Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by the presence of various autoantibodies, particularly antinuclear antibody (ANA) (1). SLE manifests with diverse clinical features and simultaneous involvement of multiple organs and systems (2). Within the first year of disease onset, approximately 40% of SLE patients will develop organ damage (3), while around 50% will experience permanent organ damage within 5 years (4). Early diagnosis of SLE is crucial for effective treatment. Therefore, biomarkers, especially immunological biomarkers, have emerged as valuable tools for accurate diagnosis, assessment of disease activity, and achieving optimal disease control.

The discovery of lupus cells has garnered significant attention in diagnosing SLE (5). With the identification and development of ANA detected through indirect immunofluorescence (IIF) on Human epithelial type-2 (HEp-2) cells, it has replaced lupus cells as an important component in classifying individuals with SLE (6–8). In fact, positive ANA at any time has been defined as a required entry criterion according to the latest EULAR/ACR-2019 criteria (9).

However, unlike its role in classifying and diagnosing SLE, serum ANA titer is not recommended as a monitoring indicator for disease activity due to uncertain correlation between serum ANA titer and SLE disease activity levels (10). Furthermore, severe relapse of lupus nephritis may be accompanied by the disappearance of ANA (11), indicating that negative conversion or loss of immunofluorescence ANA could suggest unfavorable prognoses for severe patients (12).

Previous studies have demonstrated the presence of urinary ANA (13–15); however, their significance and utility remain unexplored. Do patients with positive urine ANA and/or anti-ENA antibodies exhibit a distinct phenotype that can be utilized in assessing systemic or kidney disease activity? This study aims to further investigate the association between urine autoantibodies and disease activity as well as organ involvement in SLE.

Although new biomarkers have made great progress in increasing the accuracy of SLE diagnosis (18) and assessing disease activity (19, 20), conventional biomarkers like anti-dsDNA antibodies (21), and complement factors (22) continue to hold an indispensable role in diagnosing and assessing SLE. In the latest 2019 classification criteria for SLE by EULAR/ACR, anti-dsDNA antibody and complement components remain crucial elements for classification purposes (9).

ANA titers may fluctuate alongside changes in both the underlying disease state of SLE itself as well as immunosuppressant usage. A study on belimumab has indicated that up to 30% of screened SLE patients are found to be ANA negative, implying that clinically significant cases exist especially among those treated with glucocorticoids and immunosuppressants (23). Oh Chan Kwon et al. reported that seroconversion to ANA negativity (titer <1:40) occurred in 9.7% of individuals with SLE. Furthermore, patients who experienced negative seroconversion for antinuclear antibodies exhibited significantly lower risk of systemic lupus erythematosus flare-ups (adjusted hazard ratio 0.13, p = 0.007), whereas an increase in ANA titer was associated with elevated risk of experiencing a flare-up in SLE (24). According to general logic, elevation in serum ANA titer often signifies increased activity within one or more plasma cells present within the patient’s body and consequently suggests heightened disease activity within their case of SLE; however, this is not always true (24, 25) due to various factors such as assay variation (26), substrates used during testing procedures (27), formation of immune complexes (28), and protein loss from kidney (11, 12).

Meanwhile, several studies have confirmed the presence of autoantibodies in urine. N L Meryhew et al. reported that urine ANA could be detected by indirect immunofluorescence (IIF) in 32% of SLE patients using HEp-2 cell substrate. Sixty-two percent of SLE patients with urine ANA had proteinuria (13). Williams et al. (14) and Macanovic et al. (15) reported the detection of anti-DNA antibodies in the urine of lupus nephritis patients. Consistent with these findings, our present study observed a positive rate of urinary ANA at 33.3%, which increased gradually with increasing urinary protein levels. Even among SLE patients with urinary protein at 1+, more than one-third showed detectable levels of ANA in their urine, suggesting that urinary ANA is a common phenomenon in LN patients. However, prior investigations have not explored the significance associated with the presence of autoantibodies in urine.

As shown in Table 3, individuals within the uANA-positive group exhibited elevated levels of both urine anti-dsDNA antibodies and disease activity scores including SLEDAI-2000 score as well as RSLEDAI score and NRSLEDAI score compared to the negative group. Moreover (in line with this), there was a significant positive correlation between uANA titers and both SLEDAI scores as well as RSLEDAI scores; indicating that uANA is associated with SLE total disease activity and renal involvement.

Anti-dsDNA antibodies exhibit high specificity for systemic lupus erythematosus (SLE) and are detectable in the bloodstream years before clinical diagnosis (29). Numerous studies have investigated the role of anti-dsDNA antibodies in kidney injury associated with SLE (30–32). Levels of anti-dsDNA antibodies correlate with disease activity, particularly in patients with lupus nephritis (33, 34). The strong association between serum anti-dsDNA antibodies and SLE disease activity has been extensively established (35). Pan et al. discovered that an upsurge in anti-dsDNA titer predicted the subsequent development of a severe SLE flare within 6 months. However, an increase in anti-dsDNA titer did not serve as a predictive factor for renal flares (36). This implies that there is no inherent association between serum levels of anti-dsDNA antibodies and renal involvement in SLE. Since elevated serum levels of anti-dsDNA antibodies are linked with disease activity, it would be reasonable to anticipate increased levels during episodes of lupus nephritis flares. Surprisingly, Ho, A et al. found that serum levels of anti-dsDNA antibodies did not escalate but rather decreased during these flares (37), further supporting the absence of correlation between serum antibody levels and the flares of lupus nephritis. Similar to the findings of the two studies above, there was no significant association between serum anti-dsDNA antibody levels and renal disease activity (RSLEDAI) scores in our current study.

However, our study demonstrated significantly higher levels of urine anti-dsDNA antibodies in the LN group, consistent with previous reports on excretion of anti-dsDNA antibodies in urine (14, 28, 38). In the present study, urine anti-dsDNA antibody levels exhibited a noteworthy positive correlation with RSLEDAI scores, indicating their potential relevance to renal involvement. Further investigations are warranted to elucidate whether urine anti-dsDNA antibody levels can serve as predictive markers for SLE renal flares.

In addition to the presence of urine ANA and urine anti-dsDNA antibodies, the detection of urinary anti-ENA series antibodies is also highly prevalent. Anti-Sm antibodies exhibit high specificity for SLE and are often detectable prior to diagnosis (29). Immune deposits containing anti-Sm antibodies have been identified in the glomeruli of SLE patients (39). However, the clinical significance of anti-Sm antibodies remains uncertain. One study suggested a correlation between serum anti-Sm antibodies and increased renal involvement (40), while another study found no association between serum anti-Sm antibodies and renal involvement (41). Given these conflicting findings, current evidence does not support the use of anti-Sm antibodies as reliable prognostic or activity markers in SLE. Therefore, it is worth investigating whether urine anti-Sm antibodies are associated with renal involvement. The presence of anti-Sm antibodies in urine primarily results from renal leakage of plasma anti-Sm antibodies. In this study, patients with positive urinary anti-Sm antibody tests exhibited 100% renal involvement, which was significantly higher compared to those with negative urinary anti-Sm antibody tests and those with positive urinary other anti-ENA antibodies, including anti-nRNP/Sm, anti-SSA, and anti-SSB antibodies. This suggests that in patients without renal involvement at diagnosis, a positive urine screening for anti-Sm antibodies may indicate future renal involvement; however, further research is needed to establish its true predictive value.

Meanwhile, according to Table 2, the positive rate of urine anti-ENA antibodies decreases gradually with increasing urine dilution. The gradual decrease or disappearance of urine anti-ENA antibodies after dilution is attributed to the reduction in antibody levels and limitations in reagent detection sensitivity. This suggests that higher dilutions may enhance the specificity of specific antibodies for disease diagnosis and assessment but at the expense of sensitivity.

In clinical practice, some patients with SLE have been treated with glucocorticoids and immunosuppressants for an extended period; however, their serum ANA titers have consistently remained high, while the levels of anti-dsDNA antibody and complement have failed to normalize despite stable disease manifestations. Moreover, seropositivity for ANA has long been a classification criterion for SLE without establishing a correlation between ANA titers and disease activity. Although serum levels of anti-dsDNA antibody were associated with SLE disease activity, no association was found between current serum levels and renal involvement. These findings suggest that neither serum ANA nor anti-dsDNA antibodies or complement accurately reflect the disease activity in SLE. This study highlights the close correlation between urinary ANA and overall SLE disease activity, as well as the association of renal disease activity with both urinary ANA and urinary anti-dsDNA antibody levels. Therefore, it is worth investigating whether urine-based biomarkers such as urinary ANA and anti-dsDNA antibodies can be utilized to assess renal disease activity in SLE patients. Additionally, exploring whether the presence of autoantibodies in urine can predict future disease flares holds significant research potential.

The current study was a single-center, small-sample study, necessitating further expansion of the sample size and inclusion of additional study centers. Additionally, the impact of glucocorticoids and immunosuppressants on antinuclear antibodies has been demonstrated in both laboratory and clinical settings (24). In this study, patients in the LN group received higher doses of glucocorticoids and had a greater proportion of immunosuppressant usage compared to those in the non-LN group, which may have influenced the findings. We made every effort to exclude other diseases as potential causes of proteinuria based on a definitive diagnosis of SLE, following standard clinical practice. As reported by Pisetsky et al. (26), the frequency of ANA negativity varies depending on the assay kit used, highlighting the need for further investigations to determine if our results align with those obtained using different assay kits.

In conclusion, urine ANA is associated with both global SLEDAI and SLEDAI scores. Urine anti-Sm antibody is associated with increased renal involvement in SLE. Notably, the urine anti-dsDNA antibody level, rather than the serum anti-dsDNA antibody level, exhibits a significant association with RSLEDAI in SLE.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Medical Ethics Committees of Qilu Hospital of Shandong University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

YZ: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft. XQ: Data curation, Methodology, Writing – review & editing. LW: Data curation, Methodology, Writing – review & editing. LS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Supervision, Validation, Writing – review & editing.