https://orcid.org/0009-0007-5573-0958
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide. While most infected individuals who survive do so with no long-term consequences, approximately 10 to 70% develop long-term sequelae. Of particular concern has been the development of autoimmune diseases. Viral triggers for autoimmune disease have been thoroughly studied for previous viral infections and several recent studies have sought to investigate the link between SARS-CoV-2 and new onset autoimmune disease. Several reviews have also been conducted on the topic, however, many of these reviews are limited in focus, emphasizing biological mechanisms and case reports, as opposed to estimates of risk. Further, these reviews do not capture more recent cohort studies that have been published investigating the association between SARS-CoV-2 and new onset autoimmune disease. Therefore, there is a need for a more comprehensive and temporally updated systematically conducted review of the literature to address the question What is the risk of incident (i.e., new onset) autoimmune disease following a SARS-CoV-2 infection among adults (≥18 years)?. A systematic search of MEDLINE, EMBASE, CINAHL, and grey literature will be conducted, with results screened in duplicate in two stages: 1) Title and abstract screening and 2) Full text screening. A standardized data extraction sheet will be used on any studies passing through both stages of screening to extract details on publication, study population, exposure, and outcomes. Narrative and tabular synthesis of overall findings will be conducted, with diversity and heterogeneity of included studies discussed. If possible, a meta-analysis will also be conducted to combine findings of risk across the included studies. This protocol has been registered to PROSPERO (registration number: CRD42024594446).
Citation: Grima AA, Hiraki LT, Bolotin S, Paterson AD, Brooks JD (2025) New onset autoimmune disease following a SARS-CoV-2 infection: A systematic review protocol. PLoS One 20(10): e0335766. https://doi.org/10.1371/journal.pone.0335766
Editor: Jan René Nkeck, University of Yaounde I Faculty of Medicine and Biomedical Sciences: Universite de Yaounde I Faculte de Medecine et des Sciences Biomedicales, CAMEROON
Received: May 2, 2025; Accepted: October 15, 2025; Published: October 30, 2025
Copyright: © 2025 Grima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: No datasets were generated or analysed during the current study. All relevant data from this study will be made available upon study completion.
Funding: AAG has received funding from the Canadian Institutes of Health Research (https://cihr-irsc.gc.ca/e/193.html) (FRN: 193341) and is also supported by Canadian Statistical Sciences Institute (CANSSI) Strategic Training for Advanced Genetic Epidemiology (STAGE) (https://canssiontario.utoronto.ca/opportunities/trainingprograms/canssi-ontario-stage-training-program/) PhD trainee research funding. The funders had no part in this protocol and will have no part in the systematic review.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: LTH is a Canada Research Chair in Genetics of Rare Systemic Inflammatory Diseases, a Chair of the American College of Rheumatology (ACR) Committee on Research, a Board Member of the Rheumatology Research Foundation, and a Consultant for J&J.
Introduction
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide, causing over 770 million reported cases of coronavirus disease 2019 (COVID-19) and over 7 million reported deaths to date [1], although these numbers may represent a large underestimate of the true burden of the pandemic [2–4]. In Canada there have been over 4.7 million confirmed cases and over 50 thousand confirmed deaths to date [1]. While the majority of infected individuals who survive do so with no long-term consequences, approximately 10–70% develop long-term sequelae [5,6]. Of particular concern has been the development of autoimmune diseases following a SARS-CoV-2 infection.
In general, autoimmune diseases arise when the body does not recognize its own cells and tissues resulting in an immune response against itself [7]. This ultimately leads to damage in the targeted tissue. Autoimmune diseases are not specific to one area of the body, instead this self-directed immune response can occur in any number of organ systems, and as such, there are many different autoimmune disease types [7]. For example, rheumatoid arthritis is an inflammatory autoimmune disease which leads to destruction of the diarthrodial joints [8]. Type 1 diabetes however, results from a self-targeted immune response destroying pancreatic B-cells [8].
Studies have uncovered complex underlying causes of autoimmune diseases, including genetic predispositions (often a combination of several genes) and environmental factors (including chemical exposure, diet, and viral infections) [9,10]. Viral triggers for autoimmune disease, in particular, have been thoroughly studied with numerous examples documented [11–13] and three mechanisms for this phenomenon proposed [10,14].
Several recent studies have sought to investigate the link between SARS-CoV-2 and new onset autoimmune disease [15–18]. The authors of one such study were able to conduct a large retrospective cohort study utilizing global COVID-19 data [15]. They looked at new diagnoses of various autoimmune conditions among those with and without a history of COVID-19 infection. Associated risks of the majority of conditions they investigated were higher among those who had a history of a COVID-19 infection compared to those who did not, including the risks of rheumatoid arthritis, systemic lupus erythematosus, and psoriasis [15].
Several reviews have also been conducted on new onset autoimmune disease following SARS-CoV-2 infection [19–23]. Many of these reviews however are limited in focus, emphasizing biological mechanisms and case reports, as opposed to estimates of risk. For example, the review by Liu et al. is mainly mechanistic with some cases of autoimmune disease [19]. Alternatively, these reviews focus on specific autoimmune disease subtypes rather than autoimmune disease as a whole. For example, Gracia-Ramos et al. presented findings on new onset rheumatic autoimmune diseases [22] and Nabizadeh et al. on autoimmune encephalitis [20]. Further, these reviews do not capture more recent cohort studies that have been published investigating the association between SARS-CoV-2 and new onset autoimmune disease, such as those by Chang et al., Lim et al., Peng et al., Tesch et al., and Hileman et al. [15–18,24]. Therefore, there is a need for a more comprehensive and temporally updated systematically conducted review of the literature.
The objective of this systematic review is to answer the question: What is the risk of incident (i.e., new onset) autoimmune disease following a SARS-CoV-2 infection among adults (≥18 years)? Additionally, this review will evaluate the quality of this evidence.
Methods
The Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) 2015 checklist was used to guide the development of this protocol (Table in S1 Table).
Eligibility criteria
As per Joanna Briggs Institute guidance for risk/etiology reviews, the Population, Exposure, and Outcome, or PEO, framework will be used as the basis of determining study inclusion criteria for this review [25,26].
Population
The population for this review will be any individuals 18 years of age or older (i.e., adults). Individuals are not required to have a particular condition as the review will be focused on new onset autoimmune disease. Studies focusing solely on a pediatric population will be excluded from this review. The reasoning for this is that pediatrics are a distinct patient population, with autoimmune diseases being rarer in children [27]. The clinical course of an autoimmune disease may also differ between children and adults [28]. If a potential study for inclusion includes both children and adults, the study would only be included if it provides age stratified risk estimates.
Exposure
The exposure for this review will be SARS-CoV-2 infection. Studies which do not have SARS-CoV-2 infection as the exposure will be excluded from this review. Any type of reported SARS-CoV-2 infection (i.e., self-report, polymerase chain reaction confirmed, positive antigen test, etc.) will be acceptable for the exposure. The reason for no test type restriction is that different testing methods were available at different points of the pandemic and availability of testing types also may have varied by place of residence (e.g., province/state, country, etc.). Thus, studies conducted in different regions or countries may have captured a positive test in a different way. This should allow our review to provide a more comprehensive overview of the literature, and test types will be noted in the narrative synthesis.
Outcome
To be eligible for inclusion a study must report new onset autoimmune disease as its outcome. A list of autoimmune diseases was compiled from outcomes used in several recent cohort studies on the topic and reviewed by a rheumatologist (LTH) (Table in S2 Table). This list formed the basis of the search strategy, but any new onset autoimmune disease will be included in the review.
For a study to be relevant to this review and thus included, the outcome must occur following a SARS-CoV-2 infection. For example, if a study reported on autoimmune disease presentations of the infection itself, then the study would not be included in this review. If a different study reported on disease flare ups in rheumatoid arthritis patients following a SARS-CoV-2 infection, then this study would also not be included as it focuses on prevalent autoimmune disease. However, if a study reported on incident multiple sclerosis in individuals who have a history of SARS-CoV-2 infection then this study would be included. Both composite (i.e., overall autoimmune disease risk) and disease-specific outcomes are of interest for this review.
Study timeline
Eligible studies will be restricted to publishing dates between December 2019 and present. This is to ensure capture of only studies related to the current COVID-19 pandemic and thus SARS-CoV-2 infections.
Study design
The focus of this review is on autoimmune disease risk, as such case-reports, commentaries, and editorials will be excluded as these are not study designs which evaluate risk. Reviews will also be excluded but those relevant to the research question will be flagged for reference review.
Language
No exclusions will be made on the basic of language. Non-English language studies will be translated to English and subsequently screened at the full text screening stage.
Information sources
A literature search of MEDLINE, EMBASE, and CINAHL will be conducted. Grey Literature will also be searched using Canada’s Drug Agency Grey Matters resource [29]. Lastly, studies that were included in relevant reviews on the topic will also be screened to ensure no studies were missed by our search. As discussed above in Eligibility Criteria, the search will be restricted to December 2019 to present.
Search strategy
The search included subject headings and keywords for SARS-CoV-2, post-COVID conditions and long COVID, and autoimmune diseases. Search terms for SARS-CoV-2 were based on search strings from Research Information Specialists at Canada’s Drug Agency [30], and search terms for long COVID were based on filters from the Geoffrey & Robyn Sperber Health Sciences Library, University of Alberta [31]. Search strategies for excluding animal studies were obtained from publicly available systematic review resources [32,33]. Lastly, search terms for autoimmune disease were based on a review by Coriddi et al. [34].
The full search strategies are available in the S3-S5 Files. There are many cases where antiquated, non-standard, exclusionary, and potentially offensive terms for the COVID-19 pandemic have been used in past and present literature [35]. In light of this, the authors have included such terms in the search strategies in order to conduct a sensitive, comprehensive search for relevant studies. The authors of this review recognize and acknowledge the inappropriate and harmful nature of these terms, and indicate that the full search strategies include them, so that the reader can determine how they would like to proceed [35].
Study records
Data management.
Records identified through the literature search will be uploaded to Covidence, an online systematic review tool. Study records can be screened by multiple users within Covidence’s platform. Data extraction is also possible through Covidence. Screening pilots to ensure agreement between reviewers and data extraction will occur using Microsoft Excel.
Selection process.
All articles captured by the search will be screened in two stages: 1) Title and abstract screening and 2) Full text screening. Titles and abstracts will be screened by two independent reviewers, with any disagreements resolved through discussion or a third screener. Pilots in batches of 50 articles will be used to ensure agreement between reviewers reaches ≥75% prior to the start of formal screening. Articles that proceed to the full text screening stage will also be subject to screening by two independent reviewers and pilots will also be used to ensure reviewer agreement reaches ≥75%. Reasons for exclusion at the full text stage will be recorded for any excluded articles. A Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagram will be created to summarize the study selection process [36]. Screening of articles is currently in progress and the below proposed analysis is anticipated to be completed by the end of 2025, with manuscript submission in the beginning of 2026.
Data collection process.
A standardized data extraction sheet will be developed and used for all articles passing through the second stage of article screening. Data extraction will either be conducted by two independent reviewers with discussion or a third reviewer to resolve conflicts, or by one reviewer followed by validation by a second independent reviewer. If more than one article presents the same study data, data from the most up to date article will be selected as the primary record and missing data supplemented from the other study record. Outcome measures will be extracted as presented in the source text (i.e., risk ratio, hazard ratio, rate, etc.).
Data items
The data to be extracted from included studies will include:
- Publication details (e.g., publication year, etc.)
- Study details (e.g., study design, sample size, funding, etc.)
- Study population (e.g., age, race and ethnicity, etc.)
- Exposure details (e.g., type of test, infection severity, etc.)
- Outcomes (e.g., autoimmune disease types and counts, risk/measures of association, etc.) [37,38]
Risk of bias in individual studies
All included articles will undergo critical appraisal at the study level by two independent reviewers, with any disagreements resolved through discussion or a third reviewer [37]. This critical appraisal will include an assessment of internal validity and risk of bias. Joanna Briggs Institute critical appraisal checklists appropriate to study design will be utilized to ensure the same standards are applied to each article [37]. Data synthesis will include a summary of the quality of evidence for new onset autoimmune diseases post SARS-CoV-2 infection.
Data synthesis
Narrative and tabular synthesis of the data extracted from included studies will be conducted for this systematic review [26,37]. These will include synthesis of study characteristics, quality, and overall findings of the included studies. The clinical diversity (i.e., participants, outcomes, etc.) and methodological diversity (i.e., study design, outcome measurement, risk of bias, etc.) will be discussed [39]. Statistical heterogeneity of included studies will also be assessed using the Cochrane Q statistic (P < 0.10) and the I2 statistic with standard thresholds [38,39].
If possible (sufficient number of studies, reported measures of association, acceptable heterogeneity), a meta-analysis will be conducted to combine findings across the included studies [26,37]. A meta-analysis would be conducted for composite risk, disease-specific risk, or both.
Studies will be restricted to only those with test negative controls for a sensitivity analysis. A second sensitivity analysis will exclude all studies utilizing only rapid antigen tests from the analysis.
Meta-bias(es)
A funnel plot will be produced, and asymmetry evaluated in order to investigate the potential for small-study effects [40].
Confidence in cumulative evidence
In addition to evaluating the risk of bias for individual study outcomes (as described in Risk of bias in individual studies), the overall quality of the evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation framework [41].
Discussion
If any amendments to this protocol are required, changes will be noted on PROSPERO (registration number: CRD42024594446).
Supporting information
S1 Table. PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 checklist: recommended items to address in a systematic review protocol*.
https://doi.org/10.1371/journal.pone.0335766.s001
(DOCX)
S2 Table. Autoimmune disease outcomes and their respective International Classification of Diseases (ICD) −10 code(s).
https://doi.org/10.1371/journal.pone.0335766.s002
(DOCX)
Acknowledgments
Eden A. Kinzel (University of Toronto Librarian) for providing an initial search strategy consultation.
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