific signatures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigation of serum biomarkers in Rheumatoid and Psoriatic arthritis patients for disease-specific signatures James Veale, Áine Gorman, Douglas Veale, Ursula Fearon, Carl Orr, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6197103/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jul, 2025 Read the published version in Arthritis Research & Therapy → Version 1 posted 10 You are reading this latest preprint version Abstract Background Rheumatoid arthritis (RA) and Psoriatic arthritis (PsA) are systemic auto-immune disease of unknown aetiology that leads to systemic inflammation and synovial joint destruction. Identification of specific serum proteins that selectively regulate these diseases, or which precede disease development could have great potential as disease biomarkers and predictors. Methods Serum level of C-reactive protein (CRP), sICAM-1, sVCAM-1, Serum amyloid A (SAA), Matrix metalloproteinases (MMPs 1,3 and 9) and metabolic markers: Active Glucose-dependent Insulinotropic polypeptide (GIP), active Glucagon-like peptide-1 (GLP-1), C-Peptide, Glucagon, Insulin, Leptin, Pancreatic Polypeptide (PP) were measured by multiplex analysis by MSD assay. Results Serum level of sICAM-1, MMP1, MMP3, PP, c-Peptide, CRP and SAA were specifically upregulated in RA, but not in PsA disease, displaying high sensitivity (ROC curves), thus making them suitable markers for discriminating RA from PsA patients, especially in the early phase of the diseases. Differences in gender, BMI, and disease activity were observed. This is the first study which directly compare serum metabolic markers between diseases and identify specific disease signatures between RA and PsA. In addition, this study, identified that CRP, SAA, GLP-1, GIP-1, Leptin and PP serum protein precede disease onset, as are already altered in the serum of ‘individual at risk’ of developing RA. Of these CRP, SAA, Leptin and PP might predicted IAR conversion to RA+, thus making them suitable candidate for disease prediction. Conclusions Altogether, this study identifies selective serum marker associated with RA and PsA, which are pathotype-specific and are predictor of RA disease onset. Rheumatoid Arthritis Psoriatic Arthritis serum biomarkers inflammation disease pathotypes. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Rheumatoid arthritis (RA) and Psoriatic arthritis (PsA) are two autoimmune systemic disease that affects ~ 1% of the population worldwide leading to synovial joint inflammation, physical disability, and increased mortality. Treating RA and PsA patients early is imperative to reducing disease progression and improving long-term outcomes, therefore latest research is aimed at the identification of biomarkers, in serum and blood, which could predict disease onset and progression. Serologic studies are often used in the RA clinics to determine the presence of autoantibodies, specifically anti–citrullinated protein antibodies (ACPAs) and rheumatic factor (RF), which have been shown to be detectable months to years prior to the onset of clinically identifiable disease, thus serving as current biomarker to identify ‘individual at risk’ (IAR) which may subsequently develop RA ( 1 , 2 ), however these do not account for seronegative RA patients and PsA patients, which normally lack these autoantibodies. Currently, CRP and SAA are often measured in RA and PsA patients to evaluate inflammatory status and has become the gold standard in the monitoring a wide spectrum of inflammatory diseases ( 3 ). In addition, soluble ICAM-1 and VCAM-1 have been shown to be increased in the serum of RA patients and correlate with disease activity ( 4 ). New technologies, such as multi proteomic approaches, have been utilised in the development of protein markers panels that are specific for RA vs PsA ( 5 ). However further studies are required to validate biomarkers that distinguish specific patients’ groups, and importantly needed for identification of novel biomarker which could predict RA onset and progression, as well as the insurgence of co-morbidity, including metabolic dysfunction. This study identifies selective vascular, metabolic and MMPs markers which are differentially expressed in the serum of RA and PsA patients, compared to healthy subjects (HC), and are mostly specific for the RA pathotype. In addition, some of these markers preceded disease onset, as selective proteins were already altered in the serum of IAR patients compared to HC. ROC curves and correlation studies confirmed that the measurement of vascular, metabolic and MMPs markers together, could aid into the identification of disease-specific profile, onset, and progression. Methods Patients’ demographic. Blood was collected from healthy controls (HC n = 15), individual at risk (IAR n = 36), RA (n = 74) and PsA (n = 97) patients, demographic, including age, gender, DAS28 and treatments are found in Table 1. All individuals gave full written consent, and ethics were approved by Saint Vincent University Hospital research ethics committee, Dublin, Ireland. Serum collection . Bloods were collected and centrifuged for 5 minutes at 1800 rpm to collect serum. Serums were aliquoted and stored at -80°C until usage. Multiplex analysis . Serum level of C-reactive protein (CRP), sICAM-1, sVCAM-1, Serum amyloid A (SAA), Matrix metalloproteinases (MMPs 1,3 and 9) and metabolic markers: Active Glucose-dependent Insulinotropic polypeptide (GIP), active Glucagon-like peptide-1 (GLP-1), C-Peptide, Glucagon, Insulin, Leptin, Pancreatic Polypeptide (PP) were measured by multiplex analysis by using MSD assay (Meso Scale Diagnostics, USA) according to the manufacturer’s protocol. Statistical analysis. Data were analysed with the GraphPad Prism 10 software. Differences between groups were analysed by the Non-parametric One-way analysis of variance (ANOVA) Kruskal-Wallis test (*) or non-parametric Mann-Whitney t-test (#) and */ # p < 0.05, **/ ## p < 0.01, ***/ ### p < 0 .001, ****/ #### p < 0.0001 values were considered as significant. Correlation matrices were analysed with non-parametric Spearman correlations, with 95% Confidence Interval. Principal component analysis (PCA) was performed with standardize scale, and loading plots generated. Receiver operator characteristic (ROC) curves were generated with the Wilson/Brown methods and area under the curve were generated. The specific test used can be found detailed in corresponding figure legends. Results Vascular, metabolic and MMPs serum markers are differentially increased in RA and PsA patients. Multiplex analysis was performed to analyse multiple inflammatory and metabolic markers in the serum of RA and PsA patients, using healthy subjects (HC) as control. A strong increase in inflammatory markers CRP and SAA was observed in RA and PsA patients when compared to HC serum (Fig. 1 A p < 0.0001), in accordance with previous studies ( 6 , 7 ), however the values were higher in RA vs PsA patients (p < 0.05). Interestingly, we also observed an increase in soluble ICAM and VCAM protein, both shown to be associated with disease activity ( 4 ), in RA vs HC (p < 0.001 and p < 0.0001), which, however was not observed for PsA patients, displaying significance differences when compared to RA (p < 0.0001 and p < 0.01). Serum MMPs have been shown to be associated with increased inflammation and progression of joint damage in early RA ( 8 , 9 ). In this study, we observed a significant increase in MMP1 and MMP3 (p < 0.01) in the serum of RA patients compared to HCs; in contrast a significant decrease in serum MMP9 was observed (p < 0.05) (Fig. 1 B). Both MMP1 and MMP3 levels were unaltered in PsA vs HC, showing significancy differences when compared to RA (p < 0.001 and p < 0.05), while MMP9 was significantly decreased when compared to HC (p < 0.01). RA and PsA are multifeatured disease which is often associated to different co-morbidities, including obesity, cardiovascular disease and insulin resistance ( 10 , 11 ), therefore we evaluated whether metabolic markers were altered in the serum of RA and PsA patients; interestingly, we observed that active GLP-1 (p < 0.01), GIP-1 (p < 0.0001), Insulin (p < 0.05), PP (p < 0.05) and c-Peptide (p < 0.01) were all significantly increased in the serum of RA patients, when compared to HC (Fig. 1 C). A trending increase in Leptin was also observed, however did not reach statistical significance. Interestingly, GLP-1 levels were increased in PsA patients, at a higher level, when compared to both HC (p < 0.0001) and RA (p < 0.01). GIP-1, Insulin and Leptin were increased in PsA patients vs HC (p < 0.001, p < 0.01 and p < 0.05). In addition, both PP and c-Peptide were unaltered in PsA vs HC and showed significant differences with respect to RA patients (p < 0.05). Altogether, these data suggest that circulatory serum markers are differentially regulated in RA vs PsA patients. We next evaluated whether these markers were correlating with disease activity, and we observed CRP, MMP1, MMP3, Leptin and PP had a trending increase in the high DAS28 (< 3.2) RA cohort vs low DAS28 (< 3.2), however they did not reach significance. (Supplementary Fig. 1A). In PsA trending increases were observed for MMP9 (p = 0.07), Leptin (p = 0.06) and sICAM-1 (p = 0.09), in the high DAS28 vs the low DAS28 groups. The incidence for RA in women is greater than that the observed in men, while PsA affect equally the genders, which a trending increase in men ( 12 – 14 ), overall, however women have a poorer prognosis in terms of long-term pain and disease activity ( 15 , 16 ). In our RA cohort we observed that selective markers were differentially expressed among Female and Male patients, with sVCAM-1 (p = 0.06), MMP3 (p < 0.01) and PP (p < 0.05) being higher in Male vs Female, and Leptin (p < 0.05) being higher in Female vs Male (Supplementary Fig. 1B). In PsA sICAM-1 (p < 0.01), sVCAM-1 (p = 0.08) and Insulin (p < 0.05) were higher in Male, while Leptin (p < 0.01) was higher in the Female cohort. Recent studies have suggested obesity should be considered a confounding factor for RA and PsA disease severity and progression ( 17 , 18 ), therefore, we stratified patients into high BMI (> 25) and low BMI (< 25) (Supplementary Fig. 1C), and observed that selective metabolic markers were higher in the RA BMI high group, including Leptin (p < 0.01) and c-Peptide (p = 0.08). In contrast SAA (p < 0.05) was decreased in the high BMI group. In PsA an increase was observed for CRP (p = 0.07) and GLP-1 (p < 0.05) high BMI group, All the other markers were unaltered between the two groups. RA patients can be divided in two main subgroups based on the presence or absence of autoantibody ( 19 , 20 ) therefore we stratified the RA patients in seropositive vs seronegative patients (Supplementary Fig. 2), based on the presence of RF and/or ACPA. We observed that seropositive RA patients displayed increased serum markers, including CRP (p < 0.05), SAA (p = 0.05), sICAM (p < 0.05), sVCAM (p = 0.07), and GLP-1 (p = 0.07) GIP-1. Altogether, these suggest that the vascular, metabolic and MMPs serum markers analysis are selective altered in specific patients’ subgroups in RA and PsA. Serum markers differentially correlate in disease pathotypes. Correlation matrix and PCA analysis were performed to evaluate the relationship rate among all the serum markers analysed, and to identify a predictive panel of markers disease-specific (Fig. 2 ). When comparing correlation matrixes between RA (Fig. 2 A) and PsA (Fig. 2 B), we can clearly observe a different correlation distribution, which a higher number of markers correlated in RA vs PsA (in blue shades). The analysis of the correlation matrix with non-parametric Spearman correlation, confirmed this observation (Supplementary Fig. 3). For example, MMP1 in RA was significantly correlating with MMP3, MMP9, Insulin, c-Peptide, CRP, SAA and s-ICAM-1, while in PsA it only correlated with MMP9, s-ICAM-1 and s-VCAM-1, with a trending correlation with Glucagon. Principal component analysis (PCA) analysis revealed two defined clusters in RA (Fig. 2 C), with two set of clusters correlating together, in contrast three clusters were identified in PsA. Cluster 1 in RA included sVCAM-1, c-Peptide, sICAM-1, Glucagon, PP, MMP9 and Insulin, while Cluster 2 included MMP1, MMP3, CRP, SAA, GLP-1, GIP-1 and Leptin, thus suggesting the markers within the two clusters might be expressed together in patients. Interestingly, in PsA the markers correlated differently in 3 Clusters, with cluster 1 including GLP-1, GIP-1, Glucagon, Insulin and c-Peptide; Cluster 2 including Leptin, MMP9, PP and MMP3, and Cluster 3 including MMP1, sICAM-1, sVCAM-1, CRP and SAA (Fig. 2 D). All together these data suggest that in RA and PsA serum markers correlate and cluster differently, thus confirming significant differences between the two diseases. Selective serum markers sensitivity makes them great candidate as RA biomarkers. In order to evaluate the diagnostic value of the evaluated serum marker in RA and PsA, we performed receiver operator characteristic (ROC) curve analysis, which allow measurement of the sensitivity and specificity of each marker in RA and PsA vs HC. In RA all the markers analysed resulted in a significant ROC curve (Fig. 3 , in red), except for Glucagon that didn’t show significant sensitivity. CRP, SAA, sICAM-1, sVCAM-1, MMP9, GLP-1, GIP-1 and c-Peptide showed the highest sensitivity. In PsA only CRP, SAA, sVCAM-1, MMP9, GLP-1, GIP-1, Insulin and Leptin were found significant for their sensitivity (Fig. 3 in green). Interestingly, CRP, SAA, GLP-1 and GIP-1 fully overlapped between RA and PsA, thus making them strong candidate markers for both diseases, whereas sICAM-1, MMP1, MMP3, PP and c-Peptide were exclusively significant in RA, thus suggesting that they could be more unique as RA biomarkers. Selective inflammatory, metabolic mediators and MMPs precede disease onset. Having established that selective soluble molecules are altered in the serum of RA patients specifically, we next sought to investigate whether these markers could precede disease onset. Therefore we measured serum markers in ‘individual at risk’ (IAR), a cohort of individuals which have RA autoantibodies in circulation, but they still did not develop any clinical symptoms, however they are at risk of developing seropositive RA within their life time ( 21 , 22 ). We compared the value of serum markers in IAR vs RA + . Interestingly, there was a stepwise increase in inflammatory/vascular markers CRP (p < 0.05) and SAA (p < 0.01), from HC, to IAR, to RA + , (Fig. 4 A), suggesting that the increase in these markers is associated with a susceptibility to development of RA. In contrast MMP9 was significantly decreased in the serum of IAR (p < 0.001), at levels even lower than those observed in RA + (Fig. 4 B). When investigating the metabolic markers, a stepwise increase was observed for active GLP-1 (p < 0.01 vs HC) and GIP-1 (p < 0.001 vs HC) and Leptin (p = 0.07 vs HC) (Fig. 4 C), suggesting these markers were already altered in ‘individual at risk’ of developing RA. We next stratified the individual’s at-risk cohort into non-convertors and convertors to RA + , within the timeframe of the study. Interestingly, we observed that IAR convertors displayed higher levels of CRP (p < 0.01), SAA (p < 0.01), Leptin (p = 0.09) and PP (p < 0.05) (Supplementary Fig. 4), when compared to the individual that did not convert, thus displaying levels like the one observed in established seropositive RA patients. Altogether, this suggest that selective markers might be predictor of disease conversion. Selective inflammatory, metabolic mediators and MMPs could be predictive of disease To investigate whether these soluble markers investigated displayed high sensitivity and could be predictive of RA onset, we compared ROC curves of RA + vs HC (Fig. 5 A red), to the one obtained from IAR and HC (Fig. 5 A in orange); interestingly CRP, SAA and GIP-1 curves overlapped and displayed high sensitivity (p < 0.0001). In addition, MMP9 (RA + p < 0.0001, IAR p < 0.001) GLP-1 (RA + p < 0.0001, IAR p < 0.01), and Leptin (RA + p < 0.05, IAR p = 0.06) also showed comparative profiles. To evaluate the correlation degrees of serums markers in HC vs IAR vs RA, we performed correlations matrixes (Fig. 5 B). The degree of correlations is displayed, and it is clearly visible that in HC there is a little of degree of correlation of these markers, including, for example MMPs correlating to each other (Supplementary Fig. 5). However, in IAR and RA + comparable degree of correlation can be observed, with IAR having correlations in between HC and RA + . Interestingly, selective markers, including sICAM-1, displayed a higher degree of correlation with MMPs and metabolic markers in IAR in respect to RA + (Supplementary Fig. 5). PCA analysis displayed that in both IAR and RA + patients serum markers clustered in 3 area, with Leptin being present in both cluster 1. For Cluster 3, SAA, sICAM-1, c-Peptide, sVCAM-1 and MMP1 clustered together in both IAR and RA + (Fig. 5 C) thus suggesting that the measurements of these markers together might aid in identify individual at risk which might convert to RA + . Discussion Rheumatoid and psoriatic arthritis have overlapping clinical manifestation, especially at the early phase of the disease, which render a specific diagnosis difficult ( 19 , 23 , 24 ); one of the main biomarker which can distinguish RA from PsA, are the presence/absence of autoantibodies, however a proportion of RA patients do not present autoantibodies, and recent studies suggest that antibodies against citrullinated proteins (ACPAs) are also found in 5.0–17.5% of PsA patients ( 25 , 26 ). In light of these observations, identifying novel biomarkers which distinguish RA from PsA, could help in disease stratification, and in an early specific diagnosis. In this work we explore the presence of 14 serum proteins in RA and PsA patients, in the area of vascularity, metabolism and cartilage degradation, and we investigated how these could be differentially expressed between the two diseases. CRP is the gold standard biomarkers in the monitoring inflammatory diseases, and especially in RA ( 3 ), whereas in PsA, only ~ 50% of the patients have high level of this marker, also in the presence of active disease( 27 ). Our results are consistent with these observations, displaying high levels of CRP in both RA and PsA, but with a significantly higher levels observe in RA vs PsA. SAA protein is expressed in inflamed synovial tissue, therefore it is considered a better marker for Inflammatory Rheumatic Diseases (IRD)( 7 ); our data demonstrated that, like CRP, this marker is upregulated in RA patients at higher level in respect to PsA, thus suggesting a more significant role in RA vs PsA diseases. Soluble ICAM-1 and VCAM-1 have been shown to be increased in the serum of RA patients and correlate with disease activity ( 4 ), however little is known about their role in PsA patients. Our data suggest that both sICAM-1 and sVCAM-1 are expressed in a RA > PsA > HC fashion, with sVCAM-1 being significantly higher in RA vs PsA patients. Interestingly, among these markers CRP and sICAM-1 correlated with disease activity (DAS28) in PsA at a higher degree that the one observed in RA. In addition, both sICAM-1 and sVCAM-1 were higher in the male cohort in respect to the female cohort, and sICAM-1 displayed higher level in patients with a BMI > 25 in PsA patients. When stratifying RA patients in seropositive and seronegative all four vascular markers were found higher in the RA + serum. MMPs have an important role in in the destruction of articular cartilage in both RA and PsA( 28 , 29 ). In our cohort we observed that both MMP1 and 3 in were increased in the serum of RA patients compared to healthy and PsA. This is in agreement with previous studies which have shown an increase in serum MMP1 and MMP3, and their association to erosion and disease progression in RA( 8 , 30 ), although display for the first time the difference in expression among the two diseases. Interestingly, we observed that MMP9 was significantly downregulated in both RA and PsA patients (HC > RA > PsA). The literature on serum MMP9 levels is contradictory, with previous studies showing either an increase ( 31 ) or a decrease of MMP9 ( 32 ) in the serum of RA patients. MMP9 has been shown to be sensitive to biologics treatments, including Infliximab ( 33 ). When stratifying our cohort into naïve, patients receiving bDMARDs or csDMARDS, we observed that patients on biologics showed the highest decrease in serum MMP9 in respect to healthy subjects (Supplementary Fig. 6), thus agreeing with previous observations. Interestingly, MMP3 were showed trending increase in the high DAS28 cohort in RA only, thus confirming it might act as a specific biomarker for RA. Interesting MMP3 was found higher in the Male cohort in RA only, thus suggesting a gender confounder in its regulation. Obesity and increased body mass index has been associated with a higher severity of RA and PsA disease ( 17 , 34 – 36 ), however the results remain elusive and directive comparative studies are required. Here we observed that metabolic PP and c-Peptide were increased exclusivity in the serum of RA patients, with levels in PsA similar to the HC. GIP-1 was increased in a RA > PsA > HC fashion. Interestingly GLP-1, Insulin and Leptin were increased in PsA more than RA and HC. Of these Leptin was higher in high DAS28 samples in PsA, while PP was higher in the RA high DAS28 cohort and most of the metabolic markers were higher in the high BMI group, thus confirming their connection with obesity. This is the first study which directly compare serum metabolic markers between diseases and identify specific disease signatures between RA and PsA. ROC analysis identifies specific markers highly sensitive for RA but not PsA disease, these included sICAM-1, MMP1, MMP3, PP and c-Peptide, therefore we believe that measuring these markers, together with the classical CRP and SAA, could aid in discriminating RA from PsA diseases, thus helping with diagnosis and specific treatment. In addition, correlation matrixes confirmed a high degree of correlation of these markers in RA, among themselves and in relation to the classical inflammatory markers CRP and SAA, thus making them great candidate for disease stratification. A bigger cohort of patients is necessary to validate these observations. In the second part of the study, we were interested to investigate whether the specific RA-serum markers could precede disease onset, and for this reason we measure serum levels in individual-at-risk of developing RA. These individuals already present autoantibodies in circulation and are at high change to develop RA, but they still don’t present clinical symptoms and inflammation( 1 , 2 ). Previous studies from our team have demonstrated that these individuals already present cellular dysregulation, with circulatory cells being metabolic active ( 37 , 38 ). Interestingly, in our cohort, CRP, SAA, GLP-1, GIP-1, Leptin and PP were all already significantly increased in the serum of IAR when compared to HC, with levels in between HC and RA (RA > IAR > HC), thus indicating that these markers could predict disease onset. Interestingly, CRP, SAA, Leptin and PP markers were predictors protein for RA conversions, resulting increased at level similar to the one observed to RA + in the individual that converted to RA within the timeframe of this study. These markers all showed a great degree of sensitive and fully overlapped with RA ROC curves, and a high degree of correlation among themselves, thus making them great candidate for RA disease predictors. Overall, this study identified for the first time serum proteins sICAM-1, MMP1, MMP3, PP, c-Peptide, CRP and SAA which are specific for RA disease and could aid in discriminating RA from PsA patients, especially in the early phase of the diseases. In addition, this study, identified that CRP, SAA, GLP-1, GIP-1, Leptin and PP serum protein precede disease onset, as are already altered in the serum of IAR. Of these CRP, SAA, Leptin and PP might predict IAR conversion to RA + , thus making them great candidate for disease progression. Declarations Ethical approval This study was approved by Saint Vincent University Hospital research ethics committee, Dublin, Ireland. Written informed was obtained from the participant. All authors have critically reviewed and approved the final manuscript to be published. Consent for publication Not applicable Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Data availability No datasets were generated or analysed during the current study. Funding: This research was funded by Center for Arthritis and Rheumatic Diseases, CARD 2019-01, Science Foundation Ireland-Irish Research Council pathway 21/PATH-S/9327 and Arthritis Ireland. Author Contributions: VM, CO and UF: conceptualization, visualization, and supervision. VM, CO, AG, JV, DV and UF: methodology and writing—original draft preparation. JV, AG, VM: validation, formal analysis, and investigation. VM, UF, DV: resources and funding acquisition. VM: project administration. All authors contributed to the article and approved the submitted version. Acknowledgments : The authors would like to thank the excellent staff in the Rheumatology Department in SVUH for all the help in patients’ recruitment. In addition, they express sincere thanks to all the patients who consented to be involved in this study. References Boeters DM, Raza K, Mil AHMvanderH, Review. Which patients presenting with arthralgia eventually develop rheumatoid arthritis? The current state of the art. RMD Open [Internet]. 2017 Nov [cited 2023 Jun 19];3(2):e000479. Available from: /pmc/articles/PMC5687532/ Novella-Navarro M, Plasencia-Rodríguez C, Nuño L, Balsa A. Risk Factors for Developing Rheumatoid Arthritis in Patients With Undifferentiated Arthritis and Inflammatory Arthralgia. Frontiers in Medicine. Volume 8. Frontiers Media S.A.; 2021. p. 668898. 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Specific Autoantibodies Precede the Symptoms of Rheumatoid Arthritis: A Study of Serial Measurements in Blood Donors. Arthritis Rheum. 2004;50(2):380–6. Gerlag DM, Raza K, Van Baarsen LGM, Brouwer E, Buckley CD, Burmester GR, et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: Report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann Rheum Dis. 2012;71(5):638–41. Ohta R, Sano C. Challenges in Diagnosing Psoriatic Arthritis in Primary Care: A Meta-Ethnographic Study. Cureus [Internet]. 2023 Nov 26 [cited 2025 Mar 5];15(11):e49443. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10750965/ Karmacharya P, Wright K, Achenbach SJ, Bekele D, Crowson CS, Ogdie A et al. Diagnostic Delay in Psoriatic Arthritis: A Population-based Study. J Rheumatol [Internet]. 2021 Sep 1 [cited 2025 Mar 5];48(9):1410–6. Available from: https://www.jrheum.org/content/48/9/1410 Zhu J, Shi XF, Chu CQ. Autoantibodies in psoriatic arthritis: are they of pathogenic relevance? Chin Med J (Engl) [Internet]. 2020 Dec 20 [cited 2025 Mar 5];133(24):2899. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7752680/ Behrens F, Koehm M, Thaçi D, Gnann H, Greger G, Wittig BM et al. Anti-citrullinated protein antibodies are linked to erosive disease in an observational study of patients with psoriatic arthritis. Rheumatology (Oxford) [Internet]. 2016 Oct 1 [cited 2025 Mar 5];55(10):1791. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC5034218/ Houttekiet C, De Vlam K, Neerinckx B, Lories R. Systematic review of the use of CRP in clinical trials for psoriatic arthritis: a concern for clinical practice? RMD Open [Internet]. 2022 Feb 1 [cited 2025 Mar 5];8(1):e001756. Available from: https://rmdopen.bmj.com/content/8/1/e001756 Burrage PS, Mix KS, Brinckerhoff CE. Matrix metalloproteinases: Role in arthritis. Front Biosci. 2006;11(1 P447–888):529–43. Malemud CJ. Matrix Metalloproteinases and Synovial Joint Pathology. Prog Mol Biol Transl Sci [Internet]. 2017 [cited 2025 Mar 5];148:305–25. Available from: https://pubmed.ncbi.nlm.nih.gov/28662824/ Ribbens C, Martin y Porras M, Franchimont N, Kaiser MJ, Jaspar JM, Damas P, et al. Increased matrix metalloproteinase-3 serum levels in rheumatic diseases: Relationship with synovitis and steroid treatment. Ann Rheum Dis [Internet]. 2002;61(2):161–6. Available from: /pmc/articles/PMC1753989/. Hasan HA, Al-Hadithi HS, Gorial FI. Validity of Serum Matrix Metalloproteinase 9 in Diagnosis of Rheumatoid Arthritis: A Case-Control Study from Iraq. J Nat Sci Res [Internet]. 2016 [cited 2024 Mar 4];6(12):44–7. Available from: https://iiste.org/Journals/index.php/JNSR/article/view/31354 Rahat MA, Safieh M, Simanovich E, Pasand E, Gazitt T, Haddad A et al. The role of EMMPRIN/CD147 in regulating angiogenesis in patients with psoriatic arthritis. Arthritis Res Ther [Internet]. 2020 Dec 1 [cited 2024 Feb 21];22(1):1–12. Available from: https://arthritis-research.biomedcentral.com/articles/ 10.1186/s13075-020-02333-6 Kotani T, Takeuchi T, Takai S, Yoshida S, Hata K, Nagai K, et al. Serum Levels of Matrix Metalloproteinase (MMP) 9, a Risk Factor for Acute Coronary Syndrome, Are Reduced Independently of Serum MMP-3 by Anti-TNF-α Antibody (Infliximab) Therapy in Patients With Rheumatoid Arthritis. J Pharmacol Sci. 2012;120(1):50–3. Iqbal SM, Burns L, Grisanti J. Effect of Body Mass Index on the Disease Activity of Patients With Rheumatoid Arthritis in a Gender-Specific Manner and the Association of Respective Serum C-Reactive Protein Levels With the Body’s Inflammatory Status. Baker JF, England BR, Mikuls TR, Sayles H, Cannon GW, Sauer BC et al. Obesity, Weight Loss, and Progression of Disability in Rheumatoid Arthritis. Arthritis Care Res [Internet]. 2018 Dec 1 [cited 2024 Mar 4];70(12):1740–7. Available from: /pmc/articles/PMC6205912/. Kumthekar A, Ogdie A. Obesity and Psoriatic Arthritis: A Narrative Review. Rheumatol Ther [Internet]. 2020 Sep 1 [cited 2025 Mar 5];7(3):447. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7410935/ McGarry T, Hanlon MM, Marzaioli V, Cunningham CC, Krishna V, Murray K et al. Rheumatoid arthritis CD14 + monocytes display metabolic and inflammatory dysfunction, a phenotype that precedes clinical manifestation of disease. Clin Transl Immunol [Internet]. 2021 [cited 2021 Apr 22];10(1). Available from: Cunningham CC, Wade S, Floudas A, Orr C, McGarry T, Wade S et al. Serum miRNA Signature in Rheumatoid Arthritis and At-Risk Individuals. Front Immunol [Internet]. 2021 Mar 3 [cited 2025 Mar 5];12:633201. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7966707/ Tables Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1demographics.doc VealeandMarzaiolisupplementaryfigures2025.pptx Cite Share Download PDF Status: Published Journal Publication published 10 Jul, 2025 Read the published version in Arthritis Research & Therapy → Version 1 posted Editorial decision: Revision requested 15 May, 2025 Reviews received at journal 07 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviewers agreed at journal 30 Apr, 2025 Reviews received at journal 04 Apr, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers invited by journal 23 Mar, 2025 Editor assigned by journal 14 Mar, 2025 Submission checks completed at journal 14 Mar, 2025 First submitted to journal 10 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6197103","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":434144327,"identity":"b6b54865-4208-451c-bbc1-096e35928dc2","order_by":0,"name":"James Veale","email":"","orcid":"","institution":"Trinity College Dublin","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Veale","suffix":""},{"id":434144328,"identity":"a688124e-bf45-4ae3-be8b-ee20bd5aa680","order_by":1,"name":"Áine Gorman","email":"","orcid":"","institution":"University College Dublin","correspondingAuthor":false,"prefix":"","firstName":"Áine","middleName":"","lastName":"Gorman","suffix":""},{"id":434144329,"identity":"f94f52ef-4232-41de-b39a-4948f5182fba","order_by":2,"name":"Douglas Veale","email":"","orcid":"","institution":"University College Dublin","correspondingAuthor":false,"prefix":"","firstName":"Douglas","middleName":"","lastName":"Veale","suffix":""},{"id":434144330,"identity":"be4f8971-58b7-4437-a8d6-eb88cf580723","order_by":3,"name":"Ursula Fearon","email":"","orcid":"","institution":"Trinity College Dublin","correspondingAuthor":false,"prefix":"","firstName":"Ursula","middleName":"","lastName":"Fearon","suffix":""},{"id":434144332,"identity":"5a4783c4-0751-45ab-b771-3a6b02e33bc1","order_by":4,"name":"Carl Orr","email":"","orcid":"","institution":"University College Dublin","correspondingAuthor":false,"prefix":"","firstName":"Carl","middleName":"","lastName":"Orr","suffix":""},{"id":434144336,"identity":"1078b098-c59a-4360-99b8-033b569dcd14","order_by":5,"name":"Viviana Marzaioli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYNACAwYGfiAlAWIQr0WyjTQtIF3HQFqIAbrtZx9/+FFgk7j5fvPDGwwFNoS1mJ1JNzDsMUhL3HaMzdiCwSCNCC0H0hgSeAwOG5sd42ED+uUwEVrOP2M4+AeoxbgNrOU/EVpupDE2A22RM2ADazlAjJZnzMwyBmlyEsfSjC0SDJKJcVga88c3f2x4+JsPP7zx4Y8dYS2oIIFUDaNgFIyCUTAKsAMAq2oyL6aIDwQAAAAASUVORK5CYII=","orcid":"","institution":"Trinity College Dublin","correspondingAuthor":true,"prefix":"","firstName":"Viviana","middleName":"","lastName":"Marzaioli","suffix":""}],"badges":[],"createdAt":"2025-03-10 15:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6197103/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6197103/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13075-025-03608-6","type":"published","date":"2025-07-10T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79665720,"identity":"9e019956-4cf9-4055-9146-7d5342cf5c1b","added_by":"auto","created_at":"2025-04-01 10:09:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVascular, metabolic and MMPs serum markers are differentially increased in RA and PsA patients\u003c/strong\u003e. Serum from HC (n=15), RA (n=74) and PsA (n=97) patients were collected, and MSD multiplex analysis was performed. \u003cstrong\u003eA)\u003c/strong\u003e vascular markers \u003cstrong\u003eB)\u003c/strong\u003e MMPs, and \u003cstrong\u003eC)\u003c/strong\u003e metabolic markers. Data are presented as Mean ± SEM and statistical differences among groups were obtained with non-parametric One-way ANOVA analysis (Kruskal-Wallis test with Dunn’s post-hoc test).\u0026nbsp; *p \u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, **** p\u0026lt;0001. Due the high heterogenicity of the samples, selective pairs were further analysis with Mann–Whitney t-test. \u003csup\u003e#\u003c/sup\u003ep \u0026lt;0.05, \u003csup\u003e##\u003c/sup\u003e p\u0026lt;0.01, \u003csup\u003e###\u003c/sup\u003e p\u0026lt;0.001, \u003csup\u003e#### \u003c/sup\u003ep\u0026lt;0001.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/2c7f819aa90a54a27a1e799b.jpg"},{"id":79665724,"identity":"8ddb456b-ee32-4258-9aeb-1a08b19a806c","added_by":"auto","created_at":"2025-04-01 10:09:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":140365,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelective serum markers are differentially correlated and clustered in RA and PsA patients. \u003c/strong\u003eSerum from HC (n=15), RA (n=74) and PsA (n=97) patients were collected, and MSD multiplex analysis was performed. Non-parametric Spearman correlation matrixes were obtained and heatmaps created for \u003cstrong\u003eA)\u003c/strong\u003e RA and \u003cstrong\u003eB)\u003c/strong\u003e PsA patients. p-values associated with the correlation matrix can be found in the Supplementary Figure 3. PCA analysis for \u003cstrong\u003eC)\u003c/strong\u003eRA and \u003cstrong\u003eD)\u003c/strong\u003e PsA patients. Standardize analysis was used for the PCA analysis and loadings for PC1 and PC2 are shown.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/60c92593b81d6318731c3dfe.jpg"},{"id":79665728,"identity":"8feec7ce-ca2e-48ff-92b5-21a6c037f636","added_by":"auto","created_at":"2025-04-01 10:09:33","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":142562,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpecificity and sensitivity of serum markers in RA and PsA patients. \u003c/strong\u003eReceiver operating characteristic (ROC) curves for RA vs HC (in red) and PsA vs HC (in red) with Wilson/Brown method and CI of 95%. AUC under the curves and p value are expressed for \u003cstrong\u003eA)\u003c/strong\u003e vascular markers \u003cstrong\u003eB)\u003c/strong\u003eMMPs, and \u003cstrong\u003eC)\u003c/strong\u003e metabolic markers. *p \u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, **** p\u0026lt;0001\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/f8a7257e440fa884307c1b70.jpg"},{"id":79665725,"identity":"5295234b-32b2-40f8-a528-099fc7d3f6d3","added_by":"auto","created_at":"2025-04-01 10:09:33","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVascular, metabolic and MMPs serum precede RA disease onset\u003c/strong\u003e. Serum from HC (n=15), IAR (n=44) and RA\u003csup\u003e+\u003c/sup\u003e (n=53) patients were collected, and MSD multiplex analysis was performed. \u003cstrong\u003eA)\u003c/strong\u003e vascular markers \u003cstrong\u003eB)\u003c/strong\u003e MMPs, and \u003cstrong\u003eC)\u003c/strong\u003e metabolic markers. Data are presented as Mean ± SEM and statistical differences among groups were obtained with non-parametric One-way ANOVA analysis (Kruskal-Wallis test with Dunn’s post-hoc test).\u0026nbsp; *p \u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, **** p\u0026lt;0001. Due the high heterogenicity of the samples, selective pairs were further analysis with Mann–Whitney t-test. \u003csup\u003e#\u003c/sup\u003ep \u0026lt;0.05, \u003csup\u003e##\u003c/sup\u003e p\u0026lt;0.01, \u003csup\u003e###\u003c/sup\u003e p\u0026lt;0.001, \u003csup\u003e#### \u003c/sup\u003ep\u0026lt;0001.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/7f97a0e8e8946b5a2035f90e.jpg"},{"id":79666324,"identity":"05a4de83-dc37-4890-a262-55e490c48d30","added_by":"auto","created_at":"2025-04-01 10:17:33","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":140553,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpecificity and sensitivity of serum markers in IAR and RA\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003epatients. A) \u003c/strong\u003eReceiver operating characteristic (ROC) curves for RA\u003csup\u003e+\u003c/sup\u003e vs HC (in red) and IAR vs HC (in orange) with Wilson/Brown method and CI of 95%. AUC under the curves and p value are expressed for selective serum markers. *p \u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, **** p\u0026lt;0001. \u003cstrong\u003eB) \u003c/strong\u003eNon-parametric Spearman correlation matrixes were obtained and heatmaps created for HC, IAR and RA\u003csup\u003e+\u003c/sup\u003e patients.\u0026nbsp; p-values associated with the correlation matrix can be found in the Supplementary Figure 5. \u003cstrong\u003eC)\u003c/strong\u003e PCA analysis for IAR and RA\u003csup\u003e+\u003c/sup\u003e patients. Standardize analysis was used for the PCA analysis and loadings for PC1 and PC2 are shown.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/cf433813c7ea03f998a1e31a.jpg"},{"id":86699410,"identity":"d8aa51d3-4fbb-4e6c-90e4-862205992b3a","added_by":"auto","created_at":"2025-07-14 16:09:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1485153,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/e1b7433d-93a0-40eb-b5cf-cf6f3938e1f4.pdf"},{"id":79666322,"identity":"798aca6b-f4ff-49c6-9ee4-fdb4add3586d","added_by":"auto","created_at":"2025-04-01 10:17:33","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":226816,"visible":true,"origin":"","legend":"","description":"","filename":"Table1demographics.doc","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/afde2dccf9ce6fb81d53b91a.doc"},{"id":79665726,"identity":"eca6732d-f03f-42db-891d-4db66393cf2d","added_by":"auto","created_at":"2025-04-01 10:09:33","extension":"pptx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4576340,"visible":true,"origin":"","legend":"","description":"","filename":"VealeandMarzaiolisupplementaryfigures2025.pptx","url":"https://assets-eu.researchsquare.com/files/rs-6197103/v1/c9c648b578fd9ae8226c974e.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigation of serum biomarkers in Rheumatoid and Psoriatic arthritis patients for disease-specific signatures","fulltext":[{"header":"Background","content":"\u003cp\u003eRheumatoid arthritis (RA) and Psoriatic arthritis (PsA) are two autoimmune systemic disease that affects\u0026thinsp;~\u0026thinsp;1% of the population worldwide leading to synovial joint inflammation, physical disability, and increased mortality. Treating RA and PsA patients early is imperative to reducing disease progression and improving long-term outcomes, therefore latest research is aimed at the identification of biomarkers, in serum and blood, which could predict disease onset and progression. Serologic studies are often used in the RA clinics to determine the presence of autoantibodies, specifically anti\u0026ndash;citrullinated protein antibodies (ACPAs) and rheumatic factor (RF), which have been shown to be detectable months to years prior to the onset of clinically identifiable disease, thus serving as current biomarker to identify \u0026lsquo;individual at risk\u0026rsquo; (IAR) which may subsequently develop RA (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), however these do not account for seronegative RA patients and PsA patients, which normally lack these autoantibodies. Currently, CRP and SAA are often measured in RA and PsA patients to evaluate inflammatory status and has become the gold standard in the monitoring a wide spectrum of inflammatory diseases (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In addition, soluble ICAM-1 and VCAM-1 have been shown to be increased in the serum of RA patients and correlate with disease activity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). New technologies, such as multi proteomic approaches, have been utilised in the development of protein markers panels that are specific for RA vs PsA (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However further studies are required to validate biomarkers that distinguish specific patients\u0026rsquo; groups, and importantly needed for identification of novel biomarker which could predict RA onset and progression, as well as the insurgence of co-morbidity, including metabolic dysfunction.\u003c/p\u003e \u003cp\u003eThis study identifies selective vascular, metabolic and MMPs markers which are differentially expressed in the serum of RA and PsA patients, compared to healthy subjects (HC), and are mostly specific for the RA pathotype. In addition, some of these markers preceded disease onset, as selective proteins were already altered in the serum of IAR patients compared to HC. ROC curves and correlation studies confirmed that the measurement of vascular, metabolic and MMPs markers together, could aid into the identification of disease-specific profile, onset, and progression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003ePatients\u0026rsquo; demographic.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBlood was collected from healthy controls (HC n\u0026thinsp;=\u0026thinsp;15), individual at risk (IAR n\u0026thinsp;=\u0026thinsp;36), RA (n\u0026thinsp;=\u0026thinsp;74) and PsA (n\u0026thinsp;=\u0026thinsp;97) patients, demographic, including age, gender, DAS28 and treatments are found in Table\u0026nbsp;1. All individuals gave full written consent, and ethics were approved by Saint Vincent University Hospital research ethics committee, Dublin, Ireland.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSerum collection\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eBloods were collected and centrifuged for 5 minutes at 1800 rpm to collect serum. Serums were aliquoted and stored at -80\u0026deg;C until usage.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMultiplex analysis\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eSerum level of C-reactive protein (CRP), sICAM-1, sVCAM-1, Serum amyloid A (SAA), Matrix metalloproteinases (MMPs 1,3 and 9) and metabolic markers: Active Glucose-dependent Insulinotropic polypeptide (GIP), active Glucagon-like peptide-1 (GLP-1), C-Peptide, Glucagon, Insulin, Leptin, Pancreatic Polypeptide (PP) were measured by multiplex analysis by using MSD assay (Meso Scale Diagnostics, USA) according to the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis.\u003c/h2\u003e \u003cp\u003eData were analysed with the GraphPad Prism 10 software. Differences between groups were analysed by the Non-parametric One-way analysis of variance (ANOVA) Kruskal-Wallis test (*) or non-parametric Mann-Whitney t-test (#) and */\u003csup\u003e#\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **/\u003csup\u003e##\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***/\u003csup\u003e###\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0 .001, ****/\u003csup\u003e####\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 values were considered as significant. Correlation matrices were analysed with non-parametric Spearman correlations, with 95% Confidence Interval. Principal component analysis (PCA) was performed with standardize scale, and loading plots generated. Receiver operator characteristic (ROC) curves were generated with the Wilson/Brown methods and area under the curve were generated. The specific test used can be found detailed in corresponding figure legends.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eVascular, metabolic and MMPs serum markers are differentially increased in RA and PsA patients.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMultiplex analysis was performed to analyse multiple inflammatory and metabolic markers in the serum of RA and PsA patients, using healthy subjects (HC) as control. A strong increase in inflammatory markers CRP and SAA was observed in RA and PsA patients when compared to HC serum (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), in accordance with previous studies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), however the values were higher in RA \u003cem\u003evs\u003c/em\u003e PsA patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Interestingly, we also observed an increase in soluble ICAM and VCAM protein, both shown to be associated with disease activity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), in RA vs HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), which, however was not observed for PsA patients, displaying significance differences when compared to RA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eSerum MMPs have been shown to be associated with increased inflammation and progression of joint damage in early RA (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In this study, we observed a significant increase in MMP1 and MMP3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in the serum of RA patients compared to HCs; in contrast a significant decrease in serum MMP9 was observed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Both MMP1 and MMP3 levels were unaltered in PsA vs HC, showing significancy differences when compared to RA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while MMP9 was significantly decreased when compared to HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eRA and PsA are multifeatured disease which is often associated to different co-morbidities, including obesity, cardiovascular disease and insulin resistance (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), therefore we evaluated whether metabolic markers were altered in the serum of RA and PsA patients; interestingly, we observed that active GLP-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), GIP-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), Insulin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), PP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and c-Peptide (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were all significantly increased in the serum of RA patients, when compared to HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). A trending increase in Leptin was also observed, however did not reach statistical significance. Interestingly, GLP-1 levels were increased in PsA patients, at a higher level, when compared to both HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and RA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). GIP-1, Insulin and Leptin were increased in PsA patients \u003cem\u003evs\u003c/em\u003e HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, both PP and c-Peptide were unaltered in PsA vs HC and showed significant differences with respect to RA patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAltogether, these data suggest that circulatory serum markers are differentially regulated in RA vs PsA patients.\u003c/p\u003e \u003cp\u003eWe next evaluated whether these markers were correlating with disease activity, and we observed CRP, MMP1, MMP3, Leptin and PP had a trending increase in the high DAS28 (\u0026lt;\u0026thinsp;3.2) RA cohort \u003cem\u003evs\u003c/em\u003e low DAS28 (\u0026lt;\u0026thinsp;3.2), however they did not reach significance. (Supplementary Fig.\u0026nbsp;1A). In PsA trending increases were observed for MMP9 (p\u0026thinsp;=\u0026thinsp;0.07), Leptin (p\u0026thinsp;=\u0026thinsp;0.06) and sICAM-1 (p\u0026thinsp;=\u0026thinsp;0.09), in the high DAS28 vs the low DAS28 groups.\u003c/p\u003e \u003cp\u003eThe incidence for RA in women is greater than that the observed in men, while PsA affect equally the genders, which a trending increase in men (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), overall, however women have a poorer prognosis in terms of long-term pain and disease activity (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In our RA cohort we observed that selective markers were differentially expressed among Female and Male patients, with sVCAM-1 (p\u0026thinsp;=\u0026thinsp;0.06), MMP3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and PP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) being higher in Male vs Female, and Leptin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) being higher in Female vs Male (Supplementary Fig.\u0026nbsp;1B). In PsA sICAM-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), sVCAM-1 (p\u0026thinsp;=\u0026thinsp;0.08) and Insulin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were higher in Male, while Leptin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was higher in the Female cohort.\u003c/p\u003e \u003cp\u003eRecent studies have suggested obesity should be considered a confounding factor for RA and PsA disease severity and progression (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), therefore, we stratified patients into high BMI (\u0026gt;\u0026thinsp;25) and low BMI (\u0026lt;\u0026thinsp;25) (Supplementary Fig.\u0026nbsp;1C), and observed that selective metabolic markers were higher in the RA BMI high group, including Leptin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and c-Peptide (p\u0026thinsp;=\u0026thinsp;0.08). In contrast SAA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was decreased in the high BMI group. In PsA an increase was observed for CRP (p\u0026thinsp;=\u0026thinsp;0.07) and GLP-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) high BMI group, All the other markers were unaltered between the two groups.\u003c/p\u003e \u003cp\u003eRA patients can be divided in two main subgroups based on the presence or absence of autoantibody (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) therefore we stratified the RA patients in seropositive \u003cem\u003evs\u003c/em\u003e seronegative patients (Supplementary Fig.\u0026nbsp;2), based on the presence of RF and/or ACPA. We observed that seropositive RA patients displayed increased serum markers, including CRP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), SAA (p\u0026thinsp;=\u0026thinsp;0.05), sICAM (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), sVCAM (p\u0026thinsp;=\u0026thinsp;0.07), and GLP-1 (p\u0026thinsp;=\u0026thinsp;0.07) GIP-1.\u003c/p\u003e \u003cp\u003eAltogether, these suggest that the vascular, metabolic and MMPs serum markers analysis are selective altered in specific patients\u0026rsquo; subgroups in RA and PsA.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSerum markers differentially correlate in disease pathotypes.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCorrelation matrix and PCA analysis were performed to evaluate the relationship rate among all the serum markers analysed, and to identify a predictive panel of markers disease-specific (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When comparing correlation matrixes between RA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and PsA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), we can clearly observe a different correlation distribution, which a higher number of markers correlated in RA \u003cem\u003evs\u003c/em\u003e PsA (in blue shades). The analysis of the correlation matrix with non-parametric Spearman correlation, confirmed this observation (Supplementary Fig.\u0026nbsp;3). For example, MMP1 in RA was significantly correlating with MMP3, MMP9, Insulin, c-Peptide, CRP, SAA and s-ICAM-1, while in PsA it only correlated with MMP9, s-ICAM-1 and s-VCAM-1, with a trending correlation with Glucagon.\u003c/p\u003e \u003cp\u003ePrincipal component analysis (PCA) analysis revealed two defined clusters in RA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), with two set of clusters correlating together, in contrast three clusters were identified in PsA. Cluster 1 in RA included sVCAM-1, c-Peptide, sICAM-1, Glucagon, PP, MMP9 and Insulin, while Cluster 2 included MMP1, MMP3, CRP, SAA, GLP-1, GIP-1 and Leptin, thus suggesting the markers within the two clusters might be expressed together in patients. Interestingly, in PsA the markers correlated differently in 3 Clusters, with cluster 1 including GLP-1, GIP-1, Glucagon, Insulin and c-Peptide; Cluster 2 including Leptin, MMP9, PP and MMP3, and Cluster 3 including MMP1, sICAM-1, sVCAM-1, CRP and SAA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). All together these data suggest that in RA and PsA serum markers correlate and cluster differently, thus confirming significant differences between the two diseases.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSelective serum markers sensitivity makes them great candidate as RA biomarkers.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn order to evaluate the diagnostic value of the evaluated serum marker in RA and PsA, we performed receiver operator characteristic (ROC) curve analysis, which allow measurement of the sensitivity and specificity of each marker in RA and PsA \u003cem\u003evs\u003c/em\u003e HC. In RA all the markers analysed resulted in a significant ROC curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, in red), except for Glucagon that didn\u0026rsquo;t show significant sensitivity. CRP, SAA, sICAM-1, sVCAM-1, MMP9, GLP-1, GIP-1 and c-Peptide showed the highest sensitivity. In PsA only CRP, SAA, sVCAM-1, MMP9, GLP-1, GIP-1, Insulin and Leptin were found significant for their sensitivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e in green). Interestingly, CRP, SAA, GLP-1 and GIP-1 fully overlapped between RA and PsA, thus making them strong candidate markers for both diseases, whereas sICAM-1, MMP1, MMP3, PP and c-Peptide were exclusively significant in RA, thus suggesting that they could be more unique as RA biomarkers.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSelective inflammatory, metabolic mediators and MMPs precede disease onset.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eHaving established that selective soluble molecules are altered in the serum of RA patients specifically, we next sought to investigate whether these markers could precede disease onset. Therefore we measured serum markers in \u0026lsquo;individual at risk\u0026rsquo; (IAR), a cohort of individuals which have RA autoantibodies in circulation, but they still did not develop any clinical symptoms, however they are at risk of developing seropositive RA within their life time (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). We compared the value of serum markers in IAR vs RA\u003csup\u003e+\u003c/sup\u003e. Interestingly, there was a stepwise increase in inflammatory/vascular markers CRP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and SAA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), from HC, to IAR, to RA\u003csup\u003e+\u003c/sup\u003e, (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), suggesting that the increase in these markers is associated with a susceptibility to development of RA.\u003c/p\u003e \u003cp\u003eIn contrast MMP9 was significantly decreased in the serum of IAR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), at levels even lower than those observed in RA\u003csup\u003e+\u003c/sup\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eWhen investigating the metabolic markers, a stepwise increase was observed for active GLP-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 \u003cem\u003evs\u003c/em\u003e HC) and GIP-1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 \u003cem\u003evs\u003c/em\u003e HC) and Leptin (p\u0026thinsp;=\u0026thinsp;0.07 vs HC) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), suggesting these markers were already altered in \u0026lsquo;individual at risk\u0026rsquo; of developing RA.\u003c/p\u003e \u003cp\u003eWe next stratified the individual\u0026rsquo;s at-risk cohort into non-convertors and convertors to RA\u003csup\u003e+\u003c/sup\u003e, within the timeframe of the study. Interestingly, we observed that IAR convertors displayed higher levels of CRP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), SAA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Leptin (p\u0026thinsp;=\u0026thinsp;0.09) and PP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Supplementary Fig.\u0026nbsp;4), when compared to the individual that did not convert, thus displaying levels like the one observed in established seropositive RA patients. Altogether, this suggest that selective markers might be predictor of disease conversion.\u003c/p\u003e\n\u003ch3\u003eSelective inflammatory, metabolic mediators and MMPs could be predictive of disease\u003c/h3\u003e\n\u003cp\u003eTo investigate whether these soluble markers investigated displayed high sensitivity and could be predictive of RA onset, we compared ROC curves of RA\u003csup\u003e+\u003c/sup\u003e vs HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA red), to the one obtained from IAR and HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA in orange); interestingly CRP, SAA and GIP-1 curves overlapped and displayed high sensitivity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In addition, MMP9 (RA\u003csup\u003e+\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, IAR p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) GLP-1 (RA\u003csup\u003e+\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, IAR p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and Leptin (RA\u003csup\u003e+\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, IAR p\u0026thinsp;=\u0026thinsp;0.06) also showed comparative profiles.\u003c/p\u003e \u003cp\u003eTo evaluate the correlation degrees of serums markers in HC vs IAR vs RA, we performed correlations matrixes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The degree of correlations is displayed, and it is clearly visible that in HC there is a little of degree of correlation of these markers, including, for example MMPs correlating to each other (Supplementary Fig.\u0026nbsp;5). However, in IAR and RA\u003csup\u003e+\u003c/sup\u003e comparable degree of correlation can be observed, with IAR having correlations in between HC and RA\u003csup\u003e+\u003c/sup\u003e. Interestingly, selective markers, including sICAM-1, displayed a higher degree of correlation with MMPs and metabolic markers in IAR in respect to RA\u003csup\u003e+\u003c/sup\u003e (Supplementary Fig.\u0026nbsp;5).\u003c/p\u003e \u003cp\u003ePCA analysis displayed that in both IAR and RA\u003csup\u003e+\u003c/sup\u003e patients serum markers clustered in 3 area, with Leptin being present in both cluster 1. For Cluster 3, SAA, sICAM-1, c-Peptide, sVCAM-1 and MMP1 clustered together in both IAR and RA\u003csup\u003e+\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) thus suggesting that the measurements of these markers together might aid in identify individual at risk which might convert to RA\u003csup\u003e+\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRheumatoid and psoriatic arthritis have overlapping clinical manifestation, especially at the early phase of the disease, which render a specific diagnosis difficult (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e); one of the main biomarker which can distinguish RA from PsA, are the presence/absence of autoantibodies, however a proportion of RA patients do not present autoantibodies, and recent studies suggest that antibodies against citrullinated proteins (ACPAs) are also found in 5.0\u0026ndash;17.5% of PsA patients (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In light of these observations, identifying novel biomarkers which distinguish RA from PsA, could help in disease stratification, and in an early specific diagnosis.\u003c/p\u003e \u003cp\u003eIn this work we explore the presence of 14 serum proteins in RA and PsA patients, in the area of vascularity, metabolism and cartilage degradation, and we investigated how these could be differentially expressed between the two diseases. CRP is the gold standard biomarkers in the monitoring inflammatory diseases, and especially in RA (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), whereas in PsA, only\u0026thinsp;~\u0026thinsp;50% of the patients have high level of this marker, also in the presence of active disease(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Our results are consistent with these observations, displaying high levels of CRP in both RA and PsA, but with a significantly higher levels observe in RA vs PsA. SAA protein is expressed in inflamed synovial tissue, therefore it is considered a better marker for Inflammatory Rheumatic Diseases (IRD)(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e); our data demonstrated that, like CRP, this marker is upregulated in RA patients at higher level in respect to PsA, thus suggesting a more significant role in RA vs PsA diseases. Soluble ICAM-1 and VCAM-1 have been shown to be increased in the serum of RA patients and correlate with disease activity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), however little is known about their role in PsA patients. Our data suggest that both sICAM-1 and sVCAM-1 are expressed in a RA\u0026thinsp;\u0026gt;\u0026thinsp;PsA\u0026thinsp;\u0026gt;\u0026thinsp;HC fashion, with sVCAM-1 being significantly higher in RA vs PsA patients. Interestingly, among these markers CRP and sICAM-1 correlated with disease activity (DAS28) in PsA at a higher degree that the one observed in RA. In addition, both sICAM-1 and sVCAM-1 were higher in the male cohort in respect to the female cohort, and sICAM-1 displayed higher level in patients with a BMI\u0026thinsp;\u0026gt;\u0026thinsp;25 in PsA patients.\u003c/p\u003e \u003cp\u003eWhen stratifying RA patients in seropositive and seronegative all four vascular markers were found higher in the RA\u003csup\u003e+\u003c/sup\u003e serum.\u003c/p\u003e \u003cp\u003eMMPs have an important role in in the destruction of articular cartilage in both RA and PsA(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In our cohort we observed that both MMP1 and 3 in were increased in the serum of RA patients compared to healthy and PsA. This is in agreement with previous studies which have shown an increase in serum MMP1 and MMP3, and their association to erosion and disease progression in RA(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), although display for the first time the difference in expression among the two diseases. Interestingly, we observed that MMP9 was significantly downregulated in both RA and PsA patients (HC\u0026thinsp;\u0026gt;\u0026thinsp;RA\u0026thinsp;\u0026gt;\u0026thinsp;PsA). The literature on serum MMP9 levels is contradictory, with previous studies showing either an increase (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) or a decrease of MMP9 (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) in the serum of RA patients. MMP9 has been shown to be sensitive to biologics treatments, including Infliximab (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). When stratifying our cohort into na\u0026iuml;ve, patients receiving bDMARDs or csDMARDS, we observed that patients on biologics showed the highest decrease in serum MMP9 in respect to healthy subjects (Supplementary Fig.\u0026nbsp;6), thus agreeing with previous observations. Interestingly, MMP3 were showed trending increase in the high DAS28 cohort in RA only, thus confirming it might act as a specific biomarker for RA. Interesting MMP3 was found higher in the Male cohort in RA only, thus suggesting a gender confounder in its regulation.\u003c/p\u003e \u003cp\u003eObesity and increased body mass index has been associated with a higher severity of RA and PsA disease (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), however the results remain elusive and directive comparative studies are required. Here we observed that metabolic PP and c-Peptide were increased exclusivity in the serum of RA patients, with levels in PsA similar to the HC. GIP-1 was increased in a RA\u0026thinsp;\u0026gt;\u0026thinsp;PsA\u0026thinsp;\u0026gt;\u0026thinsp;HC fashion. Interestingly GLP-1, Insulin and Leptin were increased in PsA more than RA and HC. Of these Leptin was higher in high DAS28 samples in PsA, while PP was higher in the RA high DAS28 cohort and most of the metabolic markers were higher in the high BMI group, thus confirming their connection with obesity. This is the first study which directly compare serum metabolic markers between diseases and identify specific disease signatures between RA and PsA.\u003c/p\u003e \u003cp\u003eROC analysis identifies specific markers highly sensitive for RA but not PsA disease, these included sICAM-1, MMP1, MMP3, PP and c-Peptide, therefore we believe that measuring these markers, together with the classical CRP and SAA, could aid in discriminating RA from PsA diseases, thus helping with diagnosis and specific treatment. In addition, correlation matrixes confirmed a high degree of correlation of these markers in RA, among themselves and in relation to the classical inflammatory markers CRP and SAA, thus making them great candidate for disease stratification. A bigger cohort of patients is necessary to validate these observations.\u003c/p\u003e \u003cp\u003eIn the second part of the study, we were interested to investigate whether the specific RA-serum markers could precede disease onset, and for this reason we measure serum levels in individual-at-risk of developing RA. These individuals already present autoantibodies in circulation and are at high change to develop RA, but they still don\u0026rsquo;t present clinical symptoms and inflammation(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Previous studies from our team have demonstrated that these individuals already present cellular dysregulation, with circulatory cells being metabolic active (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, in our cohort, CRP, SAA, GLP-1, GIP-1, Leptin and PP were all already significantly increased in the serum of IAR when compared to HC, with levels in between HC and RA (RA\u0026thinsp;\u0026gt;\u0026thinsp;IAR\u0026thinsp;\u0026gt;\u0026thinsp;HC), thus indicating that these markers could predict disease onset. Interestingly, CRP, SAA, Leptin and PP markers were predictors protein for RA conversions, resulting increased at level similar to the one observed to RA\u003csup\u003e+\u003c/sup\u003e in the individual that converted to RA within the timeframe of this study. These markers all showed a great degree of sensitive and fully overlapped with RA ROC curves, and a high degree of correlation among themselves, thus making them great candidate for RA disease predictors.\u003c/p\u003e \u003cp\u003eOverall, this study identified for the first time serum proteins sICAM-1, MMP1, MMP3, PP, c-Peptide, CRP and SAA which are specific for RA disease and could aid in discriminating RA from PsA patients, especially in the early phase of the diseases. In addition, this study, identified that CRP, SAA, GLP-1, GIP-1, Leptin and PP serum protein precede disease onset, as are already altered in the serum of IAR. Of these CRP, SAA, Leptin and PP might predict IAR conversion to RA\u003csup\u003e+\u003c/sup\u003e, thus making them great candidate for disease progression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by Saint Vincent University Hospital research ethics committee, Dublin, Ireland. \u0026nbsp;Written informed was obtained from the participant. All authors have critically reviewed and approved the final manuscript to be published.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by Center for Arthritis and Rheumatic Diseases, CARD 2019-01, Science Foundation Ireland-Irish Research Council pathway 21/PATH-S/9327 and Arthritis Ireland.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eVM, CO and UF: conceptualization, visualization, and supervision. VM, CO, AG, JV, DV and UF: methodology and writing—original draft preparation. JV, AG, VM: validation, formal analysis, and investigation. VM, UF, DV: resources and funding acquisition. VM: project administration. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e: The authors would like to thank the excellent staff in the Rheumatology Department in SVUH for all the help in patients’ recruitment. In addition, they express sincere thanks to all the patients who consented to be involved in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBoeters DM, Raza K, Mil AHMvanderH, Review. Which patients presenting with arthralgia eventually develop rheumatoid arthritis? The current state of the art. RMD Open [Internet]. 2017 Nov [cited 2023 Jun 19];3(2):e000479. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.wileyonlinelibrary.com/journal/cti\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCunningham CC, Wade S, Floudas A, Orr C, McGarry T, Wade S et al. Serum miRNA Signature in Rheumatoid Arthritis and At-Risk Individuals. Front Immunol [Internet]. 2021 Mar 3 [cited 2025 Mar 5];12:633201. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pmc.ncbi.nlm.nih.gov/articles/PMC7966707/\u003c/span\u003e\u003cspan address=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC7966707/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"arthritis-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arrt","sideBox":"Learn more about [Arthritis Research \u0026 Therapy](http://arthritis-research.biomedcentral.com/)","snPcode":"13075","submissionUrl":"https://submission.nature.com/new-submission/13075/3","title":"Arthritis Research \u0026 Therapy","twitterHandle":"@ArthritisRes","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rheumatoid Arthritis, Psoriatic Arthritis, serum biomarkers, inflammation, disease pathotypes.","lastPublishedDoi":"10.21203/rs.3.rs-6197103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6197103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRheumatoid arthritis (RA) and Psoriatic arthritis (PsA) are systemic auto-immune disease of unknown aetiology that leads to systemic inflammation and synovial joint destruction. Identification of specific serum proteins that selectively regulate these diseases, or which precede disease development could have great potential as disease biomarkers and predictors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSerum level of C-reactive protein (CRP), sICAM-1, sVCAM-1, Serum amyloid A (SAA), Matrix metalloproteinases (MMPs 1,3 and 9) and metabolic markers: Active Glucose-dependent Insulinotropic polypeptide (GIP), active Glucagon-like peptide-1 (GLP-1), C-Peptide, Glucagon, Insulin, Leptin, Pancreatic Polypeptide (PP) were measured by multiplex analysis by MSD assay.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSerum level of sICAM-1, MMP1, MMP3, PP, c-Peptide, CRP and SAA were specifically upregulated in RA, but not in PsA disease, displaying high sensitivity (ROC curves), thus making them suitable markers for discriminating RA from PsA patients, especially in the early phase of the diseases. Differences in gender, BMI, and disease activity were observed. This is the first study which directly compare serum metabolic markers between diseases and identify specific disease signatures between RA and PsA. In addition, this study, identified that CRP, SAA, GLP-1, GIP-1, Leptin and PP serum protein precede disease onset, as are already altered in the serum of \u0026lsquo;individual at risk\u0026rsquo; of developing RA. Of these CRP, SAA, Leptin and PP might predicted IAR conversion to RA+, thus making them suitable candidate for disease prediction.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAltogether, this study identifies selective serum marker associated with RA and PsA, which are pathotype-specific and are predictor of RA disease onset.\u003c/p\u003e","manuscriptTitle":"Investigation of serum biomarkers in Rheumatoid and Psoriatic arthritis patients for disease-specific signatures","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 10:09:28","doi":"10.21203/rs.3.rs-6197103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-15T14:23:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-07T08:40:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180313849368872312537926140294801218682","date":"2025-05-01T19:31:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303260958790593722848187804012685436655","date":"2025-04-30T09:08:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T07:04:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"223123101664004816923709075128041562904","date":"2025-03-24T11:49:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-23T16:52:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-14T14:44:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-14T13:55:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Arthritis Research \u0026 Therapy","date":"2025-03-10T15:45:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"arthritis-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arrt","sideBox":"Learn more about [Arthritis Research \u0026 Therapy](http://arthritis-research.biomedcentral.com/)","snPcode":"13075","submissionUrl":"https://submission.nature.com/new-submission/13075/3","title":"Arthritis Research \u0026 Therapy","twitterHandle":"@ArthritisRes","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"07722624-65f9-4d28-a118-c134c584adba","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T16:03:17+00:00","versionOfRecord":{"articleIdentity":"rs-6197103","link":"https://doi.org/10.1186/s13075-025-03608-6","journal":{"identity":"arthritis-research-and-therapy","isVorOnly":false,"title":"Arthritis Research \u0026 Therapy"},"publishedOn":"2025-07-10 15:57:02","publishedOnDateReadable":"July 10th, 2025"},"versionCreatedAt":"2025-04-01 10:09:28","video":"","vorDoi":"10.1186/s13075-025-03608-6","vorDoiUrl":"https://doi.org/10.1186/s13075-025-03608-6","workflowStages":[]},"version":"v1","identity":"rs-6197103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6197103","identity":"rs-6197103","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}