Original Investigation

Infectious Diseases

Key Points

Question 
Is COVID-19 associated with an increased risk of autoimmune and autoinflammatory disorders?

Findings 
This cohort study including 354 527 individuals with COVID-19 and 6 134 940 controls identified a significant elevation in the risk of multiple incident autoimmune and autoinflammatory disorders subsequent to COVID-19. Notably, certain disease risks exhibited a positive association with the severity of COVID-19.

Meaning 
These findings suggest that autoimmune and autoinflammatory connective tissue disorders may manifest as post–COVID-19 sequelae, highlighting the potential long-term health ramifications associated with COVID-19; long-term management should include evaluating the development of such disorders in patients who had COVID-19.

Importance 
Multiple cases of autoimmune and autoinflammatory diseases after COVID-19 have been reported. However, their incidences and risks have rarely been quantified.

Objective 
To investigate the incidences and risks of autoimmune and autoinflammatory connective tissue disorders after COVID-19.

Design, Setting, and Participants 
This was a retrospective population-based study conducted between October 8, 2020, and December 31, 2021, that used nationwide data from the Korea Disease Control and Prevention Agency COVID-19 National Health Insurance Service cohort and included individuals who received a diagnosis of COVID-19 via polymerase chain reaction testing and a control group with no evidence of COVID-19 identified from National Health Insurance Service of Korea cohort. Data analysis was conducted from September 2022 to August 2023.

Exposures 
Receipt of diagnosis of COVID-19.

Main Outcomes and Measures 
The primary outcomes were the incidence and risk of autoimmune and autoinflammatory connective tissue disorders following COVID-19. A total of 32 covariates, including demographics, socioeconomic statuses, lifestyle factors, and comorbidity profiles, were balanced through inverse probability weighting. The incidences and risks of autoimmune and autoinflammatory connective tissue disorders were compared between the groups using multivariable Cox proportional hazard analyses.

Results 
A total of 354 527 individuals with COVID-19 (mean [SD] age, 52.24 [15.55] years; 179 041 women [50.50%]) and 6 134 940 controls (mean [SD] age, 52.05 [15.63] years; 3 074 573 women [50.12%]) were included. The risks of alopecia areata (adjusted hazard ratio [aHR], 1.12; 95% CI, 1.05-1.19), alopecia totalis (aHR, 1.74; 95% CI, 1.39-2.17), antineutrophil cytoplasmic antibody–associated vasculitis (aHR, 2.76; 95% CI, 1.64-4.65), Crohn disease (aHR, 1.68; 95% CI, 1.31-2.15), and sarcoidosis (aHR, 1.59; 95% CI, 1.00-2.52) were higher in the COVID-19 group. The risks of alopecia totalis, psoriasis, vitiligo, vasculitis, Crohn disease, ulcerative colitis, rheumatoid arthritis, adult-onset Still disease, Sjögren syndrome, ankylosing spondylitis, and sarcoidosis were associated with the severity of COVID-19.

Conclusions and Relevance 
In this retrospective cohort study, COVID-19 was associated with a substantial risk for autoimmune and autoinflammatory connective tissue disorders, indicating that long-term management of patients with COVID-19 should include evaluation for such disorders.

COVID-19 is widespread, and its association with various other diseases have been reported.^1–6 Possible associations of COVID-19 with autoimmune diseases also have been suggested,⁷ because SARS-CoV-2 appears to perturb self-tolerance and trigger autoimmune reactions via cross-reactivity that may lead to the development of autoimmune diseases.⁶ A growing body of literature^7–9 has reported various disease cases—including alopecia areata, vitiligo, systemic lupus erythematosus (SLE), vasculitis, and pediatric inflammatory multisystemic syndrome—that involve immunologic responses following SARS-CoV-2 infection, suggesting the potential existence of underlying immune dysregulations in individuals with COVID-19.

Due to the potential involvement of SARS-CoV-2 infection in cardiopulmonary failure, with its severity being a crucial factor for patients’ overall mortality, extensive evaluation of cardiovascular and respiratory outcomes following COVID-19 infection has been conducted.^2,10 Although similarities between COVID-19 and several autoimmune diseases have been suggested,⁶ a comprehensive evaluation of autoimmune or inflammatory diseases as postacute COVID-19 sequelae has not yet been established. Thus, this nationwide, population-based study aimed to estimate the incidence and risk of various autoimmune and autoinflammatory connective tissue disorders following COVID-19.

This cohort study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline and was approved by the Korean National Institute for Bioethics Policy with a waiver of informed consent due to the use of deidentified data. We used nationwide, population-based data from the Korea Disease Control and Prevention Agency (KDCA) COVID-19 National Health Insurance Service (NHIS) registry. The NHIS COVID-19 registry is managed by the Korean government and collates information regarding the date of diagnosis, route of infection, and mortality outcomes of individuals with confirmed COVID-19. Korea has a single health care insurance system (NHIS) that covers more than 99% of the entire Korean population and provides comprehensive information regarding socioeconomic status, inpatient and outpatient care, diagnoses of disease, procedures, and prescriptions of the enrolled patients.¹¹

Because Korea was 1 of the last countries to exhibit the nationwide spread of COVID-19, the number of confirmed COVID-19 cases before October 2020 was very small (24 352 cases [0.047%] estimated on the basis of the total population of Korea in 2020).^12,13 Owing to the data anonymization policy established by the Korean government, our database excluded the information collected on or before October 7, 2020. Among the 581 500 individuals who received a confirmed COVID-19 diagnosis between October 8, 2020, and December 31, 2021, we extracted the data of only those who underwent a general health examination for further covariate control (354 886 individuals). The general health examination is provided by the Korean government annually or biannually to all employees, householders, and citizens aged 40 years or older.^14,15 It includes health assessments such as blood and urine tests, anthropometric measurements, and also gathers information about an individual’s lifestyle and behavior through structured questionnaires.¹⁵ Finally, individuals who had tested positive for COVID-19 via polymerase chain reaction testing and were alive at the date of diagnosis were identified (Figure 1). All individuals underwent polymerase chain reaction testing at government-operated triage rooms located across various cities, including both individuals who exhibited symptoms and individuals who were asymptomatic and working or residing in high-risk environments. The date of positive COVID-19 test result served as the study index date for the COVID-19 cohort.

For comparison, we identified 9 875 232 individuals stratified by birth year and sex who had no evidence of SARS-CoV-2 infection (ie, those in the NHIS database who were not registered in the NHIS COVID-19 registry) as the primary control cohort (approximately 20% of the total Korean population) from the entire Korean population in 2020.¹³ Then, we extracted data from only those who had general health examination data (6 160 655 individuals), and those who were alive by October 8, 2020 (6 160 499 individuals). To ensure that the control group had a similar observational period as the COVID-19 group, we randomly assigned the study index date for the control participants according to the distribution of the study index date in the COVID-19 group; hence, the proportion of people enrolled on a certain date was the same in both the control and COVID-19 groups. The study population was followed up from the study index date to each disease diagnosis, emigration, death, or the end of the study period (December 31, 2021).

The incidences and risks of autoimmune and autoinflammatory connective tissue disorders were assessed during the follow-up of those without a history of such outcomes before the study index date. The occurrence of outcome diseases was defined as at least 3 medical visits with the corresponding International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnostic code. To validate our cohort and analyses, outcomes of cardiovascular diseases that were reported to be associated with COVID-19¹⁰ and outcomes less likely to be associated with COVID-19 were set as the positive and negative control outcomes, respectively, and were examined. The predefined outcomes and corresponding ICD-10 codes are summarized in eTable 1 in Supplement 1.

The demographics, socioeconomic statuses, lifestyle factors, and comorbidity profiles of the study population were obtained from the NHIS database. We set covariates that may potentially be associated with the disease outcome on the basis of previous literature and the biological plausibility of associations.^{10,14,16–18} The predefined covariates are listed in the eMethods in Supplement 1.

The propensity scores for individuals were estimated as the probability of belonging to the COVID-19 cohort on the basis of the covariates and were used to calculate the inverse probability weights, which were calculated as follows: probability of belonging to the COVID-19 cohort / (1 − the probability of being in the COVID-19 cohort). Covariate balances before and after the application of probability weights were assessed using standardized mean differences. We then estimated the risks of predefined outcomes for COVID-19 vs control cohorts. Statistical estimates were derived using the multivariable Cox proportional hazard analysis after adjusting for all covariates used for inverse probability weighting. For each analysis, individuals who had already received a diagnosis with the target outcome at the index date or before were excluded; hence, the analysis included only individuals at risk. To further investigate specific populations within both groups, we then conducted subgroup analyses according to age, sex, severity of COVID-19 (intensive care unit [ICU] care vs non-ICU care), and COVID-19 vaccination status. Viral vector vaccines (ChAdOx1, Oxford-AstraZeneca; Ad26.COV2.S, Janssen-Johnson & Johnson), mRNA vaccines (BNT162b2, Pfizer-BioNTech; mRNA-1273, Moderna), and protein subunit vaccines (NVX-CoV2373, Novavax) were supplied on a national basis. Vaccination completion was assessed according to the schedules recommended for each vaccine. All statistical analyses were performed using SAS statist