Clinico-Serological Profiling and Diagnostic Re-classification of U1 snRNP-Positive Patients: A Cross-Sectional Study from Eastern India

Clinico-Serological Profiling and Diagnostic Re-classification of U1 snRNP-Positive Patients: A Cross-Sectional Study from Eastern India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinico-Serological Profiling and Diagnostic Re-classification of U1 snRNP-Positive Patients: A Cross-Sectional Study from Eastern India Shubham Khurana, Ravi kirti, Mala Mahto, Pratap Patra, Shamsad Ahmad, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9256254/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 21 You are reading this latest preprint version Abstract Objectives: To classify adult patients testing positive for U1 small nuclear ribonucleoprotein (snRNP) antibodies into mixed Connective tissue disease (MCTD), systemic lupus erythematosus (SLE), and other autoimmune diagnoses, and to compare these criteria-based diagnoses with the original diagnoses made by clinicians. Design: Record-based cross-sectional study. Setting: A tertiary care academic hospital in Eastern India. Participants: 170 consecutive patients aged >16 years who tested positive for U1 snRNP antibodies between 1 January 2023 and 31 December 2023. Results: The cohort had a mean age of 36.8 years (SD 15.2) and was predominantly female (80.6%). The most common revised diagnosis was SLE (n=61, 35.9%), followed by "others" (n=60, 35.3%) and MCTD (n=23, 13.5%). Raynaud’s phenomenon (91.3%) and puffy fingers (39.1%) were strong discriminatory markers for MCTD, while renal involvement (77.0%) and hypocomplementemia (55.7%) strongly favored SLE. Pulmonary arterial hypertension was exclusive to the MCTD group (52.2%) in this cohort. Diagnostic re-evaluation resulted in the reclassification of 36% of clinician-diagnosed MCTD cases as SLE. Conclusions: U1 snRNP positivity is not pathognomonic for MCTD and was more frequently associated with SLE in this cohort. The high prevalence of undifferentiated cases necessitates longitudinal surveillance. Reliance on serology alone risks misclassification Detailed clinical phenotyping is essential for accurate diagnosis. Key Message What is already known? Anti-U1-RNP antibodies are a mandatory serological criterion for Mixed Connective Tissue Disease (MCTD) but are also frequently detected in Systemic Lupus Erythematosus (SLE) and Systemic Sclerosis (SSc). What this study adds? This is one of the first studies in Eastern India to apply the 2019 Japanese Research Committee and EULAR/ACR criteria to a U1 snRNP-positive cohort. Application of these modern criteria revealed that 36% of patients clinically diagnosed with MCTD were reclassified as SLE. Renal involvement (77.0%) and Pulmonary Arterial Hypertension (52.2%) were identified as the most robust clinical discriminators between SLE and MCTD respectively. Significance: Highlights the high prevalence of undifferentiated cases (35.3%) and identifies renal involvement and PAH as the primary clinical discriminators for SLE and MCTD, respectively. Introduction The identification of antibodies against U1 small nuclear ribonucleoprotein (U1 snRNP) in 1972 defined mixed connective tissue disease (MCTD) as a distinct clinical entity combining features of systemic lupus erythematosus (SLE), systemic sclerosis (SSc), and polymyositis. [1] While these antibodies are a mandatory serological entry criterion for MCTD, subsequent research has demonstrated that they are not exclusive to the condition, occurring in 30–40% of SLE patients and nearly 14% of SSc patients. [2,3] This serological overlap creates significant diagnostic ambiguity. A positive U1 snRNP result identifies a U1 snRNP-associated autoimmune process but does not automatically confirm MCTD. Misclassification carries clinical risks, as the therapeutic requirements for SLE (e.g. renal protection) differ fundamentally from those of MCTD (e.g. pulmonary hypertension monitoring). Despite the routine use of U1 snRNP testing, epidemiological data on the clinico-etiological profile of these patients in India remain limited. To our knowledge, this is the first study from Eastern India to apply the 2019 Japanese criteria to a U1 snRNP-positive cohort. This study aimed to determine the prevalence of various autoimmune diagnoses among U1 snRNP-positive patients at a tertiary center in Eastern India. We specifically sought to classify patients using the updated 2019 Japanese Research Committee and 2019 EULAR/ACR criteria for SLE and to evaluate the concordance between these criteria-based diagnoses and real-world clinical impressions. Methods Study Design and Setting This was a record-based cross-sectional study conducted at the tertiary care academic hospital. The study protocol was approved by the Institutional Ethics Committee. Participants Participants were identified from the biochemistry laboratory records. All patients aged > 16 years who tested positive for U1 snRNP antibody between 1 January 2023 and 31 December 2023 were included. Data Collection Demographic, clinical, and laboratory data were extracted from the hospital information system (HIS) and physical case records. Collected parameters included complete blood count (CBC), liver and kidney function tests, C-reactive protein (CRP), and comprehensive antinuclear antibody (ANA) profiles. Where records were incomplete, supplementary data were collected via telephonic interviews after obtaining verbal consent. Diagnostic Classification To establish a "Revised Diagnosis," the following standardized criteria were applied to all participants: MCTD: 2019 Diagnostic criteria by the Japanese Research Committee. [4] SLE: 2019 EULAR/ACR Classification Criteria.[5] Systemic Sclerosis: 2013 ACR/EULAR Classification Criteria. [6] Rheumatoid Arthritis (RA): 2010 ACR/EULAR Classification Criteria.[7] Sample size calculation Sample size was calculated based on the following assumptions: Assuming that 35% of the SLE patients in the population have U1snRNP antibodies and no. of SLE patients visiting OPD in a year is 200, a sample size of 95 would be required for estimating the proportion of U1snRNP positive patients who have SLE with 7% absolute precision and 95% confidence. However, all patients (n = 170) fulfilling the inclusion criteria were included in the study. Statistical Analysis Data were analyzed using Jamovi software. Categorical variables were expressed as frequencies and percentages. The agreement between the clinician’s diagnosis and the revised diagnosis was assessed using Cohen’s kappa (kappa). Patient and Public Involvement Patients and the public were not involved in the design, conduct, or reporting of this research. Results Demographics and Serology A total of 170 patients were included. The mean age was 36.8 years (SD 15.2), with a female predominance (80.6%). While U1 snRNP positivity was the inclusion criterion, serological profiles showed significant overlap. SLE-specific antibodies (anti-dsDNA and anti-Smith) were detected in 35.3% of the total cohort but were present in 86.9% of those revised as SLE. Distribution of Diagnoses Distribution of the revised diagnoses after application of objective criteria is shown in Table 1 . SLE was the most common revised diagnosis (35.9%, n = 61), while MCTD was identified in only 13.5% (n = 23) of the patients. Table 1 Distribution of revised diagnoses Revised diagnosis Counts % of Total SLE 61 35.9% MCTD 23 13.5% Rheumatoid Arthritis 16 9.4% Systemic Sclerosis 10 5.9% Others 60 35.3% Total 170 100% Discriminatory Clinical Features Vascular and Fibrotic Features : Raynaud’s phenomenon was present in 91.3% of MCTD and 90.0% of SSc patients, compared to only 47.5% of SLE patients. Puffy fingers were observed in 39.1% of MCTD patients compared to 3.3% of SLE patients. Organ Involvement : Renal involvement was very common in SLE (77.0%), compared to MCTD (26.1%) and SSc (10.0%). Pulmonary Arterial Hypertension (PAH) was a common feature in the MCTD group (52.2%) but was absent in the SLE group. Immunological Markers : Low complement levels (C3/C4) were observed in 55.7% of SLE patients versus 13.0% of MCTD patients. Diagnostic Discordance Comparison of clinician vs. revised diagnoses showed substantial agreement (kappa = 0.78). However, notable discordance occurred: 9 patients (36%) diagnosed clinically as MCTD were reclassified as SLE upon criteria application. Conversely, 5 patients diagnosed clinically as SSc were reclassified as MCTD. Comparison of clinician and revised diagnoses has been shown in Table 2 below. Table 2 Comparison of Clinician and Revised Diagnoses Revised Diagnosis Clinician’s Diagnosis MCTD OTHERS Rheumatoid Arthritis SLE Systemic Sclerosis Total MCTD 12 4 0 9 0 25 OTHERS 4 56 0 2 0 62 Rheumatoid Arthritis 0 0 16 0 0 16 SLE 2 0 0 50 0 52 Systemic Sclerosis 5 0 0 0 10 15 Total 23 60 16 61 10 170 Agreement and Cohen’s Kappa ● Overall agreement: 84.1% of cases had matching clinician and revised diagnoses. ● Cohen’s kappa: 0.78, which indicates substantial agreement between clinician’s and revised diagnosis categories. Discussion The study reveals substantial heterogeneity in disease classification, challenging the notion that U1 snRNP positivity uniquely identifies mixed connective tissue disease (MCTD). Among 170 consecutive U1 snRNP-positive patients, systemic lupus erythematosus (SLE) emerged as the most common revised diagnosis (35.9%), followed closely by “others”/undifferentiated connective tissue disease (35.3%). MCTD comprised only 13.5% of the study cohort. These findings align with the growing body of literature questioning whether MCTD represents a distinct clinical entity or a subset of SLE and overlap syndromes [9]. The predominance of SLE in our U1 snRNP-positive population (35.9%) corroborates global epidemiological data where anti-U1-RNP antibodies are detected in 25–40% of SLE patients [8]. This significant overlap supports the hypothesis that while anti-U1-RNP is the serological hallmark of MCTD, its presence in isolation is rare. Our findings echo the multicenter analysis by Koutsogianni et al., which observed that nearly half of anti-RNP positive patients eventually meet SLE criteria [10]. The shift in diagnosis from MCTD to SLE upon applying strict 2019 EULAR/ACR criteria in our study highlights the higher sensitivity of modern criteria in capturing multisystem autoimmune presentations that might otherwise be labeled MCTD based on serology. A critical finding of this study is the high prevalence (35.3%) of the "others" category. This group probably represents undifferentiated connective tissue disease (UCTD), a condition characterized by serological autoimmunity and clinical symptoms that do not meet the criteria for a defined connective tissue disease (CTD). Longitudinal studies suggest that 30–40% of UCTD patients evolve into a defined CTD (most commonly SLE or SSc) within 5 years, while the remainder maintain a "stable UCTD" phenotype [11]. The absence of major organ involvement in this group (0% renal, 0% PAH) is consistent with the generally benign prognosis of stable UCTD described by Mosca et al. [12]. This necessitates a shift in management strategy for this subgroup. Rather than aggressive immunosuppression, these patients require "vigilant observation" to detect early transition to defined CTD. Additionally, the high proportion of "others" may also reflect referral patterns where patients with non-specific symptoms (arthralgia, fatigue) are tested for ANA early in the disease course, capturing them in the pre-differentiated phase. Renal involvement proved to be the most robust clinical discriminator in this cohort, present in 77.0% of SLE patients versus only 26.1% of MCTD patients. Pathophysiologically, this distinction is crucial. SLE-associated renal disease typically involves immune-complex mediated glomerulonephritis (proliferative LN), whereas renal involvement in MCTD, when it occurs, is more often membranous or associated with scleroderma-renal crisis vascular changes [13]. The high specificity of renal disease for SLE in this study implies that the presence of proteinuria or active urinary sediment in a U1 snRNP-positive patient should almost invariably trigger an evaluation for SLE and consideration of renal biopsy, as "pure" MCTD rarely presents with severe proliferative nephritis [14]. Pulmonary arterial hypertension (PAH) was observed in 52.2% of our MCTD patients but was notably absent in the SLE group. This stark contrast underscores the vascular-dominant pathology of MCTD compared to the inflammatory-dominant pathology of SLE. The strong association of PAH with MCTD supports the inclusion of PAH as a "characteristic organ involvement" in the 2019 Japanese criteria. Given that PAH remains the leading cause of mortality in MCTD [15], these findings justify mandatory baseline echocardiographic screening for all U1 snRNP-positive patients who do not have a clear SLE diagnosis. The study demonstrates that U1 snRNP antibodies rarely travel alone in SLE. The presence of anti-dsDNA (86.9% of SLE patients) and anti-Smith antibodies (significantly higher in SLE) serves as a critical "rule-out" for pure MCTD. This supports the concept of "linked autoantibody sets," where SLE is characterized by a broad autoimmune response (epitope spreading to Sm/dsDNA), whereas MCTD is characterized by a restricted response primarily against the U1-70k polypeptide [8]. The high prevalence of hypocomplementemia in our SLE group (55.7%) versus MCTD (13.0%) further distinguishes the immune-complex consumption pathology of SLE from the T-cell/endothelial pathology of MCTD. The demographic profile of this cohort (mean age 36.8 years, female predominance) mirrors global trends, but the specific antibody prevalence differs slightly from Western cohorts. A higher rate of SLE/SSc overlap features was seen compared to some European studies, which may reflect genetic differences in the Indian population, similar to the higher severity of SLE seen in Asian cohorts [16]. While providing robust cross-sectional data, this study is limited by the lack of longitudinal follow-up. Thus it could not be determined that what proportion of patients from the "others" category eventually progress to SLE or SSc. Furthermore, qualitative antibody profiles were used rather than quantitative assays for specific U1-RNP subunits (e.g., anti-70k vs. anti-A/C), which recent studies suggest may offer better diagnostic specificity [2]. Strengths and Limitations of this Study This is one of the first studies in India to classify U1 snRNP-positive patients using the 2019 Japanese Research Committee and 2019 EULAR/ACR criteria. The study utilized a large, consecutive sample (n=170) with complete enumeration, minimizing selection bias. The cross-sectional design limits the ability to track the diagnostic evolution of the 35.3% of patients classified as “others” or undifferentiated. As a single-center tertiary care study, findings may reflect a referral bias toward more severe autoimmune presentations. Conclusions U1 snRNP positivity is not synonymous with MCTD. In this Indian cohort, the antibody was most frequently associated with SLE and undifferentiated disease. Clinicians must integrate serology with specific clinical phenotypes—specifically renal and vascular features, to ensure accurate diagnosis and appropriate management. Declarations Data Availability Statement Data are available upon reasonable request. De-identified participant data will be made available to researchers upon request to the corresponding author. Conflict of Interest: Conflicts of Interest and Source of Funding: The authors of this work have nothing to disclose. Funding Statement: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Ethics Statements Patient consent for publication: Not applicable. Ethics approval : This study involves human participants and was approved by the Institutional Ethics Committee of AIIMS Patna. The study relied on retrospective data; verbal consent was obtained for supplementary telephonic interviews. Statement of Non-duplication: This manuscript is a unique submission and is not being considered for publication elsewhere. Funding Statement: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors: Shubham Khurana Department of General Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email: [email protected] Ravi kirti Department of General Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email: [email protected] Mala Mahto Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email: [email protected] Pratap Patra Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email : [email protected] Shamsad Ahmad Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email: [email protected] Swetalina Pradhan Department of Dermatology, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India. Email: [email protected] Corresponding Author: Shubham Khurana Department of General Medicine, AIIMS Patna Phulwari Sharif, Patna, Bihar, India 801507 Email: [email protected] Phone: 8398082373 Author Contributions Shubham Khurana was responsible for data collection, data curation, and formal statistical analysis and wrote the original draft of the manuscript. Ravikirti conceptualized and planned the study methodology and provided overall supervision and reviewed and edited the manuscript for intellectual content. Mala Mahto planned the study methodology and helped in collecting all biochemistry lab results data. Pratap Patra helped in collection of data and reviewed the manuscript. Shamsad Ahmad helped in formal statistical analysis. Swetalina Pradhan planned the study methodology and reviewed manuscript. All authors read and approved the final manuscript. Guarantor Statement Shubham khurana accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. References Sharp GC, Irvin WS, Tan EM, Gould RG, Holman HR. Mixed connective tissue disease—an apparently distinct rheumatic disease syndrome associated with a specific antibody to an extractable nuclear antigen (ENA). Am J Med . 1972;52(2):148–159. Kattah NH, Kattah MG, Utz PJ. The U1-snRNP complex: structural properties relating to autoimmune pathogenesis in rheumatic diseases. Immunol Rev . 2010;233(1):126–145. Ihn H, Yamane K, Yazawa N, et al. Distribution and antigen specificity of anti-U1RNP antibodies in patients with systemic sclerosis. Clin Exp Immunol . 1999;117(2):383. Tanaka Y, Kuwana M, Fujii T, et al. 2019 Diagnostic criteria for mixed connective tissue disease (MCTD): From the Japan research committee of the ministry of health, labor, and welfare for systemic autoimmune diseases. Mod Rheumatol . 2021;31(1):29–33. Aringer M, Costenbader KH, Daikh DI, et al. 2019 EULAR/ACR Classification Criteria for Systemic Lupus Erythematosus. Arthritis Rheumatol . 2019;71(9):1400–1412. van den Hoogen F, Khanna D, Fransen J, et al. 2013 classification criteria for systemic sclerosis: an American college of rheumatology/European league against rheumatism collaborative initiative. Ann Rheum Dis . 2013;72(11):1747–1755. Aletaha D, Neogi T, Silman AJ, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum . 2010;62(9):2569–2581. Dima A, Jurcut C, Baicus C. The impact of anti-U1-RNP positivity: systemic lupus erythematosus versus mixed connective tissue disease. Rheumatol Int . 2018;38(7):1169–1178. Reiseter S, Gunnarsson R, Corander J, et al. Clinical profiling of Mixed Connective Tissue Disease: A comparison with Systemic Lupus Erythematosus and Systemic Sclerosis. J Autoimmun . 2021;117:102588. Koutsogianni A, Moutsopoulos HM, Tzioufas AG. The clinical spectrum of anti-U1RNP(+) patients: Long term follow-up from a single center cohort. Ann Rheum Dis . 2024;83(Suppl 1):2056. Mosca M, Tani C, Vagnani S, Carli L, Bombardieri S. The diagnosis and classification of undifferentiated connective tissue diseases. J Autoimmun . 2014;48-49:50–52. Iudici M, Mosca M. Undifferentiated connective tissue disease: a condition at risk for systemic lupus erythematosus? Lupus . 2022;31(9):1021–1025. Fenaroli P, Bruscino A, Morreale M, et al. Renal involvement in Mixed Connective Tissue Disease: A review of the literature. Reumatismo . 2023;75(1):15–22. Hajas A, Szodoray P, Nakken B, et al. Clinical course, prognosis, and causes of death in mixed connective tissue disease. J Rheumatol . 2013;40(7):1134–1142. Reiseter S, Gunnarsson R, Mogens Aaløkken T, et al. Progression and mortality of interstitial lung disease in mixed connective tissue disease: a long-term observational nationwide cohort study. Rheumatology (Oxford) . 2018;57(2):255–262. Jakes RW, Bae SC, Louthrenoo W, et al. Systematic review of the epidemiology of systemic lupus erythematosus in the Asia-Pacific region: prevalence, incidence, clinical features, and mortality. Arthritis Care Res (Hoboken) . 2012;64(2):159–168. Additional Declarations No competing interests reported. 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Japanese Research Committee and EULAR/ACR criteria to a U1 snRNP-positive cohort. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eApplication of these modern criteria revealed that 36% of patients clinically diagnosed with MCTD were reclassified as SLE. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRenal involvement (77.0%) and Pulmonary Arterial Hypertension (52.2%) were identified as the most robust clinical discriminators between SLE and MCTD respectively. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSignificance: Highlights the high prevalence of undifferentiated cases (35.3%) and identifies renal involvement and PAH as the primary clinical discriminators for SLE and MCTD, respectively.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe identification of antibodies against U1 small nuclear ribonucleoprotein (U1 snRNP) in 1972 defined mixed connective tissue disease (MCTD) as a distinct clinical entity combining features of systemic lupus erythematosus (SLE), systemic sclerosis (SSc), and polymyositis. [1] While these antibodies are a mandatory serological entry criterion for MCTD, subsequent research has demonstrated that they are not exclusive to the condition, occurring in 30\u0026ndash;40% of SLE patients and nearly 14% of SSc patients. [2,3]\u003c/p\u003e \u003cp\u003eThis serological overlap creates significant diagnostic ambiguity. A positive U1 snRNP result identifies a U1 snRNP-associated autoimmune process but does not automatically confirm MCTD. Misclassification carries clinical risks, as the therapeutic requirements for SLE (e.g. renal protection) differ fundamentally from those of MCTD (e.g. pulmonary hypertension monitoring).\u003c/p\u003e \u003cp\u003eDespite the routine use of U1 snRNP testing, epidemiological data on the clinico-etiological profile of these patients in India remain limited. To our knowledge, this is the first study from Eastern India to apply the 2019 Japanese criteria to a U1 snRNP-positive cohort. This study aimed to determine the prevalence of various autoimmune diagnoses among U1 snRNP-positive patients at a tertiary center in Eastern India. We specifically sought to classify patients using the updated 2019 Japanese Research Committee and 2019 EULAR/ACR criteria for SLE and to evaluate the concordance between these criteria-based diagnoses and real-world clinical impressions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis was a record-based cross-sectional study conducted at the tertiary care academic hospital.\u003c/p\u003e \u003cp\u003e The study protocol was approved by the Institutional Ethics Committee.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eParticipants were identified from the biochemistry laboratory records. All patients aged\u0026thinsp;\u0026gt;\u0026thinsp;16 years who tested positive for U1 snRNP antibody between 1 January 2023 and 31 December 2023 were included.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eDemographic, clinical, and laboratory data were extracted from the hospital information system (HIS) and physical case records. Collected parameters included complete blood count (CBC), liver and kidney function tests, C-reactive protein (CRP), and comprehensive antinuclear antibody (ANA) profiles. Where records were incomplete, supplementary data were collected via telephonic interviews after obtaining verbal consent.\u003c/p\u003e\n\u003ch3\u003eDiagnostic Classification\u003c/h3\u003e\n\u003cp\u003eTo establish a \"Revised Diagnosis,\" the following standardized criteria were applied to all participants:\u003c/p\u003e \u003cp\u003eMCTD: 2019 Diagnostic criteria by the Japanese Research Committee. [4]\u003c/p\u003e \u003cp\u003eSLE: 2019 EULAR/ACR Classification Criteria.[5]\u003c/p\u003e \u003cp\u003eSystemic Sclerosis: 2013 ACR/EULAR Classification Criteria. [6]\u003c/p\u003e \u003cp\u003eRheumatoid Arthritis (RA): 2010 ACR/EULAR Classification Criteria.[7]\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eSample size was calculated based on the following assumptions:\u003c/p\u003e \u003cp\u003eAssuming that 35% of the SLE patients in the population have U1snRNP antibodies and no. of SLE patients visiting OPD in a year is 200, a sample size of 95 would be required for estimating the proportion of U1snRNP positive patients who have SLE with 7% absolute precision and 95% confidence. However, all patients (n\u0026thinsp;=\u0026thinsp;170) fulfilling the inclusion criteria were included in the study.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using Jamovi software. Categorical variables were expressed as frequencies and percentages. The agreement between the clinician\u0026rsquo;s diagnosis and the revised diagnosis was assessed using Cohen\u0026rsquo;s kappa (kappa).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePatient and Public Involvement\u003c/strong\u003e \u003cp\u003ePatients and the public were not involved in the design, conduct, or reporting of this research.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographics and Serology\u003c/h2\u003e \u003cp\u003eA total of 170 patients were included. The mean age was 36.8 years (SD 15.2), with a female predominance (80.6%). While U1 snRNP positivity was the inclusion criterion, serological profiles showed significant overlap. SLE-specific antibodies (anti-dsDNA and anti-Smith) were detected in 35.3% of the total cohort but were present in 86.9% of those revised as SLE.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of Diagnoses\u003c/h2\u003e \u003cp\u003eDistribution of the revised diagnoses after application of objective criteria is shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. SLE was the most common revised diagnosis (35.9%, n\u0026thinsp;=\u0026thinsp;61), while MCTD was identified in only 13.5% (n\u0026thinsp;=\u0026thinsp;23) of the patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of revised diagnoses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRevised diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCounts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of Total\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCTD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatoid Arthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystemic Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiscriminatory Clinical Features\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eVascular and Fibrotic Features\u003c/span\u003e: Raynaud\u0026rsquo;s phenomenon was present in 91.3% of MCTD and 90.0% of SSc patients, compared to only 47.5% of SLE patients. Puffy fingers were observed in 39.1% of MCTD patients compared to 3.3% of SLE patients.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOrgan Involvement\u003c/span\u003e: Renal involvement was very common in SLE (77.0%), compared to MCTD (26.1%) and SSc (10.0%). Pulmonary Arterial Hypertension (PAH) was a common feature in the MCTD group (52.2%) but was absent in the SLE group.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eImmunological Markers\u003c/span\u003e: Low complement levels (C3/C4) were observed in 55.7% of SLE patients versus 13.0% of MCTD patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic Discordance\u003c/h2\u003e \u003cp\u003eComparison of clinician vs. revised diagnoses showed substantial agreement (kappa\u0026thinsp;=\u0026thinsp;0.78). However, notable discordance occurred: 9 patients (36%) diagnosed clinically as MCTD were reclassified as SLE upon criteria application. Conversely, 5 patients diagnosed clinically as SSc were reclassified as MCTD. Comparison of clinician and revised diagnoses has been shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Clinician and Revised Diagnoses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eRevised Diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinician\u0026rsquo;s Diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCTD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOTHERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRheumatoid Arthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSystemic Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCTD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTHERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatoid Arthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystemic Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAgreement and Cohen\u0026rsquo;s Kappa\u003c/h2\u003e \u003cp\u003e ● Overall agreement: 84.1% of cases had matching clinician and revised diagnoses.\u003c/p\u003e \u003cp\u003e● Cohen\u0026rsquo;s kappa: 0.78, which indicates substantial agreement between clinician\u0026rsquo;s and revised diagnosis categories.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study reveals substantial heterogeneity in disease classification, challenging the notion that U1 snRNP positivity uniquely identifies mixed connective tissue disease (MCTD). Among 170 consecutive U1 snRNP-positive patients, systemic lupus erythematosus (SLE) emerged as the most common revised diagnosis (35.9%), followed closely by \u0026ldquo;others\u0026rdquo;/undifferentiated connective tissue disease (35.3%). MCTD comprised only 13.5% of the study cohort. These findings align with the growing body of literature questioning whether MCTD represents a distinct clinical entity or a subset of SLE and overlap syndromes [9].\u003c/p\u003e \u003cp\u003eThe predominance of SLE in our U1 snRNP-positive population (35.9%) corroborates global epidemiological data where anti-U1-RNP antibodies are detected in 25\u0026ndash;40% of SLE patients [8]. This significant overlap supports the hypothesis that while anti-U1-RNP is the serological hallmark of MCTD, its presence in isolation is rare. Our findings echo the multicenter analysis by Koutsogianni et al., which observed that nearly half of anti-RNP positive patients eventually meet SLE criteria [10]. The shift in diagnosis from MCTD to SLE upon applying strict 2019 EULAR/ACR criteria in our study highlights the higher sensitivity of modern criteria in capturing multisystem autoimmune presentations that might otherwise be labeled MCTD based on serology.\u003c/p\u003e \u003cp\u003eA critical finding of this study is the high prevalence (35.3%) of the \"others\" category. This group probably represents undifferentiated connective tissue disease (UCTD), a condition characterized by serological autoimmunity and clinical symptoms that do not meet the criteria for a defined connective tissue disease (CTD). Longitudinal studies suggest that 30\u0026ndash;40% of UCTD patients evolve into a defined CTD (most commonly SLE or SSc) within 5 years, while the remainder maintain a \"stable UCTD\" phenotype [11]. The absence of major organ involvement in this group (0% renal, 0% PAH) is consistent with the generally benign prognosis of stable UCTD described by Mosca et al. [12]. This necessitates a shift in management strategy for this subgroup. Rather than aggressive immunosuppression, these patients require \"vigilant observation\" to detect early transition to defined CTD. Additionally, the high proportion of \"others\" may also reflect referral patterns where patients with non-specific symptoms (arthralgia, fatigue) are tested for ANA early in the disease course, capturing them in the pre-differentiated phase.\u003c/p\u003e \u003cp\u003eRenal involvement proved to be the most robust clinical discriminator in this cohort, present in 77.0% of SLE patients versus only 26.1% of MCTD patients. Pathophysiologically, this distinction is crucial. SLE-associated renal disease typically involves immune-complex mediated glomerulonephritis (proliferative LN), whereas renal involvement in MCTD, when it occurs, is more often membranous or associated with scleroderma-renal crisis vascular changes [13]. The high specificity of renal disease for SLE in this study implies that the presence of proteinuria or active urinary sediment in a U1 snRNP-positive patient should almost invariably trigger an evaluation for SLE and consideration of renal biopsy, as \"pure\" MCTD rarely presents with severe proliferative nephritis [14].\u003c/p\u003e \u003cp\u003ePulmonary arterial hypertension (PAH) was observed in 52.2% of our MCTD patients but was notably absent in the SLE group. This stark contrast underscores the vascular-dominant pathology of MCTD compared to the inflammatory-dominant pathology of SLE. The strong association of PAH with MCTD supports the inclusion of PAH as a \"characteristic organ involvement\" in the 2019 Japanese criteria. Given that PAH remains the leading cause of mortality in MCTD [15], these findings justify mandatory baseline echocardiographic screening for all U1 snRNP-positive patients who do not have a clear SLE diagnosis.\u003c/p\u003e \u003cp\u003eThe study demonstrates that U1 snRNP antibodies rarely travel alone in SLE. The presence of anti-dsDNA (86.9% of SLE patients) and anti-Smith antibodies (significantly higher in SLE) serves as a critical \"rule-out\" for pure MCTD. This supports the concept of \"linked autoantibody sets,\" where SLE is characterized by a broad autoimmune response (epitope spreading to Sm/dsDNA), whereas MCTD is characterized by a restricted response primarily against the U1-70k polypeptide [8]. The high prevalence of hypocomplementemia in our SLE group (55.7%) versus MCTD (13.0%) further distinguishes the immune-complex consumption pathology of SLE from the T-cell/endothelial pathology of MCTD.\u003c/p\u003e \u003cp\u003eThe demographic profile of this cohort (mean age 36.8 years, female predominance) mirrors global trends, but the specific antibody prevalence differs slightly from Western cohorts. A higher rate of SLE/SSc overlap features was seen compared to some European studies, which may reflect genetic differences in the Indian population, similar to the higher severity of SLE seen in Asian cohorts [16].\u003c/p\u003e \u003cp\u003eWhile providing robust cross-sectional data, this study is limited by the lack of longitudinal follow-up. Thus it could not be determined that what proportion of patients from the \"others\" category eventually progress to SLE or SSc. Furthermore, qualitative antibody profiles were used rather than quantitative assays for specific U1-RNP subunits (e.g., anti-70k vs. anti-A/C), which recent studies suggest may offer better diagnostic specificity [2].\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eStrengths and Limitations of this Study\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThis is one of the first studies in India to classify U1 snRNP-positive patients using the 2019 Japanese Research Committee and 2019 EULAR/ACR criteria.\u003c/li\u003e\n \u003cli\u003eThe study utilized a large, consecutive sample (n=170) with complete enumeration, minimizing selection bias.\u003c/li\u003e\n \u003cli\u003eThe cross-sectional design limits the ability to track the diagnostic evolution of the 35.3% of patients classified as \u0026ldquo;others\u0026rdquo; or undifferentiated.\u003c/li\u003e\n \u003cli\u003eAs a single-center tertiary care study, findings may reflect a referral bias toward more severe autoimmune presentations.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Conclusions","content":"\u003cp\u003eU1 snRNP positivity is not synonymous with MCTD. In this Indian cohort, the antibody was most frequently associated with SLE and undifferentiated disease. Clinicians must integrate serology with specific clinical phenotypes\u0026mdash;specifically renal and vascular features, to ensure accurate diagnosis and appropriate management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available upon reasonable request. De-identified participant data will be made available to researchers upon request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConflicts of Interest and Source of Funding: The authors of this work have nothing to disclose.\u003c/p\u003e\n\u003cp\u003eFunding Statement: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: This study involves human participants and was approved by the Institutional\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics Committee of AIIMS Patna. The study relied on retrospective data; verbal consent was obtained for supplementary telephonic interviews.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Non-duplication:\u003c/strong\u003e This manuscript is a unique submission and is not being considered for publication elsewhere.\u003c/p\u003e\u003ch2\u003eFunding Statement:\u003c/h2\u003e \u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthors:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShubham Khurana\u003c/p\u003e\n\u003cp\u003eDepartment of\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eGeneral Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eRavi kirti\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of General Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eMala Mahto\u003c/p\u003e\n\u003cp\u003eDepartment of Biochemistry, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePratap Patra\u003c/p\u003e\n\u003cp\u003eDepartment of Pediatrics, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail :[email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eShamsad Ahmad\u003c/p\u003e\n\u003cp\u003eDepartment of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail:[email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSwetalina Pradhan\u003c/p\u003e\n\u003cp\u003eDepartment of Dermatology, All India Institute of Medical Sciences (AIIMS), Patna, Bihar, India.\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Author:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShubham Khurana\u003c/p\u003e\n\u003cp\u003eDepartment of General Medicine, AIIMS Patna\u003c/p\u003e\n\u003cp\u003ePhulwari Sharif, Patna, Bihar, India 801507\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003ePhone: 8398082373\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShubham Khurana was responsible for data collection, data curation, and formal statistical analysis and \u0026nbsp;wrote the original draft of the manuscript.\u003c/p\u003e\n\u003cp\u003eRavikirti conceptualized and planned the study methodology and provided overall supervision and reviewed and edited the manuscript for intellectual content. Mala Mahto planned the study methodology and helped in collecting all biochemistry lab results data.\u003c/p\u003e\n\u003cp\u003ePratap Patra helped in collection of data and reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003eShamsad Ahmad helped in formal statistical analysis.\u003c/p\u003e\n\u003cp\u003eSwetalina Pradhan planned the study methodology and reviewed manuscript.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuarantor Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShubham khurana accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSharp GC, Irvin WS, Tan EM, Gould RG, Holman HR. Mixed connective tissue disease\u0026mdash;an apparently distinct rheumatic disease syndrome associated with a specific antibody to an extractable nuclear antigen (ENA). \u003cem\u003eAm J Med\u003c/em\u003e. 1972;52(2):148\u0026ndash;159.\u003c/li\u003e\n\u003cli\u003eKattah NH, Kattah MG, Utz PJ. The U1-snRNP complex: structural properties relating to autoimmune pathogenesis in rheumatic diseases. \u003cem\u003eImmunol Rev\u003c/em\u003e. 2010;233(1):126\u0026ndash;145.\u003c/li\u003e\n\u003cli\u003eIhn H, Yamane K, Yazawa N, et al. Distribution and antigen specificity of anti-U1RNP antibodies in patients with systemic sclerosis. \u003cem\u003eClin Exp Immunol\u003c/em\u003e. 1999;117(2):383.\u003c/li\u003e\n\u003cli\u003eTanaka Y, Kuwana M, Fujii T, et al. 2019 Diagnostic criteria for mixed connective tissue disease (MCTD): From the Japan research committee of the ministry of health, labor, and welfare for systemic autoimmune diseases. \u003cem\u003eMod Rheumatol\u003c/em\u003e. 2021;31(1):29\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eAringer M, Costenbader KH, Daikh DI, et al. 2019 EULAR/ACR Classification Criteria for Systemic Lupus Erythematosus. \u003cem\u003eArthritis Rheumatol\u003c/em\u003e. 2019;71(9):1400\u0026ndash;1412.\u003c/li\u003e\n\u003cli\u003evan den Hoogen F, Khanna D, Fransen J, et al. 2013 classification criteria for systemic sclerosis: an American college of rheumatology/European league against rheumatism collaborative initiative. \u003cem\u003eAnn Rheum Dis\u003c/em\u003e. 2013;72(11):1747\u0026ndash;1755.\u003c/li\u003e\n\u003cli\u003eAletaha D, Neogi T, Silman AJ, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. \u003cem\u003eArthritis Rheum\u003c/em\u003e. 2010;62(9):2569\u0026ndash;2581.\u003c/li\u003e\n\u003cli\u003eDima A, Jurcut C, Baicus C. The impact of anti-U1-RNP positivity: systemic lupus erythematosus versus mixed connective tissue disease. \u003cem\u003eRheumatol Int\u003c/em\u003e. 2018;38(7):1169\u0026ndash;1178.\u003c/li\u003e\n\u003cli\u003eReiseter S, Gunnarsson R, Corander J, et al. Clinical profiling of Mixed Connective Tissue Disease: A comparison with Systemic Lupus Erythematosus and Systemic Sclerosis. \u003cem\u003eJ Autoimmun\u003c/em\u003e. 2021;117:102588.\u003c/li\u003e\n\u003cli\u003eKoutsogianni A, Moutsopoulos HM, Tzioufas AG. The clinical spectrum of anti-U1RNP(+) patients: Long term follow-up from a single center cohort. \u003cem\u003eAnn Rheum Dis\u003c/em\u003e. 2024;83(Suppl 1):2056.\u003c/li\u003e\n\u003cli\u003eMosca M, Tani C, Vagnani S, Carli L, Bombardieri S. The diagnosis and classification of undifferentiated connective tissue diseases. \u003cem\u003eJ Autoimmun\u003c/em\u003e. 2014;48-49:50\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eIudici M, Mosca M. Undifferentiated connective tissue disease: a condition at risk for systemic lupus erythematosus? \u003cem\u003eLupus\u003c/em\u003e. 2022;31(9):1021\u0026ndash;1025.\u003c/li\u003e\n\u003cli\u003eFenaroli P, Bruscino A, Morreale M, et al. Renal involvement in Mixed Connective Tissue Disease: A review of the literature. \u003cem\u003eReumatismo\u003c/em\u003e. 2023;75(1):15\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eHajas A, Szodoray P, Nakken B, et al. Clinical course, prognosis, and causes of death in mixed connective tissue disease. \u003cem\u003eJ Rheumatol\u003c/em\u003e. 2013;40(7):1134\u0026ndash;1142.\u003c/li\u003e\n\u003cli\u003eReiseter S, Gunnarsson R, Mogens Aal\u0026oslash;kken T, et al. Progression and mortality of interstitial lung disease in mixed connective tissue disease: a long-term observational nationwide cohort study. \u003cem\u003eRheumatology (Oxford)\u003c/em\u003e. 2018;57(2):255\u0026ndash;262.\u003c/li\u003e\n\u003cli\u003eJakes RW, Bae SC, Louthrenoo W, et al. Systematic review of the epidemiology of systemic lupus erythematosus in the Asia-Pacific region: prevalence, incidence, clinical features, and mortality. \u003cem\u003eArthritis Care Res (Hoboken)\u003c/em\u003e. 2012;64(2):159\u0026ndash;168.\u003c/li\u003e\n\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":"bmc-rheumatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brhm","sideBox":"Learn more about [BMC Rheumatology](http://bmcrheumatol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/brhm/default.aspx","title":"BMC Rheumatology","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9256254/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9256254/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjectives: To classify adult patients testing positive for U1 small nuclear ribonucleoprotein (snRNP) antibodies into mixed Connective tissue disease (MCTD), systemic lupus erythematosus (SLE), and other autoimmune diagnoses, and to compare these criteria-based diagnoses with the original diagnoses made by clinicians.\u003c/p\u003e\n\u003cp\u003eDesign: Record-based cross-sectional study.\u003c/p\u003e\n\u003cp\u003eSetting: A tertiary care academic hospital in Eastern India.\u003c/p\u003e\n\u003cp\u003eParticipants: 170 consecutive patients aged \u0026gt;16 years who tested positive for U1 snRNP antibodies between 1 January 2023 and 31 December 2023.\u003c/p\u003e\n\u003cp\u003eResults: The cohort had a mean age of 36.8 years (SD 15.2) and was predominantly female (80.6%). The most common revised diagnosis was SLE (n=61, 35.9%), followed by \"others\" (n=60, 35.3%) and MCTD (n=23, 13.5%). Raynaud’s phenomenon (91.3%) and puffy fingers (39.1%) were strong discriminatory markers for MCTD, while renal involvement (77.0%) and hypocomplementemia (55.7%) strongly favored SLE. Pulmonary arterial hypertension was exclusive to the MCTD group (52.2%) in this cohort. Diagnostic re-evaluation resulted in the reclassification of 36% of clinician-diagnosed MCTD cases as SLE.\u003c/p\u003e\n\u003cp\u003eConclusions: U1 snRNP positivity is not pathognomonic for MCTD and was more frequently associated with SLE in this cohort. The high prevalence of undifferentiated cases necessitates longitudinal surveillance. Reliance on serology alone risks misclassification Detailed clinical phenotyping is essential for accurate diagnosis.\u003c/p\u003e","manuscriptTitle":"Clinico-Serological Profiling and Diagnostic Re-classification of U1 snRNP-Positive Patients: A Cross-Sectional Study from Eastern India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 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