Correlation between serum β2-microglobulin level and systemic lupus erythematosus disease activity: A PRISMA-compliant meta-analysis

1. Introduction

Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by alternate phases of flares and remissions, which often leads to chronic inflammation and damage to multiple organs with substantial morbidity and mortality.[1–3] The pathogenesis of SLE is intricate and remains incompletely understood, yet excessive B- and T-cell activation, autoantibody production, and imbalance between immune complex formation and its clearance have been widely proposed to be key drivers in the development and progression of SLE.[4,5] The selection of a therapeutic regimen for SLE depends on the degree of disease activity, and therefore methods to determine this activity level are of great importance in clinical practice.[6]

Several inflammatory biomarkers, such as sedimentation rate and C-reactive protein level, are commonly used to evaluate the degree of SLE activity.[7] However, these inflammatory markers lack specificity and are unreliable. In addition, many other serological markers, including anti-C1q antibodies, anti-dsDNA, and C3 complement components, have also been measured to assess SLE disease activity but have not been found to correlate with all SLE manifestations.[8] Furthermore, there are some standardized disease activity assessment tools that integrate laboratory and clinical manifestations, such as the SLE Disease Activity Index (SLEDAI) and the British Isles Lupus Assessment Group index (BILAG). Nevertheless, it is time-consuming and inconvenient in daily practice to assess SLE disease activity using these assessment tools. Hence, it is imperative to develop novel and efficient tools to evaluate SLE disease activity.

Beta 2-microglobulin (β2-MG) is a low-molecular-weight protein (11 kDa) that is extensively expressed on the surface of all nucleated cells.[9] In physiological conditions, the daily formation of β2-MG is 50 to 200 mg with a plasma half-life of 2 hours, and its serum level is low.[10] It has been well established that lymphocyte activity during lymphoproliferative and autoimmune disease processes has a significant effect on β2-MG levels.[11,12] Interestingly, mounting evidence shows that serum β2-MG levels are often elevated in patients with autoimmune diseases, including SLE, rheumatoid arthritis (RA), and Sjogren syndrome, compared to their healthy counterparts.[13,14] More importantly, numerous clinical studies have reported that serum β2-MG level is associated with SLE disease activity, suggesting that serum β2-MG may be used as a tool for evaluating SLE disease activity.[15–18] In contrast, some studies have found no significant relationship between serum β2-MG level and SLE disease activity. The conclusions of these studies may be biased due to limited sample size; however, a review of their findings in comparison to other studies is necessary. Therefore, in this study, we conducted a comprehensive meta-analysis of the published literature to evaluate the association between serum β2-MG levels and SLE disease activity.

2. Methods 2.1. Database search strategy

This meta-analysis was performed according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A systematic search was conducted in PubMed, Web of Science, Embase, and CNKI databases from the earliest entry through April 2022 for relevant literature on the correlation between serum β2-MG levels and SLE disease activity.

2.2. Eligibility criteria

The inclusion criteria for eligible studies were as follows: case–control or retrospective cohort design; patients divided into SLE and health control groups or active SLE and inactive SLE groups based on the SLE Disease Activity Index (SLEDAI) score; reported Spearman correlation coefficient or Pearson correlation coefficient value for the correlation between serum β2-MG level and SLE disease activity, and (or) serum β2-MG levels (presented as mean and standard deviation/error) in active SLE patients and inactive counterparts; and published in English or Chinese. The exclusion criteria were as follows: nonhuman research, conference abstracts, or review literature; unrelated topics; enrollment of overlapping populations; and unavailability of data for the pooled analysis.

2.3. Data extraction and quality assessment

Data were extracted by 2 independent investigators from eligible studies which included the first author’s name, publication year, study region, sample sizes of active/inactive SLE patients and normal controls, mean age, sex ratio, detection method for serum β2-MG, Spearman or Pearson correlation coefficient (r) value for describing the correlation between serum β2-MG levels and SLE disease activity, mean value, and standard deviation or error of serum β2-MG levels. When only the Spearman correlation coefficient value was provided in the included studies, we converted it into a Pearson correlation coefficient value as previously described. Two investigators independently evaluated the quality of potentially eligible studies with reference to the Newcastle–Ottawa Scale,[19] and studies scored 0 to 3, 4 to 6, and 7 to 9 points were regarded as low, moderate, and high quality, respectively.

2.4. Statistical analysis

STATA version 12.0 (Stata Corporation, College Station, TX) was used to perform the statistical analysis. The differences between serum β2-MG levels in SLE patients versus healthy controls and active SLE patients versus inactive SLE counterparts were depicted by standardized mean differences (SMDs) with 95% confidence intervals (95% CIs). In addition, the correlation between serum β2-MG levels and SLE disease activity was evaluated using pooled correlation coefficients. For this, we first transformed the Pearson correlation coefficients into Fisher r- to z-values, and then subjected these data to meta-analysis, the results of which were stated as the Fisher z values with 95% CIs.[20–22] The heterogeneity among the included studies was assessed using Cochran Q test and I2 index.[23] When the P value was <0.05, or (and) I2 was >50%, there was considered to be significant heterogeneity, and subsequently a random-effect model was selected for calculating the pooled results. To decipher the potential sources of heterogeneity, subgroup and meta-regression analyses were performed based on sample size, study region, method of detecting serum β2-MG level, and definition of disease activity. Sensitivity analysis was performed to evaluate the influence of each eligible study on the combined results. Funnel plots and Begg and Egger tests were utilized to evaluate publication bias.[24–26] A P value <.05 was defined as statistically significant.

3. Results 3.1. Literature selection

A total of 143 studies were initially retrieved from a systematic search of PubMed, Web of Science, Embase, and CNKI databases. Among these, 62 duplicates were excluded. After screening the titles and abstracts of the remaining 81 articles, 53 articles were removed due to their classification as case reports, letters, conference abstracts, reviews, nonclinical studies, or unrelated topics. Next, the full texts of the remaining 28 studies were carefully reviewed, and another 12 articles were excluded due to unavailability of necessary data mentioned in the inclusion criteria and overlapping patient data. Thus, 16 studies involving a combined 1368 SLE patients and 423 healthy controls were included in this meta-analysis.[15–18,27–38] The details of the study selection process are presented in Figure 1.

F1Figure 1.:

PRISMA flowchart for identifying eligible studies. PRISMA = Preferred Reporting Items for Systematic Review and Meta-Analysis.

3.2. Study characteristics

The included studies were published between 2010 and 2021. The sample sizes of eligible studies ranged from 23 to 200 patients or participants. There were 9 articles enrolling patients from China,[17,28,30,31,33–37] and 7 articles from the United States,[18] Korea,[27] Spain,[29] Brazil,[6] Egypt,[15] and Iran.[16] In 7 studies, serum β2-MG levels were measured using an enzyme-linked immunosorbent assay (ELISA).[15,17,27,29,33,36,38] All the included studies reported the correlation coefficient between serum β2-MG levels and SLE disease activity. The serum β2-MG levels in SLE patients and healthy controls were compared in 7 studies,[15,17,28,30,33,34,36] and 10 studies compared the serum β2-MG levels between active SLE patients and inactive patients.[15,17,28,30,31,33–37] The Newcastle–Ottawa Scale scores of the included studies ranged from 6 to 7, indicating that the included studies were of high quality. The detailed baseline characteristics of the eligible studies are summarized in Table 1.

Table 1 - Characteristics of eligible studies. Study Country SLE Female (%) Control Female (%) Detection methods Definition of active SLE NOS Sample size Mean age Sample size Mean age Active/inactive Active/inactive Aghdashi, 2019 Iran 50 32.01 ± 1.61 NA 25 30.28 ± 1.11 NA ELISA SLEDAI ≥ 8 6 Guo, 2019 China 28/34 34.42 ± 5.87 NA 35 34 ± 9 NA ELISA SLEDAI ≥ 10 6 Hermansen, 2012 USA 26 41 100 10 28 100 Multiplex SLEDAI ≥ 3 6 Kim, 2010 Korea 100 32.8 ± 10.9 NA 50 29.5 ± 5.9 NA ELISA NA 6 Li, 2020 China 31/28 43. 96 ± 12. 73 91 65 43. 48 ± 12. 65 91 LEITA SLEDAI ≥ 10 6 Liang, 2020 China 28/20 34. 69 ± 4.97 73 42 33. 58 ± 4. 25 71 ELISA SLEDAI ≥ 10 6 Liu, 2015 China 100/40 38 ± 12 62 50 39 ± 14 NA LEITA NA 6 Liu, 2021 China 94/106 36.34 ± 8.87 90 100 35.45 ± 9.56 85 ELISA SLEDAI ≥ 10 7 Nashwa, 2019 Egypt 20/20 30.50 ± 5.21/30.65 ± 5.07 80 20 30.35 ± 4.40 80 Nephelometry SLEDAI ≥ 4 6 Silva, 2012 Spain 42 37.1 ± 13.1 88 NA NA NA ELISA SLEDAI-2K ≥ 6 6 Skare, 2014 Brazil 129 40.1 ± 11.3 96.9 NA NA NA Chemiluminescence NA 6 Wang, 2021 China 23/27 43.57 ± 5.16/44.51 ± 5.37 48 NA NA NA NA SLEDAI-2K ≥ 10 6 Wei, 2021 China 23/29 38. 82 ± 9. 27/37. 97 ± 8. 90 71 26 37. 49 ± 8. 73 69 NA SLEDAI ≥ 10 6 Xu, 2017 China 40/67 38.83 ± 13.38 94 NA NA NA Radioimmunoassay SLEDAI ≥ 10 6 Zhang, 2019 China 76/118 34.2 ± 13.6/39.9 ± 14.4 89 NA NA NA NA SLEDAI ≥ 10 6 Żychowska, 2018 China 69 34.5 ± 11 90 NA NA NA ELISA NA 6

ELISA = enzyme-linked immunosorbent assay, LEITA = Latex-enhanced immunoturbidimetric assay, NA = not available, NOS = Newcastle–Ottawa Scale, SLE = systemic lupus erythematosus, SLEDAI = Systemic Lupus Erythematosus Disease Activity Index; SLEDAI-2K = Systemic Lupus Erythematosus Disease Activity Index 2000.


3.3. Meta-analysis of serum β2-MG levels in SLE patients and correlation with disease activity

A total of 7 studies reported serum β2-MG levels in SLE patients and their healthy counterparts.[15,17,28,30,33,34,36] There was significant heterogeneity (I2 = 96.7%, P < .01), so chose a random-effect model to perform a meta-analysis comparing the serum β2-MG levels between SLE patients and healthy controls. As shown in Figure 2, serum β2-MG levels were significantly higher in SLE patients than in their healthy counterparts (pooled SMD: 3.98, 95% CI: 2.50–5.46, P < .01). In addition, a total of 10 articles compared serum β2-MG levels between active and inactive SLE patients.[15,17,28,30,31,33–37] The random-effects model was used for the pooled analysis, again due to substantial heterogeneity (I2 = 94.5%, P < .01). We found that active SLE patients had a significantly higher level of serum β2-MG than inactive SLE patients (pooled SMD: 1.89, 95% CI: 1.20–2.58, P < .01; Fig. 3). Furthermore, all of the included studies evaluated the correlation of the serum β2-MG level with SLE disease activity by calculating the correlation coefficients.[15–18,27–38] In view of the significant heterogeneity (I2 = 88.9%, P < .01), we again selected a random-effect model to synthetize the correlation coefficients and confirmed the positive correlation between serum β2-MG level and SLE disease activity (pooled Fisher z = 0.78, 95% CI: 0.61–0.96, P < .01; Fig. 4).

F2Figure 2.:

Meta-analysis comparing the serum β2-MG levels between SLE patients and health controls. β2-MG = beta 2-microglobulin, CI = confidence interval, SLE = systemic lupus erythematosus, SMD = standardized mean difference.

F3Figure 3.:

Meta-analysis comparing the serum β2-MG levels between active patients and inactive patients. β2-MG = beta 2-microglobulin, CI = confidence interval, SMD = standardized mean difference.

F4Figure 4.:

Meta-analysis evaluating the correlation between the serum β2-MG level and SLE disease activity. β2-MG = beta 2-microglobulin, CI = confidence interval, SLE = systemic lupus erythematosus.

3.4. Subgroup analysis and meta-regression analysis

To investigate the potential sources of heterogeneity in the pooled results, we performed subgroup and meta-regression analyses by sample size, study region, detection method, and definition of SLE disease activity. The results showed that the serum β2-MG level was significantly higher in active SLE patients than in inactive SLE patients (Table 2) and was positively correlated with SLE disease activity (Table 3) in all subgroups regardless of sample size, study region, detection method, and definition of SLE disease activity. However, significant heterogeneity remained in each subgroup analysis and our meta-regression analyses did not yield significant results (Tables 2 and 3).

Table 2 - Subgroup analyses for the pooled results of differences in serum β2-microglobulin levels between active and inactive SLE patients. Variables No. of studies Pooled estimate (95% CI) P value Heterogeneity Meta-regression I 2 (%) P value Tau2 I 2 (%) P value Sample size 0.94 94.78 .26  n <100 6 1.822 (1.117–2.528) <.01 85.3 <.01  n ≥100 4 1.951 (0.639–3.263) <.01 97.7 <.01 Country 0.95 94.78 .26  Other country 1 3.145 (2.204–4.085) <.01 – –  China 9 1.762 (1.046–2.478) <.01 94.8 <.01 Measuring methods 0.85 92.1 .17  ELISA 3 2.594 (1.509–3.68) <.01 90.2 <.01  Other methods 7 1.576 (0.878–2.275) <.01 92.6 <.01 Definition of activity 1.1 94.9 .64  SLEDAI ≥10 7 1.777 (0.975–2.58) <.01 94.8 <.01  Other methods 3 2.162 (0.486–3.838) .01 95.2 <.01

CI = confidence interval, ELISA = enzyme-linked immunosorbent assay, SLE = systemic lupus erythematosus, SLEDAI = Systemic Lupus Erythematosus Disease Activity Index.


Table 3 - The correlation between serum β2-microglobulin level and disease severity of SLE in different subgroups. Variables No. of studies Pooled estimate (95% CI) P value Heterogeneity Meta-regression I 2 (%) P value Tau2 I 2 (%) P value Sample size 0.09 89.57 .42  n <100 10 0.838 (0.677–0.998) <.01 67.6 <.01  n ≥100 6 0.687 (0.341–1.032) <.01 95.3 <.01 Country 0.09

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