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Review Article

Autoimmune Diseases Co-occurring Within Individuals and Within Families: A Systematic Review

Somers, Emily C.*†; Thomas, Sara L.*; Smeeth, Liam; Hall, Andrew J.*

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doi: 10.1097/01.ede.0000193605.93416.df
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Abstract

Autoimmune diseases include a diverse group of chronic disorders associated with substantial public health impact.1 Anecdotal evidence suggests that autoimmune diseases tend to coexist both within individuals and within families, and the concept of an autoimmune diathesis is widely accepted. However, the patterns of association among autoimmune diseases have not been evaluated in a systematic fashion, and it is unclear whether clinical reports of comorbid autoimmune diseases represent chance findings or true associations.

Animal models demonstrate a clear association between different types of autoimmune disorders. For example, nonobese diabetic mice frequently develop thyroiditis and sialoadenitis in addition to autoimmune insulin-dependent diabetes.2 These mice crossed with KRN mice (a T-cell receptor transgenic line) develop a disease, closely resembling human rheumatoid arthritis.3 SJL mice (a model of experimental autoimmune encephalomyelitis) are highly susceptible to a number of experimentally induced autoimmune diseases.4 Although genetic background is important, exogenous factors (such as level of microbial exposure or xenobiotics) can modulate the development of disease in autoimmune-prone animal models.5–7

Common features in the immunoepidemiology of various autoimmune diseases are recognized, and reports of shared risk factors are emerging.8–10 However, the etiologies of most autoimmune diseases remain poorly understood. Because autoimmune diseases are conventionally treated by separate medical specialties according to type of organ involvement, there are missed opportunities to study these diseases as a group. We are interested in the premise that interaction between genetic background and early life programming due to environmental exposures may result in general susceptibility to autoimmune disease. Characterization of the extent to which particular combinations of autoimmune diseases occur in excess of that expected by chance may offer insight into shared pathophysiological mechanisms.

We undertook a systematic literature review to quantify the coexistence of selected autoimmune diseases within individuals and families. We reviewed the associations among 4 autoimmune diseases: insulin-dependent diabetes mellitus (IDDM), autoimmune (Hashimoto) thyroiditis (AIT), rheumatoid arthritis (RA), and multiple sclerosis (MS). We chose to focus on these diseases for several reasons. Evidence of associations between these diseases in animal models imparts plausibility for their coexistence in humans. Moreover, these diseases are sufficiently common, in contrast to many other autoimmune diseases, to provide a reasonable expectation of detecting them in combination.

A further consideration is that these disorders are widely considered to be TH1-associated. Mosmann et al11 described 2 functional subsets of T-helper cells in mice, TH1 and TH2, characterized by different patterns of cytokine secretion. TH1 and TH2 cells are also distinguishable on the basis of chemokine receptors.12 Immune-mediated disorders in mouse models can be classified as TH1- or TH2-associated according to the predominant cytokine profile. Although this is an oversimplified approach for the classification of disease in humans, and additional subsets of T cells have been more recently identified (Th3 and Tr1),13 the 4 diseases that we included in this review have nonetheless been described as having characteristics of TH1 predominance.14,15 One can speculate that mutual genetic or environmental factors influencing cytokine regulation or T-cell polarization are relevant to TH1-associated disorders, and that these conditions would tend to coexist within individuals and possibly within families.

METHODS

Identification of Studies and Data Extraction

We identified studies quantifying the coexistence of selected autoimmune diseases, published through March 2004, from Medline (Ovid) and Embase electronic databases. These databases cover literature from 1966 and from 1980, respectively. Identification of articles was performed by searching the databases on a combination of thesaurus terms. No language restrictions were applied. In Medline, thesaurus terms for the 4 prespecified autoimmune diseases were exploded for “diabetes mellitus, type 1,” “multiple sclerosis,” “arthritis, rheumatoid,” and “thyroiditis, autoimmune” or “thyroiditis, subacute” or “thyroid diseases.” For all diseases, the search was restricted to the subheadings of complications, epidemiology, etiology, genetics, and physiopathology. The results from each search were crosstabulated with all the other searches to identify publications with any combination of at least 2 of the specified diseases. A similar search strategy was used in Embase (list of terms available on request). Review articles published within the last 5 years on the epidemiology of each of the autoimmune diseases were also identified. Reference lists from all relevant articles were examined for studies that were not captured by the computerized searches. A textbook on rheumatic disease epidemiology16 was also reviewed.

Studies were eligible for inclusion in the review if the coexistence of 2 or more prespecified autoimmune diseases, either within individuals or among first-degree relatives (parents, siblings, children), was reported. Uncontrolled case series were eligible if a denominator was documented. For studies of individuals, the denominator was the total number of index disease cases. For family studies, the denominator was considered to be the number of relatives rather than the number of families. Studies were excluded if: (1) they were clinical/laboratory studies that selected patients based on prespecified proportions of comorbid autoimmune conditions (eg, a case–control study of patients with RA with IDDM versus patients with RA without IDDM); (2) they were restricted to seroprevalence of autoantibodies rather than clinical disease (because autoantibodies can occur in healthy individuals); (3) there was insufficient distinction between diagnostic categories (eg, type 1 vs type 2 diabetes, rheumatoid arthritis vs osteoarthritis, autoimmune vs nonautoimmune thyroid disease); (4) they were restricted to families having multiple members with autoimmune diseases; (5) they were restricted to women during pregnancy or the postpartum period; or (6) their results were not sufficiently clear to determine prevalence. Furthermore, articles were excluded if autoimmune disease coexistence was reported in the context of a known genetic syndrome, eg, autoimmune polyglandular syndrome.17 For studies with index disease case groups meeting eligibility criteria, but control groups failing to meet criteria (eg, cross-sectional studies that recruited “healthy controls”), only data regarding the index disease case groups were included in this review. For the purposes of this review, we did not consider patients with only “subclinical” hypothyroidism (elevated thyroid-stimulating hormone [TSH] but normal thyroid function, ie, normal circulating concentrations of free T3 and T4) to have autoimmune thyroiditis.18

A primary reviewer screened all titles and abstracts of publications identified by the literature search for eligibility. Articles were rejected if they clearly did not meet eligibility criteria. The full text of all articles possibly meeting inclusion criteria was obtained and screened. A secondary reviewer was consulted in cases in which eligibility of the article was unclear.

We categorized each study according to index and comorbid disease. For example, if a series of patients with RA was evaluated for the presence of another disease, we considered RA to be the index disease and any secondary condition as comorbid. Controls (when applicable) were persons who did not have the index disease but may have been positive for the comorbid disease. For the family studies, we use the term “case proband” to represent individuals with the index disease and the term “control proband” for nonindex disease controls. Similarly, “case relatives” are relatives of the case probands, and “control relatives” are relatives of the control probands. We included any results regarding the prevalence of comorbid disease among probands in the section on intraindividual disease.

We used a standardized data collection form to extract data, including study design and population, number of index disease cases and controls, incidence/prevalence of coexistent autoimmune diseases, diagnostic criteria used for index and comorbid diseases, potential confounding factors (eg, sex, age), and crude and adjusted relative risk estimates (odds ratios [OR] or standardized prevalence ratios, as appropriate) with 95% confidence intervals (CIs). The effect estimates refer to comorbid autoimmune diseases within index disease cases compared with controls. For family studies, data collection was modified to include the number of index disease and control probands, and the number and proportion of relatives of probands with coexistent autoimmune diseases.

Analysis

We computed comorbid autoimmune disease prevalence and corresponding exact binomial 95% CIs separately for index disease cases and controls. For studies that included raw data from control or reference groups without presentation of risk estimates relative to the index group, we calculated measures of relative risk (RR) and 95% CIs. We used ORs and exact 95% CIs for case–control studies. For studies including population-based reference data, we calculated standardized prevalence ratios (SPRs) and CIs based on the Poisson distribution for comparison of the observed number of comorbid cases with that expected based on the population reference values. We assessed heterogeneity among studies (within each combination of diseases) by exact likelihood ratio tests and Monte Carlo inference to determine whether it was appropriate to obtain pooled estimates of prevalence or relative risk. We conducted statistical analyses using Stata version 8 (Stata Corp., College Station, TX) and StatXact version 6 (Cytel Software Corp., Cambridge, MA).

RESULTS

Studies Identified

We identified 1187 publications from the Medline and Embase searches, of which we judged 86 to be potentially eligible based on initial screening. Of these, 39 met inclusion criteria. We identified a further 67 articles from reference lists for screening, of which 15 fit inclusion criteria. Thus, in total, we included 54 articles in this review. Studies are summarized in Tables 1 and 2.

TABLE 1
TABLE 1:
Summary of Studies Examining Coexistence of Autoimmune Diseases Within Individuals, Grouped by Index Disease
TABLE 1
TABLE 1:
Continued
Table
Table
TABLE 1
TABLE 1:
Continued
Table
Table
TABLE 1
TABLE 1:
Continued
TABLE 2
TABLE 2:
Main Findings From Studies Examining Coexistence of Autoimmune Diseases Within Families
TABLE 2
TABLE 2:
Continued

Comorbidity of Autoimmune Diseases Within Individuals

Fifty-two studies examined the coexistence within individuals of at least 2 of the selected autoimmune diseases. Only 16 of these studies had control groups or presented expected values based on population data. For each of the within-individual studies, the prevalence estimates and 95% CI for comorbid autoimmune diseases within index disease cases are displayed in a forest plot (Fig. 1). For context, background prevalence estimates based on data from a systematic review of epidemiologic data from the United States by Jacobson et al19 are as follows: RA 0.86%, IDDM 0.19%, AIT 0.79% adults/0.53% children (10–19 years), and MS 0.06%. However, these estimates provide only a crude comparison for the studies summarized in this review, because the populations varied considerably in terms of demographic structures, geographic locations, and time periods.

FIGURE 1.
FIGURE 1.:
Forest plot displaying prevalence estimates for comorbid autoimmune diseases within index disease populations. Due to substantial heterogeneity between studies, pooled prevalence estimates are not presented. The majority of studies were uncontrolled so measures of association are not displayed. The studies with asterisks are those that involved juvenile patients with rheumatoid arthritis.

With the exception of comorbid RA among MS index cases, there was strong evidence of heterogeneity for all disease combinations (P for heterogeneity all <0.0001). Given such heterogeneity, we did not focus on pooled estimates or perform an overall meta-analysis. Study findings are reviewed here according to each index disease category.

Rheumatoid Arthritis

Eleven intraindividual studies included RA as the index disease; one additional study included juvenile rheumatoid arthritis (JRA) index cases. Five studies examined the coexistence of IDDM20–24 with IDDM prevalence among RA index cases ranging from 0.32% to 5.95%. Of the 2 studies with controls,21,22 ORs were undefined, because neither study found any coexistent IDDM in the control groups. Neither study adjusted for confounders such as sex or age. The only population-based study, which arguably followed the most rigorous methodology, found no association between IDDM and RA when standardized to the source population.

Eight studies20,22,25–30 examined the prevalence of comorbid AIT (autoimmune thyroiditis) among RA index cases, with estimates ranging from 0.5% to 9.8%. A ninth study of JRA index cases found 4.5% prevalence for comorbid AIT.31 Of the 4 controlled studies,22,25,27,28 all found increased odds ratios for AIT among the RA cases versus controls, although CIs were wide and overlapped one in 2 cases. One of the studies was from a postmortem setting, limiting its comparability to the other studies.25 The only population-based study found no association based on expected values from the source population.20

Insulin-Dependent Diabetes Mellitus

Twenty-seven studies32–58 with IDDM as the index disease were identified. All studies assessed coexistent AIT and one also examined coexistent JRA.47 Comorbid AIT prevalence among the IDDM cases ranged from 0% to 24%. The study with the second highest prevalence40 was a long-term follow-up assessment of adults who had been diagnosed with IDDM as children or adolescents; the other studies were conducted in pediatric to young adult populations. None of the studies was population-based, and the only controlled study45 found no cases of AIT in the control group of “healthy” children, although it is unclear whether the latter category excluded children with prevalent clinical thyroid disease.

Multiple Sclerosis

Seven studies were included,59–65 some of which explored more than one comorbid disease. The coexistence of RA was assessed in 5 studies,59–62,64 with prevalence estimates ranging from 0.35% to 2.4%; a sixth study65 that assessed comorbid JRA found 0.28% prevalence. Comorbid RA among patients with MS was the only disease combination for which there was no evidence of heterogeneity among studies (P = 0.17). The weighted mean prevalence of RA in patients with MS was 0.63% (excluding the JRA study). Two studies61,64 had control groups; one found no cases of comorbid RA among hospital-based controls, and the other found an OR of less than 1.0 for comorbid RA among MS cases versus spouse or friend controls, although the CIs were wide and overlapped one. A third study62 documented an SPR of 0.60 (95% CI = 0.2–1.41), but the reference values were derived from geographic regions outside of the MS study area.

IDDM coexistence was assessed in 6 studies,59,61–65 with prevalence estimates ranging from 0% to 2.6%. There was no evidence for an association between IDDM and MS in the 2 controlled studies.61,64 However, the study that included referent data from its source population found an increased association between IDDM and MS.63

Five studies examining the prevalence of coexistent AIT among MS cases documented estimates ranging from 0.48% to 3.9%.59,60,62,64,65 Neither study with referents or controls found evidence of association between AIT and MS.62,64

Autoimmune Thyroiditis

Six studies included AIT as the index disease.66–71 All assessed comorbid RA, with prevalence estimates ranging from 1.4% to 17.6%. There was no consistent trend for association between RA and AIT in the 4 controlled studies.68–71

Comorbidity of Autoimmune Diseases Within Families

Nine studies examined coexistent disease among family members of index disease cases, only 2 of which did not report proband data.72,73

Rheumatoid Arthritis

Three controlled studies assessed IDDM prevalence among family members of RA cases21,22,72; a fourth study was conducted among family members of JRA cases.73 The data suggest an increased prevalence of IDDM among family members of patients with RA or those with JRA versus relatives of controls. Findings from the JRA study indicate an increased odds of AIT in the case versus control relatives, but no association for MS.

Insulin-Dependent Diabetes Mellitus

A single study47 examined the coexistence of the selected autoimmune diseases among family members of patients with IDDM. The prevalences of comorbid JRA and AIT among first-degree family members were 0.97% and 2.7%, respectively.

Multiple Sclerosis

Four studies assessed IDDM in relatives of probands,61,63–65 with a suggestion of increased prevalence of IDDM among relatives of MS probands, based on 2 controlled studies61,64 and a third with referent population data.63

Three of the studies also assessed RA; there was lack of association for RA among relatives of MS probands in the 2 controlled studies.61,64 Two studies assessed AIT; the only controlled study found increased odds of AIT among relatives of MS probands versus control relatives.64

Autoimmune (Hashimoto) Thyroiditis

We found no family studies with AIT as the index disease meeting eligibility criteria for this review.

DISCUSSION

This review focuses on 4 TH1-associated autoimmune disorders. The concept that autoimmune diseases tend to coexist is fairly well established in the clinical community, although based largely on anecdotal evidence. Further conjecture that TH1-predominant conditions in particular might be expected to correlate with one another adds impetus to the need to quantify relationships among such diseases. To our knowledge, this review represents the first systematic attempt to evaluate the evidence from observational studies linking a group of TH1-associated autoimmune diseases.

We chose to focus on studies of clinical autoimmune disease. We excluded studies in which the index or comorbid conditions were based on autoantibody seropositivity in the absence of clinical disease. It is important to draw a distinction between “autoimmunity” and “autoimmune disease.” Autoimmunity such as the presence of autoreactive T and B lymphocytes (eg, autoantibodies) is not necessarily associated with pathology or adverse clinical manifestations. In fact, the concept of autoreactivity has evolved to include the premise that low levels are physiological and may be involved in lymphocyte selection.74 Furthermore, transient elevations in autoantibody levels may occur as a byproduct of nonautoimmune phenomena such as infections.75,76 The biochemical milieu (eg, cytokine profile) and environmental factors are thought to be important determinants of whether autoimmunity progresses to clinical disease.

Our decision to restrict this review to data on clinical disease was particularly relevant to the issue of thyroid autoimmunity, because studies examining the presence of comorbid thyroid autoantibodies accounted for a large number of exclusions. Although autoantibodies are useful as diagnostic tools, they have low sensitivity and specificity when screening for or classifying autoimmune diseases. For example, the prevalence of thyroid microsomal (peroxidase) antibodies in the general population may range up to 12% and even higher among the elderly.77 Furthermore, in a longitudinal, population-based study, Hawkins et al77 determined that of 135 people with positive thyroid microsomal antibodies at baseline, 53 (39%) were negative at 6 years follow up. It should be noted that interpretation of autoantibody studies would need to account for factors such as assay methodology and sensitivity, and the autoantibody titers used as cutoffs to indicate positive versus negative results.

Of the 54 studies that met criteria for inclusion in this review, the majority were reports of uncontrolled series. Due to substantial heterogeneity among studies, it was inappropriate to derive pooled estimates to summarize the data, except for the prevalence of RA among patients with MS. Although far from conclusive, the literature suggests some positive associations between diseases. Data appear to support an increased prevalence of AIT in both patients with RA and those with IDDM—a finding that corresponds with common clinical opinion. The IDDM studies predominantly included children and adolescents. Although only one within-individual IDDM study was controlled, the high prevalence estimates for comorbid AIT are remarkable given that AIT is generally found in older individuals. Conversely, one would expect RA and IDDM to be increased among patients with AIT if etiologic factors are shared between these diseases. Overall, the evidence points to an increased prevalence of RA among patients with AIT, but there are insufficient data to evaluate comorbid IDDM. An intriguing finding is the suggestion of a modest inverse association between RA and MS based on studies within patients with MS and relatives of MS probands. Likewise, the weighted mean prevalence of RA among patients with MS is lower than conventional estimates for RA in the general population, although caution should be applied for this type of comparison. It is even more difficult to draw inference for the other combinations of diseases studied. However, it is interesting to note the pattern of investigations that have been undertaken. Reports related to patients with IDDM focused almost exclusively on comorbid AIT, whereas for MS, each of the other autoimmune diseases was studied. RA and AIT investigations were limited to each other and IDDM. None of the intraindividual studies looked at comorbid MS. Furthermore, only 9 family studies were included.

Numerous factors are likely to have contributed to the broad spectrum of results. The studies varied considerably in terms of their underlying populations and structure. Characteristics of the patient populations undoubtedly affect prevalence estimates. Sex, age, and, to a lesser extent, race are known to be strongly associated with autoimmune diseases, making it critical to account for these factors. Although most studies provided summary statistics for age and sex, the analyses did not adjust for their confounding effects. Information on race was reported in only a few instances. Duration of index disease may also be a key issue, although many of the reports did not include such data. Study designs also differed; few of the studies were population-based, and several of the hospital- or clinic-based series did not describe their selection procedures. The extent to which the data are generalizable from the tertiary care setting must be considered, because a substantial proportion of the studies was based on such populations. Conditions such as autoimmune thyroid disorders may also fail to reach hospital attention. Alternatively, the possibility of surveillance bias must be entertained in that the rate of detection of comorbid conditions may increase during the diagnosis or clinical management of chronic conditions such as those included in this review.

Interestingly, studies involving MS index cases tended to have larger sample sizes, and more often included population-based data, in comparison with studies for other diseases. Correspondingly, as depicted in Figure 1, the ranges of prevalence estimates for comorbid diseases among MS index patients were considerably narrower than for other disease combinations, and there was lack of evidence for heterogeneity between studies of RA among MS index cases.

Varying diagnostic criteria were used for the classification of cases, and, over time, the characteristics of diagnostic tests evolved (eg, autoantibody assays). Because in general, the sensitivity of tests improves over time, prevalence rates could spuriously increase. These changes are likely to have had particular influence on the diagnosis of autoimmune thyroiditis. For instance, there has been a shift in practice from histologic diagnosis to diagnosis based on clinical and laboratory evidence. Because the studies spanned approximately 75 years, however, genuine changes in prevalence and incidence rates are also plausible. For serologic studies relying on laboratory testing as the basis for AIT diagnosis, it is often unclear whether treatments affecting thyroid function (including thyroid replacement therapy) were accounted for. Also, nomenclature and classification schemes for thyroid diseases have not been standardized to the same extent as for other diseases considered in this review. In fact, not one of the studies included here referred to published guidelines for the diagnosis of thyroid disease. This seriously affects the comparability among epidemiologic studies, which use various terminology and case definitions. Moreover, it is important not to group overt and subclinical hypothyroidism, because the latter indicates a mild state of thyroid hypofunction rather than a disease entity.18 In addition, some studies define the term “subclinical hypothyroidism” as elevated serum TSH, whereas others consider it to mean elevated serum TSH in conjunction with thyroid autoantibodies.78

Given the low prevalence of many autoimmune diseases, individual studies tend to have inadequate sample sizes and power to demonstrate whether an association exists between various autoimmune diseases. Unfortunately, we could not perform meta-analyses given the variability between studies. Publication bias is another issue in that studies with positive results may be more likely to be published. For the present topic, this problem may have been mitigated by the fact that in many studies, the association between autoimmune diseases was not intended as a primary outcome but rather as supplemental information. Case ascertainment may also differ in studies designed to look at “any autoimmune disease” versus those with a predesignated list of diseases.

These issues make it difficult to draw firm conclusions about the extent of coexistence of the selected autoimmune diseases within individuals and families. Further research in this area can be useful, because it is clear that the co-occurrence of autoimmune diseases is likely to be as much due to common environmental factors as genetic susceptibility.

ACKNOWLEDGMENTS

We thank Ekua Yankah, Susanne Groener, Csilla Kaposvari, and Mariana Kaplan for assisting with translations of published papers.

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