Integrated transcriptomic and proteomic analysis reveals innate and adaptive immune dynamics in systemic autoinflammatory diseases

Integrated transcriptomic and proteomic analysis reveals innate and adaptive immune dynamics in systemic autoinflammatory diseases | 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 Letter Integrated transcriptomic and proteomic analysis reveals innate and adaptive immune dynamics in systemic autoinflammatory diseases Matthijs Wijngaarden, Rogier Wijck, Djo Hasan, Sigrid Swagemakers, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6173310/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Immune responses in systemic autoinflammatory disease (SAID) were investigated by multi-omics analysis, integrating RNA expression and proteomic data. By identifying the top 10 co-expressed transcripts of IL1B and BLNK, we demonstrated the simultaneous activation of pro- and anti-inflammatory pathways in 338 SAID patients, with less activation in 68 negative controls. Our findings highlight the role of adaptive immune system-related genes in SAID, suggesting a reciprocal relationship between innate and adaptive immunity. Notably, negative controls exhibited active immune responses despite the absence of symptoms, an important consideration for data interpretation. In addition, we demonstrated how transcriptomic and proteomic profiling using heatmaps can verify treatment response, using the top 30 transcripts from 19 ANA-positive SAID patients and the top 30 proteins from 60 SAID patients with follow-up samples. These findings advance our understanding of the pathology of SAID and provide a valuable framework for treatment monitoring. Health sciences/Diseases/Immunological disorders/Autoimmune diseases Biological sciences/Immunology/Autoimmunity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Main Text Cases and controls were recruited through the Institutional Review Board-approved ImmunAID consortium (IMMUNome Project Consortium for Autoinflammatory Disorders, approved by the South West-Frenchay Research Ethics Committee; REC Reference: 20/SW/0022) and subjected to RNA sequencing (RNA-Seq) profiling. Detailed cohort information is available in the Supplementary Consortium files. All Illumina Next-Generation Sequencing was conducted in a single laboratory in five batches at the Paris Brain Institute (Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France), followed by transcript mapping. To assess immune status, we analysed 20 representative transcripts associated with innate and adaptive immune responses (Supplementary Table 1, genes 1-20). Batch effects were removed, and log2 geometric means were normalized using Partek® software (Partek Inc., St. Louis, MO). Data analysis was performed using OmniViz software (version 3.8; OmniViz, Maynard, MA) and Partek® software. Heatmaps were generated with markers as columns and individual cases and controls as rows, with upregulated transcripts shown in red and downregulated transcripts shown in blue. We generated RNA-Seq heatmaps for the top 10 genes co-expressed with IL1B and BLNK in 338 SAID patients and 68 negative controls. These two distinct genes were selected due to their central role in immune responses. Gene expression data were sorted by the intensity of IL1B (Fig. 1) or BLNK (Fig. 2). IL1B , encoding the IL-1β protein, is a potent proinflammatory cytokine and a key mediator of innate immunity 1,2 , whereas BLNK , encoding the B cell linker protein, is essential for B cell receptor signalling, nuclear factor-kappa B activation, cell cycle entry, and B cell survival 3,4 . Genes co-expressed with IL1B were considered indicative of innate immune responses, whereas those co-expressed with BLNK were associated with B cell-mediated adaptive immunity (Supplementary Table 1, genes 1-10 and 11-20). Our analysis revealed that proinflammatory and anti-inflammatory gene expression profiles (labelled with different colours in the headers) were simultaneously elevated (red) or suppressed (blue) (Fig. 1, Fig. 2), a phenomenon previously reported in the literature 5-7 . Genes within the innate and adaptive groups showed a strong positive intragroup correlation, as expected (mean Pearson’s r = 0.731, p << 0.01; mean Pearson’s r = 0.858, p << 0.01; see Supplementary Table 2 for full correlation and adjusted p-values). Surprisingly, genes co-expressed with BLNK showed a slightly negative correlation compared to innate immune-related genes (mean Pearson’s r = -0.2, p = 0.006). Entering these 20 genes into STRING DB results in a highly connected network, with both the innate and adaptive clusters being particularly connected by the interconnectivity of CD19 (Supplementary Fig. 1). This gene has previously been reported to interact with both the innate and adaptive immune systems 8 . These findings suggest that activation of the innate immune system does not necessarily drive concomitant activation of the adaptive immune system, and vice versa, an observation that may provide novel insights into immune system dynamics in SAID. Although systemic autoinflammatory diseases (SAIDs) are primarily associated with dysregulation of the innate immune system 1 , emerging evidence suggests that the adaptive immune system also plays a role. A review of the literature revealed the presence of autoantibodies – a sensitive marker of autoimmune activation 9-11 – in several SAIDs, including Adult-Onset Still's Disease (AOSD) 12 , Behçet’s disease 13 , Kawasaki Disease 14 , Schnitzler’s syndrome 15,16 , Sweet syndrome (neutrophilic dermatosis) 17,18 , systemic-onset juvenile idiopathic arthritis (SOJIA) 19 , Takayasu’s arteritis 20 , and recurrent pericarditis 21 . The absence of autoantibodies in some SAIDs and autoimmune diseases may originate from technical limitations in autoantibody detection 22 . The slow development of reliable autoantibody assays, as well as potential genetic mutations that affect autoantibody production, pose challenges in identifying disease-specific markers. Currently, only a small fraction of autoantibody tests have received regulatory approval for clinical use. Many remain classified as “research use only” or “laboratory-developed tests”, with only a few have undergone health technology assessment. Approximately 90% of known autoantibody tests remain "orphaned" due to the high cost of regulatory approval, making commercial development infeasable 22 . Interestingly, transcriptomic analysis revealed that control samples exhibited gene expression patterns similar to those observed in SAID patients (Fig. 1, Fig. 2). This unexpected finding challenges the conventional distinction between diseased and healthy controls and complicates efforts to differentiate inflammatory diseases based solely on transcriptomic profiles, a challenge noted in previous studies 23 . When comparing the expression of 10 innate and 10 adaptive immune-related genes between patients and controls using the Mann-Whitney U test corrected for multiple comparisons, no statistically significant differential expressions expression pattern emerged between patients and controls (Supplementary Table 3). These findings highlight the complexity of immune activation in SAID. Further studies are needed to refine transcriptomic approaches to differentiate SAID patients from healthy controls and to explore the full spectrum of immune system involvement in autoinflammatory diseases. RNA-Seq was performed in 52 SAID patients at 2 time points during disease progression, including information on prescribed therapy (Fig. 3, Fig. 4). When sorting the transcriptomic data by IL1B , we observed that gene expression levels co-expressed with IL1B were consistently lower in posttreatment samples compared to pretreatment samples (Fig. 3, Supplementary Table 4). Conversely, the expression levels of genes co-expressed with BLNK were consistently higher in posttreatment samples (Fig. 4, Supplementary Table 4). Wilcoxon signed-rank tests were performed to validate these findings, showing that 14 of the 20 measured genes yield statistically significant differences between pretreatment and posttreatment after correction for multiple sampling (Supplementary Table 4). Although this study was not designed to evaluate treatment efficacy, these findings suggest a possible effect of prescribed therapies of prescribed therapies, including nonsteroidal anti-inflammatory drugs (NSAIDs), acetaminophen, corticosteroids, and biologicals (anti-IL-1 and anti-IL-6 antibodies), at the gene expression level of innate immune responses. These results warrant further investigation in a randomized controlled trial. Regulatory T cells (Treg) play a central role in adaptive immunity by maintaining central and peripheral tolerance through suppression of autoreactive T cells 11 . A key marker of Tregs is FOXP3 , a transcription factor of the FOX protein family that controls their regulatory function 29 . FOXP1 , a closely related transcription factor, is essential for FOXP3 -mediated chromatin binding, and its downregulation is known to impair Treg function 30 . Importantly, FOXP3 + is critical for the suppressive function of highly immunosuppressive regulatory B cells (Bregs) that secrete IL-10, IL-35, and TGF-β 11 . Our data revealed a correlation between FOXP1 transcript levels and therapeutic response in SAID, suggesting a mechanistic link between autoinflammation and adaptive immune regulation. To investigate this, we compared SAID patients with clinically confirmed active inflammation to true-negative controls. Of these patients, 19 were ANA positive, confirming the involvement of activated adaptive immune responses. Hierarchical clustering of inflammatory RNA markers in control samples revealed two subgroups: 43 healthy individuals with no evidence of immune activation and 25 controls with an underlying inflammatory signature. Significance Analysis of Microarrays (SAM), a modified t-statistic to identify differentially expressed genes between two or more groups, comparing the transcriptomes of the 19 ANA-positive SAID patients with the 43 true-negative controls revealed a distinct transcriptomic signature (Fig. 5, Supplementary Table 1, genes 21-50). As shown in Fig. 5, pretreatment SAID patients, including ANA-positive cases, showed a clear transcriptomic distinction from posttreatment and true-negative controls. Remarkably, the post-treatment transcriptomic profiles closely resembled those of true-negative controls, suggesting that treatment response can be quantitatively assessed using this signature. Notably, FOXP1 was among the top 15 upregulated genes in both true-negative controls and posttreatment samples (B), supporting its potential role in Treg/Breg function in SAIDs. This is further supported by the observed upregulation of ZFP36L2 , which encodes RNA-binding proteins essential for T cell activation and autoreactive T cell regulation 31 . These findings suggest that adaptive immune regulatory mechanisms, particularly those involving FOXP1 and Tregs/Bregs, may play a more significant role in SAIDs than previously appreciated. Further research is needed to elucidate their contribution to disease pathophysiology and therapeutic response. We also analysed proteomic changes before and after treatment using SomaScan in 60 SAID patients with follow-up samples. Fig. 6 shows a heatmap of the top 30 most differentially expressed proteins, of which 15 were upregulated before treatment and downregulated after treatment, while the other 15 showed the opposite pattern (Supplementary Table 1, genes 51-65 and genes 66-80, respectively). These 30 genes were obtained by performing a SAM test, extracting the most differentially expressed proteins of SAID patients with their follow-up samples. Compared with pretreatment samples, posttreatment samples showed a marked reduction in an acute-phase protein network, including C-reactive protein (CRP). Specifically, CRP levels were significantly lower in 50 of the 60 posttreatment samples. CRP plays a well-documented role in proinflammatory innate immune responses 32 , and a similar downward trend was observed in other acute phase proteins. The majority of the 15 proteins upregulated in pretreatment samples are related to the acute phase response (Supplementary Table 1, genes 51-65). A protein interaction network generated using STRING DB for these 30 proteins is shown in Supplementary Fig. 2. Our study showed that both proinflammatory and anti-inflammatory responses are simultaneously activated in 338 SAID patients and, to a lesser extent, in the 68 negative controls. These findings suggest that negative controls are not devoid of immune activation, an important consideration for future studies. Additionally, our results suggest a potential reciprocal relationship between innate and adaptive immune responses in SAID. Furthermore, we demonstrated that a treatment that primarily targets innate immune responses significantly alters RNA the expression levels of innate immune-related genes and the proteomic expression of CRP. However, these treatments had no apparent effect on the RNA expression of genes related to adaptive immunity, an observation that warrants further investigation. Finally, we confirmed the utility of transcriptomic and proteomic profiling in monitoring treatment response. RNA-Seq heatmaps of the top 30 transcripts from 19 ANA-positive SAID patients and the top 30 proteins from 60 posttreatment samples effectively captured treatment effects. These findings provide a foundation for future studies investigating immune response modulation and therapeutic efficacy in SAID. Declarations Competing interests PvdS: None; DH: None; MvW: None; RvW: None; SS: None; PR: None; BF:none; DS: None; VS: Chief Medical Officer Owkin ( https://www.owkin.com/ ) Author contributions PvdS and DS conceived the project; SS RvW PvdS devised the methodology; SS RvW MvW DH PvdS conducted the investigations; RvW MvW PvdS were responsible for data curation; SS RvW MvW PvdS analyzed the data; SS; MvW and RvW DH visualized the experiments; PvdS acquired resources; RvW and PvdS responsible for project administration and reporting to EU; PvdS supervised the project; DH and PvdS wrote the original draft of the manuscript; RvW MvW SS DS PR were involved in manuscript review and editing. Availability of data The datasets generated and/or analysed during the current study are not publicly available for privacy reasons, but are available from the corresponding author upon reasonable request. References Lopez-Castejon, G. & Brough, D. Understanding the mechanism of IL-1β secretion. 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Vassili Soumelis works as a Chief Medical Officer at Owkin Company Supplementary Files 10SupplementaryFigure1.pdf Supplementary Figure 1 14SupplementaryTable3.pdf Supplementary Table 3 15SupplementaryTable4.pdf Supplementary Table 4 11SupplementaryFigure2.pdf Supplementary Figure 2 13SupplementaryTable2.pdf Supplementary Table 2 16Supplementarystatisticalanalysesexplained.pdf Supplementary statistical analyses explained 12SupplementaryTable1.pdf Supplementary Table 1 Cite Share Download PDF Status: Under Review Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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1","display":"","copyAsset":false,"role":"figure","size":948018,"visible":true,"origin":"","legend":"\u003cp\u003eAn RNA-Seq heatmap of the gene expression levels of 20 genes in 338 SAIDs patients and 68 negative controls. Data are sorted by IL1B. Pink headings indicate proinflammatory properties, green headings indicate anti-inflammatory properties, and the pink to green gradient coloured heading indicates both proinflammatory and anti-inflammatory properties (ATF). Low transcript expressions are represented by blue colour and high transcript expressions are represented by red colour. AOSD: Adult-Onset Still’s disease; CAPS: Cryopyrin-Associated Autoinflammatory Syndromes; FMF: Familial Mediterranean Fever; HIDS: Hyper IgD Syndrome; SOJIA: Systemic-Onset Juvenile Idiopathic Arthritis; TRAPS: TNF Receptor-Associated Periodic Syndrome.\u003c/p\u003e","description":"","filename":"F1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/b05db466795ccfa1be7caf62.jpg"},{"id":94987723,"identity":"96d10616-f260-472d-b5a7-9e9df0868e4f","added_by":"auto","created_at":"2025-11-03 07:02:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":925814,"visible":true,"origin":"","legend":"\u003cp\u003eAn RNA-Seq heatmap of the gene expression levels of 20 genes in 338 SAIDs patients and 68 negative controls. Data are sorted by BLNK. Pink headings indicate proinflammatory properties, green headings indicate anti-inflammatory properties, and the pink to green gradient coloured heading indicates both proinflammatory and anti-inflammatory properties (ATF). Low transcript expressions are represented by blue colour and high transcript expressions are represented by red colour. AOSD: Adult-Onset Still’s disease; CAPS: Cryopyrin-Associated Autoinflammatory Syndromes; FMF: Familial Mediterranean Fever; HIDS: Hyper IgD Syndrome; SOJIA: Systemic-Onset Juvenile Idiopathic Arthritis; TRAPS: TNF Receptor-Associated Periodic Syndrome.\u003c/p\u003e","description":"","filename":"F2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/32514d8e365cf80d2ff0436a.jpg"},{"id":94915909,"identity":"a35fe1e4-fbf5-40cf-8af0-e0690d918b86","added_by":"auto","created_at":"2025-11-01 11:44:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":265447,"visible":true,"origin":"","legend":"\u003cp\u003eAn RNA-Seq heatmap of the gene expression levels of 20 genes in 52 SAIDs patients. Blood samples were collected at enrolment (pretreatment) and after a follow-up period (posttreatment). Data are sorted by IL1B at enrolment. The treatments administered and the reported responses are shown in the last five columns. AOSD: Adult-Onset Still’s disease; SOJIA: Systemic-Onset Juvenile Idiopathic Arthritis.\u003c/p\u003e","description":"","filename":"F3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/b229e28a8fa9c50fd7f50eec.jpg"},{"id":94987627,"identity":"8b244add-65c2-4b7e-bd27-ec7734c770ad","added_by":"auto","created_at":"2025-11-03 07:02:11","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":266237,"visible":true,"origin":"","legend":"\u003cp\u003eAn RNA-Seq heatmap of the gene expression levels of 20 genes in 52 SAIDs patients. Blood samples were collected at enrollment (pretreatment) and after a follow-up period (posttreatment). Data are sorted by BLNK at enrolment. The treatments administered and the reported responses are shown in the last five columns. AOSD: Adult-Onset Still’s disease; SOJIA: Systemic-Onset Juvenile Idiopathic Arthritis.\u003c/p\u003e","description":"","filename":"F4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/fa63768779ab86a7505e6095.jpg"},{"id":94988128,"identity":"5e8de595-c73d-45bd-a3a0-9fb4e076ceca","added_by":"auto","created_at":"2025-11-03 07:05:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5858390,"visible":true,"origin":"","legend":"\u003cp\u003eProteomic signatures of patients with a positive antinuclear autoantibody (ANA) test, patients after treatment, and true-negative controls. True-negative controls consist of 41 individuals with follow-up samples excluding 27 with an activated transcriptomic signature consistent with inflammation. This is verified by a t-test using our inflammatory markers, which showed a strong subcategorization between individuals with an activated or inactivated inflammatory state. Patients with a follow-up sample are highlighted in yellow. AOSD: Adult-Onset Still’s disease.\u003c/p\u003e","description":"","filename":"F5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/86c1bcadb278bd1f4549a9c7.jpg"},{"id":94915919,"identity":"2cf61536-71c7-4b7e-b90f-68c4227f4d9f","added_by":"auto","created_at":"2025-11-01 11:44:25","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7918572,"visible":true,"origin":"","legend":"\u003cp\u003eA heatmap of the top 30 most differentially expressed proteins from proteomic profiles generated using the Somalogic Inc platform in 60 treated and untreated SAID patients who have a follow-up sample. In 50 patients, CRP levels were clearly lower in the follow-up samples than in the first samples. In 10 other patients, CRP levels were higher in the follow-up samples than in the first samples. AOSD: Adult-Onset Still’s disease; SOJIA: Systemic-Onset Juvenile Idiopathic Arthritis; IUO: Inflammation of Unknown Origin.\u003c/p\u003e","description":"","filename":"F6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/88f719778ecf52e7ef889283.jpg"},{"id":94990928,"identity":"f97ee672-9c5c-4608-b736-f327b13da9e0","added_by":"auto","created_at":"2025-11-03 07:18:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16615946,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/d1aa44c4-e97c-41c3-830c-0daae94fd178.pdf"},{"id":94915907,"identity":"905beb7d-5a50-49f5-a2b6-ba6fcec7df8c","added_by":"auto","created_at":"2025-11-01 11:44:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":168030,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"10SupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/c8c521b796c99fa455657206.pdf"},{"id":94915903,"identity":"e6b1b2c8-ed4f-44a5-9333-bc1c793e0934","added_by":"auto","created_at":"2025-11-01 11:44:24","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":108891,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"14SupplementaryTable3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/049b2acf8a21e7bc542c03ad.pdf"},{"id":94915908,"identity":"ef2593c5-c593-4320-b79f-628f3dfc1af1","added_by":"auto","created_at":"2025-11-01 11:44:24","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":130105,"visible":true,"origin":"","legend":"Supplementary Table 4","description":"","filename":"15SupplementaryTable4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/58a916b66b81e0857a8cb922.pdf"},{"id":94915910,"identity":"e9bf8ebd-1171-43ca-972c-f8c89987d83c","added_by":"auto","created_at":"2025-11-01 11:44:24","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":192319,"visible":true,"origin":"","legend":"Supplementary Figure 2","description":"","filename":"11SupplementaryFigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/d05709869ca3e6490bfd819a.pdf"},{"id":94988030,"identity":"c32481ea-f30e-4737-ae2c-a9ac768d2678","added_by":"auto","created_at":"2025-11-03 07:02:55","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":71819,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"13SupplementaryTable2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/fb182d6a071dc7c98655b592.pdf"},{"id":94987988,"identity":"61363021-a542-4075-afb2-791230e72394","added_by":"auto","created_at":"2025-11-03 07:02:43","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":232316,"visible":true,"origin":"","legend":"Supplementary statistical analyses explained","description":"","filename":"16Supplementarystatisticalanalysesexplained.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/43a9ccb468d3cf057fddae2b.pdf"},{"id":94915913,"identity":"967ad594-6a4e-4974-abe7-a330c1681a14","added_by":"auto","created_at":"2025-11-01 11:44:25","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":308885,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"12SupplementaryTable1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173310/v1/2ec9455f5c9b181613bf0bc4.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nVassili Soumelis works as a Chief Medical Officer at Owkin Company","formattedTitle":"Integrated transcriptomic and proteomic analysis reveals innate and adaptive immune dynamics in systemic autoinflammatory diseases","fulltext":[{"header":"Main Text","content":"\u003cp\u003eCases and controls were recruited through the Institutional Review Board-approved ImmunAID consortium (IMMUNome Project Consortium for Autoinflammatory Disorders, approved by the South West-Frenchay Research Ethics Committee; REC Reference: 20/SW/0022) and subjected to RNA sequencing (RNA-Seq) profiling. Detailed cohort information is available in the Supplementary Consortium files. All Illumina Next-Generation Sequencing was conducted in a single laboratory in five batches at the Paris Brain Institute (Institut du Cerveau, H\u0026ocirc;pital Piti\u0026eacute;-Salp\u0026ecirc;tri\u0026egrave;re, Paris, France), followed by transcript mapping.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo assess immune status, we analysed 20 representative transcripts associated with innate and adaptive immune responses (Supplementary Table 1, genes 1-20). Batch effects were removed, and log2 geometric means were normalized using Partek\u0026reg; software (Partek Inc., St. Louis, MO). Data analysis was performed using OmniViz software (version 3.8; OmniViz, Maynard, MA) and Partek\u0026reg; software. Heatmaps were generated with markers as columns and individual cases and controls as rows, with upregulated transcripts shown in red and downregulated transcripts shown in blue.\u003c/p\u003e\n\u003cp\u003eWe generated RNA-Seq heatmaps for the top 10 genes co-expressed with \u003cem\u003eIL1B\u003c/em\u003e and \u003cem\u003eBLNK\u003c/em\u003e in 338 SAID patients and 68 negative controls. These two distinct genes were selected due to their central role in immune responses. Gene expression data were sorted by the intensity of \u003cem\u003eIL1B\u003c/em\u003e (Fig. 1) or \u003cem\u003eBLNK\u0026nbsp;\u003c/em\u003e(Fig. 2). \u003cem\u003eIL1B\u003c/em\u003e, encoding the IL-1\u0026beta; protein, is a potent proinflammatory cytokine and a key mediator of innate immunity\u003csup\u003e1,2\u003c/sup\u003e, whereas \u003cem\u003eBLNK\u003c/em\u003e, encoding the B cell linker protein, is essential for B cell receptor signalling, nuclear factor-kappa B activation, cell cycle entry, and B cell survival\u003csup\u003e3,4\u003c/sup\u003e. Genes co-expressed with \u003cem\u003eIL1B\u003c/em\u003e were considered indicative of innate immune responses, whereas those co-expressed with \u003cem\u003eBLNK\u003c/em\u003e were associated with B cell-mediated adaptive immunity (Supplementary Table 1, genes 1-10 and 11-20).\u003c/p\u003e\n\u003cp\u003eOur analysis revealed that proinflammatory and anti-inflammatory gene expression profiles (labelled with different colours in the headers) were simultaneously elevated (red) or suppressed (blue) (Fig. 1, Fig. 2), a phenomenon previously reported in the literature\u003csup\u003e5-7\u003c/sup\u003e. Genes within the innate and adaptive groups showed a strong positive intragroup correlation, as expected (mean Pearson\u0026rsquo;s r = 0.731, p \u0026lt;\u0026lt; 0.01; mean Pearson\u0026rsquo;s r = 0.858, p \u0026lt;\u0026lt; 0.01; see Supplementary Table 2 for full correlation and adjusted p-values). Surprisingly, genes co-expressed with \u003cem\u003eBLNK\u003c/em\u003e showed a slightly negative correlation compared to innate immune-related genes (mean Pearson\u0026rsquo;s r = -0.2, p = 0.006). Entering these 20 genes into STRING DB results in a highly connected network, with both the innate and adaptive clusters being particularly connected by the interconnectivity of CD19 (Supplementary Fig. 1). This gene has previously been reported to interact with both the innate and adaptive immune systems\u003csup\u003e8\u003c/sup\u003e. These findings suggest that activation of the innate immune system does not necessarily drive concomitant activation of the adaptive immune system, and vice versa, an observation that may provide novel insights into immune system dynamics in SAID.\u003c/p\u003e\n\u003cp\u003eAlthough systemic autoinflammatory diseases (SAIDs) are primarily associated with dysregulation of the innate immune system\u003csup\u003e1\u003c/sup\u003e, emerging evidence suggests that the adaptive immune system also plays a role. A review of the literature revealed the presence of autoantibodies \u0026ndash; a sensitive marker of autoimmune activation\u003csup\u003e9-11\u003c/sup\u003e \u0026ndash; in several SAIDs, including Adult-Onset Still\u0026apos;s Disease (AOSD)\u003csup\u003e12\u003c/sup\u003e, Beh\u0026ccedil;et\u0026rsquo;s disease\u003csup\u003e13\u003c/sup\u003e, Kawasaki Disease\u003csup\u003e14\u003c/sup\u003e, Schnitzler\u0026rsquo;s syndrome\u003csup\u003e15,16\u003c/sup\u003e, Sweet syndrome (neutrophilic dermatosis)\u003csup\u003e17,18\u003c/sup\u003e, systemic-onset juvenile idiopathic arthritis (SOJIA)\u003csup\u003e19\u003c/sup\u003e, Takayasu\u0026rsquo;s arteritis\u003csup\u003e20\u003c/sup\u003e, and recurrent pericarditis\u003csup\u003e21\u003c/sup\u003e. \u0026nbsp;The absence of autoantibodies in some SAIDs and autoimmune diseases may originate from technical limitations in autoantibody detection\u003csup\u003e22\u003c/sup\u003e. The slow development of reliable autoantibody assays, as well as potential genetic mutations that affect autoantibody production, pose challenges in identifying disease-specific markers. Currently, only a small fraction of autoantibody tests have received regulatory approval for clinical use. Many remain classified as \u0026ldquo;research use only\u0026rdquo; or \u0026ldquo;laboratory-developed tests\u0026rdquo;, with only a few have undergone health technology assessment. Approximately 90% of known autoantibody tests remain \u0026quot;orphaned\u0026quot; due to the high cost of regulatory approval, making commercial development infeasable\u003csup\u003e22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, transcriptomic analysis revealed that control samples exhibited gene expression patterns similar to those observed in SAID patients (Fig. 1, Fig. 2). This unexpected finding challenges the conventional distinction between diseased and healthy controls and complicates efforts to differentiate inflammatory diseases based solely on transcriptomic profiles, a challenge noted in previous studies\u003csup\u003e23\u003c/sup\u003e. When comparing the expression of 10 innate and 10 adaptive immune-related genes between patients and controls using the Mann-Whitney U test corrected for multiple comparisons, no statistically significant differential expressions expression pattern emerged between patients and controls (Supplementary Table 3). These findings highlight the complexity of immune activation in SAID. Further studies are needed to refine transcriptomic approaches to differentiate SAID patients from healthy controls and to explore the full spectrum of immune system involvement in autoinflammatory diseases.\u003c/p\u003e\n\u003cp\u003eRNA-Seq was performed in 52 SAID patients at 2 time points during disease progression, including information on prescribed therapy (Fig. 3, Fig. 4). When sorting the transcriptomic data by \u003cem\u003eIL1B\u003c/em\u003e, we observed that gene expression levels co-expressed with \u003cem\u003eIL1B\u003c/em\u003e were consistently lower in posttreatment samples compared to pretreatment samples (Fig. 3, Supplementary Table 4). Conversely, the expression levels of genes co-expressed with \u003cem\u003eBLNK\u003c/em\u003e were consistently higher in posttreatment samples (Fig. 4, Supplementary Table 4). Wilcoxon signed-rank tests were performed to validate these findings, showing that 14 of the 20 measured genes yield statistically significant differences between pretreatment and posttreatment after correction for multiple sampling (Supplementary Table 4). Although this study was not designed to evaluate treatment efficacy, these findings suggest a possible effect of prescribed therapies of prescribed therapies, including nonsteroidal anti-inflammatory drugs (NSAIDs), acetaminophen, corticosteroids, and biologicals (anti-IL-1 and anti-IL-6 antibodies), at the gene expression level of innate immune responses. These results warrant further investigation in a randomized controlled trial.\u003c/p\u003e\n\u003cp\u003eRegulatory T cells (Treg) play a central role in adaptive immunity by maintaining central and peripheral tolerance through suppression of autoreactive T cells\u003csup\u003e11\u003c/sup\u003e. A key marker of Tregs is \u003cem\u003eFOXP3\u003c/em\u003e, a transcription factor of the FOX protein family that controls their regulatory function\u003csup\u003e29\u003c/sup\u003e. \u003cem\u003eFOXP1\u003c/em\u003e, a closely related transcription factor, is essential for \u003cem\u003eFOXP3\u003c/em\u003e-mediated chromatin binding, and its downregulation is known to impair Treg function\u003csup\u003e30\u003c/sup\u003e. Importantly, \u003cem\u003eFOXP3\u003c/em\u003e+ is critical for the suppressive function of highly immunosuppressive regulatory B cells (Bregs) that secrete IL-10, IL-35, and TGF-\u0026beta;\u003csup\u003e11\u003c/sup\u003e. Our data revealed a correlation between \u003cem\u003eFOXP1\u003c/em\u003e transcript levels and therapeutic response in SAID, suggesting a mechanistic link between autoinflammation and adaptive immune regulation. To investigate this, we compared SAID patients with clinically confirmed active inflammation to true-negative controls. Of these patients, 19 were ANA positive, confirming the involvement of activated adaptive immune responses. Hierarchical clustering of inflammatory RNA markers in control samples revealed two subgroups: 43 healthy individuals with no evidence of immune activation and 25 controls with an underlying inflammatory signature. Significance Analysis of Microarrays (SAM), a modified t-statistic to identify differentially expressed genes between two or more groups, comparing the transcriptomes of the 19 ANA-positive SAID patients with the 43 true-negative controls revealed a distinct transcriptomic signature (Fig. 5, Supplementary Table 1, genes 21-50). As shown in Fig. 5, pretreatment SAID patients, including ANA-positive cases, showed a clear transcriptomic distinction from posttreatment and true-negative controls. Remarkably, the post-treatment transcriptomic profiles closely resembled those of true-negative controls, suggesting that treatment response can be quantitatively assessed using this signature. Notably, \u003cem\u003eFOXP1\u003c/em\u003e was among the top 15 upregulated genes in both true-negative controls and posttreatment samples (B), supporting its potential role in Treg/Breg function in SAIDs. This is further supported by the observed upregulation of \u003cem\u003eZFP36L2\u003c/em\u003e, which encodes RNA-binding proteins essential for T cell activation and autoreactive T cell regulation\u003csup\u003e31\u003c/sup\u003e. These findings suggest that adaptive immune regulatory mechanisms, particularly those involving \u003cem\u003eFOXP1\u003c/em\u003e and Tregs/Bregs, may play a more significant role in SAIDs than previously appreciated. Further research is needed to elucidate their contribution to disease pathophysiology and therapeutic response.\u003c/p\u003e\n\u003cp\u003eWe also analysed proteomic changes before and after treatment using SomaScan in 60 SAID patients with follow-up samples. Fig. 6 shows a heatmap of the top 30 most differentially expressed proteins, of which 15 were upregulated before treatment and downregulated after treatment, while the other 15 showed the opposite pattern (Supplementary Table 1, genes 51-65 and genes 66-80, respectively). These 30 genes were obtained by performing a SAM test, extracting the most differentially expressed proteins of SAID patients with their follow-up samples. Compared with pretreatment samples, posttreatment samples showed a marked reduction in an acute-phase protein network, including C-reactive protein (CRP). Specifically, CRP levels were significantly lower in 50 of the 60 posttreatment samples. CRP plays a well-documented role in proinflammatory innate immune responses\u003csup\u003e32\u003c/sup\u003e, and a similar downward trend was observed in other acute phase proteins. The majority of the 15 proteins upregulated in pretreatment samples are related to the acute phase response (Supplementary Table 1, genes 51-65). A protein interaction network generated using STRING DB for these 30 proteins is shown in Supplementary Fig. 2.\u003c/p\u003e\n\u003cp\u003eOur study showed that both proinflammatory and anti-inflammatory responses are simultaneously activated in 338 SAID patients and, to a lesser extent, in the 68 negative controls. These findings suggest that negative controls are not devoid of immune activation, an important consideration for future studies. Additionally, our results suggest a potential reciprocal relationship between innate and adaptive immune responses in SAID.\u0026nbsp;Furthermore, we demonstrated that a treatment that primarily targets innate immune responses significantly alters RNA the expression levels of innate immune-related genes and the proteomic expression of CRP. However, these treatments had no apparent effect on the RNA expression of genes related to adaptive immunity, an observation that warrants further investigation. Finally, we confirmed the utility of transcriptomic and proteomic profiling in monitoring treatment response. RNA-Seq heatmaps of the top 30 transcripts from 19 ANA-positive SAID patients and the top 30 proteins from 60 posttreatment samples effectively captured treatment effects. These findings provide a foundation for future studies investigating immune response modulation and therapeutic efficacy in SAID.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003ePvdS: None; DH: None; MvW: None; RvW: None; SS: None; PR: None; BF:none; DS: None; VS: Chief Medical Officer Owkin (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.owkin.com/\u003c/span\u003e\u003cspan address=\"https://www.owkin.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003ePvdS and DS conceived the project; SS RvW PvdS devised the methodology; SS RvW MvW DH PvdS conducted the investigations; RvW MvW PvdS were responsible for data curation; SS RvW MvW PvdS analyzed the data; SS; MvW and RvW DH visualized the experiments; PvdS acquired resources; RvW and PvdS responsible for project administration and reporting to EU; PvdS supervised the project; DH and PvdS wrote the original draft of the manuscript; RvW MvW SS DS PR were involved in manuscript review and editing.\u003c/p\u003e\u003ch2\u003eAvailability of data\u003c/h2\u003e \u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available for privacy reasons, but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLopez-Castejon, G. \u0026amp; Brough, D. 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Front Immunol 14, 1264383 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6173310/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6173310/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Immune responses in systemic autoinflammatory disease (SAID) were investigated by multi-omics analysis, integrating RNA expression and proteomic data. By identifying the top 10 co-expressed transcripts of IL1B and BLNK, we demonstrated the simultaneous activation of pro- and anti-inflammatory pathways in 338 SAID patients, with less activation in 68 negative controls. Our findings highlight the role of adaptive immune system-related genes in SAID, suggesting a reciprocal relationship between innate and adaptive immunity. Notably, negative controls exhibited active immune responses despite the absence of symptoms, an important consideration for data interpretation. In addition, we demonstrated how transcriptomic and proteomic profiling using heatmaps can verify treatment response, using the top 30 transcripts from 19 ANA-positive SAID patients and the top 30 proteins from 60 SAID patients with follow-up samples. These findings advance our understanding of the pathology of SAID and provide a valuable framework for treatment monitoring.","manuscriptTitle":"Integrated transcriptomic and proteomic analysis reveals innate and adaptive immune dynamics in systemic autoinflammatory diseases","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-01 11:44:20","doi":"10.21203/rs.3.rs-6173310/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsmed","sideBox":"Learn more about [Communications Medicine](http://www.nature.com/commsmed)","snPcode":"43856","submissionUrl":"https://mts-commsmed.nature.com/cgi-bin/main.plex","title":"Communications Medicine","twitterHandle":"@commsmedicine","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"205c7fe7-2779-4de2-845d-1b2daef5abea","owner":[],"postedDate":"November 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":45601945,"name":"Health sciences/Diseases/Immunological disorders/Autoimmune diseases"},{"id":45601946,"name":"Biological sciences/Immunology/Autoimmunity"}],"tags":[],"updatedAt":"2026-02-01T23:35:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-01 11:44:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6173310","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6173310","identity":"rs-6173310","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}