COVID-19 immune trace: predictors of rheumatoid arthritis development

Full Text

Introduction

Autoimmune rheumatic diseases (ARDs) are chronic conditions with a multifactorial mechanism. Gender differences play a significant role in their development, with a high prevalence among women, accounting for 78 % of all ARD cases. Recently, changes in the microbiome have also been recognized as one of the contributing factors to the development of immune-mediated inflammatory rheumatic diseases (IMIRDs) [1]. Despite the fact that ARDs are diagnosed in 5 % of the population, there is currently a steady increase in the incidence of these pathologies [2].

During the COVID-19 pandemic, it was hypothesized that the onset of ARDs could be associated with virus-induced autoimmunity. This process may occur through various mechanisms, including molecular mimicry and breakdown of immune tolerance [1, 3]. However, the role of viruses in the development of autoimmune diseases is not yet fully understood and requires further investigation. The triggering role of COVID-19 in the development of ARDs is most likely linked to hyperproduction of proinflammatory cytokines (IFN-γ, IL-1, IL-6, IL-12, and TNF-α) and chemokines (CCL2, CXCL10, CXCL9, and IL-8), leading to a “cytokine storm”. In the treatment of rheumatic diseases, these cytokines are key therapeutic targets [4].

Scientific literature describes cases of post-viral arthritis following infections such as hepatitis C and alphaviruses. For example, arthritis with regressing clinical manifestations has been observed in parvovirus B19 infection, hepatitis B, and rubella [5]. COVID-19 is frequently associated with arthralgia and myalgia, occurring in 44 % and 15 % of cases, respectively [6]. Moreover, studies have shown that arthralgia persists in 27.3 % of cases even two months after COVID-19 [7].

One of the manifestations of autoimmunity characteristic of SARS-CoV-2 is the detection of autoantibodies. Specifically, antinuclear antibodies were found in 30 % of COVID-19 convalescents. Antinuclear factor was detected in 57.6 % [8; 7]. Cases of rheumatoid arthritis (RA) development following SARS-CoV-2 infection have been described. These cases were characterized by positive rheumatoid arthritis markers such as rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibodies (ACPA) [4; 9]. According to the COVID-19 Global Rheumatology Alliance (GRA) registry, among 7,263 COVID-19 patients, 2,956 (40.7 %) had RA, 1,794 (17.73 %) had systemic lupus erythematosus, 713 (7.05 %) had spondyloarthritis, etc.¹

The phenomenon of RA onset in patients previously negative for RA markers via a citrulline-independent pathway requires further investigation [5]. Some patients continue to exhibit signs of autoimmunity after SARS-CoV-2 infection, with a subset developing autoimmune diseases. Several studies confirm an association between COVID-19 and the development of autoimmune diseases, including RA [10]. Rheumatoid arthritis is a multifactorial disease with genetic predisposition, characterized by systemic manifestations [11]. Investigating the impact of novel coronavirus infection on RA development is particularly relevant for analyzing persistent joint syndrome in patients during the post-COVID period.

The objective of the study was to assess the impact of coronavirus infection on the development of true arthritis in patients with post-COVID joint syndrome.

Materials and Methods

A prospective cohort study was conducted involving 1,014 patients from the clinical registry of SARS-CoV-2 PCR-confirmed cases. The study evaluated rheumatologic history data from outpatient records. Laboratory tests were performed including peripheral blood parameters and immunological assays.

Inclusion criteria: PCR-confirmed SARS-CoV-2 infection, chest CT (MSCT).

Exclusion criteria: Patients with documented history of autoimmune rheumatic, hematologic, or oncologic diseases; patients with elevated acute-phase reactants according to outpatient records.

Statistical analysis was performed using StatTech v. 4.7.1 software (developer: StatTech LLC, Russia). Quantitative parameters were assessed for normal distribution using the Shapiro-Wilk test (for sample sizes < 50) or Kolmogorov-Smirnov test (for sample sizes >50). For non-normally distributed data, quantitative variables were described using median (Me) with lower and upper quartiles (Q₁–Q₃). Categorical data were presented as absolute values with percentages. 95 % confidence intervals for proportions were calculated using the Clopper-Pearson method. Between-group comparisons of non-normally distributed quantitative variables were performed using the Mann–Whitney U-test. The direction and strength of correlation between two quantitative variables were assessed using Spearman’s rank correlation coefficient (for non-normally distributed parameters). A predictive model for quantitative outcome dependence on factors was developed using linear regression. The discriminative ability of quantitative predictors was evaluated using ROC curve analysis. Optimal cut-off values were determined by Youden’s index. Statistical significance was set at p< 0.05.

Results and Discussion

According to the clinical registry of 1,014 COVID-19-confirmed patients, joint syndrome was detected in 283 cases. The median age was 45 years (36.0–55.0), with statistically significant evidence that joint syndrome development was associated with younger age (p< 0.001). Patients in this group were monitored for 9 months, with evaluation of peripheral blood and biochemical parameters. Immunological tests–rheumatoid factor (RF), anti-cyclic citrullinated peptide antibodies (ACPAs), and antinuclear factor (ANF)–were performed in both patients with joint syndrome and those without it but with confirmed COVID-19 infection who consented to additional testing. Patients with persistent joint syndrome were recommended periodic rheumatologist follow-ups every 3 months, with laboratory parameter monitoring. Gender-based distribution and immunological marker profiles were analyzed. ANF was detected in 271 patients with joint syndrome and in 125 COVID-19 patients without rheumatologic symptoms but with identical clinical and laboratory parameters. Among joint syndrome patients, 30.3 % had ANF titers >1:160, showing statistically significant evidence (p< 0.001). No statistical significance was found for other immunological markers. Over the 9-month period, RA was confirmed in 26 patients with joint syndrome. Gender distribution: 8 men (30.8 %) and 18 women (69.2 %), with no statistical significance. In patients with available immunological test results from the COVID-19 registry, statistical significance was observed in the association between RA development and RF/ACPAs (Table 1).

 

Table 1 Descriptive statistics of categorical variables by RA status

Indicator	Category	RA, n (%)		p
		Not confirmed	Confirmed
ANF	ANF-negative	193 (52.0)	16 (64.0)	0.246
	ANF-positive	178 (48.0)	9 (36.0)
RF	RF-negative	310 (90.4)	9 (36.0)	< 0.001*
	RF-positive	33 (9.6)	17 (64.0)
ACPA	ACPA-negative	332 (96.8)	14 (52.0)	< 0.001*
	ACPA-positive	11 (3.2)	12 (48.0)

 

In patients with confirmed RA during the post-COVID period among those with joint syndrome, ANF was detected in 9 individuals (36 %), while ACPA positivity was observed in 12 % (48 % of RA patients). RA was significantly more frequent in the group with positive RF and negative ACPA (p< 0.001). The odds of RF-positive RA were 16.700 times higher compared to the non-RA group, with statistically significant difference in odds (95 % CI: 6.844–40.750). For ACPA-positive patients, the risk of RA development was 27.860 times higher (95 % CI: 10.371–74.839). No statistically significant differences in ANF were found when comparing RA groups (p=0.246) (method used: Pearson’s chi-square test). Statistically significant differences were also identified in peripheral blood parameters (Table 2).

 

Table 2 Analysis of peripheral blood parameters by RA status

Parameter	Category	РА			p
		Me	Q1 – Q3	n
WBC, 10³/μL	RA not confirmed	5.5	3.5–8.7	983	< 0.001*
	RA confirmed	3.5	2.7–5.3	26
Hb, g/L	RA not confirmed	131.0	121.0–143.8	982	< 0.001*
	RA confirmed	116.0	99.5–128.0	26
RBC, 10⁶/μL	RA not confirmed	4.6	4.0–4.9	976	0.010*
	RA confirmed	4.2	3.4–4.6	26
Lymph, %	RA not confirmed	23.6	14.2–32.7	980	0.463
	RA confirmed	22.1	15.0–29.1	26
Platelets, 10³/μL	RA not confirmed	181.0	153.0–247.0	982	0.126
	RA confirmed	161.0	23.8–251.5	26
ESR, mm/h	RA not confirmed	18.0	8.0–30.0	981	< 0.001*
	RA confirmed	31.0	17.2–48.2	26

Note: * indicates statistically significant differences (p< 0.05).

 

Comparative analysis of white blood cells (WBC), hemoglobin (Hb), red blood cells (RBC), and ESR by RA status revealed statistically significant differences (p< 0.001). Alongside immunological markers, WBC levels — detectable during acute COVID-19 — may serve as predictive markers for autoimmune disease development. Elevated ESR was also identified as a predisposing factor for autoimmunity (Fig. 1, a, b).

 

Fig. 1. RA dependence: a – on WBC level; b – on ESR level; c – on D-dimer level

 

Of particular interest are the results from the analysis of biochemical parameters in COVID-19 registry patients with confirmed RA. Evaluation of AST, ALT, creatinine, and total protein by RA status revealed statistically significant differences (p< 0.001). RA patients exhibited lower AST, ALT, and total protein levels, though all values remained within reference ranges. No statistically significant associations were found for acute-phase reactants (ferritin and CRP) as potential arthritis-promoting factors. Statistically significant differences (p< 0.001) were observed in D-dimer levels by RA status (Fig. 1, c).

Patients also underwent evaluation of RA development odds depending on administered drug therapies: antiretroviral therapy (ART), interleukin-6 inhibitors (IL-6i), and antimicrobial agents. When assessing the odds, the ART group showed 1.267 times higher odds of RA compared to the non-RA group, though these odds differences were not statistically significant (95 % CI: 0.074–21.801). Similarly, no statistically significant odds differences were found in either the IL-6 inhibitor group or the antimicrobial agents group (OR = 0.763; 95 % CI: 0.260–2.239).

When assessing sex/age characteristics in the RA group, no statistically significant differences were identified (p=0.146) (method used: Pearson’s chi-square test). However, women had 1.851 times higher odds of RA development compared to the control group, though these odds differences were not statistically significant (95 % CI: 0.797–4.298).

When assessing RA development risk relative to lung involvement severity based on CT findings, no statistically significant differences were established (p=0.289) (method used: Pearson’s chi-square test).

We analyzed rheumatoid arthritis development among patients with joint syndrome following novel coronavirus infection. In the group of RA patients with a history of post-COVID joint syndrome, statistically significant differences were identified (p< 0.001) (method used: Fisher’s exact test). All 26 RA cases were confirmed in the joint syndrome group (Fig. 2). The arthralgia group showed 143.488 times higher odds of RA development, with statistically significant odds differences (95 % CI: 8.714–2362.817).

  

Fig. 2. Association between RA and joint syndrome in the post-COVID period

 

The study results incorporating laboratory, clinical, and immunological test data demonstrated that COVID-19 may trigger development of true rheumatic autoimmune disease. The obtained data show that rheumatoid arthritis risk is particularly pronounced in patients with post-COVID rheumatologic manifestations and is associated with joint syndrome developing de novo during or after coronavirus infection. Predictive factors contributing to rheumatoid arthritis development include leukocyte levels below 3.5 thousand, elevated ESR, and positivity for RA-characteristic serological markers.

Conclusions

Preventive measures aimed at early identification of at-risk patients for RA development following coronavirus infection include monitoring of laboratory parameters, immunological tests, and clinical examination findings. Further investigation of this issue is warranted due to the increasing incidence of autoimmune diseases, necessitating in-depth analysis of potential triggers such as COVID-19.

 

¹ Data from The COVID%19 Global Rheumatology Alliance Global Registry, available at: https://rheumcovid.org/updates/combined%data.html.

About the authors

A. K. Karibova

City Clinical Hospital

Author for correspondence.
Email: solomon687@gmail.com
ORCID iD: 0009-0003-3690-3041

Head of the Department of Rheumatology

Russian Federation, Makhachkala

O. V. Khlynova

Ye.A. Vagner Perm State Medical University

Email: solomon687@gmail.com
ORCID iD: 0000-0003-4860-0112

DSc (Medicine), Professor, Head of the Department of Hospital Therapy and Cardiology

Russian Federation, Perm

M. T. Kudaev

Dagestan State Medical University

Email: solomon687@gmail.com
ORCID iD: 0000-0001-5446-1775

DSc (Medicine), Professor, Head of the Department of Therapy

Russian Federation, Makhachkala

S. Sh. Akhmedkhanov

Dagestan State Medical University

Email: solomon687@gmail.com
ORCID iD: 0000-0002-8935-220X

DSc (Medicine), Professor, Head of the Department of Internal Diseases of the Pediatric and Dental Faculties

Russian Federation, Makhachkala

D. I. Mustafaev

Dagestan State Medical University

Email: solomon687@gmail.com
ORCID iD: 0009-0004-6333-3790

Resident

Russian Federation, Makhachkala

References

Supplementary files