Difference and connection of clinical features and antinuclear antibody patterns in new-onset Systemic Lupus Erythematosus cross age groups

Difference and connection of clinical features and antinuclear antibody patterns in new-onset Systemic Lupus Erythematosus cross age groups | 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 Difference and connection of clinical features and antinuclear antibody patterns in new-onset Systemic Lupus Erythematosus cross age groups Muxue Gong, Ning Li, Chao Sun, Dengxiao Hong, Xin Wang, Ming Ye, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4903780/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To investigate the differences in clinical features, and the relationship between antinuclear antibody (ANA) patterns, autoantibodies, and symptoms among different age groups in new-onset Systemic Lupus Erythematosus (SLE), we conducted a retrospective cohort study involving 556 patients diagnosed with SLE. These patients were classified into three groups: Group 1: juvenile-onset SLE (< 18 years); Group 2: early-onset adult SLE (18-50 years); and Group 3: late-onset SLE (≥ 50 years). We utilized a clustering heatmap to identify variations and associations of autoantibodies among the groups. The Kruskal-Wallis test was performed to compare clinical feature across the groups. The correlation heatmap were used to analyze the relationship of ANA patterns with symptoms. We found late-onset SLE patients exhibited more severe kidney damage and a higher likelihood of infection. ;Late-onset patients with a speckled ANA pattern were more prone to developing Raynaud's phenomenon. It is important for early-onset adult SLE patients with a homogeneous ANA pattern to be vigilant about the possibility of renal disorders and skin involvement. It is the first Chinese JSLE, early-onset ASLE and late-onset SLE study for ANA patterns, which enrolled a large number of newly diagnosed patients. These novel findings contribute to the diagnosis and prevention of SLE. Health sciences/Diseases/Rheumatic diseases/Systemic lupus erythematosus Biological sciences/Immunology New-onset SLE Juvenile-onset SLE Late-onset SLE ANA patterns Figures Figure 1 Figure 2 Figure 3 Highlights 1. Patients with late-onset SLE were related to ILD, more severe kidney damage and infection. 2. Early-onset adult patients with homogeneous pattern need to be aware of renal disorder. 3. Late-onset patients with speckled pattern are more likely to develop Reynold's phenomenon. 4. Homogeneous pattern linked to anti-dsDNA antibody in late-onset SLE can assist in diagnosis. Introduction Systemic lupus erythematosus (SLE) is an autoimmune disease, the infectious, drug, and other factors can stimulate the production of multiple autoantibodies that can cause inflammation and other damages in multiple organs 1 , 2 . However, the mechanism of SLE is undefined. Juvenile-onset SLE (JSLE) is a rare disease, which accounts for 10%- 20% of all SLE cases 3 , 4 . Some studies reported that patients with JSLE had more severe condition compared to that with adult-onset SLE (ASLE) 5 , 6 . Late-onset SLE which less clinical manifestations occurred accounts for 2–20% of all SLE cases 7 . It often have delayed diagnosis because of its concealment 8 . Previous studies showed that the mortality may be higher in patients with JSLE and late-onset SLE 4 , 7 , 9 , 10 . Therefore, comparing autoantibodies, clinical and serological features among newly diagnosed patients of different age groups can provide insights into the correlation between age of onset and organ involvement, this information can guide drug therapy, prevent complications, and delay the progression of SLE at an early stage. Testing autoantibody by the indirect immunofluorescence assay (IIFA) on HEp-2 cells is the common diagnostic method of SLE 11 . Some antinuclear antibody (ANA) staining patterns are associated with specific autoantibodies. For instance, the homogenous staining pattern may be linked with anti-histone antibody 12 . Using ANA patterns and autoantibody can aid diagnosis of suspected SLE 12 , and detecting the correlation between ANA patterns and symptoms in initial patients can predict severe complications for timely intervention in early phase of the disease. However, there are less studies on the correlation of ANA patterns with symptoms in different age groups. This study aims to compare autoantibodies, disease progression, laboratory data, and clinical features among various age groups, including JSLE, early-onset ASLE and late-onset SLE. Additionally, it explored the relationship of ANA patterns with autoantibodies and symptoms through a retrospective cohort study. Results Comparison of autoantibodies in three groups The distribution of autoantibodies in three groups is shown in Fig. 1 . The positive frequency of anti-chromatin antibody was highest in three groups. The presence of anti-dsDNA (56.0% vs 70.5%, P = 0.016) and anti-Sm (46.8% vs 60.6%, P = 0.036) antibodies in Group 3 were significantly lower than that in Group 2. The positive rate of anti-R52 antibody in Group 1 was 25.7% compared to 54.6% in Group 2 ( P = 0.004), according to the heatmap and statistical analysis (Supplemental Table S1 ). As shown in Fig. 1 , the autoantibodies were divided into 4 clusters: cluster 1 consisted of anti-Sm and anti-SmRNP antibodies; cluster 2 was composed of anti-dsDNA and anti-chromatin antibodies; cluster 3 was formed by anti-R60, anti-R52 and anti-SSB antibodies; anti-P antibody was a separate cluster. The difference on initial clinical features and course of disease between three groups The comparison of initial symptoms among three groups are summarized in Table 1. Arthritis was common first sign of all patients with SLE in this study. Patients in Group 1 (54.3% vs 17.4%, P <0.001) and Group 2 (36.5% vs 17.4%, P = 0.001) were more likely to present with malar rash as first symptom than that in Group 3. The proportion of patients with initial symptoms of alopecia (18.4% vs 4.6%, P = 0.001) in Group 2 were more than that in Group 1. Interstitial lung disease (ILD) was more frequent at the time of diagnosis in Group 3 than that in Group 2 (16.5% vs 4.8%, P <0.001). The patients in Group 3 had longer course of the disease than that in Group 1 (16.70 ± 35.67 vs 4.22 ± 10.32, P = 0.031) and 2 (16.70 ± 35.67 vs 10.44 ± 31.05, P = 0.012). Comparison of disease activity and laboratory data among three groups Figure 2 showed the difference on disease activity and serological results between three groups. The levels of serum creatinine (SCr) and blood urea nitrogen (BUN) in Group 3 were significantly higher compared to Group 1 ( P <0.001; P = 0.002, respectively) and Group 2 ( P = 0.006; P = 0.039, respectively), while Group 2 had higher SCr levels than that in Group 1 ( P = 0.018). The albumin (Alb) concentrations of Group 2 ( P = 0.001) and 3 ( P <0.001) were lower than Group 1, and Group 1 had a lower levels of globulin (Glb) compared to Group 2 ( P = 0.030) and 3 ( P = 0.014). The SLEDAI score of Group 2 was significantly higher than Group 3 ( P = 0.004). Group 1 had a lower level of C-reactive protein (CRP) than that in Group 2 ( P = 0.007) and 3 ( P = 0.002). Higher levels of Immunoglobulin A (IgA) and lower levels of Immunoglobulin M (IgM) were observed in Group 3 than that in Group 1 ( P <0.001; P = 0.014, respectively) and Group 2 ( P <0.001; P = 0.019, respectively), while the levels of IgA of Group 2 was higher than Group 1 ( P <0.001). The relationship between ANA patterns and autoantibodies Table 2 shows the correlation between ANA patterns and autoantibodies in different groups. The patients with anti-Sm antibody were more likely to have speckled staining pattern in Group 1 (70.6% vs 26.7%, P = 0.032) and Group 2 (53.3% vs 40.8%, P = 0.020), but had fewer homogeneous pattern in Group 1(23.5% vs 66.7%, P = 0.031). The percentage of homogeneous pattern in patients with anti-SmRNP antibody was lower than that without it in Group 1 (25.0% vs 75.0%, P = 0.010) and Group 2 (34.2% vs 44.8%, P = 0.043), while the proportion of speckled pattern in patients with anti-SmRNP antibody was higher in Group 2 (55.3% vs 36.3%, P <0.001). The patients with anti-dsDNA in Group 2 (48.5% vs 12.8%, P <0.001) and Group 3 (57.1% vs 4.8%, P <0.001) were more likely to have homogeneous pattern, but had fewer speckled pattern (39.7% vs 69.7%, P <0.001; 28.6% vs 66.7%, P <0.001, respectively). The prevalence of homogeneous pattern in patients with anti-P (42.6% vs 31.6%, P = 0.032), anti-SSB (46.2% vs 34.3%, P = 0.028) and anti-chromatin antibodies (44.9% vs 20.2%, P <0.001) was higher in Group 2. Speckled pattern was less frequent in Group 2 of patients with anti-R60 (44.8% vs 56.3%, P = 0.039) and anti-chromatin (45.3% vs 56.7%, P = 0.048) antibodies. The proportion of speckled pattern in Group 3 of patients with anti-R52 antibody was 56.8% compared to 36.2% in patients without it ( P = 0.048). Table 2 The relationship between autoantibodies and ANA pattern among three groups. Group Autoantibody ANA pattern Patients with the autoantibody (%) Patients without the autoantibody (%) P < 18 years Sm Speckled 12/17 (70.6%) 4/15 (26.7%) 0.032 Homogeneous 4/17 (23.5%) 4/15 (66.7%) 0.031 SmRNP Homogeneous 5/20 (25.0%) 9/12 (75.0%) 0.010 18–50 years dsDNA Speckled 104/262 (39.7%) 76/109 (69.7%) <0.001 Homogeneous 127/262 (48.5%) 14/109 (12.8%) <0.001 Sm Speckled 122/229 (53.3%) 58/142 (40.8%) 0.020 P Homogeneous 92/216 (42.6%) 49/155 (31.6%) 0.032 R60 Speckled 113/252 (44.8%) 67/119 (56.3%) 0.039 SSB Homogeneous 54/117 (46.2%) 87/254 (34.3%) 0.028 chromatin Speckled 121/267 (45.3%) 59/104 (56.7%) 0.048 Homogeneous 120/267 (44.9%) 21/104 (20.2%) <0.001 SmRNP Speckled 131/237 (55.3%) 49/134 (36.3%) <0.001 Homogeneous 81/237 (34.2%) 60/134 (44.8%) 0.043 ≥ 50 years dsDNA Speckled 14/49 (28.6%) 28/42 (66.7%) <0.001 Homogeneous 28/49 (57.1%) 2/42 (4.8%) <0.001 R52 Speckled 25/44 (56.8%) 17/47 (36.2%) 0.048 P: anti-ribosomal P protein. The correlation of ANA patterns with initial clinical features between three groups As shown in Fig. 3 , there was no correlation between ANA pattern and initial symptoms in Group 1. The speckled pattern was negatively correlated with malar rash and renal disorders, while malar rash and renal disorders were associated with the presence of a homogeneous pattern in Group 2. There was a positive correlation between the speckled pattern and Raynaud's phenomenon in Group 3. Discussion An overall understanding on the significance of ANA patterns can assist in diagnosis and predict organs involvement. There are less studies on association of ANA patterns with autoantibodies and symptoms among patients of different age groups, especially in the newly diagnosed patients, which can hardly influenced by treatment, and the results can better reflect the difference and association. In addition, the relationship between age of onset and symptoms is controversial. In this study, we detect the relationship of age of onset and ANA patterns with autoantibodies and clinical features in initial patients to do early diagnosis and targeted treatment timely to postpone the development of SLE and avoid the organ injury as soon as possible. Anti-dsDNA and anti-Sm antibodies are included in ACR criteria for SLE because of their high specificity. In this study, we found lower presence of them in patients with late-onset SLE compared to those with early-onset ASLE, which conformed to previous studies by Riveros Frutos A et al 7 and Boddaert J et al 13 . It may explain delayed diagnosis of late-onset patients. But the results of some early researches were inconsistent or contradictory to our findings 14 , 9 . Meanwhile, anti-R52 antibody was more prevalent in patients with early-onset ASLE than those with JSLE, which was also observed in other study 4 . The relationship of autoantibodies with age is controversial, which could be explained by different grouping methods, course of disease and ethnicity. The correlation among autoantibodies was detected by cluster analysis, and the autoantibodies were classified into 4 clusters, which were essentially comparable with earlier findings 15 . Incidence of malar rash in patients with early-onset SLE compared to late-onset SLE, consistent with previous studies 7 , 9 , 10 . Malar rash, as an initial presentation, was rarer with increasing age according to our results, and it was regarded as an important reason for missed-diagnosis of late-onset SLE 10 . Patients with early-onset ASLE were more likely to present alopecia than patients with late-onset SLE, as earlier researches reported 8 , 14 . It may be attribute to the rarity of skin rash in patients with late-onset SLE 16 . In addition, patients with late-onset SLE were more likely to develop ILD. It was consistent with previous studies that have reported more pulmonary manifestation in patients with late-onset SLE 8 . ILD was usually seen in patients with a long history of SLE 17 . Late-onset SLE is often delayed diagnosis 8 , which was also found in this study. Therefore, it may be the possible explanation of higher incidence of ILD in patients with late-onset SLE. In our study, we found that patients with early-onset ASLE had inferior renal function, and patients with late-onset SLE had the worst renal function at the time of initial diagnosis, which may be attributed to the effects of SLE or degenerative changes. It could explain the higher levels of Alb observed in patients with JSLE in our study. However, a study by Abdel-Nabi HH et al. did not show significant differences in SCr and BUN levels between patients with JSLE and ASLE 18 . This discrepancy could be due to variations in ethnicity and study design. Although reports suggest a lower incidence of severe symptoms in patients with late-onset SLE 8 , it's important to remain cautious about the potential for more serious kidney damage. Our findings also revealed that disease activity was lower in patients with late-onset SLE compared to those with early-onset ASLE, which is consistent with previous research 7 . According to our results, C-Reactive Protein (CRP) levels were lower in patients with JSLE than in other age groups. Previous study showed that the level of CRP did not remarkably increased related to SLE 2 . Therefore, it need to consider the possibility of infection. Further follow-up is needed to explore the relationship between late-onset SLE and infection which is the principal reason of hospitalization and death 19 . Regarding antibodies, patients with JSLE exhibited increased levels of IgM, while patients with late-onset SLE showed an increase in IgA. We did not observe any differences in blood cell counts, Erythrocyte Sedimentation Rate (ESR), complement levels, and liver enzymes among the three age groups. ANA staining patterns are correlated to the nuclear antigens targeted. Previous study reported that homogeneous pattern was associated with anti-dsDNA antibody, and speckled pattern was related to anti-Sm/RNP antibody 12 , 20 , which were conformed in patients with ASLE and early-onset SLE respectively according to our results. Anti-R52 antibody was associated to higher prevalence of speckled pattern, which was consistent with early studies 12 , 20 , but the result of anti-R60 antibody in patients with early-onset ASLE was opposite. In an investigation from Sweden, anti-SSA antibody was related to homogeneous/speckled pattern (a mixed type) in patients with SLE 21 . It may explained the difference. Homogeneous pattern was associated to anti-P, anti-chromatin and anti- SSB antibody in patients with early-onset ASLE in this study, which were essentially comparable with previous investigation 21 , 22 , 23 . Moreover, we had some noteworthy findings: the prevalence of homogeneous pattern was positive correlated with malar rash and renal involvement in patients with early-onset ASLE (speckled pattern was opposite). Anti-dsDNA antibody which was common among early-onset ASLE in this study was associated to homogeneous pattern and less often associated to speckled pattern. Kidney and skin involvement were intimately linked to anti-dsDNA antibody 24 . These may be the possible explanation. Speckled pattern was positive correlated with Raynaud's phenomenon in patients with late-onset SLE, which may be explained by the relationship between anti-Sm/RNP antibody and Raynaud's phenomenon 25 , 26 . These new findings need more confirmation by others, and we will collect more data and follow up. It is the first Chinese JSLE, early-onset ASLE and late-onset SLE retrospective cohort study for ANA patterns, which enrolled a large number of newly diagnosed patients without treatment. All the data we collected were at early stage of the disease, so our research can assist in diagnosis and predict organ involvement in patients of different ages by detecting the relationship of ANA patterns with autoantibodies, initial symptoms and complications which had less studies on, to control disease progression at very early stages. Nevertheless, sample with JSLE were few, so we did not find the association of ANA patterns with symptoms. In addition, we only detect homogeneous and speckled patterns in this study because of less presence of other staining patterns in patients. We will collect more cases to perfect our research in the future. In conclusion, we suggested that patients with late-onset SLE need to consider serious renal damage, ILD and infection. The physicians need to pay attention to ANA pattern for the correlation of homogeneous pattern with anti-dsDNA antibody in elderly patients, because of delayed diagnosis of them. Late-onset patients with speckled pattern are more likely to develop Raynaud's phenomenon, if patients have chest distress and oppressed, pulmonary arterial hypertension (PAH) should be noted 27 . Patients with early-onset ASLE are likely to have high disease activity, and they with homogeneous pattern need to be aware of renal disorder. Methods Subjects The essential information, the course of disease and the clinical data were collected from 556 hospitalized patients with new-onset SLE between 2012 and 2022 at the First Affiliated Hospital of Bengbu Medical College after giving informed consent, 90.3% was female. All cases met the updated 1997 American College of Rheumatology (ACR) classification criteria for SLE 28 , which are used to diagnose symptoms and complications. Disease activity was assessed using the SLE Disease Activity Index 2000 (SLEDAI-2000) criteria. There were 34 patients (6.1%) developed JSLE with age of diagnosis < 18 years (Group 1: < 18 years) 4 , 108 patients (19.4%) had late-onset SLE with age of diagnosis ≥ 50 years (Group 3: ≥ 50 years) 7 , and the other 414 patients (74.5%) were assigned to the early-onset adult group (Group 2: 18-50 years). Ethical approvals and informed consent were obtained and provided from all participants. The study had received ethical approval by the Ethics Committee of the First Affiliated Hospital of Bengbu Medical College [No.2022 (149)]. All experiments were performed in accordance with relevant guidelines and regulations. Laboratory tests The autoantibodies were tested by using line immunoassay. ANA titers were detected by immunofluorescence assay. ANA-staining patterns were visualized under fluorescence microscopy. Statistical analysis Cluster analysis with Ward’s method was used to detect the relationship between autoantibodies, and plotting the clustering heatmap by Origin 2021 software. Using SPSS 27.0 software to perform statistical analysis. The Kruskal-Wallis test was used to compare the autoantibodies, clinical manifestations, laboratory measurements, disease activity and course of disease among three groups. The correlation between ANA pattern and autoantibodies among three groups was determined by the Chi-square test. Spearman correlation analysis of ANA pattern and clinical features were performed by using Correlation Heatmap tool in Hiplot Pro (https://hiplot.com.cn/), a comprehensive web service for biomedical data analysis and visualization. A value of P < 0.05 was considered significant for the above-mentioned tests. Declarations Competing interests: The authors declare that they have no competing interests. Ethic statement Ethical approvals and informed consent were obtained and provided from all participants. The study had received ethical approval by the Ethics Committee of the First Affiliated Hospital of Bengbu Medical College [No.2022 (149)]. All experiments were performed in accordance with relevant guidelines and regulations. Funding: This study was supported by the Natural Science Foundation of Anhui Provincial (2108085MH258) Author Contribution CX, MG designed the work. ZL, TW, CX, XW, MY, CS performed patient clinical assessment. DH, NL, MG collected the data of patients. MG analyzed the data. CX, MG wrote the manuscript. CX reviewed the manuscript. All authors read and approved the final version of the manuscript. Acknowledgement We thank Xiaoyue Xu for her excellent statistical advice. 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Mehra, S. & Fritzler, M. J. The spectrum of anti-chromatin/nucleosome autoantibodies: independent and interdependent biomarkers of disease. J Immunol Res 2014 , 368274, doi:10.1155/2014/368274 (2014). Arroyo-Ávila, M. et al. Clinical associations of anti-Smith antibodies in PROFILE: a multi-ethnic lupus cohort. Clin Rheumatol 34 , 1217-1223, doi:10.1007/s10067-015-2941-y (2015). Sulcebe, G. & Morcka, K. Diagnostic and prognostic significance of different antinuclear antibodies in more than 1000 consecutive Albanian patients with rheumatic diseases. Clin Exp Rheumatol 10 , 255-261 (1992). Tselios, K., Gladman, D. D. & Urowitz, M. B. Systemic lupus erythematosus and pulmonary arterial hypertension: links, risks, and management strategies. Open Access Rheumatol 9 , 1-9, doi:10.2147/oarrr.S123549 (2017). Hochberg, M. C. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 40 , 1725, doi:10.1002/art.1780400928 (1997). Table Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files supplementaltableS1.docx Table1.docx Cite Share Download PDF Status: Posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4903780","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":355144122,"identity":"06a92b45-73f2-4208-862c-42f6dee14af4","order_by":0,"name":"Muxue Gong","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Muxue","middleName":"","lastName":"Gong","suffix":""},{"id":355144123,"identity":"69425169-6895-483c-8485-b3b4dd0cdfe5","order_by":1,"name":"Ning Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Li","suffix":""},{"id":355144124,"identity":"ea57a55f-d6c9-4fef-aded-fae1ee68ba0a","order_by":2,"name":"Chao Sun","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Sun","suffix":""},{"id":355144125,"identity":"6120b87d-a00e-471c-8352-f6c8a5da9942","order_by":3,"name":"Dengxiao Hong","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dengxiao","middleName":"","lastName":"Hong","suffix":""},{"id":355144126,"identity":"608a3be7-8cbd-49a9-aa94-1ec73f251716","order_by":4,"name":"Xin Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Wang","suffix":""},{"id":355144127,"identity":"e18faeb9-2e37-430c-a62f-5e26707b3e60","order_by":5,"name":"Ming Ye","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"Ye","suffix":""},{"id":355144128,"identity":"61e6fe34-b0d5-4464-9d3a-4725e314f292","order_by":6,"name":"Tao Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Wang","suffix":""},{"id":355144129,"identity":"210790be-51c0-4053-9134-b3f92cb556d7","order_by":7,"name":"Zhijun Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhijun","middleName":"","lastName":"Li","suffix":""},{"id":355144130,"identity":"4e90d2b7-9357-4ddc-9bf7-336cd687ce72","order_by":8,"name":"Changhao Xie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIie3QsQrCMBCA4ZRCXFK7SYtgX6Glqw/TLE6dpaOipJN7xck3yOh4odCp2rXgUvEFKq6CppNjMgrmHw4C9w0XhEymn8xmcswJHm0A+kyLWANZzFxSUVHU+qSM/SKNS2erAcLmyLoHsymHtAdnhQJ3AgrS3vJoz7AkZw7+CUX7Q6Iigk0dRigXOw5RjZLwqkc8ykvSAWU6pFkPJIx9RhAIHeK3Vh4Vl0R+Mg7FqvbUt4ybsur65Zvg4H5/vrJ54E4VBHlywcLfp2J9yAU5XhqLJpPJ9L99ADzlUNlJAZRxAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Bengbu Medical University","correspondingAuthor":true,"prefix":"","firstName":"Changhao","middleName":"","lastName":"Xie","suffix":""}],"badges":[],"createdAt":"2024-08-13 03:33:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4903780/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4903780/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66644016,"identity":"a1dfa923-e5b6-4520-a30e-7b88d76a879e","added_by":"auto","created_at":"2024-10-15 06:38:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":460863,"visible":true,"origin":"","legend":"\u003cp\u003eA clustering heatmap with the patients as abscissa and autoantibodies as ordinate illustrating the distribution of autoantibodies in three groups. The color red means positivity and blue means negativity. The brand at top of the figure means different age groups of patients. On the left side of the picture is the results of cluster analysis of autoantibodies. P: anti-ribosomal P protein.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/4301cd9b00ccc31c4f42c8bb.png"},{"id":66644098,"identity":"5460cea1-928d-4c0c-b892-2be9adea0dc7","added_by":"auto","created_at":"2024-10-15 06:38:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":483464,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of SLEDAI scores and laboratory data among three groups.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/2a1ad338e9c37438ce132f7b.png"},{"id":66644099,"identity":"6d9d9040-d536-4168-b3e1-782a2a41151e","added_by":"auto","created_at":"2024-10-15 06:38:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":971600,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between ANA pattern and clinical features among there groups.\u003c/p\u003e\n\u003cp\u003eCorr: Spearman correlation coefficient. The cross in the figure means no statistical significance.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/d648775e3282aa8d5dfeab27.png"},{"id":66646172,"identity":"9a403ec2-0fef-4a62-aa36-043d39ddd5c7","added_by":"auto","created_at":"2024-10-15 06:54:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2581702,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/e5a245e5-3aa9-4cc8-ad62-64b1bd440b10.pdf"},{"id":66644018,"identity":"065e38d4-fa1d-494a-9bee-5025103710d6","added_by":"auto","created_at":"2024-10-15 06:38:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14620,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaltableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/be49db266025749f9c26af25.docx"},{"id":66644012,"identity":"d86e9126-be46-4f23-90c7-9b461b15f7a7","added_by":"auto","created_at":"2024-10-15 06:38:40","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":31752,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4903780/v1/6fda496cd334499b9303977b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Difference and connection of clinical features and antinuclear antibody patterns in new-onset Systemic Lupus Erythematosus cross age groups","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Patients with late-onset SLE were related to ILD, more severe kidney damage and infection.\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Early-onset adult patients with homogeneous pattern need to be aware of renal disorder.\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Late-onset patients with speckled pattern are more likely to develop Reynold\u0026apos;s phenomenon.\u003c/p\u003e\n\u003cp\u003e4. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Homogeneous pattern linked to anti-dsDNA antibody in late-onset SLE can assist in diagnosis.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSystemic lupus erythematosus (SLE) is an autoimmune disease, the infectious, drug, and other factors can stimulate the production of multiple autoantibodies that can cause inflammation and other damages in multiple organs\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. However, the mechanism of SLE is undefined.\u003c/p\u003e \u003cp\u003eJuvenile-onset SLE (JSLE) is a rare disease, which accounts for 10%- 20% of all SLE cases\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Some studies reported that patients with JSLE had more severe condition compared to that with adult-onset SLE (ASLE)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Late-onset SLE which less clinical manifestations occurred accounts for 2\u0026ndash;20% of all SLE cases\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. It often have delayed diagnosis because of its concealment\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Previous studies showed that the mortality may be higher in patients with JSLE and late-onset SLE\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Therefore, comparing autoantibodies, clinical and serological features among newly diagnosed patients of different age groups can provide insights into the correlation between age of onset and organ involvement, this information can guide drug therapy, prevent complications, and delay the progression of SLE at an early stage.\u003c/p\u003e \u003cp\u003eTesting autoantibody by the indirect immunofluorescence assay (IIFA) on HEp-2 cells is the common diagnostic method of SLE\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Some antinuclear antibody (ANA) staining patterns are associated with specific autoantibodies. For instance, the homogenous staining pattern may be linked with anti-histone antibody\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Using ANA patterns and autoantibody can aid diagnosis of suspected SLE\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, and detecting the correlation between ANA patterns and symptoms in initial patients can predict severe complications for timely intervention in early phase of the disease. However, there are less studies on the correlation of ANA patterns with symptoms in different age groups.\u003c/p\u003e \u003cp\u003eThis study aims to compare autoantibodies, disease progression, laboratory data, and clinical features among various age groups, including JSLE, early-onset ASLE and late-onset SLE. Additionally, it explored the relationship of ANA patterns with autoantibodies and symptoms through a retrospective cohort study.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eComparison of autoantibodies in three groups\u003c/h2\u003e \u003cp\u003eThe distribution of autoantibodies in three groups is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The positive frequency of anti-chromatin antibody was highest in three groups. The presence of anti-dsDNA (56.0% vs 70.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) and anti-Sm (46.8% vs 60.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) antibodies in Group 3 were significantly lower than that in Group 2. The positive rate of anti-R52 antibody in Group 1 was 25.7% compared to 54.6% in Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), according to the heatmap and statistical analysis (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the autoantibodies were divided into 4 clusters: cluster 1 consisted of anti-Sm and anti-SmRNP antibodies; cluster 2 was composed of anti-dsDNA and anti-chromatin antibodies; cluster 3 was formed by anti-R60, anti-R52 and anti-SSB antibodies; anti-P antibody was a separate cluster.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eThe difference on initial clinical features and course of disease between three groups\u003c/h2\u003e \u003cp\u003eThe comparison of initial symptoms among three groups are summarized in Table\u0026nbsp;1. Arthritis was common first sign of all patients with SLE in this study. Patients in Group 1 (54.3% vs 17.4%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and Group 2 (36.5% vs 17.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) were more likely to present with malar rash as first symptom than that in Group 3. The proportion of patients with initial symptoms of alopecia (18.4% vs 4.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) in Group 2 were more than that in Group 1. Interstitial lung disease (ILD) was more frequent at the time of diagnosis in Group 3 than that in Group 2 (16.5% vs 4.8%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). The patients in Group 3 had longer course of the disease than that in Group 1 (16.70\u0026thinsp;\u0026plusmn;\u0026thinsp;35.67 vs 4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.32, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) and 2 (16.70\u0026thinsp;\u0026plusmn;\u0026thinsp;35.67 vs 10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;31.05, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eComparison of disease activity and laboratory data among three groups\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e showed the difference on disease activity and serological results between three groups. The levels of serum creatinine (SCr) and blood urea nitrogen (BUN) in Group 3 were significantly higher compared to Group 1 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002, respectively) and Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039, respectively), while Group 2 had higher SCr levels than that in Group 1 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). The albumin (Alb) concentrations of Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and 3 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) were lower than Group 1, and Group 1 had a lower levels of globulin (Glb) compared to Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030) and 3 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014). The SLEDAI score of Group 2 was significantly higher than Group 3 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Group 1 had a lower level of C-reactive protein (CRP) than that in Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) and 3 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). Higher levels of Immunoglobulin A (IgA) and lower levels of Immunoglobulin M (IgM) were observed in Group 3 than that in Group 1 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014, respectively) and Group 2 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019, respectively), while the levels of IgA of Group 2 was higher than Group 1 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eThe relationship between ANA patterns and autoantibodies\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the correlation between ANA patterns and autoantibodies in different groups. The patients with anti-Sm antibody were more likely to have speckled staining pattern in Group 1 (70.6% vs 26.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032) and Group 2 (53.3% vs 40.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), but had fewer homogeneous pattern in Group 1(23.5% vs 66.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031). The percentage of homogeneous pattern in patients with anti-SmRNP antibody was lower than that without it in Group 1 (25.0% vs 75.0%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and Group 2 (34.2% vs 44.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043), while the proportion of speckled pattern in patients with anti-SmRNP antibody was higher in Group 2 (55.3% vs 36.3%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). The patients with anti-dsDNA in Group 2 (48.5% vs 12.8%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and Group 3 (57.1% vs 4.8%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) were more likely to have homogeneous pattern, but had fewer speckled pattern (39.7% vs 69.7%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; 28.6% vs 66.7%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, respectively). The prevalence of homogeneous pattern in patients with anti-P (42.6% vs 31.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032), anti-SSB (46.2% vs 34.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028) and anti-chromatin antibodies (44.9% vs 20.2%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) was higher in Group 2. Speckled pattern was less frequent in Group 2 of patients with anti-R60 (44.8% vs 56.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039) and anti-chromatin (45.3% vs 56.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048) antibodies. The proportion of speckled pattern in Group 3 of patients with anti-R52 antibody was 56.8% compared to 36.2% in patients without it (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048).\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe relationship between autoantibodies and ANA pattern among three groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutoantibody\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eANA pattern\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients with the autoantibody (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients without the autoantibody (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12/17 (70.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4/15 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.032\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4/17 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4/15 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.031\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmRNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5/20 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9/12 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.010\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edsDNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e104/262 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76/109 (69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e127/262 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14/109 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122/229 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58/142 (40.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92/216 (42.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49/155 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.032\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e113/252 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67/119 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.039\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54/117 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87/254 (34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.028\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echromatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121/267 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59/104 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.048\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e120/267 (44.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21/104 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmRNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e131/237 (55.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49/134 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81/237 (34.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60/134 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.043\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edsDNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14/49 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28/42 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHomogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28/49 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2/42 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeckled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25/44 (56.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17/47 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.048\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eP: anti-ribosomal P protein.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eThe correlation of ANA patterns with initial clinical features between three groups\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, there was no correlation between ANA pattern and initial symptoms in Group 1. The speckled pattern was negatively correlated with malar rash and renal disorders, while malar rash and renal disorders were associated with the presence of a homogeneous pattern in Group 2. There was a positive correlation between the speckled pattern and Raynaud's phenomenon in Group 3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAn overall understanding on the significance of ANA patterns can assist in diagnosis and predict organs involvement. There are less studies on association of ANA patterns with autoantibodies and symptoms among patients of different age groups, especially in the newly diagnosed patients, which can hardly influenced by treatment, and the results can better reflect the difference and association. In addition, the relationship between age of onset and symptoms is controversial. In this study, we detect the relationship of age of onset and ANA patterns with autoantibodies and clinical features in initial patients to do early diagnosis and targeted treatment timely to postpone the development of SLE and avoid the organ injury as soon as possible.\u003c/p\u003e \u003cp\u003eAnti-dsDNA and anti-Sm antibodies are included in ACR criteria for SLE because of their high specificity. In this study, we found lower presence of them in patients with late-onset SLE compared to those with early-onset ASLE, which conformed to previous studies by Riveros Frutos A et al\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and Boddaert J et al\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. It may explain delayed diagnosis of late-onset patients. But the results of some early researches were inconsistent or contradictory to our findings \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Meanwhile, anti-R52 antibody was more prevalent in patients with early-onset ASLE than those with JSLE, which was also observed in other study\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The relationship of autoantibodies with age is controversial, which could be explained by different grouping methods, course of disease and ethnicity. The correlation among autoantibodies was detected by cluster analysis, and the autoantibodies were classified into 4 clusters, which were essentially comparable with earlier findings\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIncidence of malar rash in patients with early-onset SLE compared to late-onset SLE, consistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Malar rash, as an initial presentation, was rarer with increasing age according to our results, and it was regarded as an important reason for missed-diagnosis of late-onset SLE\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Patients with early-onset ASLE were more likely to present alopecia than patients with late-onset SLE, as earlier researches reported\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. It may be attribute to the rarity of skin rash in patients with late-onset SLE\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In addition, patients with late-onset SLE were more likely to develop ILD. It was consistent with previous studies that have reported more pulmonary manifestation in patients with late-onset SLE\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. ILD was usually seen in patients with a long history of SLE\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Late-onset SLE is often delayed diagnosis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, which was also found in this study. Therefore, it may be the possible explanation of higher incidence of ILD in patients with late-onset SLE.\u003c/p\u003e \u003cp\u003eIn our study, we found that patients with early-onset ASLE had inferior renal function, and patients with late-onset SLE had the worst renal function at the time of initial diagnosis, which may be attributed to the effects of SLE or degenerative changes. It could explain the higher levels of Alb observed in patients with JSLE in our study. However, a study by Abdel-Nabi HH et al. did not show significant differences in SCr and BUN levels between patients with JSLE and ASLE\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This discrepancy could be due to variations in ethnicity and study design. Although reports suggest a lower incidence of severe symptoms in patients with late-onset SLE\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, it's important to remain cautious about the potential for more serious kidney damage. Our findings also revealed that disease activity was lower in patients with late-onset SLE compared to those with early-onset ASLE, which is consistent with previous research\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. According to our results, C-Reactive Protein (CRP) levels were lower in patients with JSLE than in other age groups. Previous study showed that the level of CRP did not remarkably increased related to SLE\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Therefore, it need to consider the possibility of infection. Further follow-up is needed to explore the relationship between late-onset SLE and infection which is the principal reason of hospitalization and death\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Regarding antibodies, patients with JSLE exhibited increased levels of IgM, while patients with late-onset SLE showed an increase in IgA. We did not observe any differences in blood cell counts, Erythrocyte Sedimentation Rate (ESR), complement levels, and liver enzymes among the three age groups.\u003c/p\u003e \u003cp\u003eANA staining patterns are correlated to the nuclear antigens targeted. Previous study reported that homogeneous pattern was associated with anti-dsDNA antibody, and speckled pattern was related to anti-Sm/RNP antibody\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, which were conformed in patients with ASLE and early-onset SLE respectively according to our results. Anti-R52 antibody was associated to higher prevalence of speckled pattern, which was consistent with early studies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, but the result of anti-R60 antibody in patients with early-onset ASLE was opposite. In an investigation from Sweden, anti-SSA antibody was related to homogeneous/speckled pattern (a mixed type) in patients with SLE\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. It may explained the difference. Homogeneous pattern was associated to anti-P, anti-chromatin and anti- SSB antibody in patients with early-onset ASLE in this study, which were essentially comparable with previous investigation\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Moreover, we had some noteworthy findings: the prevalence of homogeneous pattern was positive correlated with malar rash and renal involvement in patients with early-onset ASLE (speckled pattern was opposite). Anti-dsDNA antibody which was common among early-onset ASLE in this study was associated to homogeneous pattern and less often associated to speckled pattern. Kidney and skin involvement were intimately linked to anti-dsDNA antibody\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. These may be the possible explanation. Speckled pattern was positive correlated with Raynaud's phenomenon in patients with late-onset SLE, which may be explained by the relationship between anti-Sm/RNP antibody and Raynaud's phenomenon\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These new findings need more confirmation by others, and we will collect more data and follow up.\u003c/p\u003e \u003cp\u003eIt is the first Chinese JSLE, early-onset ASLE and late-onset SLE retrospective cohort study for ANA patterns, which enrolled a large number of newly diagnosed patients without treatment. All the data we collected were at early stage of the disease, so our research can assist in diagnosis and predict organ involvement in patients of different ages by detecting the relationship of ANA patterns with autoantibodies, initial symptoms and complications which had less studies on, to control disease progression at very early stages. Nevertheless, sample with JSLE were few, so we did not find the association of ANA patterns with symptoms. In addition, we only detect homogeneous and speckled patterns in this study because of less presence of other staining patterns in patients. We will collect more cases to perfect our research in the future.\u003c/p\u003e \u003cp\u003eIn conclusion, we suggested that patients with late-onset SLE need to consider serious renal damage, ILD and infection. The physicians need to pay attention to ANA pattern for the correlation of homogeneous pattern with anti-dsDNA antibody in elderly patients, because of delayed diagnosis of them. Late-onset patients with speckled pattern are more likely to develop Raynaud's phenomenon, if patients have chest distress and oppressed, pulmonary arterial hypertension (PAH) should be noted\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Patients with early-onset ASLE are likely to have high disease activity, and they with homogeneous pattern need to be aware of renal disorder.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eSubjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe essential information, the course of disease and the clinical data were collected from 556 hospitalized patients with new-onset SLE between 2012 and 2022 at the First Affiliated Hospital of Bengbu Medical College after giving informed consent, 90.3% was female. All cases met the updated 1997 American College of Rheumatology (ACR) classification criteria for SLE\u003csup\u003e28\u003c/sup\u003e, which are used to diagnose symptoms and complications. Disease activity was assessed using the SLE Disease Activity Index 2000 (SLEDAI-2000) criteria. There were 34 patients (6.1%) developed JSLE with age of diagnosis\u0026nbsp;\u0026lt;\u0026nbsp;18 years (Group 1:\u0026nbsp;\u0026lt;\u0026nbsp;18 years)\u003csup\u003e4\u003c/sup\u003e, 108 patients (19.4%) had late-onset SLE with age of diagnosis \u0026ge; 50 years (Group 3: \u0026ge; 50 years)\u003csup\u003e7\u003c/sup\u003e, and the other 414 patients (74.5%) were assigned to the early-onset adult group (Group 2: 18-50 years).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthical approvals and informed consent were obtained and provided from all participants. The study had received ethical approval by the Ethics Committee of the First Affiliated Hospital of Bengbu Medical College [No.2022 (149)]. All experiments were performed in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory tests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe autoantibodies were tested by using line immunoassay. ANA titers were detected by immunofluorescence assay. ANA-staining patterns were visualized under fluorescence microscopy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCluster analysis with Ward\u0026rsquo;s method was used to detect the relationship between autoantibodies, and plotting the clustering heatmap by Origin 2021 software. Using SPSS 27.0 software to perform statistical analysis. The Kruskal-Wallis test was used to compare the autoantibodies, clinical manifestations, laboratory measurements, disease activity and course of disease among three groups. The correlation between ANA pattern and autoantibodies among three groups was determined by the Chi-square test. Spearman correlation analysis of ANA pattern and clinical features were performed by using Correlation Heatmap tool in Hiplot Pro (https://hiplot.com.cn/), a comprehensive web service for biomedical data analysis and visualization. A value of P \u0026lt; 0.05 was considered significant for the above-mentioned tests.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthic statement\u003c/h2\u003e \u003cp\u003e Ethical approvals and informed consent were obtained and provided from all participants. The study had received ethical approval by the Ethics Committee of the First Affiliated Hospital of Bengbu Medical College [No.2022 (149)]. All experiments were performed in accordance with relevant guidelines and regulations.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study was supported by the Natural Science Foundation of Anhui Provincial (2108085MH258)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCX, MG designed the work. ZL, TW, CX, XW, MY, CS performed patient clinical assessment. DH, NL, MG collected the data of patients. MG analyzed the data. CX, MG wrote the manuscript. CX reviewed the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank Xiaoyue Xu for her excellent statistical advice.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eXiao, Z. X., Miller, J. S. \u0026amp; Zheng, S. G. An updated advance of autoantibodies in autoimmune diseases. \u003cem\u003eAutoimmun Rev\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 102743, doi:10.1016/j.autrev.2020.102743 (2021).\u003c/li\u003e\n\u003cli\u003eAringer, M. 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Antinuclear Antibody Testing for the Diagnosis of Systemic Lupus Erythematosus. \u003cem\u003eMed Clin North Am\u003c/em\u003e \u003cstrong\u003e105\u003c/strong\u003e, 387-396, doi:10.1016/j.mcna.2020.10.003 (2021).\u003c/li\u003e\n\u003cli\u003eBoddaert, J.\u003cem\u003e et al.\u003c/em\u003e Late-onset systemic lupus erythematosus: a personal series of 47 patients and pooled analysis of 714 cases in the literature. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 348-359, doi:10.1097/01.md.0000147737.57861.7c (2004).\u003c/li\u003e\n\u003cli\u003eTian, N.\u003cem\u003e et al.\u003c/em\u003e Long-Term Kidney Prognosis and Pathological Characteristics of Late-Onset Lupus Nephritis. \u003cem\u003eFront Med (Lausanne)\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 882692, doi:10.3389/fmed.2022.882692 (2022).\u003c/li\u003e\n\u003cli\u003eHoffman, I. E.\u003cem\u003e et al.\u003c/em\u003e Specific antinuclear antibodies are associated with clinical features in systemic lupus erythematosus. \u003cem\u003eAnn Rheum Dis\u003c/em\u003e \u003cstrong\u003e63\u003c/strong\u003e, 1155-1158, doi:10.1136/ard.2003.013417 (2004).\u003c/li\u003e\n\u003cli\u003eKuhn, A.\u003cem\u003e et al.\u003c/em\u003e The Diagnosis and Treatment of Systemic Lupus Erythematosus. \u003cem\u003eDtsch Arztebl Int\u003c/em\u003e \u003cstrong\u003e112\u003c/strong\u003e, 423-432, doi:10.3238/arztebl.2015.0423 (2015).\u003c/li\u003e\n\u003cli\u003eKamen, D. L. \u0026amp; Strange, C. Pulmonary manifestations of systemic lupus erythematosus. \u003cem\u003eClin Chest Med\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 479-488, doi:10.1016/j.ccm.2010.05.001 (2010).\u003c/li\u003e\n\u003cli\u003eAbdel-Nabi, H. H. \u0026amp; Abdel-Noor, R. A. Comparison between disease onset patterns of Egyptian juvenile and adult systemic lupus erythematosus (single centre experience). \u003cem\u003eLupus\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 1039-1044, doi:10.1177/0961203318760208 (2018).\u003c/li\u003e\n\u003cli\u003eBarber, M. R. W. \u0026amp; Clarke, A. E. Systemic lupus erythematosus and risk of infection. \u003cem\u003eExpert Rev Clin Immunol\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 527-538, doi:10.1080/1744666x.2020.1763793 (2020).\u003c/li\u003e\n\u003cli\u003eAlsubki, R.\u003cem\u003e et al.\u003c/em\u003e Association between antinuclear antibodies (ANA) patterns and extractable nuclear antigens (ENA) in HEp-2 cells in patients with autoimmune diseases in Riyadh, Saudi Arabia. \u003cem\u003eIntractable Rare Dis Res\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 89-94, doi:10.5582/irdr.2020.03012 (2020).\u003c/li\u003e\n\u003cli\u003eFrodlund, M., Dahlstr\u0026ouml;m, O., Kastbom, A., Skogh, T. \u0026amp; Sj\u0026ouml;wall, C. Associations between antinuclear antibody staining patterns and clinical features of systemic lupus erythematosus: analysis of a regional Swedish register. \u003cem\u003eBMJ Open\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, e003608, doi:10.1136/bmjopen-2013-003608 (2013).\u003c/li\u003e\n\u003cli\u003eAndrade, L. E. C., Damoiseaux, J., Vergani, D. \u0026amp; Fritzler, M. J. Antinuclear antibodies (ANA) as a criterion for classification and diagnosis of systemic autoimmune diseases. \u003cem\u003eJ Transl Autoimmun\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 100145, doi:10.1016/j.jtauto.2022.100145 (2022).\u003c/li\u003e\n\u003cli\u003ePasoto, S. G., Viana, V. S. \u0026amp; Bonfa, E. The clinical utility of anti-ribosomal P autoantibodies in systemic lupus erythematosus. \u003cem\u003eExpert Rev Clin Immunol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1493-1503, doi:10.1586/1744666x.2014.966692 (2014).\u003c/li\u003e\n\u003cli\u003eMehra, S. \u0026amp; Fritzler, M. J. The spectrum of anti-chromatin/nucleosome autoantibodies: independent and interdependent biomarkers of disease. \u003cem\u003eJ Immunol Res\u003c/em\u003e \u003cstrong\u003e2014\u003c/strong\u003e, 368274, doi:10.1155/2014/368274 (2014).\u003c/li\u003e\n\u003cli\u003eArroyo-\u0026Aacute;vila, M.\u003cem\u003e et al.\u003c/em\u003e Clinical associations of anti-Smith antibodies in PROFILE: a multi-ethnic lupus cohort. \u003cem\u003eClin Rheumatol\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 1217-1223, doi:10.1007/s10067-015-2941-y (2015).\u003c/li\u003e\n\u003cli\u003eSulcebe, G. \u0026amp; Morcka, K. Diagnostic and prognostic significance of different antinuclear antibodies in more than 1000 consecutive Albanian patients with rheumatic diseases. \u003cem\u003eClin Exp Rheumatol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 255-261 (1992).\u003c/li\u003e\n\u003cli\u003eTselios, K., Gladman, D. D. \u0026amp; Urowitz, M. B. Systemic lupus erythematosus and pulmonary arterial hypertension: links, risks, and management strategies. \u003cem\u003eOpen Access Rheumatol\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 1-9, doi:10.2147/oarrr.S123549 (2017).\u003c/li\u003e\n\u003cli\u003eHochberg, M. C. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. \u003cem\u003eArthritis Rheum\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 1725, doi:10.1002/art.1780400928 (1997).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"New-onset SLE, Juvenile-onset SLE, Late-onset SLE, ANA patterns","lastPublishedDoi":"10.21203/rs.3.rs-4903780/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4903780/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo investigate the differences in clinical features, and the relationship between antinuclear antibody (ANA) patterns, autoantibodies, and symptoms among different age groups in new-onset Systemic Lupus Erythematosus (SLE), we conducted a retrospective cohort study involving 556 patients diagnosed with SLE. These patients were classified into three groups: Group 1: juvenile-onset SLE (\u0026lt; 18 years); Group 2: early-onset adult SLE (18-50 years); and Group 3: late-onset SLE (≥ 50 years). We utilized a clustering heatmap to identify variations and associations of autoantibodies among the groups. The Kruskal-Wallis test was performed to compare clinical feature across the groups. The correlation heatmap were used to analyze the relationship of ANA patterns with symptoms. We found late-onset SLE patients exhibited more severe kidney damage and a higher likelihood of infection. ;Late-onset patients with a speckled ANA pattern were more prone to developing Raynaud's phenomenon. It is important for early-onset adult SLE patients with a homogeneous ANA pattern to be vigilant about the possibility of renal disorders and skin involvement. It is the first Chinese JSLE, early-onset ASLE and late-onset SLE study for ANA patterns, which enrolled a large number of newly diagnosed patients. These novel findings contribute to the diagnosis and prevention of SLE.\u003c/p\u003e","manuscriptTitle":"Difference and connection of clinical features and antinuclear antibody patterns in new-onset Systemic Lupus Erythematosus cross age groups","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 06:38:10","doi":"10.21203/rs.3.rs-4903780/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"71e4b93c-d6bc-42cf-ab99-1d139045f2e3","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":37750148,"name":"Health sciences/Diseases/Rheumatic diseases/Systemic lupus erythematosus"},{"id":37750149,"name":"Biological sciences/Immunology"}],"tags":[],"updatedAt":"2024-10-15T06:38:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-15 06:38:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4903780","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4903780","identity":"rs-4903780","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}