A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations

A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations | 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 Article A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations Jonathan Carapetis, Emmy Okello, Timothy Barnett, Casey Shannon, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4345781/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 Acute Rheumatic Fever (ARF) is a systemic inflammatory condition triggered by Group A Streptococcus infection, with timely diagnosis critical to prevent Rheumatic Heart Disease. ARF pathogenesis is poorly understood and diagnosis is based on clinical criteria. Here, we compared ARF cases and well-defined controls from two Uganda cohorts. We identified a 5-protein signature that discriminates ARF patients from clinically-similar conditions (receiver operating characteristic-area under the curve (ROC-AUC)=1.0, n=18 definite ARF vs n=9 known alternate diagnosis; ROC-AUC=0.97, n=18 definite ARF vs n=13 unknown alternate diagnosis), which retained very good diagnostic value in a validation cohort (ROC-AUC=0.83 n=26 definite ARF vs n=13 unknown alternate diagnosis). Pathway analysis identified the epithelial-mesenchymal transition pathway as highly-associated with acute ARF, suggesting that tissue damage and repair is central to ARF pathogenesis. Our findings require further validation, yet highlight the potential for proteomics to identify clinically useful diagnostic biomarkers that would revolutionise ARF diagnosis and treatment. Health sciences/Biomarkers/Diagnostic markers Biological sciences/Biochemistry/Proteomics Figures Figure 1 Figure 2 Introduction Rheumatic Heart Disease (RHD) is the most common acquired cardiovascular disease among children and young adults, with at least 40.5 million current clinical cases and 2.8 million new cases each year 1 . RHD causes 340,000 deaths annually, and is the greatest cardiovascular disease-related loss of disability-adjusted life years among 10-14 year olds 2 . The global distribution of RHD is strongly associated with conditions of social deprivation and the disease remains endemic in most low-and-middle-income countries 3 . RHD follows Acute Rheumatic Fever (ARF), a systemic inflammatory condition triggered by preceding Group A Streptococcus (GAS) infection in predisposed individuals. The prevailing hypothesis for the pathogenesis of ARF involves molecular mimicry between GAS antigens and heart valvular tissue leading to an autoimmune response 3 . Recurrent ARF episodes cause cumulative valve damage that ultimately manifests as a chronic dysfunction of the heart valve(s) known as RHD. Antibiotic prophylaxis to prevent recurrent GAS infections and resulting ARF is the only proven way to reduce RHD severity; high adherence to antibiotic prophylaxis dramatically improves outcomes 4,5 . In contrast, missed ARF cases often result in young adults presenting with advanced RHD (85%) and significant cardiovascular complications (56%) 6 . Outcomes for these patients are poor 7 , yet diagnosis with ARF is rare in Africa and other low-resource settings despite a large burden of RHD 8 . This prevents implementation of antibiotic prophylaxis in these settings. Improving accurate and early detection of ARF would significantly reduce the global burden of RHD. ARF diagnosis relies on a constellation of clinical features, laboratory testing, electrocardiogram (ECG) and, when possible, echocardiogram, combined with confirmation of recent GAS infection 9 . This poses a significant problem in low-resource settings, where GAS infections are endemic and laboratory and cardiac investigation facilities are rarely available or affordable. Even in settings where such facilities are available, the diagnostic criteria have imperfect sensitivity and specificity. A confirmatory test for ARF would be a significant advance. In this study we conducted a multi-omic interrogation of ARF patients and controls from two populations in Uganda. Our analyses identified a plasma protein biomarker signature that could discriminate ARF cases from clinically-similar inflammatory conditions, and provides new insights into the pathogenesis of this disease. Results Tissue damage and repair pathways are elevated in ARF Limited understanding of the pathogenic mechanism(s) of ARF precludes the development of improved diagnostic, prophylactic and therapeutic approaches for this disease. As a systemic disease, we reasoned that peripheral blood biomarkers may provide biological insight into ARF pathogenesis and would likely resolve during convalescence. To investigate this, we compared samples from acute and convalescent ARF cases and well-defined controls ( Fig. S1, Table 1, Source Data ), using a combination of peripheral white blood cell (WBC)-based (transcriptomics, epigenetics, flow cytometry; Supplementary Note 1), and plasma-based proteomics ( Fig. 1 ) and metabolomics (Supplementary Note 2) analyses. Participants from two geographically-distinct populations from Uganda were employed for discovery (Mulago: n=18 cases, n=9 known alternate diagnosis, n=13 unknown alternate diagnosis) and validation (Mbrara: n=26 cases, n=13 unknown alternate diagnosis). Comparison of proteomic data for ARF patient samples at presentation (0 weeks, n=26) and 1 (n=10), 6 (n=16) and 12 (n=16) weeks follow-up identified 2006 proteins as differentially abundant at presentation (adjusted p value <0.05; Source Data ). Pathway analysis ( Fig. 1a ) identified several enriched pathways including those associated with tissue damage (Allograft Rejection; adjusted p-value = 2.4 x 10 -25 ) and repair (Epithelial Mesenchymal Transition; adjusted p-value = 2.1 x 10 -36 ) ( Fig. 1a ). These tissue-centric responses were accompanied by substantial changes in major acute phase plasma proteins such as C-reactive protein (CRP), and serum amyloid proteins 1 (SAA1) and 2 (SAA2), each of which were highly upregulated at acute presentation, with levels gradually returning to those of healthy and RHD control groups during ARF convalescence ( Fig. S2 ). Accompanying this response was a similar upregulation and resolution of multiple components of the complement (e.g. C3, C5) and coagulation (e.g. F10, TFPI) pathways ( Fig. S2 ), supporting previous studies implicating these responses in ARF 10 . The adaptive immune response is central to current understanding of ARF pathogenesis. Supporting this, we observed strong elevation of interleukins-2 (IL-2) and -7 (IL-7; Fig. 1b ), and associated changes in the white blood cell transcriptome ( Supplementary Note 1 ; Fig. S3a ) 11 . However, elevated levels of cytokines classically associated with ARF (e.g. IL-6; Fig. S3a) were less strong. We also observed a strong signal for immunoglobulin D (IGHD) that was sustained during ARF convalescence and remained high in RHD controls ( Fig. 1b ). As a similar signal was not observed for IgM ( Fig. S3b ), the presence of IGHD in peripheral blood plasma may be unrelated to its general association with developing B cells. How ARF-associated immune responses translate to tissue damage, and particularly valvular damage in the heart, is not well understood. We identified multiple components of the Epithelial-Mesenchymal Transition pathway as differentially regulated in ARF ( Fig. S4 ). The most highly differentially regulated proteins in the pathway were HBEGF (Heparin-binding EGF growth factor), SCUBE1 (Signal peptide, CUB domain and EGF like domain containing 1), and PACSIN2 (Protein kinase C and casein kinase substrate in neurons 2; Fig. 1c ). Accompanying these changes were multiple extracellular matrix (ECM) proteins either highly upregulated (TNC, LAMC2, MFAP5) or downregulated (COL1A1, LUM, NID2, FBLN1, GPC1), along with proteases (MMP13, 9, 1, 3, PRSS3 and HTRA), protease modulators (TIMP1) and other effectors (CRISPLD2) associated with ECM modelling. We also observed multiple components of the vascular endothelial growth factor (VEGF) pathway that were upregulated (VEGFA and VEGFD) or downregulated (VEGFC). A 5-protein signature discriminates ARF from similar conditions ARF diagnosis currently relies on a complex rubric of clinical criteria and general markers of inflammation (e.g. CRP), with no specific biomarker that can reliably discriminate ARF cases from related clinical presentations. While not necessary for diagnosis, the value of biomarkers can be enhanced if the measured entities capture pathophysiological relationships to clinical endpoints, indicating the measured biomarkers relate to mechanisms 12 . We thus undertook a multi-omic analysis of ARF cases and known alternate diagnoses to reveal possible biomarkers that might relate to pathogenesis ( Fig. S5 ). Receiver Operating Characteristic calculations identified a strong biomarker Area Under Curve (AUC) signal within the plasma proteomics data ( Figure S5a ), with no increase in AUC values observed with integration of data across different omics platforms ( Fig. S5b ). This suggested that a subset of plasma proteins might be useful to differentiate ARF from related inflammatory conditions. We next compared protein signatures from individuals with definite ARF with individuals with known and unknown alternate diagnosis obtained from one of our study sites (Mulago; definite ARF n=18, unknown alternate diagnosis n=13, known alternate diagnosis n = 9). Using penalized logistic regression (elastic net; glmnet), we identified a 22-protein signature that discriminated the ARF group from the known and unknown alternate diagnosis groups (cross-validation AUC=0.852; Fig. 2a ; Fig. S6 ). Exploration of the elastic net parameter space with decreasing numbers of proteins ( Fig. S7 ), indicated that the smallest model with performance within 1 standard error of the maximum achieved included five protein targets (cross-validation AUC=0.835; Fig. 2a , shaded/bold). We confirmed that this five-protein panel performed well when classifying clinical cases with both known and unknown alternate diagnosis used in training the model (Mulago; Fig. 2b ) and a new set of samples (testing) from the Mbarara site ( Fig. 2c ; definite ARF n=26, unknown alternate diagnosis n=13). Performance in this test set was similar to what we observed in cross-validation. The five-protein panel distinguished ARF from alternate diagnoses, with better performance among those with clearly defined alternate diagnoses (known alternate diagnosis) as compared to those with overlapping symptoms who did not meet criteria for ARF (unknown alternate diagnosis; Fig. 2b ). This would be expected in an ARF diagnostic biomarker as a there would likely be some true ARF cases contained within the unknown alternate diagnosis group. The ideal ARF biomarker would accurately identify individuals during the acute phase of disease, but not individuals with resolved ARF or chronic RHD. We next tested the five-protein panel as a discriminative biomarker of acute-phase ARF compared to other clinical classes ( Fig. 2d ), including possible ARF (n=22; AUC=0.82), RHD without ARF (n=15; AUC=1.0), and healthy controls (n=16; AUC=0.98). In each comparison, the five-protein panel showed a high degree of discrimination. Finally, when applied to ARF samples taken during convalescence, the diagnostic value of this five-protein panel dissipated ( Fig. 2e ), emphasizing utility as an acute diagnostic. Discussion The current scientific consensus is that ARF is an autoimmune reaction to preceding GAS infection, where molecular mimicry between GAS surface molecules and heart antigens drives the characteristic damage to the heart valves 3 . However, this disease is notoriously hard to diagnose, and relies on a complex rubric of clinical features and non-specific measures of inflammation 9 . In this study, we describe a plasma protein biomarker signature that discriminates ARF patients from clinically-similar inflammatory conditions. Notably, addition of results from additional 'omics technologies (metabolomics, immune cell profiling, transcriptomics) did not improve the overall discrimination of this small panel of protein biomarkers. While our findings need to be validated in additional cohorts, including from geographically distinct populations, they do highlight the promise of proteomics to identify ARF disease-related tissue signatures that, if confirmed, could lead to clinically-useful biomarkers. While the underlying pathogenesis of ARF is generally believed to be immune-mediated, the multiple clinical manifestations (carditis, chorea, joint pain and skin manifestations) likely have different underlying biological mechanisms. Without knowing the pathogenic mechanisms underlying the different manifestations of ARF, it is difficult to interpret what would be expected when specific presentations are or are not present, since molecular events may still be occurring sub-clinically in the absence of symptoms. The identification of multiple protein components in plasma associated with the Epithelial- (and Endothelial-) Mesenchymal Transition pathway ( Fig. S4 ) as highly-associated with acute ARF suggests that tissue damage and repair may be central to ARF pathogenesis, and likely contributes to the valve damage and fibro-inflammatory process that results in chronic RHD. HBEGF (Heparin-binding EGF growth factor) is a secreted growth factor produced by monocytes and macrophages during tissue damage that signals through EGF receptors during wound healing and angiogenesis. HBEGF has been found to play a critical role during cardiac valve tissue development in mice, by regulating mesenchymal proliferation required during normal cardiac valve formation 13 . High circulating HBEGF levels during ARF could dysregulate mesenchymal organisation during valvular repair. SCUBE1 (Signal peptide, CUB domain and EGF like domain containing 1) is highly expressed in the vascular endothelium and participates in VEGFA signalling and thrombogenesis 14 . SCUBE1 plasma levels have been associated with cardiac endothelial damage 15 . PACSIN2 (Protein kinase C and casein kinase substrate in neurons 2) has been shown to be important during development of the mouse heart; but as an endocytic protein, the source and function of higher plasma levels of PACSIN2 was not obvious 16 . The high differential abundance of HBEGF, SCUBE1 and PACSIN2 in ARF compared to RHD, and the similar kinetics of HBEGF and SCUBE1 during progression of ARF convalescence suggest they may represent useful targets to follow during ARF and RHD disease progression. The proteomic signature identified in this study (ARF at the time of initial diagnosis) differs from that seen in chronic, severe RHD. In the largest study to date 17 , including 215 African patients with severe RHD, a machine learning approach identified a six-protein signature that distinguished RHD cases from healthy controls. The proteins that emerged in that study as most discriminatory were those involved in an ongoing inflammatory response, including complement component C7, adipotnectin, quiescin oxidates 1, fibulin-1, and ficolin-3 17 . It is unsurprising that this signature does not overlap with the ARF signature in our study, but does suggest that additional biomarkers may be able to identify those acute ARF cases who will develop RHD. In this context, we identified several plasma proteins that remained elevated 12 weeks after acute presentation (e.g. PACSIN2, MNDA, SERPIN E2) and IGHD that also remained elevated in RHD patients. The identification of elevated IGHD in ARF and RHD is intriguing, as several studies have also shown elevated IgD in other autoimmune diseases 18 , and IgD signalling in B cells is preferentially activated by multivalent antigens, which might include the GAS M and collagen-like proteins that are proposed to play a central role in ARF pathogenesis 3,19 . Future work should aim to recruit and analyze a wider spectrum of ARF and RHD patients, capturing those with differential outcomes over time and across the RHD severity spectrum to further understand these differences. While our proteomic approach to biomarker discovery for ARF fulfilled most recommendations for biomarker identification, this study has several limitations. The patients all came from Uganda, and this narrow geographic focus as well as the relatively small sample size could be barriers to generalizability of this study. Future work will need to replicate these signatures in a diverse global cohort. The small sample size also did not allow investigation of specific signatures unique to each of the clinical manifestations of ARF (e.g. carditis vs chorea). Additionally, as the existing diagnostic criteria for ARF have imperfect sensitivity and specificity, until we find a sensitive and specific diagnostic biomarker a better gold standard does not exist. Ultimately, biomarkers may substitute for clinically relevant endpoints providing a faster, cheaper and more precise diagnostic and/or prognostic insight 12 . The aptamer-based proteomics platform we employed has provided clinically useful biomarkers demonstrating feasibility for translation into clinical application, as has been achieved in other areas of medicine 20-23 . Furthermore, proteomic approaches supporting point-of-care testing have also been successfully developed 24 along with platforms that allow translation into low resource settings 25 . Future work will require translation of candidate biomarker signature(s) into appropriate testing platforms, and prospectively evaluating diagnostic performance through clinical trials on children presenting to clinical sites with possible ARF. In conclusion, we report a proteomic pathogenesis and diagnostic biomarker signature in ARF. Novel pathways centering around inflammation, tissue damage and repair emerged that represent plausible mechanisms of ARF pathogenesis. Embedded in this pathogenesis signature was a highly discriminatory set of five proteins that could distinguish ARF from infectious and inflammatory diseases that clinically overlap. While further mechanistic and clinical validation is required to replicate these results, our results demonstrate feasibility of a clinically useful ARF diagnostic biomarker that could substantially improve ARF diagnosis globally. Methods Inclusion and Ethics This research is highly relevant to local communities in Uganda. The study protocol was approved by the Makerere University School of Medicine Research and Ethics committee (REC REF 2017-042), and the Uganda National Council for Science and Technology (HS 2215). This study was conducted in partnership with local researchers at the The Uganda Heart Institute who were involved in the design, data collection, analysis, and reporting. Study Design, Settings, and Participants This was a planned case-control sub-study under a larger prospective epidemiological study conducted in Uganda between 2018 and 2020. The detailed recruitment methods of the parent study have been previously published 26,27 . ARF clinics were established at Mbarara Regional Referral Hospital (Western Region) and at Mulago National Referral Hospital (Central Region). Community and provider sensitization was conducted through direct education and mass media approaches. Children aged 3-17 years of age who presented with either history of fever in the past 48 hours and a joint complaint, suspicion of rheumatic carditis, or suspicion of chorea were invited to the clinic for additional evaluation. Additionally, for this sub-study, three control groups were recruited under an amendment of the original ethics from various hospital and community settings for each case of ARF, including one each from the categories of children with RHD without ARF, children with overlapping clinical presentation who had confirmed alternate infectious or inflammatory conditions (i.e., sickle cell crisis, malaria, influenza), and healthy controls with no signs or symptoms of acute infection or inflammatory condition. All parents signed a written informed consent prior to their child’s participation, and children eight years of age and older also signed a written informed assent. Participants selected for this study included 50 children diagnosed with definite ARF, 43 children diagnosed with possible ARF, 16 children classified as healthy, 38 children with alternate diagnoses with overlapping clinical phenotypes (9 children with known alternate diagnoses, 29 children with unknown alternate diagnosis), and 18 children with chronic RHD without ARF. All ARF presentations were the first known diagnosis as we were unable to discriminate between initial and recurrent ARF episodes. The median age of the cohort was 9 years (IQR 6-12 years), 48% were female, and 64 (39%) were recruited at the Mbarara site (as compared to Mulago site). Intake Procedures The same intake protocol was utilized for ARF cases and controls. Components of data collection have been described in detail elsewhere 26 , and include a history of the present illness, past medical history, family history, physical exam, point of care testing for Group A Streptococcus (Thermofisher Scientific rapid antigen detection kit, Waltham MA, USA), HIV (Determine, Abbott, Chicago, IL, USA), and malaria (CareStart, Apacor, Berkshire, England), electrocardiogram, and focused echocardiogram. A blood sample was also taken for clinical testing which included a complete blood count, erythrocyte sedimentation rate, C-reactive protein, malaria blood smear, antistreptolysin O titers, and antideoxyribonuclease B titers, and biobanking, which included 10 milliliters of peripheral blood. Follow-up Procedures Diagnosis of ARF was completed only after all testing and laboratory results returned. Participant diagnosed with definite and possible ARF were invited for additional follow-up visits at 1 week, 6 weeks, and 12 weeks (Mulago) and 1 week and 12 weeks (Mbarara). During these visits, interval clinical history, physical exam, and echocardiography were performed. Additional peripheral blood samples were collected using the same protocol, when possible, for biobanking of convalescent samples. Case and Control Adjudication The same adjudication protocol, including double blinded review of all clinical, imaging, and laboratory data, was utilized for cases and controls. The 2015 Jones’ Criteria for moderate and high-risk populations and the clinical expertise of the reviewers were used to adjudicate each study participant’s data and categorize them as definite ARF, possible ARF, known alternate diagnosis, or unknown alternate diagnosis. Within the known alternate diagnosis, were the categories of RHD without ARF, overlapping infectious and inflammatory conditions, and healthy without signs of acute infection or inflammatory condition (Table 1). When two reviews were concordant, no additional review was conducted. When the two reviews were discordant, the reviewers discussed the case and came to a consensus decision. As most laboratory testing was not available immediately at the time of recruitment, many suspected ARF cases and controls were reclassified from their enrolment category during adjudication (e.g., an apparently healthy control who had elevated streptococcal titres would be excluded from counting as a pure healthy control for this sub-study). Further, many children were classified as unknown alternate diagnosis when they had symptomatic overlap with ARF but did not meet the minimum diagnostic criteria for ARF, and did not have a confirmed alternate cause for their symptoms. Final classification of individuals included in this study and accompanying diagnostic criteria (Clinical Metadata) are provided in the Source Data file. Biospecimen collection and samples storage for multi-omic analysis Peripheral whole blood was collected from eligible study participants in PAXgene and Lithium Heparin vacutainers performed by trained phlebotomists in Uganda under local (Makerere University School of Medicine Research and Ethics Committee 2017–042). Shortly after collection, whole blood samples in PAXgene tubes were stored at -80°C after 2 hours of incubation at room temperature to be used for RNA sequencing. Heparin blood was spun down to collect plasma for Proteomics and Metabolomics analysis. The plasma-depleted blood was used for Flow Cytometry analysis. The rest of the blood cells were then treated with red blood cell lysis buffer for 10 minutes, spun down and the white blood cells (WBC) were washed in phosphate buffer saline, and saved as a dry pellet at -80°C for future Epigenetics analysis. Samples were transferred to The Kids Research Institute Australia on dry ice with continuous temperature monitoring. On arrival, rigorous quality checks were employed. Samples with unclear sample identification, documentation on sample collection logs that was missing data or outside of the standard procedures (i.e., too long between sample collection and processing), visible damage or cracking to the tube, or with any other concerns, were excluded from the study. Power Analysis We anticipated our final sample size to depend on the annual incidence of ARF. To inform our recruitment strategy, a target a priori sample size calculation was performed using PASS15 (Power Analysis and Sample Size Software 2017, Kaysville, Utah). We assumed a 30% variance in the biological markers within the population (based on previous studies), and determined that with a sample size of 100 cases and 100 controls we would have 82% power to detect a 16% difference at alpha 0.01. Practicalities of recruiting cases and obtaining sufficient sample volumes in rural Uganda, together with advances in the analysis platforms, resulted in this analysis being based on a convenience sample that were available for ARF cases and controls, as outlined in Figure 1. Analysis Plan The primary goal of our biomarker discovery was to distinguish participants with definite ARF from participants with other clinically overlapping conditions; the situation where a diagnostic test would be most useful. Thus, the primary comparison for these studies was Definite ARF as compared to Alternate Diagnosis (both known and unknown). Secondary analyses considered definite ARF longitudinally over the course of convalescence, and compared to other clinical classifications including possible ARF, RHD without ARF, and healthy controls. Preliminary analysis identified study site as a significant source of variation in the proteomics data. Adjusting for this potential confounder was challenging, however, due to the uneven distribution of diagnostic classes between sites. To eliminate potential site-confounders, we leveraged samples from Mulago for initial discovery (Definite ARF vs. Alternate Diagnosis (known and unknown), using 20 times repeated 5-fold cross-validation, and testing increasingly smaller models (larger values of the glmnet penalization hyperparameter λ). We then assessed performance of the smallest model in samples from Mbarara (Definite ARF vs. Alternate Diagnosis) and studied the distribution of the model linear predictors of disease in the other diagnostic classes (Definite ARF vs. Possible ARF, RHD without ARF, and Healthy Controls) at Mulago. Participants with definite ARF were also profiled over time at both the Mulago (Enrolment, Week 1, Week 6, Week 12) and Mbarara (Enrolment, Week 12) sites, to assess if identified biomarkers were modifiable as the disease process moved from acute to convalescent. We deliberately chose not to adjust for factors such as age, sex, and ethnicity in our primary analysis, as correlations between these factors and disease status may represent genuine risk associations rather than confounding effects. SOMAscan™ Proteomics Assay: The SomaScan™ proteomic profiling platform utilizes SOMAmer reagents (single stranded, chemically-modified DNA-based aptamers) that bind to target proteins with high affinity and specificity. The assay includes 7596 individual SOMAmers reagents, of which there are 6596 unique human proteins measurable in 55ml of plasma collected from venous heparinized blood. The assays were performed by SomaLogic according to their standard protocol to quantitatively determine the proteins present. SomaScan Assay data were normalized using internal hybridization controls to mitigate bias caused by differential readout conditions in the individual microarrays due to eluate transfer, hybridization, wash, and scan. This was followed by median signal normalization across pooled calibrator replicates within each run to mitigate within-run technical variation in the calibrator signal prior to use in scaling calculations. The set of ratios of the calibrator reference value to the median of calibrator replicates for each SOMAmer reagent was used to calculate plate scale and calibration scale.; scale factor acceptance criteria per plate were predefined as between 0.4-2.5 and calibration scale factors between 0.6-1.4. In total, data were obtained for 7596 SOMAmer reagents We retained SOMAmers corresponding to human (p=7335) proteins (p=7288) that passed Somalogic quality control checks. The resulting 6664 SOMAmers reagents (corresponding to 5911 unique Uniprot protein identifiers) were used for analysis. Open-source microarray analysis software from the R/Bioconductor consortium was used to analyze the SomaScan™ microarray data (http://www.bioconductor.org/). Proteins with different relative plasma concentrations between grouped by disease stages were identified using robust linear regression model and a moderated t statistic as implemented in the R package “limma”. To provide additional biological context, proteins identified in this way were subsequently used to carry out pathway over-representation analysis using a hypergeometric test and the MSigDB Hallmark collection of gene sets. The p values were adjusted using the Benjamini-Hochberg procedure to control the false discovery rate (FDR). Proteins were considered significantly changed if they had an FDR-adjusted p value <0.05 and a fold change greater than 20%. Declarations DATA AVAILABILITY The proteomic, metabolomic and flow cytometry datasets and de-identified clinical data have been deposited in the Mendeley Data database under accession code 5ppxd6sgdb (DOI: 10.17632/5ppxd6sgdb.1). Due to ethical and legal restrictions, raw sequence and epigenomic files are not publicly available. Requests for access to these datasets or any other data supporting the findings of this study should be directed to the corresponding author [JRC]. Source data are provided with this paper. CODE AVAILABILITY Codes related to this article can be accessed via GitHub at https://github.com/T-Barnett/Okello-et-al-2025 Acknowledgments: We thank the patients, families, communities, and clinicians who participated in this study in Uganda to advance our global knowledge of ARF and RHD. Further, we thank Dr. Tom Parks from Imperial College in London who contributed expertise to the parent epidemiological study that led to participant recruitment. This work was supported by American Heart Association Strategically Focused Research Network 17SFRN33670607, The Cincinnati Children’s Heart Institute Research Core, and the The Kids Research Institute Australia. TCB is supported by a Translation fellowship from the Western Australian Future Health Research and Innovation Fund. Author contributions: AB and JRC conceptualised the study. EO, JA, PL, EN, LMO, JP and CAS recruited participants, processed samples, or interpreted diagnostic testing. 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Proteomic Approaches to Enable Point-of-Care Testing and Personalized Medicine for Psychiatric Disorders. Adv Exp Med Biol 974 , 363-370, doi:10.1007/978-3-319-52479-5_35 (2017). Yager, P. et al. Microfluidic diagnostic technologies for global public health. Nature 442 , 412-418, doi:10.1038/nature05064 (2006). Okello, E. et al. Incidence of acute rheumatic fever in northern and western Uganda: a prospective, population-based study. Lancet Glob Health 9 , e1423-e1430, doi:10.1016/S2214-109X(21)00288-6 (2021). Okello, E. et al. Active Case Finding for Rheumatic Fever in an Endemic Country. J Am Heart Assoc 9 , e016053, doi:10.1161/JAHA.120.016053 (2020). Table 1 Anti-streptolysin O titer and/or Anti-DNASE B titer ³80% for age, and/or a throat culture or rapid antigen test positive for group A b-hemolytic streptococci in a child whose presentation is suspicious for streptococcal pharyngitis. Cannot use if carditis counted as a major critiera. Cannot use if joint complaints counted as a major criteria Additional Declarations There is NO Competing Interest. Supplementary Files SourceDataNCOMMS2427256A.xlsx Source Data SupplementaryInformationNCOMMS2427256A.pdf Supplementary information nreditorialpolicychecklistNCOMMS2427256A.pdf Editorial policy Checklist NCOMMS2427256Ars.pdf Reporting Summary 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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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-4345781","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":448510799,"identity":"ece964ed-2b0e-4ec5-ba06-181ca36e7ef3","order_by":0,"name":"Jonathan 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Institute","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Martino","suffix":""},{"id":448510813,"identity":"4f7dec24-fd6f-4011-a036-7819408fb9f2","order_by":14,"name":"Emma Ndagire","email":"","orcid":"","institution":"Uganda Heart Institute","correspondingAuthor":false,"prefix":"","firstName":"Emma","middleName":"","lastName":"Ndagire","suffix":""},{"id":448510814,"identity":"62e481b5-8d80-49c5-895c-b957e907ac07","order_by":15,"name":"Linda Oyella","email":"","orcid":"","institution":"Uganda Heart Institute","correspondingAuthor":false,"prefix":"","firstName":"Linda","middleName":"","lastName":"Oyella","suffix":""},{"id":448510815,"identity":"cf0ff924-d17e-4f64-a90e-f62dbbee765e","order_by":16,"name":"Rym Ben Othman","email":"","orcid":"","institution":"Telethon Kids 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"","lastName":"Sarnacki","suffix":""},{"id":448510819,"identity":"4dab2703-9608-45b0-b4da-45ce74367e9a","order_by":20,"name":"Michael Serralha","email":"","orcid":"https://orcid.org/0000-0002-0121-2879","institution":"Telethon Kids Institute","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Serralha","suffix":""},{"id":448510820,"identity":"1ce92956-0320-4af5-a4b8-d65e71cb55b0","order_by":21,"name":"Scott Tebbutt","email":"","orcid":"https://orcid.org/0000-0002-7908-1581","institution":"PROOF","correspondingAuthor":false,"prefix":"","firstName":"Scott","middleName":"","lastName":"Tebbutt","suffix":""},{"id":448510821,"identity":"f4a82507-6473-4ca1-ba45-36618c9a4b3f","order_by":22,"name":"Andrea Beaton","email":"","orcid":"","institution":"Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Beaton","suffix":""},{"id":448510822,"identity":"4b1b14e7-7a5e-47b1-9d2d-d2c4605c36e9","order_by":23,"name":"Tobias Kollmann","email":"","orcid":"https://orcid.org/0000-0003-2403-9762","institution":"Telethon Kids Institute","correspondingAuthor":false,"prefix":"","firstName":"Tobias","middleName":"","lastName":"Kollmann","suffix":""},{"id":448510823,"identity":"6fef9adc-1cb4-4665-988e-147714de74c8","order_by":24,"name":"Wenna Lee","email":"","orcid":"","institution":"The Kids research Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Wenna","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2024-04-30 02:50:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4345781/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4345781/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81955519,"identity":"eaaaa0b5-5a4c-4922-9eb2-dd243fd70b48","added_by":"auto","created_at":"2025-05-05 09:52:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":456140,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultiple tissue damage and repair pathways associated with ARF. a\u003c/strong\u003e, Pathway over-representation analysis against MSigDB’s Hallmark collection of gene sets was carried out using proteins with differences in relative plasma concentration (adjusted p\u0026lt;0.05) when comparing healthy controls (HC) to definite ARF at 0, 1, 6, or 12+ weeks after diagnosis, and additionally for proteins exhibiting differences over time (linear trend) in definite ARF (hypergeometric test; adjusting for multiple comparisons using the Benjamini-Hochberg procedure). The results are visualized across comparisons using a heatmap. Pathways were ranked by computing the geometric mean of the adjusted p-values values obtained across comparisons. \u003cstrong\u003eb-c\u003c/strong\u003e, Temporal patterns of relative protein plasma concentration for major dysregulated proteins from the adaptive immune system (\u003cstrong\u003ea\u003c/strong\u003e) and epithelial-mesenchymal transition pathway (\u003cstrong\u003eb\u003c/strong\u003e). SOMAscan™ probe IDs are indicated. Statistical comparisons between ARF vs Healthy and ARF vs RHD are provided above corresponding datasets (Student's t-test). For each box, the data is visualised with the inner line to represent the median with the top and bottom edge representing the 1\u003csup\u003est\u003c/sup\u003e quartile and 3\u003csup\u003erd\u003c/sup\u003e quartile respectively. The whiskers span the range of data within 1.5 times the interquartile range from Q1 to Q3 and data points outside of the whiskers represent outliers. Statistical comparison between ARF acute and convalescent samples (p\u003csub\u003etrend\u003c/sub\u003e) are also provided.\u003c/p\u003e","description":"","filename":"Figure1NCOMMS2427256A.png","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/8c799159342bb35e37f7d342.png"},{"id":81954635,"identity":"79415a01-5337-4d73-98f8-31db91392845","added_by":"auto","created_at":"2025-05-05 09:44:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":776925,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA plasma protein biomarker differentiates ARF from clinically similar conditions.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, A 22 protein signature that discriminates ARF from related clinical conditions. The proteins that make up the 5-protein signature are highlighted/bolded. \u003cstrong\u003eb-c\u003c/strong\u003e, Performance of the 5-protein set in the training data (\u003cstrong\u003eb\u003c/strong\u003e; Mulago) and testing data (\u003cstrong\u003ec\u003c/strong\u003e; Mbarara). Boxplots the linear predictors from a penalized logistic regression models derived from proteomics. \u003cstrong\u003ed, \u003c/strong\u003eCorresponding area under the receiver-operator characteristic curve (AUC) when discriminating definite rheumatic fever from possible rheumatic fever (light blue), rheumatic heart disease (without rheumatic fever; green), or healthy (dark blue). \u003cstrong\u003ee\u003c/strong\u003e, Performance during convalescence (Mulago).\u0026nbsp;Boxplots of the linear predictors from a penalized logistic regression models derived from proteomics. Corresponding area under the receiver-operator characteristic curve (AUC) when discriminating acute rheumatic fever to paired convalescent time points proteomics. Statistical comparisons are as follows (2-sided Student's t-test): \u003cstrong\u003eb\u003c/strong\u003e, Def ARF vs Unknown alt p=4.4e-07 (****), Def ARF vs Known alt p=4.3e-07 (****); \u003cstrong\u003ec\u003c/strong\u003e, Def ARF vs Unknown alt p=0.00045 (***); \u003cstrong\u003ed\u003c/strong\u003e, Def ARF vs Poss ARF p=3e-04 (***), Def ARF vs RHD p=1.9e-09 (****), Def ARF vs Healthy p=1.7e-08 (****), RHD vs Healthy p=0.45 (ns, non-significant); \u003cstrong\u003ee\u003c/strong\u003e, 0 vs 1 p=0.968 (ns, non-significant), 0 vs 6 p=0.017 (*), 0 vs 12+ p=0.001 (**), 0 vs RHD p=2.5e-08 (****), 0 vs Healthy p=3.7e-08 (****). For each box, the data is visualised with the inner line to represent the median with the top and bottom edge representing the 1\u003csup\u003est\u003c/sup\u003e quartile and 3\u003csup\u003erd\u003c/sup\u003e quartile respectively. The whiskers span the range of data within 1.5 times the interquartile range from Q1 to Q3 and data points outside of the whiskers represent outliers.\u003c/p\u003e","description":"","filename":"Figure2NCOMMS2427256A.png","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/0224afb4bca459a277b7fb43.png"},{"id":81956782,"identity":"d702b77c-6520-48bb-af8d-a3d1969f6b6f","added_by":"auto","created_at":"2025-05-05 10:00:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2039511,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/a510445b-fdb1-47e7-a27d-78fd16fcabb1.pdf"},{"id":81954637,"identity":"6a22440d-a501-477f-8730-416f9c9be0bb","added_by":"auto","created_at":"2025-05-05 09:44:01","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":492585,"visible":true,"origin":"","legend":"Source Data","description":"","filename":"SourceDataNCOMMS2427256A.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/a35ed7f7e0a18d2eb3813a58.xlsx"},{"id":81954645,"identity":"8acbe4b6-18bd-4751-9e1a-70679fa83d2f","added_by":"auto","created_at":"2025-05-05 09:44:02","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":6848104,"visible":true,"origin":"","legend":"Supplementary information","description":"","filename":"SupplementaryInformationNCOMMS2427256A.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/2cb1902198ff0d586719e167.pdf"},{"id":81954638,"identity":"3a64dd04-017d-4340-8bed-69c672ac4f6c","added_by":"auto","created_at":"2025-05-05 09:44:01","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1682384,"visible":true,"origin":"","legend":"Editorial policy Checklist","description":"","filename":"nreditorialpolicychecklistNCOMMS2427256A.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/de332a8429514593d1e12b50.pdf"},{"id":81954647,"identity":"8d819c58-067e-4f21-b928-9bda5c0dc0d9","added_by":"auto","created_at":"2025-05-05 09:44:02","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2794534,"visible":true,"origin":"","legend":"\u003cp\u003eReporting Summary\u003c/p\u003e","description":"","filename":"NCOMMS2427256Ars.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345781/v1/78047adb6bf26aaef75301db.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRheumatic Heart Disease (RHD) is the most common acquired cardiovascular disease among children and young adults, with at least 40.5 million current clinical cases and 2.8 million new cases each year\u003csup\u003e1\u003c/sup\u003e. RHD causes 340,000 deaths annually, and is the greatest cardiovascular disease-related loss of disability-adjusted life years among 10-14 year olds\u003csup\u003e2\u003c/sup\u003e. The global distribution of RHD is strongly associated with conditions of social deprivation and the disease remains endemic in most low-and-middle-income countries\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eRHD follows Acute Rheumatic Fever (ARF), a systemic inflammatory condition triggered by preceding Group A \u003cem\u003eStreptococcus\u003c/em\u003e (GAS) infection in predisposed individuals. The prevailing hypothesis for the pathogenesis of ARF involves molecular mimicry between GAS antigens and heart valvular tissue leading to an autoimmune response\u003csup\u003e3\u003c/sup\u003e. Recurrent ARF episodes cause cumulative valve damage that ultimately manifests as a chronic dysfunction of the heart valve(s) known as RHD.\u0026nbsp;Antibiotic prophylaxis to prevent recurrent GAS infections and resulting ARF is the only proven way to reduce RHD severity; high adherence to antibiotic prophylaxis dramatically improves outcomes\u003csup\u003e4,5\u003c/sup\u003e. \u0026nbsp; In contrast, missed ARF cases often result in young adults presenting with advanced RHD (85%) and significant cardiovascular complications (56%)\u003csup\u003e6\u003c/sup\u003e. Outcomes for these patients are poor\u003csup\u003e7\u003c/sup\u003e, yet diagnosis with ARF is rare in Africa and other low-resource settings despite a large burden of RHD\u003csup\u003e8\u003c/sup\u003e. This prevents implementation of antibiotic prophylaxis in these settings.\u003c/p\u003e\n\u003cp\u003eImproving accurate and early detection of ARF would significantly reduce the global burden of RHD. ARF diagnosis relies on a constellation of clinical features, laboratory testing, electrocardiogram (ECG) and, when possible, echocardiogram, combined with confirmation of recent GAS infection\u003csup\u003e9\u003c/sup\u003e. This poses a significant problem in low-resource settings, where GAS infections are endemic and laboratory and cardiac investigation facilities are rarely available or affordable. Even in settings where such facilities are available, the diagnostic criteria have imperfect sensitivity and specificity. A confirmatory test for ARF would be a significant advance. In this study we conducted a multi-omic interrogation of ARF patients and controls from two populations in Uganda. Our analyses identified a plasma protein biomarker signature that could discriminate ARF cases from clinically-similar inflammatory conditions, and provides new insights into the pathogenesis of this disease.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTissue damage and repair pathways are elevated in ARF\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLimited understanding of the pathogenic mechanism(s) of ARF precludes the development of improved diagnostic, prophylactic and therapeutic approaches for this disease. As a systemic disease, we reasoned that peripheral blood biomarkers may provide biological insight into ARF pathogenesis and would likely resolve during convalescence. To investigate this, we compared samples from acute and convalescent ARF cases and well-defined controls (\u003cstrong\u003eFig. S1, Table 1, Source Data\u003c/strong\u003e), using a combination of peripheral white blood cell (WBC)-based (transcriptomics, epigenetics, flow cytometry; Supplementary Note 1), and plasma-based proteomics (\u003cstrong\u003eFig. 1\u003c/strong\u003e) and metabolomics (Supplementary Note 2) analyses. Participants from two geographically-distinct populations from Uganda were employed for discovery (Mulago: n=18 cases, n=9 known alternate diagnosis, n=13 unknown alternate diagnosis) and validation (Mbrara: n=26 cases, n=13 unknown alternate diagnosis). Comparison of proteomic data for ARF patient samples at presentation (0 weeks, n=26) and 1 (n=10), 6 (n=16) and 12 (n=16) weeks follow-up identified 2006 proteins as differentially abundant at presentation (adjusted p value \u0026lt;0.05; \u003cstrong\u003eSource Data\u003c/strong\u003e). Pathway analysis (\u003cstrong\u003eFig. 1a\u003c/strong\u003e) identified several enriched pathways including those associated with tissue damage (Allograft Rejection; adjusted p-value = 2.4 x 10\u003csup\u003e-25\u003c/sup\u003e) and repair (Epithelial Mesenchymal Transition; adjusted p-value = 2.1 x 10\u003csup\u003e-36\u003c/sup\u003e) (\u003cstrong\u003eFig. 1a\u003c/strong\u003e). These tissue-centric responses were accompanied by substantial changes in major acute phase plasma proteins such as C-reactive protein (CRP), and serum amyloid proteins 1 (SAA1) and 2 (SAA2), each of which were highly upregulated at acute presentation, with levels gradually returning to those of healthy and RHD control groups during ARF convalescence (\u003cstrong\u003eFig. S2\u003c/strong\u003e). Accompanying this response was a similar upregulation and resolution of multiple components of the complement (e.g. C3, C5) and coagulation (e.g. F10, TFPI) pathways (\u003cstrong\u003eFig. S2\u003c/strong\u003e), supporting previous studies implicating these responses in ARF\u003csup\u003e10\u003c/sup\u003e. The adaptive immune response is central to current understanding of ARF pathogenesis. Supporting this, we observed strong elevation of interleukins-2 (IL-2) and -7 (IL-7; \u003cstrong\u003eFig. 1b\u003c/strong\u003e), and associated changes in the white blood cell transcriptome (\u003cstrong\u003eSupplementary Note 1\u003c/strong\u003e; \u003cstrong\u003eFig. S3a\u003c/strong\u003e)\u003csup\u003e11\u003c/sup\u003e. However, elevated levels of cytokines classically associated with ARF (e.g. IL-6; Fig. S3a) were less strong. We also observed a strong signal for immunoglobulin D (IGHD) that was sustained during ARF convalescence and remained high in RHD controls (\u003cstrong\u003eFig. 1b\u003c/strong\u003e). As a similar signal was not observed for IgM (\u003cstrong\u003eFig. S3b\u003c/strong\u003e), the presence of IGHD in peripheral blood plasma may be unrelated to its general association with developing B cells.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;How ARF-associated immune responses translate to tissue damage, and particularly valvular damage in the heart, is not well understood. We identified multiple components of the Epithelial-Mesenchymal Transition pathway as differentially regulated in ARF (\u003cstrong\u003eFig. S4\u003c/strong\u003e). The most highly differentially regulated proteins in the pathway were HBEGF (Heparin-binding EGF growth factor), SCUBE1 (Signal peptide, CUB domain and EGF like domain containing 1), and PACSIN2 (Protein kinase C and casein kinase substrate in neurons 2; \u003cstrong\u003eFig. 1c\u003c/strong\u003e). Accompanying these changes were multiple extracellular matrix (ECM) proteins either highly upregulated (TNC, LAMC2, MFAP5) or downregulated (COL1A1, LUM, NID2, FBLN1, GPC1), along with proteases (MMP13, 9, 1, 3, PRSS3 and HTRA), protease modulators (TIMP1) and other effectors (CRISPLD2) associated with ECM modelling. We also observed multiple components of the vascular endothelial growth factor (VEGF) pathway that were upregulated (VEGFA and VEGFD) or downregulated (VEGFC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eA 5-protein signature discriminates ARF from similar conditions\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eARF diagnosis currently relies on a complex rubric of clinical criteria and general markers of inflammation (e.g. CRP), with no specific biomarker that can reliably discriminate ARF cases from related clinical presentations. While not necessary for diagnosis, the value of biomarkers can be enhanced if the measured entities capture pathophysiological relationships to clinical endpoints, indicating the measured biomarkers relate to mechanisms\u003csup\u003e12\u003c/sup\u003e. We thus undertook a multi-omic analysis of ARF cases and known alternate diagnoses to reveal possible biomarkers that might relate to pathogenesis (\u003cstrong\u003eFig. S5\u003c/strong\u003e). Receiver Operating Characteristic calculations identified a strong biomarker Area Under Curve (AUC) signal within the plasma proteomics data (\u003cstrong\u003eFigure S5a\u003c/strong\u003e), with no increase in AUC values observed with integration of data across different omics platforms (\u003cstrong\u003eFig. S5b\u003c/strong\u003e). This suggested that a subset of plasma proteins might be useful to differentiate ARF from related inflammatory conditions. We next compared protein signatures from individuals with definite ARF with individuals with known and unknown alternate diagnosis obtained from one of our study sites (Mulago; definite ARF n=18, unknown alternate diagnosis n=13, known alternate diagnosis n = 9). Using penalized logistic regression (elastic net; glmnet), we identified a 22-protein signature that discriminated the ARF group from the known and unknown alternate diagnosis groups (cross-validation AUC=0.852; \u003cstrong\u003eFig. 2a\u003c/strong\u003e; \u003cstrong\u003eFig. S6\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExploration of the elastic net parameter space with decreasing numbers of proteins (\u003cstrong\u003eFig. S7\u003c/strong\u003e), indicated that the smallest model with performance within 1 standard error of the maximum achieved included five protein targets (cross-validation AUC=0.835; \u003cstrong\u003eFig. 2a\u003c/strong\u003e, shaded/bold). We confirmed that this five-protein panel performed well when classifying clinical cases with both known and unknown alternate diagnosis used in training the model (Mulago; \u003cstrong\u003eFig. 2b\u003c/strong\u003e) and a new set of samples (testing) from the Mbarara site (\u003cstrong\u003eFig. 2c\u003c/strong\u003e; definite ARF n=26, unknown alternate diagnosis n=13). Performance in this test set was similar to what we observed in cross-validation. The five-protein panel distinguished ARF from alternate diagnoses, with better performance among those with clearly defined alternate diagnoses (known alternate diagnosis) as compared to those with overlapping symptoms who did not meet criteria for ARF (unknown alternate diagnosis; \u003cstrong\u003eFig. 2b\u003c/strong\u003e). This would be expected in an ARF diagnostic biomarker as a there would likely be some true ARF cases contained within the unknown alternate diagnosis group. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ideal ARF biomarker would accurately identify individuals during the acute phase of disease, but not individuals with resolved ARF or chronic RHD. We next tested the five-protein panel as a discriminative biomarker of acute-phase ARF compared to other clinical classes (\u003cstrong\u003eFig. 2d\u003c/strong\u003e), including possible ARF (n=22; AUC=0.82), RHD without ARF (n=15; AUC=1.0), and healthy controls (n=16; AUC=0.98). In each comparison, the five-protein panel showed a high degree of discrimination. Finally, when applied to ARF samples taken during convalescence, the\u0026nbsp;diagnostic value of this five-protein panel dissipated (\u003cstrong\u003eFig. 2e\u003c/strong\u003e), emphasizing utility as an acute diagnostic.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current scientific consensus is that ARF is an autoimmune reaction to preceding GAS infection, where molecular mimicry between GAS surface molecules and heart antigens drives the characteristic damage to the heart valves\u003csup\u003e3\u003c/sup\u003e. However, this disease is notoriously hard to diagnose, and relies on a complex rubric of clinical features and non-specific measures of inflammation\u003csup\u003e9\u003c/sup\u003e. In this study, we describe a plasma protein biomarker signature\u0026nbsp;that discriminates ARF patients from clinically-similar inflammatory conditions. Notably,\u0026nbsp;addition of results from additional \u0026apos;omics technologies (metabolomics, immune cell profiling, transcriptomics) did not improve the overall discrimination of this small panel of protein biomarkers. While our findings need to be validated in additional cohorts, including from geographically distinct populations, they do highlight the promise of proteomics to identify ARF disease-related tissue signatures that, if confirmed, could lead to clinically-useful biomarkers.\u003c/p\u003e\n\u003cp\u003eWhile the underlying pathogenesis of ARF is generally believed to be immune-mediated, the multiple clinical manifestations (carditis, chorea, joint pain and skin manifestations) likely have different underlying biological mechanisms.\u0026nbsp;Without knowing the pathogenic mechanisms underlying the different manifestations of ARF, it is difficult to interpret what would be expected when specific presentations are or are not present, since molecular events may still be occurring sub-clinically in the absence of symptoms. The identification of multiple protein components in plasma associated with the Epithelial- (and Endothelial-) Mesenchymal Transition pathway (\u003cstrong\u003eFig. S4\u003c/strong\u003e) as highly-associated with acute ARF suggests that tissue damage and repair may be central to ARF pathogenesis, and likely contributes to the valve damage and fibro-inflammatory process that results in chronic RHD. HBEGF (Heparin-binding EGF growth factor) is a secreted growth factor produced by monocytes and macrophages during tissue damage that signals through EGF receptors during wound healing and angiogenesis. HBEGF has been found to play a critical role during cardiac valve tissue development in mice, by regulating mesenchymal proliferation required during normal cardiac valve formation\u003csup\u003e13\u003c/sup\u003e. High circulating HBEGF levels during ARF could dysregulate mesenchymal organisation during valvular repair. SCUBE1 (Signal peptide, CUB domain and EGF like domain containing 1) is highly expressed in the vascular endothelium and participates in VEGFA signalling and thrombogenesis\u003csup\u003e14\u003c/sup\u003e. SCUBE1 plasma levels have been associated with cardiac endothelial damage\u003csup\u003e15\u003c/sup\u003e. PACSIN2 (Protein kinase C and casein kinase substrate in neurons 2) has been shown to be important during development of the mouse heart; but as an endocytic protein, the source and function of higher plasma levels of PACSIN2 was not obvious\u003csup\u003e16\u003c/sup\u003e. The high differential abundance of HBEGF, SCUBE1 and PACSIN2 in ARF compared to RHD, and the similar kinetics of HBEGF and SCUBE1 during progression of ARF convalescence suggest they may represent useful targets to follow during ARF and RHD disease progression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe proteomic signature identified in this study\u0026nbsp;(ARF at the time of initial diagnosis)\u0026nbsp;differs from that seen in chronic, severe RHD. In the largest study to date\u003csup\u003e17\u003c/sup\u003e, including 215 African patients with severe RHD, a machine learning approach identified a six-protein signature that distinguished RHD cases from healthy controls. The proteins that emerged in that study as most discriminatory were those involved in an ongoing inflammatory response, including complement component C7, adipotnectin, quiescin oxidates 1, fibulin-1, and ficolin-3\u003csup\u003e17\u003c/sup\u003e. \u0026nbsp; It is unsurprising that this signature does not overlap with the ARF signature in our study, but does suggest that additional biomarkers may be able to identify those acute ARF cases who will develop RHD. In this context, we identified several plasma proteins that remained elevated 12 weeks after acute presentation (e.g. PACSIN2, MNDA, SERPIN E2) and IGHD that also remained elevated in RHD patients.\u0026nbsp;The identification of elevated IGHD in ARF and RHD is intriguing, as several studies have also shown elevated IgD in other autoimmune diseases\u003csup\u003e18\u003c/sup\u003e, and IgD signalling in B cells is preferentially activated by multivalent antigens, which might include the GAS M and collagen-like proteins that are proposed to play a central role in ARF pathogenesis\u003csup\u003e3,19\u003c/sup\u003e.\u0026nbsp;Future work should aim to recruit and analyze a wider spectrum of ARF and RHD patients, capturing those with differential outcomes over time and across the RHD severity spectrum to further understand these differences. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile our proteomic approach to biomarker discovery for ARF fulfilled most recommendations for biomarker identification, this study has several limitations. The patients all came from Uganda, and this narrow geographic focus as well as the relatively small sample size could be barriers to generalizability of this study. Future work will need to replicate these signatures in a diverse global cohort. The small sample size also did not allow investigation of specific signatures unique to each of the clinical manifestations of ARF (e.g. carditis vs chorea). Additionally, as the existing diagnostic criteria for ARF have imperfect sensitivity and specificity, until we find a sensitive and specific diagnostic biomarker a better gold standard does not exist.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUltimately, biomarkers may substitute for clinically relevant endpoints providing a faster, cheaper and more precise diagnostic and/or prognostic insight\u003csup\u003e12\u003c/sup\u003e. The aptamer-based proteomics platform we employed has provided clinically useful biomarkers demonstrating feasibility for translation into clinical application, as has been achieved in other areas of medicine\u003csup\u003e20-23\u003c/sup\u003e. Furthermore, proteomic approaches supporting point-of-care testing have also been successfully developed\u003csup\u003e24\u003c/sup\u003e along with platforms that allow translation into low resource settings\u003csup\u003e25\u003c/sup\u003e. Future work will require translation of candidate biomarker signature(s) into appropriate testing platforms, and prospectively evaluating diagnostic performance through clinical trials on children presenting to clinical sites with possible ARF.\u003c/p\u003e\n\u003cp\u003eIn conclusion, we report a proteomic pathogenesis and diagnostic biomarker signature in ARF. Novel pathways centering around inflammation, tissue damage and repair emerged that represent plausible mechanisms of ARF pathogenesis. Embedded in this pathogenesis signature was a highly discriminatory set of five proteins that could distinguish ARF from infectious and inflammatory diseases that clinically overlap. While further mechanistic and clinical validation is required to replicate these results, our results demonstrate feasibility of a clinically useful ARF diagnostic biomarker that could substantially improve ARF diagnosis globally.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eInclusion and Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is highly relevant to local communities in Uganda. The study protocol was approved by the Makerere University School of Medicine Research and Ethics committee (REC REF 2017-042), and the Uganda National Council for Science and Technology (HS 2215). \u0026nbsp;This study was conducted in partnership with local researchers at the The Uganda Heart Institute who were involved in the design, data collection, analysis, and reporting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design, Settings, and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a planned case-control sub-study under a larger prospective epidemiological study conducted in Uganda between 2018 and 2020. The detailed recruitment methods of the parent study have been previously published\u003csup\u003e26,27\u003c/sup\u003e. ARF clinics were established at Mbarara Regional Referral Hospital (Western Region) and at Mulago National Referral Hospital (Central Region). Community and provider sensitization was conducted through direct education and mass media approaches. \u0026nbsp;Children aged 3-17 years of age who presented with either history of fever in the past 48 hours and a joint complaint, suspicion of rheumatic carditis, or suspicion of chorea were invited to the clinic for additional evaluation. \u0026nbsp; Additionally, for this sub-study, three control groups were recruited under an amendment of the original ethics from various hospital and community settings for each case of ARF, including one each from the categories of children with RHD without ARF, children with overlapping clinical presentation who had confirmed alternate infectious or inflammatory conditions (i.e., sickle cell crisis, malaria, influenza), and healthy\u0026nbsp;controls with no signs or symptoms of acute infection or inflammatory condition. All parents signed a written informed consent prior to their child\u0026rsquo;s participation, and children eight years of age and older also signed a written informed assent.\u003c/p\u003e\n\u003cp\u003eParticipants selected for this study included 50 children diagnosed with definite ARF, 43 children diagnosed with possible ARF, 16 children classified as healthy, 38 children with alternate diagnoses with overlapping clinical phenotypes (9 children with known alternate diagnoses, 29 children with unknown alternate diagnosis), and 18 children with chronic RHD without ARF. \u0026nbsp;All ARF presentations were the first known diagnosis as we were unable to discriminate between initial and recurrent ARF episodes. The median age of the cohort was 9 years (IQR 6-12 years), 48% were female, and 64 (39%) were recruited at the Mbarara site (as compared to Mulago site).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntake Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe same intake protocol was utilized for ARF cases and controls. \u0026nbsp; Components of data collection have been described in detail elsewhere\u003csup\u003e26\u003c/sup\u003e, and include a history of the present illness, past medical history, family history, physical exam, point of care testing for Group A \u003cem\u003eStreptococcus\u003c/em\u003e (Thermofisher Scientific rapid antigen detection kit, Waltham MA, USA), HIV (Determine, Abbott, Chicago, IL, USA), and malaria (CareStart, Apacor, Berkshire, England), electrocardiogram, and focused echocardiogram. \u0026nbsp;A blood sample was also taken for clinical testing which included a complete blood count, erythrocyte sedimentation rate, C-reactive protein, malaria blood smear, antistreptolysin O titers, and antideoxyribonuclease B titers, and biobanking, which included 10 milliliters of peripheral blood.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFollow-up Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiagnosis of ARF was completed only after all testing and laboratory results returned. Participant diagnosed with definite and possible ARF were invited for additional follow-up visits at 1 week, 6 weeks, and 12 weeks (Mulago) and 1 week and 12 weeks (Mbarara). During these visits, interval clinical history, physical exam, and echocardiography were performed. Additional peripheral blood samples were collected using the same protocol, when possible, for biobanking of convalescent samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCase and Control Adjudication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe same adjudication protocol, including double blinded review of all clinical, imaging, and laboratory data, was utilized for cases and controls. The 2015 Jones\u0026rsquo; Criteria for moderate and high-risk populations and the clinical expertise of the reviewers were used to adjudicate each study participant\u0026rsquo;s data and categorize them as definite ARF, possible ARF, known alternate diagnosis, or unknown alternate diagnosis. \u0026nbsp;Within the known alternate diagnosis, were the categories of RHD without ARF, overlapping infectious and inflammatory conditions, and healthy without signs of acute infection or inflammatory condition (Table 1). When two reviews were concordant, no additional review was conducted. When the two reviews were discordant, the reviewers discussed the case and came to a consensus decision. As most laboratory testing was not available immediately at the time of recruitment, many suspected ARF cases and controls were reclassified from their enrolment category during adjudication (e.g., an apparently healthy control who had elevated streptococcal titres would be excluded from counting as a pure healthy control for this sub-study). Further, many children were classified as unknown alternate diagnosis when they had symptomatic overlap with ARF but did not meet the minimum diagnostic criteria for ARF, and did not have a confirmed alternate cause for their symptoms. Final classification of individuals included in this study and accompanying diagnostic criteria (Clinical Metadata) are provided in the Source Data file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiospecimen collection and samples storage for multi-omic analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral whole blood was collected from eligible study participants in PAXgene and Lithium Heparin vacutainers performed by trained phlebotomists in Uganda under local (Makerere University School of Medicine Research and Ethics Committee 2017\u0026ndash;042). Shortly after collection, whole blood samples in PAXgene tubes were stored at -80\u0026deg;C after 2 hours of incubation at room temperature to be used for RNA sequencing. Heparin blood was spun down to collect plasma for Proteomics and Metabolomics analysis. The plasma-depleted blood was used for Flow Cytometry analysis. The rest of the blood cells were then treated with red blood cell lysis buffer for 10 minutes, spun down and the white blood cells (WBC) were washed in phosphate buffer saline, and saved as a dry pellet at -80\u0026deg;C for future Epigenetics analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSamples were transferred to The Kids Research Institute Australia on dry ice with continuous temperature monitoring. On arrival, rigorous quality checks were employed. Samples with unclear sample identification, documentation on sample collection logs that was missing data or outside of the standard procedures (i.e., too long between sample collection and processing), visible damage or cracking to the tube, or with any other concerns, were excluded from the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePower Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe anticipated our final sample size to depend on the annual incidence of ARF. To inform our recruitment strategy, a target \u003cem\u003ea\u0026nbsp;\u003c/em\u003e\u003cem\u003epriori\u003c/em\u003e sample size calculation was performed using\u0026nbsp;PASS15 (Power Analysis and Sample Size Software 2017, Kaysville, Utah). We assumed\u003cem\u003e\u0026nbsp;\u003c/em\u003ea 30% variance in the biological markers within the population (based on previous studies), and determined that with a sample size of 100 cases and 100 controls we would have 82% power to detect a 16% difference at alpha 0.01. Practicalities of recruiting cases and obtaining sufficient sample volumes in rural Uganda, together with advances in the analysis platforms, resulted in this analysis being based on a convenience sample that were available for ARF cases and controls, as outlined in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis Plan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary goal of our biomarker discovery was to distinguish participants with definite ARF from participants with other clinically overlapping conditions; the situation where a diagnostic test would be most useful. Thus, the primary comparison for these studies was Definite ARF as compared to Alternate Diagnosis (both known and unknown). \u0026nbsp;Secondary analyses considered definite ARF longitudinally over the course of convalescence, and compared to other clinical classifications including possible ARF, RHD without ARF, and healthy controls.\u003c/p\u003e\n\u003cp\u003ePreliminary analysis identified study site as a significant source of variation in the proteomics data. Adjusting for this potential confounder was challenging, however, due to the uneven distribution of diagnostic classes between sites. To eliminate potential site-confounders, we leveraged samples from Mulago for initial discovery (Definite ARF vs. Alternate Diagnosis (known and unknown), using 20 times repeated 5-fold cross-validation, and testing increasingly smaller models (larger values of\u0026nbsp;the glmnet\u0026nbsp;penalization hyperparameter \u0026lambda;). We then assessed performance of the smallest model in samples from Mbarara (Definite ARF vs. Alternate Diagnosis) and studied the distribution of the model linear predictors of disease in the other diagnostic classes (Definite ARF vs. Possible ARF, RHD without ARF, and Healthy Controls) at Mulago. Participants with definite ARF were also profiled over time at both the Mulago (Enrolment, Week 1, Week 6, Week 12) and Mbarara (Enrolment, Week 12) sites, to assess if identified biomarkers were modifiable as the disease process moved from acute to convalescent. We deliberately chose not to adjust for factors such as age, sex, and ethnicity in our primary analysis, as correlations between these factors and disease status may represent genuine risk associations rather than confounding effects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSOMAscan\u0026trade; Proteomics Assay:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SomaScan\u0026trade; proteomic profiling platform utilizes SOMAmer reagents (single stranded, chemically-modified DNA-based aptamers) that bind to target proteins with high affinity and specificity. The assay includes 7596 individual SOMAmers reagents, of which there are 6596 unique human proteins measurable in 55ml of plasma collected from venous heparinized blood. The assays were performed by SomaLogic according to their standard protocol to quantitatively determine the proteins present.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eSomaScan Assay data were normalized using internal hybridization controls to mitigate bias caused by differential readout conditions in the individual microarrays due to eluate transfer, hybridization, wash, and scan. This was followed by median signal normalization across pooled calibrator replicates within each run to mitigate within-run technical variation in the calibrator signal prior to use in scaling calculations. The set of ratios of the calibrator reference value to the median of calibrator replicates for each SOMAmer reagent was used to calculate plate scale and calibration scale.; scale factor acceptance criteria per plate were predefined as between 0.4-2.5 and calibration scale factors between 0.6-1.4. In total, data were obtained for 7596 SOMAmer reagents We retained SOMAmers corresponding to human (p=7335) proteins (p=7288) that passed Somalogic quality control checks. The resulting 6664 SOMAmers reagents (corresponding to 5911 unique Uniprot protein identifiers) were used for analysis.\u003c/p\u003e\n\u003cp\u003eOpen-source microarray analysis software from the R/Bioconductor consortium was used to analyze the SomaScan\u0026trade; microarray data (http://www.bioconductor.org/). Proteins with different relative plasma concentrations between grouped by disease stages were identified using robust linear regression model and a moderated \u003cem\u003et\u003c/em\u003e statistic as implemented in the R package \u0026ldquo;limma\u0026rdquo;. To provide additional biological context, proteins identified in this way were subsequently used to carry out pathway over-representation analysis using a hypergeometric test and the MSigDB Hallmark collection of gene sets. The \u003cem\u003ep\u003c/em\u003e values were adjusted using the Benjamini-Hochberg procedure to control the false discovery rate (FDR). Proteins were considered significantly changed if they had an FDR-adjusted \u003cem\u003ep\u003c/em\u003e value \u0026lt;0.05 and a fold change greater than 20%.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe proteomic, metabolomic and flow cytometry datasets and de-identified clinical data have been deposited in the Mendeley Data database under accession code 5ppxd6sgdb (DOI: 10.17632/5ppxd6sgdb.1). Due to ethical and legal restrictions, raw sequence and epigenomic files are not publicly available. Requests for access to these datasets or any other data supporting the findings of this study should be directed to the corresponding author [JRC]. Source data are provided with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCODE AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCodes related to this article can be accessed via GitHub at https://github.com/T-Barnett/Okello-et-al-2025\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients, families, communities, and clinicians who participated in this study in Uganda to advance our global knowledge of ARF and RHD. \u0026nbsp;Further, we thank Dr. Tom Parks from Imperial College in London who contributed expertise to the parent epidemiological study that led to participant recruitment. This work was supported by American Heart Association Strategically Focused Research Network 17SFRN33670607, \u0026nbsp;The Cincinnati Children\u0026rsquo;s Heart Institute Research Core, and the The Kids Research Institute Australia. TCB is supported by a Translation fellowship from the Western Australian Future Health Research and Innovation Fund.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAB and JRC conceptualised the study. EO, JA, PL, EN, LMO, JP and CAS recruited participants, processed samples, or interpreted diagnostic testing. TCB, CPS, RRB, DIB, NK, AHYL, WL, SM, DJM, RBO, MS, SJT and TRK carried out the investigation. AB, TRK and JRC supervised the study. TCB, AB, TRK and JRC wrote the original draft. All authors edited the manuscript and approved the final submission.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRoth, G. 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Assoc\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, e016053, doi:10.1161/JAHA.120.016053 (2020).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003col 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criteria\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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-4345781/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4345781/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Acute Rheumatic Fever (ARF) is a systemic inflammatory condition triggered by Group A Streptococcus infection, with timely diagnosis critical to prevent Rheumatic Heart Disease. ARF pathogenesis is poorly understood and diagnosis is based on clinical criteria. Here, we compared ARF cases and well-defined controls from two Uganda cohorts. We identified a 5-protein signature that discriminates ARF patients from clinically-similar conditions (receiver operating characteristic-area under the curve (ROC-AUC)=1.0, n=18 definite ARF vs n=9 known alternate diagnosis; ROC-AUC=0.97, n=18 definite ARF vs n=13 unknown alternate diagnosis), which retained very good diagnostic value in a validation cohort (ROC-AUC=0.83 n=26 definite ARF vs n=13 unknown alternate diagnosis). Pathway analysis identified the epithelial-mesenchymal transition pathway as highly-associated with acute ARF, suggesting that tissue damage and repair is central to ARF pathogenesis. Our findings require further validation, yet highlight the potential for proteomics to identify clinically useful diagnostic biomarkers that would revolutionise ARF diagnosis and treatment.","manuscriptTitle":"A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 09:43:57","doi":"10.21203/rs.3.rs-4345781/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d77a6416-e1e0-408a-ae1a-a48094d224a5","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":47732479,"name":"Health sciences/Biomarkers/Diagnostic markers"},{"id":47732480,"name":"Biological sciences/Biochemistry/Proteomics"}],"tags":[],"updatedAt":"2025-05-05T09:43:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 09:43:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4345781","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4345781","identity":"rs-4345781","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}