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. 2024 Dec 11;27(1):e301252. doi: 10.1136/bmjment-2024-301252

Elucidating the bidirectional association between autoimmune diseases and depression: a systematic review and meta-analysis

Yongli Li 1,2,3,1, Chengyuan Zhao 1,2,3,1, Shihua Sun 4, Guolin Mi 5, Changhong Liu 1, Guoyong Ding 3, Cheng Wang 6,*,0, Fang Tang 1,2,3,✉,0
PMCID: PMC11647340  PMID: 39663136

Abstract

Question

Collective evidence for the bidirectional association between depression and autoimmune diseases (ADs) is scarce, especially for subgroups of patients with specific ADs. We conducted a meta-analysis to determine the incidence rates and relative risks (RRs) of depression among patients with ADs, and vice versa.

Study selection and analysis

PubMed, Embase, Web of Science, Ovid, PsycNet and Cochrane were searched up to 10 September 2024. Cohort studies evaluating longitudinal risks between ADs and depression were included. Incidence rates and RRs of depression among patients with ADs and vice versa were pooled.

Findings

The analysis included 47 studies, involving over 40.77 million participants. The pooled incidence rate of depression among patients with ADs was 6.71% (95% CI 5.10% to 8.77%), with an RR of 1.85 (95% CI 1.57 to 2.19), higher in patients aged over 45 (2.30; 95% CI 1.62 to 3.26) and females (1.88; 95% CI 1.61 to 2.20). Conversely, the pooled incidence rate of ADs among depression was 0.54% (95% CI 0.24% to 1.19%), with an RR of 1.84 (95% CI 1.10 to 3.09). The incidence rate and RRs also varied across subgroups with the highest incidence rate in the musculoskeletal system and connective tissue (1.36; 95% CI 0.50 to 3.63) and RR in the genitourinary system (2.23; 95% CI 1.98 to 2.51).

Conclusions

This study identified a bidirectional association between depression and ADs, with higher RRs among patients aged over 45 and females. Especially higher risks were also found for specific types of ADs including endocrine, nutritional, and metabolic diseases, genitourinary system, and skin and subcutaneous tissue.

PROSPERO registration number

CRD42024541053.

Keywords: Depression

WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Collective evidence for the bidirectional association between depression and autoimmune diseases (ADs) is scarce, especially for subgroups of patients with specific ADs.

WHAT THIS STUDY ADDS

  • By performing a systematic review and meta-analysis of cohort studies with over 40.77 million participants, we have identified a bidirectional positive association between ADs and depression. The association varies with age, gender and types of ADs.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • The association between ADs and depression underscores the significance of informing both clinicians and patients, potentially facilitating early treatment for high-priority populations.

Introduction

Depression is a highly prevalent psychiatric disorder ranking the second among the causes of years lived with disability and serving as a leading cause of the burden of disease worldwide.1 The global incidence of depression is approximately 4333.6 per 100 000 person-years, affecting over 350 million people, of which approximately 220 million are females and 130 million are males. The incidence of depression is significantly higher in females than males.2 Autoimmune diseases (ADs) occur when the body’s immune system mistakenly attacks and destroys healthy tissue, with a notable impact on mortality and morbidity.3 4 A population-based cohort study of 22 million people in the UK found that, over the study period, the 19 ADs examined affected 10.2% of the population, with a higher incidence in females compared with males.4 A previous study has shown that depression is significantly associated with an increased risk of ADs, with patients having a history of depression exhibiting a 1.25-fold higher incidence compared with those without such a history.5 The comorbidity is associated with significantly poorer health outcomes, including longer illness duration and higher risks of suicide and self-harm, compared with individuals experiencing either depression or AD alone.5 6 In the process of diagnosis and treatment, patients with depression often receive psychiatric care, with little attention paid to their concomitant physical diseases such as ADs.7 Similarly, patients with ADs typically receive treatment in general hospitals, where assessment of their mental state may be overlooked.8 9 Therefore, this study aims to provide epidemiological evidence regarding the epidemic intensity and incidence characteristics of these diseases to enhance awareness among patients and clinicians. This will promote interdisciplinary collaboration for comprehensive treatment of these patient populations, leading to improved prognosis and reduced disease burden.

An increasing body of evidence indicates that the comorbidity association between ADs and depression is bidirectional.10,12 On one hand, the presence of ADs increases the risk of subsequent development of depression in patients. Due to the chronic and recurrent nature of ADs, patients often experience significant psychological stress, leading to the onset of depressive symptoms.13 14 Recent studies show that various ADs are risk factors for depression, including rheumatoid arthritis, inflammatory bowel disease and ankylosing spondylitis.15,17 On the other hand, depression can also increase the risk of patients developing ADs. Patients with depression often experience a significant decline in their quality of life during prolonged illness treatment,18 which may lead to immune dysregulation and subsequent inflammatory responses, potentially resulting in the development of ADs.19 Research has found that depression can exacerbate the disease activity or relapse of ADs in patients.20,22 In addition, from an etiological perspective, both ADs and depression result from the combined influence of genetic and environmental factors.18 23 The progression of both conditions is closely intertwined with the occurrence of inflammation in the body.23 24 However, the clinical epidemiological evidence remains limited.

Currently, the landscape of the bidirectional association between multiple ADs and depression is understudied, and previous studies have predominantly focused on the prevalence rate.25 These limitations restrict the identification of a comprehensive range of ADs and specific mental health disorders and they lack comparative evaluations across different populations. In this study, we conducted a comprehensive large-scale meta-analysis of bidirectional association between multiple ADs and depression and quantitatively integrated both incidence rates and relative risks (RRs). This study aims to determine the extent and direction of the risk of onset for both diseases and to identify key populations affected by both conditions. Examining the patterns and distribution of incidence trends among various subgroups facilitates a comprehensive understanding of their global occurrences. Understanding the bidirectional relationship between ADs and depression can enhance clinicians’ awareness, enabling them to provide appropriate treatment at an early stage, reduce the overall disease burden on patients, and offer guidance for preventing the secondary development of both conditions.

Methods

Search strategy

The study protocol was registered in PROSPERO (CRD42024541053) and followed the Meta-analysis of Observational Studies in Epidemiology reporting guidelines.26 We searched PubMed, Embase, Web of Science, Ovid, PsycNet and Cochrane to identify eligible studies from inception to 10 September 2024 using MeSH terms, Emtree terms and text words search strategies ‘autoimmune diseases’, ‘depression’ and ‘cohort study’ (search strategies were detailed in online supplemental table 1). In the search strategy, the search term ‘autoimmune diseases’ including 150 ADs was defined by the American Autoimmune and Related Diseases Association.27 Depression was defined by the clinical coding system (online supplemental table 2). Moreover, we examined the reference lists of the included studies to identify potentially pertinent research.

Eligibility criteria

We included cohort studies that reported risk estimates or incidence rates of any ADs or depression. Studies were excluded if the sample size was less than 1000. If a study included any overlapping participants, we only used the one with the larger sample size. Studies that were not written in English or Chinese were also excluded, as the researchers were proficient in these two languages. Full details are provided in figure 1.

Figure 1. Flow chart of the literature search and research selection process.

Figure 1

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Data extraction and quality evaluation

The data pertaining to the characteristics of the studies were extracted as follows: the first author, year of publication, region/country, source of participants, follow-up duration, sample size, mean or median age of sample, participant sex, overall incidence rate of depression and AD, means of diagnosis and assessment, baseline study years, outcome diagnosis and matching factors between the control group and the non-control group. The quality of included studies was ascertained with the Newcastle-Ottawa Quality Assessment Scale (NOS).28 This assessment allowed a total score of up to 9 points. Studies of low quality (NOS<4) were excluded from the meta-analysis. Two researchers (YL and CZ) independently conducted study selection, data extraction and quality assessment. Disagreements were resolved through negotiation between the two authors (YL and CZ) or consultation with a third researcher (FT).

Data analysis

The main analysis involved two parts: (1) assessing the incidence rate and RR of depression in patients with AD, and (2) evaluating the incidence rate and RR of AD in patients with depression. Heterogeneity within datasets was evaluated using Cochran’s Q test and the I2 statistic.29 30 Incidence rates were estimated using a logit transformation, while the DerSimonian and Laird method was used for RR estimation. We conducted subgroup and meta-regression analyses to explore heterogeneity.31 Subgroup analysis was stratified by age, gender, type of ADs and study outcome. Meta-regressions were employed to assess the impact of various factors such as region, diagnostic criteria, sample size, matching and publication year on effect measures. Leave-one-out sensitivity analyses were performed to examine individual study influence.32 Publication bias was examined with funnel plots, Egger’s test, Begg’s test and trim-and-fill method.33 34 R V.4.3.1 (R Core Team) and Stata V.16.0 (StataCorp) were used for the analysis.

Results

Search selection and characteristics

The systematic publication search yielded 48 720 results, excluding duplicate records. Subsequently, after screening and excluding 48 484 records based on title and abstract, we assessed the full text of 236 articles, and none additional articles from hand-searching. 53 cohorts from 47 publications met all inclusion criteria, encompassing 40.77 million participants (figure 1). These cohorts consist of 41 depression events and 12 AD events. The diagnosis in 44 cohorts was conducted using International Classification of Diseases criteria, and nine cohorts used other diagnostic criteria. The quality of the included studies was generally good, with NOS scores ranging from 7 to 9 (online supplemental table 3). Characteristics of all included cohort studies were presented in online supplemental table 2.

Incidence and risk of depression following ADs

We performed the meta-analysis to investigate the incidence rate and risk of depression among population with ADs. The analysis resulted in a pooled incidence rate of 6.71% (95% CI 5.10% to 8.77%) (figure 2A). For four cohorts that investigated the incidence density of depression, the pooled incidence was 18.3 cases per 1000 person-years (online supplemental figure 1). Moreover, the RR for depression among patients with ADs was 1.85 (95% CI 1.57 to 2.19) (figure 2B), showing that ADs were associated with a significantly increased risk of depression incidence. In the subgroup analysis (figure 3), age was a key risk factor for the incidence of depression following ADs. There was a notable increase in the incidence of depression among individuals aged 45 years (11.48%; 95% CI 7.58% to 17.03%), and the RR (2.30; 95% CI 1.62 to 3.26) also demonstrated a positive association (online supplemental figures 2 and 3). For females, the incidence rate of depression was 7.16% (95% CI 3.31% to 14.83%) and an RR of 1.88 (95% CI 1.61 to 2.20). For males, the analysis revealed an incidence rate of 4.61% (95% CI 1.97% to 10.37%) and an RR of 2.28 (95% CI 1.84 to 2.82) (online supplemental figures 4 and 5). There was no significant difference observed in the risk of depression between females and males. We characterised the impact of six classes of ADs on the incidence rates and RRs of depression (online supplemental figures 6 and 7). Specifically, two classes of ADs demonstrated higher incidence rates and RRs compared with the pooled values. For the nervous system, the incidence rate was 10.66% (95% CI 2.99% to 31.58%), with an RR of 2.12 (95% CI 1.51 to 2.97). For the musculoskeletal system and connective tissue, the incidence rate was 9.06% (95% CI 5.14% to 15.48%), and the RR was 2.23 (95% CI 1.51 to 3.29). However, despite the relatively low incidence rate, endocrine, nutritional and metabolic diseases exhibit a high RR (2.88; 95% CI 1.31 to 6.31), warranting further attention and investigation. Additionally, we conducted a subgroup analysis of the incidence rates and RRs of depression across different age groups for each type of ADs (online supplemental figures 8–17). The analysis revealed that the subgroup aged over 45 exhibited higher incidence rates of depression in the endocrine, nutritional and metabolic diseases and the musculoskeletal system and connective tissue, with a higher RR in the genitourinary system (test for subgroup differences: p<0.05).

Figure 2. The forest map of depression. (A) Forest plot assessing the incidence of depression in patients with autoimmune diseases. (B) Forest plot assessing the relative risk of depression for patients with autoimmune diseases compared with those without autoimmune diseases.

Figure 2

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Figure 3. Subgroup analysis assessing the depression. aSubgroup analysis assessing the incidence of depression in patients with autoimmune diseases (AD) in percentage terms (studies are grouped according to age, gender, type of ADs). bSubgroup analysis assessing the relative risk of depression for patients with ADs compared with those without ADs (studies are grouped according to age, gender, type of ADs). ☆The difference test of incidence rate of depression between subgroups, p<0.05 considered statistically significant. Types of AD subgroup containing ADs are detailed in online supplemental table 9.

Figure 3

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Incidence and risk of ADs following depression

We performed the meta-analysis to investigate the incidence rate and risk of ADs among populations with depression. The analysis yielded a pooled incidence rate of AD of 0.54% (95% CI 0.24% to 1.19%) (figure 4A). The RR for ADs among patients with depression was 1.84 (95% CI 1.10 to 3.09), indicating an association between depression and an increased incidence of ADs (figure 4B). Additionally, in one cohort study examining the incidence density of psoriasis among patients with depression, the incidence rate of psoriasis was found to be 2.98 per 1000 person-years.35 In the subgroup analysis (figure 5), the incidence rate for the age group over 45 years was 0.77% (95% CI 0.18% to 3.22%) (online supplemental figure 18), and the RR was 1.63 (95% CI 1.12 to 2.37) (online supplemental figure 19). Furthermore, the incidence rate among females was 1.30% (95% CI 0.78% to 2.17%), and the incidence rate among males was 0.78% (95% CI 0.49% to 1.24%) (online supplemental figure 20). Increased risks of ADs following depression were observed for both males and females, but they were not statistically significant (online supplemental figure 21). In addition, subgroup analysis for study outcomes indicated that the musculoskeletal system and connective tissue had the highest incidence of ADs at 1.36% (95% CI 0.50% to 3.63%), while the genitourinary system had the highest RR (2.23; 95% CI 1.98 to 2.51) (online supplemental figures 22 and 23).

Figure 4. The forest map of autoimmune diseases. (A) Forest plot assessing the incidence of autoimmune diseases in patients with depression. (B) Forest plot assessing the relative risk of autoimmune diseases for patients with depression compared with those without depression.

Figure 4

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Figure 5. Subgroup analysis assessing the autoimmune diseases (AD). aSubgroup analysis assessing the incidence of ADs in patients with depression in percentage terms (studies are grouped according to age, gender, study outcome). bSubgroup analysis assessing the relative risk of ADs for patients with depression compared with those without depression (studies are grouped according to age, gender, study outcome). ☆The difference test of incidence rate of ADs between subgroups, p<0.05 considered statistically significant. △The difference test of relative risk of ADs between subgroups, p<0.05 considered statistically significant. Study outcome subgroups containing ADs are detailed in online supplemental table 9.

Figure 5

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Sensitivity analysis, publication bias and meta-regression

No outliers were identified in the sensitivity analyses (online supplemental figures 24–26), with the exception of one study in sensitivity analysis of the RR of ADs for patients with depression (online supplemental figure 27). Overall, the results from sensitivity analyses affirmed the robustness of the findings. Concerning the RRs, no significant publication bias was detected using Begg’s test, Egger’s test or the funnel plot (online supplemental figures 28 and 29). Regarding the incidence rate of ADs in patients with depression, no significant publication bias was evident using Begg’s test or the funnel plot (online supplemental figure 30). Despite conflicting results from Egger’s test regarding the incidence rate of depression among patients with ADs, trim-and-fill analysis identified 14 missing studies (online supplemental figure 31), yielding an overall effect estimate of 0.12 (95% CI 0.09 to 0.16) with statistical significance maintained before and after trimming (p=0.00). There is no evidence suggesting that the variables included in the meta-regression and subsequent subgroup analysis have an impact on the pooled incidence rate and RR (online supplemental tables 4–8). Notably, subgroup analysis of the RR among patients with depression and ADs showed an improvement in heterogeneity within subgroups based on study outcome, suggesting that study outcome might be a source of high heterogeneity (online supplemental figure 23).

Discussion

This systematic review and meta-analysis elucidated the bidirectional risk between ADs and depression by including 53 cohorts based on 47 articles. After analysing the pooled incidence rate and pooled RR, we found that the risk of depression increases following ADs, and vice versa, suggesting a bidirectional positive association between ADs and depression. By subgroup analysis for the risk of depression among populations with ADs, we observed a higher incidence rate in aged over 45 group, indicating that middle-aged and elderly individuals may constitute a potential at-risk population. There was a discrepancy regarding the risk of depression between females and males, but the RR values indicated an increased risk of depression in both male and female patients with ADs. This may stem from the inherently higher risk of depression in females, nearly twice that of males,18 or it may be attributed to males’ under-recognition of chronic symptoms such as depression and pain.36 Additionally, sex hormones may influence the incidence of both ADs and depression by affecting inflammatory responses.37 Concerning the types of ADs, although the incidence rate of depression was lower in the endocrine, nutritional and metabolic ADs, they exhibited the highest RR. As for the risk of ADs in patients with depression, the risk of developing ADs increased in age groups older than 45 years. Regarding study outcome, depression appears more likely to lead to ADs involving the genitourinary system.

The comorbidity relationship between depression and ADs plays a pivotal role in elucidating the mechanisms underlying the overlap of depression and ADs. Both ADs and depression are closely associated with inflammatory processes,38 39 suggesting inflammatory responses could be a potential factor influencing both ADs and depression. Elevated proinflammatory cytokines such as tumour necrosis factor-alpha and interleukin-6 influence brain function through various pathways, as seen in ADs like multiple sclerosis and Graves’ disease.40,42 Inflammation may also activate the hypothalamic-pituitary-adrenal axis, increasing corticosteroid production and contributing to depression risk.43 44 Additionally, reduced brain-derived neurotrophic factor levels and impaired neuroplasticity, driven by neuroinflammation in conditions like fibromyalgia, exacerbate symptoms in both ADs and depression, highlighting a common pathophysiological link.4345,47

Patients with ADs who also have comorbid depression may experience reduced medication adherence, thereby affecting the treatment and prognosis of ADs.48 Additionally, depression, as a stress response, can trigger or exacerbate symptoms of physical illnesses.18 In terms of disease treatment, research suggests that patients with a history of depression are more likely to be diagnosed with ADs, such as inflammatory bowel disease.16 However, during depression treatment, antidepressant therapy has been shown to exert a selectively protective effect on Crohn’s disease and ulcerative colitis.13 Conversely, studies indicate a positive correlation between the administration of certain anti-inflammatory drugs used for AD treatment and the alleviation of depressive symptoms.13 The evidence underscores the connection between the two diseases, suggesting that early treatment of depression may reduce the risk of ADs and vice versa.

Our results offer various significant implications for both clinicians and patients. Clinical experience suggests that the majority of patients seek psychiatric intervention primarily for depressive disorders, often overlooking the occurrence and progression of their comorbid ADs, a trend also mirrored in clinical treatment approaches.7 Patients with ADs typically receive care solely within corresponding medical specialties, leading to an oversight of changes in their mental state by both clinicians and patients.8 9 Our study reveals a bidirectional association between these conditions, and given the typically chronic and progressive nature of depressive states and most ADs,18 49 it demonstrates that the concurrent occurrence of one disease during the treatment of the other significantly exacerbates the burden on patients and complicates therapeutic interventions.6 However, due to the substantial population prevalence of both conditions, large-scale comprehensive screening may not be practical. Therefore, it is imperative for clinicians and patients alike to heighten their awareness. Patients with ADs should recognise their susceptibility to depressive disorders and promptly seek relevant psychiatric interventions. Clinicians should remain vigilant for changes in patients’ mental health during treatment and adopt a multidisciplinary approach to care. This holds true for patients with depression as well. Patients with depression can benefit from an integrated care approach, where regular health monitoring can lead to earlier detection of comorbidities such as ADs. This allows for timely interventions, improving overall outcomes and preventing the worsening of their mental and physical conditions. This emphasis is particularly crucial for key populations identified in our research, such as the aged over 45 population, females, and those with ADs of endocrine, nutritional, and metabolic diseases, genitourinary system, and skin and subcutaneous tissue. Early identification and effective management can contribute to reducing the incidence of comorbid ADs and depression.

Strengths and limitations

This meta-analysis included a substantial number of cohort studies on depression and ADs, encompassing a comprehensive search of 150 types of ADs and involving a considerable number of participants. The inclusion of diverse cohorts across countries further allowed the identification of global trends, making the findings more robust. We conducted subgroup analysis on the type of ADs and study outcome, enabling the identification of specific populations requiring attention, such as individuals aged over 45, females and patients with ADs of the nervous system.

There were several limitations in the study. Although we explored publication bias, the incidence rate of depression among patients with ADs remained statistically significant before and after the trim-and-fill method, leading us to maintain our belief in a positive association between depression and ADs, and further research is needed to validate our findings. Second, despite exploring sources of heterogeneity through subgroup analysis and meta-regression, heterogeneity remains high. Heterogeneity improved in the subgroup analysis by study outcome, necessitating further research for exploration.

Conclusions

This meta-analysis identified a bidirectional association between depression and ADs, with the RRs being higher among aged over 45 groups and females. Especially higher risks were also found for specific types of ADs including endocrine, nutritional, and metabolic diseases, genitourinary system, and skin and subcutaneous tissue. More attention is justified for groups of patients with the highest risks in clinical management of depression and ADs for early detection and treatment. Increasing awareness among patients and clinicians can mitigate the secondary occurrence and adverse outcomes of ADs and depression. Further research is also needed to explore the underlying aetiology of this bidirectional association.

supplementary material

online supplemental file 1
bmjment-27-1-s001.pdf (1.4MB, pdf)
DOI: 10.1136/bmjment-2024-301252

Acknowledgements

The authors thank the researchers who provided their priceless data for this meta-analysis.

Footnotes

Funding: Preparation of this manuscript was supported by grants from the Natural Science Foundation of Shandong Province (ZR2023MG005 to FT, ZR2022QB152 to CW); the National Key Research and Development Program of China (2021ZD0201808 to CW); the National Natural Science Foundation of China (82304247 to CW); the Young Scholars Program of Shandong University (21320082164070 to CW); and the Science and Technology Plan Project of Jinan (202328057 to FT).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Ethics approval: Not applicable.

Data availability free text: Data are available upon reasonable request. Data extraction files from papers are available on request to the corresponding author.

Contributor Information

Yongli Li, Email: Liyongli0310@163.com.

Chengyuan Zhao, Email: a13336296368@126.com.

Shihua Sun, Email: Shihua.Sun@ki.se.

Guolin Mi, Email: dmilinlin@163.com.

Changhong Liu, Email: liuchanghong@sdhospital.com.cn.

Guoyong Ding, Email: gyding@sdfmu.edu.cn.

Cheng Wang, Email: chengwang@sdu.edu.cn.

Fang Tang, Email: tangfangsdu@gmail.com.

Data availability statement

Data are available upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

online supplemental file 1
bmjment-27-1-s001.pdf (1.4MB, pdf)
DOI: 10.1136/bmjment-2024-301252

Data Availability Statement

Data are available upon reasonable request.

Articles from BMJ Mental Health are provided here courtesy of BMJ Publishing Group

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