DEFINING AUTOIMMUNE DISEASES

The immune system comprises cellular, chemical, and soluble protein components that together protect the body against foreign substances, including infectious agents and tumor cells, while not responding to molecules that signify “self” (Chaplin, 2010; Marshall et al., 2018). Autoimmunity arises when the immune system fails to distinguish self from non-self at the level of specific regions of cell surface molecules, or epitopes, recognized by two of the major effectors of the immune system: B cells, which produce antibodies, and T cells.¹ Autoimmune disease by definition, then, is autoimmunity that results over time in a pathological outcome with self-reactive, or autoreactive, T cells and autoantibodies causing tissue damage (Brent et al., 2007; Johns Hopkins University, 2022; Rose and Bona, 1993; Rosenblum et al., 2015). In 1993, Rose and Bona reevaluated Witebsky’s postulates² defining autoimmune disease, and proposed three levels of evidence to establish that a human disease is autoimmune in origin, including direct evidence by transfer of disease with pathogenic autoantibody or autoreactive T cells, indirect evidence based on reproduction of the autoimmune disease in an animal model, and circumstantial evidence from clinical data (Rose and Bona, 1993).

The terms autoimmunity and autoimmune disease originated in the 1950s, but in 1999 the term “autoinflammatory disease” emerged, which emphasizes the critical role of the innate immune system—the quickly reacting, nonspecific component of the immune system—in chronic inflammatory diseases where autoantibodies and autoreactive T cells play less of a role in mediating pathology (Abbas et al., 2004; Brent et al., 2007; Masters et al., 2009; Rose and Mackay, 2014; Stoffels and Simon, 2014). Autoinflammatory diseases are broadly considered by the scientific community to be those conditions driven predominantly by innate immune cells, such as macrophages, mediating systemic inflammation and self-tissue pathology, whereas autoimmune diseases occur when adaptive immune cells—T cells and B cells—targeting self-antigens are the dominant response causing inflammation and tissue damage.

Some diseases are clearly autoinflammatory in nature, such as familial Mediterranean fever, Behçet’s disease, and Still’s disease (Ciccarelli et al., 2014). Others are clearly autoimmune disorders, including multiple sclerosis and systemic lupus erythematosus (SLE). However, distinguishing between autoimmune and autoinflammatory disease can be difficult because activation of the innate immune system is a prerequisite for triggering an adaptive immune response (Iwasaki and Medzhitov, 2015). In fact, for most immune-mediated inflammatory diseases such as atherosclerosis, and prototypical autoimmune diseases such as multiple sclerosis, the innate and adaptive immune systems both play a role in promoting disease, leading to the notion of a spectrum or continuum of autoinflammatory-autoimmune diseases (Hedrich, 2016; McGonagle and McDermott, 2006).

Moreover, research is showing that diseases that medical science has not historically considered to be autoimmune diseases, such as atherosclerosis, Parkinson’s disease, and cancer, have autoimmune mechanisms such as autoantibodies (de Jonge et al., 2021) and autoreactive T and B cells that contribute to the pathogenesis of disease (Ketelhuth and Hansson, 2016; Lindestam Arlehamn et al., 2020). Research on Parkinson’s disease, for example, has revealed that T cell reactivity, which prompts an attack on brain cells, is associated with early and even preclinical disease (Lindestam Arlehamn et al., 2020). However, it is outside the scope of this report to consider all diseases that involve autoimmune processes, and the report focuses on diseases that have traditionally been termed autoimmune diseases, such as multiple sclerosis and SLE.

Similarly there is no consensus regarding the number of autoimmune diseases. The National Institute of Allergy and Infectious Diseases (NIAID) website states there are more than 80 diseases (NIAID, 2017), and the Autoimmune Registry³ and the Autoimmune Association⁴ each list around 150 diseases (Autoimmune Association, 2021; Autoimmune Registry Inc., 2020). The National Institutes of Health’s (NIH’s) 2016–2018 triennial fiscal report to Congress discusses research applicable to autoimmune diseases in general as well as research on specific diseases, including SLE, multiple sclerosis, type 1 diabetes, myasthenia gravis, scleroderma, rheumatoid arthritis, myositis, juvenile idiopathic arthritis,⁵ alopecia areata, psoriasis, pemphigus vulgaris, BACH2-related immunodeficiency and autoimmunity (BRIDA), and inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis (NIH, 2016, 2019). The report notes that SLE, multiple sclerosis, type 1 diabetes, IBD, and rheumatoid arthritis are among the most common and well-known autoimmune diseases and that BRIDA is a newly described autoimmune disease.

In the medical and research community, there are two differing approaches to characterize disease. One is to characterize and name diseases according to clinical criteria such as the presence of autoantibodies for autoimmune diseases (Hargraves et al., 1948; Marshall et al., 2018). Today, medical science classifies many rheumatologic, neurologic, gastrointestinal, cutaneous, hematologic, and cardiopulmonary illnesses as “autoimmune” based on the presence of autoantibodies, for example. The emphasis on clinical presentations of disease has resulted in disease classification by clinical diagnosis and organ system. A second approach to understanding diseases is to characterize them by their biologic mechanisms—the pathways that cause, mitigate, or affect the trajectory of disease. Over the past half century, the science of autoimmunity expanded beyond the concept of autoantibodies and autoreactive T cells and led to the emergence of the understanding of the importance of the innate immune response against self and other components of inflammation as drivers of autoimmune disease (Langan et al., 2020). Studies of innate immune cells, cytokines, cell surface markers, complement, and other biological phenomena now expand the definition of “autoimmune” to include illnesses with shared immunological mechanisms (Anaya, 2012; Cho and Feldman, 2015; Gokuladhas et al., 2021). Researchers can use an understanding of biologic mechanisms to target interventions for prevention, treatment, and cure.

There is no consensus regarding boundaries of the definition of autoimmune and autoinflammatory diseases. Public stakeholders, including people living with autoimmune disease, usually do not consider autoimmune and autoinflammatory conditions together, while clinicians and investigators may consider them similar and common enough to think of them as one entity or as two closely related entities. Regardless, the criteria for diagnosing someone as having an autoimmune disease may include diagnostic or classification criteria that describe clinically identifiable phenotypes in quantitative, exclusionary, time-limited, and binary terms (American Board of Medical Specialties, n.d.; Jia et al., 2017; Lockshin et al., 2021; Thompson et al., 2018). Nonetheless, diagnostic uncertainty is common among patients with autoimmune diseases.

OCCURRENCE AND COURSE OF AUTOIMMUNE DISEASES

Data Sources and Limitations

Two commonly used measures to calculate the occurrence of a disease are incidence and prevalence. Incidence refers to the frequency of new occurrence in a population in a specified period of time—for example, the number of people newly diagnosed with a disease per year expressed as annual new cases per 100,000 persons (Porta, 2014). Prevalence refers to the total number of people with a disease in a defined time period, and it can include people recently diagnosed as well.

Incidence and prevalence data for autoimmune diseases in the United States are limited and can be difficult to find. There is no mandatory reporting system or national registry for autoimmune diseases. Much of the available incidence and prevalence data come from countries other than the United States with health care systems covering the entire population (Eriksson et al., 2013; Munk Nielsen et al., 2019; Pasvol et al., 2020; Wei et al., 2018).

For the purpose of this report, the committee sought high-quality epidemiology data, using criteria encompassing the size and diversity of the population studied and the ability to examine potential differences in disease rates across segments of the population, the length and recency of the time period covered, and the inclusion of a validation procedure to assess the accuracy of the classification criteria used to identify specific diseases within the database being used in the study. The committee preferred studies from the past decade (i.e., studies for which the data collection period included years since 2010), but such studies were unavailable for most of the autoimmune diseases selected for this report. The committee did not consider general population studies using self-reported data that did not include a medical record review for estimates of incidence or prevalence of autoimmune diseases because the accuracy of these methods is either unknown or poor (Videm et al., 2017).

Although the committee found data sources meeting some of these criteria for all of the selected diseases, none met all of the criteria. The most robust data come from studies of SLE, type 1 diabetes, and multiple sclerosis, described below:

• Data for primary Sjögren’s disease were available from Manhattan, New York, through the Manhattan Lupus Surveillance Program (2007 to 2009) (Izmirly et al., 2019). Because this effort was for a limited time period, this study does not provide data that allow assessing temporal trends in the incidence or prevalence of Sjögren’s disease. These data focus only on Sjögren’s disease (referred to as primary Sjögren’s disease) and do not include individuals with Sjögren’s disease along with other systemic rheumatic diseases such as rheumatoid arthritis and SLE. Sjögren’s disease is diagnosed in up to 30 percent of individuals with rheumatoid arthritis and up to 20 percent of individuals with SLE (Aggarwal et al., 2015a; Baer et al., 2010; Harrold et al., 2020). These rates of Sjögren’s disease co-occurrence, together with the prevalence of rheumatoid arthritis and SLE in Table 2-1, suggest that Sjögren’s disease may occur more than 20 times more frequently when co-occurring with other autoimmune diseases than when diagnosed alone. Thus, the prevalence rate data limited to primary Sjögren’s disease exclude the majority of individuals with Sjögren’s disease.
• For SLE, incidence and prevalence data from the early 2000s (2002 to 2004 or 2007 to 2009) are available from a network of population-based national lupus registries in Michigan (Somers et al., 2014); Georgia (Lim et al., 2014); California (Dall’Era et al., 2017); Manhattan, New York (Izmirly et al., 2017); and American Indian or Alaskan Native populations (Izmirly et al., 2021a,b). Because this effort occurred for a limited time period, it does not provide data allowing for assessing temporal trends in the incidence or prevalence of SLE. The Centers for Disease Control and Prevention (CDC) supported these studies.
• For antiphospholipid syndrome (APS), incidence data from 2001 to 2015 are available from the Rochester Epidemiology Project (Duarte-Garcia et al., 2019); these data were used to estimate prevalence in 2015. The population base for this study is relatively small and homogenous. Because of the high proportion of people with SLE who also have APS, the relative lack of representation of groups who are at higher risk for SLE in this study population would result in an underestimation of APS rates.
• For rheumatoid arthritis (Kawatkar et al., 2019), incidence and prevalence data from 2005 to 2014 are available from the Kaiser Permanente medical system of Southern California, which covers a large and diverse population with respect to sociodemographic characteristics.
• For psoriasis, prevalence data from 1996 to 2009 from the Kaiser Permanente medical system of Northern California was used (Asgari et al., 2013).
• For IBD, prevalence data are available for 1999 to 2001 from a study using a large database from nine health maintenance organizations (Herrinton et al., 2007). For more recent prevalence data, studies include a 2007 to 2016 study that used two private administrative health claims databases collectively covering approximately 62 million people annually (Ye et al., 2020), as well as studies in more limited populations (Hou et al., 2013; Shivashankar et al., 2017; Xu et al., 2021). The committee relied on the estimates of the larger study, while considering the variability in estimates and the strengths and limitations of this set of studies (see Box 2-1).
• For celiac disease, serology (tissue transglutaminase and endomysial IgA antibodies) data from the 2009 to 2012 National Health and Nutrition Examination Survey⁶ are available (Mardini et al., 2015). Although this study provides data on the prevalence of these antibodies in a representative sample of the U.S. population, it does not include symptom data or other details allowing for assessing disease status based on a full clinical evaluation.
• For primary biliary cholangitis (PBC), prevalence data from 2003 to 2014 are available from the Fibrotic Liver Disease Consortium (Lu et al., 2018), a large network of health care systems drawing patients from across the United States.
• For multiple sclerosis, prevalence data from 2008 to 2010 are available from a study using three public (Veterans Administration, Medicare, and Medicaid) and three private administrative health claims databases collectively covering 125 million U.S. adults (Culpepper et al., 2019; Nelson et al., 2019; Wallin et al., 2019). The data were weighted to reflect the source of insurance coverage in the U.S. population, and the study used a validation procedure to assess the sensitivity and specificity of the classification criteria. However, the design of this study did not allow for assessing incidence rates or differences in prevalence among racial or ethnic groups, or assessment of temporal trends in incidence or prevalence. The National Multiple Sclerosis Society initiated and supported this study.
• For type 1 diabetes, incidence data from 2002 to 2012 and prevalence data from 2001 to 2009 are available from the SEARCH for Diabetes in Youth study, a large population-based study conducted at five centers across the United States (Dabelea et al., 2014; Mayer-Davis et al., 2017). CDC and the National Institute of Diabetes and Digestive and Kidney Diseases initiated and supported this study.
• The committee did not find any recent (year 2000 or later) studies of incidence or prevalence of autoimmune thyroid diseases in the United States.

TABLE 2-1

Prevalence Rates of Selected Autoimmune Diseases, United States.

BOX 2-1

Variation in Inflammatory Bowel Disease Estimates.

In contrast, the Surveillance, Epidemiology, and End Results (SEER) database (NCI, 2021b) developed by the National Cancer Institute, provides easily accessible, verified data on incidence, prevalence, and mortality rates for the U.S. population in total, for males, females, as well as for five race and ethnicity groups, for all cancers, and for more than 30 individual types of cancers. It also provides trends in these rates over the past 20 years. This kind of resource is not available for autoimmune diseases.

The committee did take special note of the usefulness of the Olmsted County, Minnesota, Rochester Epidemiology Project (St. Sauver et al., 2011) conducted by the Mayo Clinic. This resource has provided epidemiologic data for rheumatoid arthritis, SLE, IBD, and many other autoimmune (and other) diseases since the 1960s, and is one of the few sources of long-term data on trends in the occurrence of these diseases. It is also a resource used for studies of prognosis, concomitant illnesses, and autoimmune-related mechanisms in other diseases. An important limitation, however, is that it covers a relatively small and homogenous population in terms of sociodemographic background,⁷ and the sample size is small for many of these diseases. NIH continues to support the Rochester Epidemiology Project.

Finding: There is no mandatory reporting system or national population-based data-collection program for autoimmune diseases, as there is for cancer through the National Cancer Institute’s SEER system.

There are also difficulties with respect to obtaining accurate data on mortality relating to autoimmune diseases. Death certificates can provide population-level data on mortality from autoimmune diseases, but they are not a good source of data pertaining to occurrence of chronic conditions that are not associated with acute mortality risks, such as most autoimmune diseases. Death certificates include information on immediate and underlying causes of death, with an additional field for other significant conditions contributing to the death. However, the completeness and accuracy of this assessment, particularly for deaths relating to autoimmune diseases, is low: studies have demonstrated considerable under-reporting of autoimmune diseases as a cause of death, with no mention of an underlying condition in 40 to 80 percent of deaths of people enrolled in clinical cohort studies of SLE and rheumatoid arthritis (Calvo-Alén et al., 2005; Molina et al., 2015). It may be difficult to quantify mortality in most autoimmune diseases since death more commonly results from—and is recorded as being the result of—complications such as cardiovascular disease, infection, or malignancy rather than specific disease causes such as lethal hemorrhage resulting from thrombocytopenia. Studies of the age at death of persons with diagnosed autoimmune diseases constitute an indirect measure of mortality. A recent Dutch study that used death certificate data concluded that “Systemic autoimmune diseases constitute a rare group of causes of death, but contribute to mortality through multiple comorbidities. Classification systems could be adapted to better encompass these diseases as a category” (Mitratza et al., 2021).

The committee also noted challenges in conducting and interpreting some clinic-based studies of mortality risk among people with specific autoimmune diseases. For example, studies based in tertiary care center(s) limit the generalizability of the findings. It is also important to distinguish between incidence and prevalence in analysis of risk over time, to report absolute risk in addition to relative risk, to address loss to follow-up, and to include a sample large enough to be able to examine the experiences of specific sociodemographic groups within the patient population.

Finding: There is a lack of accurate data on mortality associated with autoimmune diseases. Death certificates may provide incomplete information on an underlying autoimmune disease that contributed to the cause of death.

Additional Data Challenges

Studies using International Classification of Diseases (ICD) 9 or ICD 10 codes in electronic medical records to identify potential cases of autoimmune diseases may be inadequate (Moores and Sathe, 2013). Other information, such as number of visits with specific codes, medication use, and results of specific types of laboratory tests can improve the accuracy of the case ascertainment methods (Barnado et al., 2017; Liao et al., 2010). Researchers can conduct a complete medical record review to evaluate a case ascertainment algorithm’s sensitivity and specificity within the database being used (Carroll et al., 2012). Insurance-based algorithms used in the United States present an additional difficulty in terms of determining initial diagnosis for incidence studies, as medical records may be incomplete because of changes in coverage or providers. The pattern of remissions and flares seen in some autoimmune diseases presents additional challenges to determining disease prevalence. Prevalence studies based on current medication use or a specified frequency of medical visits may undercount patients experiencing prolonged periods of remission.

Epidemiology of Select Autoimmune Diseases

Prevalence Rates

Among the most common autoimmune diseases are celiac disease, rheumatoid arthritis, and psoriasis, with prevalence rates approximately 790 to 939 per 100,000 and approximately 2.3 to 2.5 million U.S. residents living with each of these diseases; IBD, with a prevalence rate of approximately 500 per 100,000; multiple sclerosis, with a prevalence rate of approximately 300 per 100,000; and type 1 diabetes, with a prevalence rate of approximately 190 per 100,000 (Table 2-1). The available data pertaining to Sjögren’s disease are limited to primary Sjögren’s disease, which does not occur in conjunction with SLE, rheumatoid arthritis, or scleroderma, and so underestimates the overall burden of this condition.

Table 2-1 does not include the autoimmune thyroid diseases Graves’ disease (hyperthyroidism) and Hashimoto’s thyroiditis (hypothyroidism) because of a lack of U.S. data covering the past 20 years. A study of Graves’ disease from 2008 to 2013 in Sheffield, United Kingdom, reported an annual incidence of 24.8 cases per 100,000 persons, with a median age at diagnosis of 44 (33 to 56) years; 80 percent of patients were women (Hussain et al., 2017). A large cohort study from the Netherlands examined thyroid medication use and thyroid hormone levels to classify overt and subclinical thyroid diseases; 3.1 percent of participants reported levothyroxine use, and 9.4 percent of the people who were not taking thyroid medications had subclinical hypothyroidism (thyroid stimulating hormone levels of 4.01–10.0 milli-International Units per liter) (Wouters et al., 2020).

Trends in Incidence and Prevalence

Trends in disease incidence are important indicators of changes in the underlying risk factors for the disease, such as an increasing or decreasing level of an environmental exposure that contributes to the development of the disease. These rates can best be ascertained from studies applying the same case ascertainment methods over time within a specific population. Trend data from U.S. studies spanning periods within the past 20 years and meeting these criteria were not available for psoriasis, multiple sclerosis, or the autoimmune thyroid diseases; for psoriasis and multiple sclerosis, the committee has included data from Canada in the following summary.

Only one study, of psoriasis incidence in Ontario, Canada, reported decreasing incidence for time periods covering 2000 to 2015 (Table 2-2). Studies of Sjögren’s disease, rheumatoid arthritis, PBC, and in some studies of IBD (ulcerative colitis and Crohn’s disease) and type 1 diabetes, found increasing incidence rates compared with pre-2000 years or during the 2000s. There was little or no trend observed in the studies of APS and multiple sclerosis.

TABLE 2-2

Trends in Incidence or Prevalence of Autoimmune Diseases in the United States and Canada.

Trends in disease prevalence can reflect changes in the incidence of disease, in the age distribution of a population, or in survival of people with the disease. Multiple sclerosis (Rotstein et al., 2018) and PBC (Lu et al., 2018) are examples of diseases for which studies have demonstrated that prevalence increased despite little change in incidence; reductions in mortality rates were also observed among people with these diseases.

In children and adolescents, the incidence or prevalence of two of the most common autoimmune diseases, IBD and type 1 diabetes, appears to have increased in the United States since 2000 (Table 2-2). The pediatric prevalence of IBD in the United States increased between 2007 to 2016 from 33.0 to 77.0 per 100,000, with Crohn’s disease being twice as prevalent as ulcerative colitis (45.9 versus 21.6) (Ye et al., 2020). Type 1 diabetes has also increased. From 2001 to 2009, a large U.S. study showed an increase in type 1 diabetes prevalence from 148 per 100,000 to 193 per 100,000 (Dabelea et al., 2014). A subsequent study of the U.S. Medicaid pediatric population during the period 2002 to 2016 showed an increase in annual type 1 diabetes prevalence from 129 to 234 per 100,000 (Chen et al., 2019). This trend was not seen, however, in a study spanning 1994 to 2010 in Olmsted County, Minnesota (Cartee et al., 2016).

Demographic Patterns with Respect to Disease Risks

Many, but not all, autoimmune diseases affect women predominantly (Figure 2-1). The diseases with the most marked sex difference in occurrence, with female-to-male ratios greater than 5:1 are SLE (Izmirly et al., 2021a,b), hyper- and hypothyroidism (Leese et al., 2008), and Sjögren’s disease (Maciel et al., 2017a, 2017b) The female-to-male ratio is lower, between 4:1 and 2:1, for multiple sclerosis (Langer-Gould et al., 2013), PBC (Lu et al., 2018), systemic sclerosis (Mayes et al., 2003), and rheumatoid arthritis (Myasoedova et al., 2010). However, for other autoimmune diseases, such as psoriasis (Icen et al., 2009), the female-to-male incidence ratio is close to or less than 1.0 and also influenced by age. Myocarditis, for example, occurs more frequently in males before age 50 (Coronado et al., 2019). Although the female-to-male ratio for APS is close to 1.0 in the only population-based study available (Duarte-Garcia et al., 2019), this ratio may be higher in populations that include a greater proportion of patients with SLE.

FIGURE 2-1

Variation in female-to-male ratio in incidence rates across the autoimmune diseases of focus. NOTES: Age ranges provided when available. APS, antiphospholipid syndrome; PBC, primary biliary cholangitis; SLE, systemic lupus erythematosus.

Regarding disease incidence in children, one study of juvenile idiopathic arthritis found an increased incidence in females compared with males in each of the age groups studied (ages 0 to 5, 6 to 10, and 11 to 15 years) (Harrold et al., 2013). Other autoimmune diseases do not show a female predominance in children, and some diseases, such as type 1 diabetes (Cartee et al., 2016), occur more frequently in boys than girls.

Although most autoimmune diseases can occur at any age, different diseases present different patterns with respect to age at onset or diagnosis. Figure 2-2 shows four patterns, all based on recent studies from Olmsted County, Minnesota. Type 1 diabetes most often occurred between 5 and 15 years of age, but incidence extended through ages 30 to 39, and rates were higher for males compared with females beginning around age 10. Incidence rates for primary Sjögren’s disease increased steadily throughout adulthood, reaching the highest rates around ages 65 to 74, with higher incidence seen in women (Maciel et al., 2017a). The peak age at diagnosis of Crohn’s disease and ulcerative colitis was 20 to 29 years, but the study also saw new cases through early and late adulthood. There was little difference in rates between males and females for Crohn’s disease, but for ulcerative colitis, rates in males were somewhat higher than in females.

FIGURE 2-2

Incidence rates of four autoimmune diseases by age and sex in Olmsted County, Minnesota. A. Type 1 diabetes, 1994–2010. B. Primary Sjögren’s disease, 1976–2015. C. Crohn’s disease, 1970–2010. D. Ulcerative (more...)

Health Disparities in Autoimmune Diseases

There are known disparities in the incidence, prevalence, severity, prognosis, outcomes, and care related to autoimmune diseases. These disparities adversely affect groups that are socially disadvantaged and marginalized based on race and ethnicity, socioeconomic status, and geographic region. In addition, these factors may interact with one another to cause, accentuate, and perpetuate health disparities at the individual patient, community, and societal levels (Reifsnider et al., 2005). While studies may report race and ethnicity as a biologic proxy for genetic origin, the committee acknowledges that the terms “race” and “ethnicity” denote the full breadth of experiences and exposures of a population, rather than a limited lens focused on genetic variability among populations (see Box 2-2).

BOX 2-2

The Constructs of Race and Ethnicity.

With respect to racial and ethnic disparities in incidence or prevalence of disease, it is important to note that no single pattern describes the patterns seen among the autoimmune diseases; for some diseases, the highest rates occur among Black individuals, while for other diseases, the highest rates occur in White individuals (Figure 2-3). Studies have reported increased rates of juvenile idiopathic arthritis, autoimmune liver disease, and SLE in Indigenous peoples in the United States and Canada (Barnabe et al., 2012; Mauldin et al., 2004; Yoshida et al., 2006). These studies reinforce the need for more directed research into autoimmune disease risk in American Indian and Alaska Native populations.

FIGURE 2-3

Variability in disease rates in the United States by race or ethnicity. A. Prevalence of systemic lupus erythematosus (females). B. Prevalence of type 1 diabetes (age < 20). C. Prevalence of celiac disease (positive serology, age > 5). (more...)

Studies have also found disparities in the severity and prognosis of many diseases according to race and ethnicity (Barton et al., 2011; Lim et al., 2019; Ventura et al., 2017). Barriers to diagnosis, access to specialist care or to enrollment in clinical trials, and affordability of treatments are all issues that can affect people with autoimmune diseases (Bailey et al., 2021; Sankar et al., 2004). These barriers can be geographic (e.g., availability of services in rural areas), economic, and rooted in sociocultural experiences that can result in mistrust of medicine or medical services.

The previous discussion has highlighted diseases with moderate to strong predominance in women and diseases with increased risk in racial and ethnic minority populations. Within the full spectrum of autoimmune diseases, however, many other autoimmune illnesses do not reflect this pattern. Differences in the incidence or severity of diseases across demographic groups may have important implications for diagnosis and management of disease and may implicate the importance of genetic susceptibility in conjunction with environmental factors in disease pathogenesis. The committee believes that these striking variations in sex, race, and age patterns among autoimmune diseases are worthy of further research.

Finding: There is a lack of population-based data from diverse populations to accurately assess the incidence, prevalence, lifetime risk, epidemiologic trends, and the extent of the impact of autoimmune diseases on the U.S. population. In addition, existing data may not distinguish sex and gender. The best available long-term data are from a relatively racially and socioeconomically homogenous population, thereby limiting its application for understanding the variation in genetic susceptibility and the variety of exposures, experiences, and socioeconomic drivers of autoimmune diseases.

Conclusion: There is a need for population-based epidemiology studies that can provide the basis for studying numerous autoimmune diseases over at least a 20-year period. This resource could collectively provide a picture of the impact of these diseases in all groups representative of the U.S. population, and investigators could use it to facilitate the kind of population-based research needed to fully understand the development and prognosis of these diseases.

Coexisting Autoimmune Diseases

Historically, medical management occurring in subspecialties according to the organ system involved may have obscured associations between autoimmune diseases. However, shared features among certain autoimmune diseases is so well recognized, particularly within rheumatology, that nomenclature distinguishes between disease that is primary (standalone) or secondary to another autoimmune condition. In one study, a second diagnosable autoimmune disease occurred in 52 percent of those diagnosed with Sjögren’s disease, 43 percent of those with antiphospholipid syndrome, 38 percent of those with SLE, and 30 percent of those with rheumatoid arthritis (Lockshin et al., 2015). The terms “primary” and “secondary” are misleading, however, since no evidence exists to support the hypotheses that one autoimmune disease precedes, causes, or dominates the other, or even that they are independently diagnosable illnesses. The appropriateness of such terminology was recently reviewed for Sjögren’s disease (Kollert and Fisher, 2020), but the concepts discussed apply to other autoimmune diseases as well. Thus, the designation of “primary” or “secondary” has largely fallen out of favor.

In the medical literature, definitions of terms such as “comorbidity” and “complication” can be fluid and overlapping (Valderas et al., 2009). That much remains unknown about autoimmune diseases further complicates the use of precise definitions. For the purpose of this report, the committee uses the definitions provided in Box 2-3.

BOX 2-3

Definitions Used in This Report for Conditions Coexisting With an Autoimmune Disease.

Abundant anecdotal evidence and case series of autoimmune disease clustering, beyond the classically described “overlap” conditions, has prompted research addressing whether co-occurrence of selected autoimmune diseases occurs within individuals and families at higher rates than expected by chance (Somers et al., 2006). Investigators have not studied all combinations of autoimmune diseases at the population level, and key studies on autoimmune coexistence within individuals have focused largely on multiple sclerosis, rheumatoid arthritis, autoimmune thyroiditis (Hashimoto’s thyroiditis), type 1 diabetes, IBD, and vitiligo as index conditions (Cooper et al., 2009). Overall, data support the idea that intra-person co-occurrence does occur at greater than expected rates for several combinations of autoimmune disease. For example, two large studies—one examining Kaiser Permanente Health Plan records and another examining two U.S. medical claim data sets—found that persons diagnosed with IBD had a significantly increased risk of developing multiple sclerosis, psoriasis or psoriatic arthritis, and rheumatoid arthritis compared with persons without an IBD diagnosis; moreover, the second study also found an increased risk of developing ankylosing spondylitis (Cohen et al., 2008; Weng et al., 2007).

A major epidemiologic study in the United Kingdom investigated the co-occurrence of four autoimmune conditions within individuals—multiple sclerosis, rheumatoid arthritis, type 1 diabetes, and autoimmune thyroiditis (Somers et al., 2009). After controlling for age and calendar year, this study documented increased co-occurrence between rheumatoid arthritis, autoimmune thyroiditis, and type 1 diabetes compared with population expected rates, regardless of diagnostic sequence; sex-specific results were consistent with the overall findings (Figure 2-4). The magnitude of association was most prominent for autoimmune thyroiditis among patients with type 1 diabetes, in which risk was more than four times that expected. A notable exception to the premise of clustering was between multiple sclerosis and rheumatoid arthritis, where findings suggested an inverse association. Importantly, this study predated the availability in the United Kingdom of tumor necrosis factor inhibitors, used today to treat some autoimmune diseases, which otherwise could have confounded results given reports of multiple sclerosis in association with such treatment. An inverse association between multiple sclerosis and rheumatoid arthritis was also supported by a pair of Danish studies of individuals and families (Eaton et al., 2007; Nielsen et al., 2008) and within families based on a systematic review (Somers et al., 2006). A broader implication is that characterization of baseline rates of coexistence provides important context for interpreting pharmacovigilance data as immunotherapy options continue to expand (Somers et al., 2009).

FIGURE 2-4

Sex-specific standardized incidence ratios and 95% confidence intervals for the existence of coexisting autoimmune diseases within each index disease category (a standardized incidence ratio of 100 indicates unity). For disease combinations for which (more...)

Family studies have also reported increased occurrence of autoimmune diseases among first degree relatives of case versus control individuals. Aside from the combinations of autoimmune diseases detected within individuals described above, additional disease associations reported in family studies include polyarteritis nodosa, Addison’s disease, Crohn’s disease, and “autoimmune diseases in general” in relatives of individuals with multiple sclerosis; autoimmune thyroid diseases and “autoimmune diseases in general” for SLE; “autoimmune diseases in general” for Sjögren’s disease; and autoimmune thyroid diseases and “autoimmune diseases in general” for idiopathic inflammatory myopathy (Cooper et al., 2009).

Finding: Limited data exist on the presence of co-occurring autoimmune diseases in individuals, and the studies have concentrated on comparatively few autoimmune diseases when measured against the large number of diseases generally accepted as being autoimmune diseases.

Conclusion: Additional research is needed to identify the patterns of a broad range of co-occurring autoimmune diseases as this could provide important context for interpreting pharmacovigilance data and provide insight into underlying biologic mechanisms that could inform strategies for the prevention, early diagnosis, and treatment of subsequent autoimmune diseases in individuals with autoimmune disease.

Morbidity, Mortality, and Quality of Life

The manifestations and consequences of autoimmune diseases vary depending on the target organs or systems. It is important to view the effects of autoimmune diseases not just through a lens directed at physical health, but through one that also views elements such as normal social interaction and development, mental health, the ability to gain an education and pursue employment, and the capacity to have children, all of which can affect quality of life (Figure 2-5).

FIGURE 2-5

Effects of autoimmune diseases and treatment. NOTE: CVD, cardiovascular disease.

For some autoimmune diseases, acute effects can be severe. Undiagnosed or inadequately controlled type 1 diabetes, for example, can lead to diabetic ketoacidosis, coma, and death. SLE has a relatively high mortality rate and a significant racial disparity in mortality, and mortality risk is significantly elevated compared with expected rates (standardized mortality ratios, 2 to 5 times higher) (Gianfrancesco et al., 2021; Jorge et al., 2018). Ten-year mortality rates in an incidence cohort of SLE in Georgia were 28 percent in Black persons and 9 percent in White persons (Lim et al., 2019). In other autoimmune diseases, absolute and relative mortality risks are lower. A meta-analysis of 35 studies of IBD reported a standardized mortality ratio of 1.08 (95 percent confidence interval 0.97–1.21) in inception cohorts of ulcerative colitis and 1.34 (95 percent confidence interval 1.15–1.56) in inception cohorts of Crohn’s disease (Bewtra et al., 2013).

For many autoimmune conditions, the underlying disease process, including a chronic inflammatory response and/or the long-term use of immunosuppressant drugs, results in increased risks of infectious disease (bacterial, viral, mycobacterial, and fungal) as well as cardiovascular disease. For example, an elevated risk of cardiovascular disease, including coronary revascularization procedures, myocardial infarction, peripheral vascular disease, and cardiovascular deaths, occurs for rheumatoid arthritis, systemic sclerosis, and SLE (Kremers et al., 2008; Kurmann et al., 2020; Man et al., 2013; McMahon et al., 2011). The concept of accelerated atherosclerosis associated with autoimmune disease is key to understanding the increased risk of cardiovascular disease seen even at relatively young ages (under 45 years of age), and the evaluation and control of cardiovascular risk factors is a vital component of clinical care for autoimmune diseases (Durante and Bronzato, 2015).

Autoimmune diseases are also associated with specific types of cancer, and there is a need for a better understanding of pathogenic mechanisms in these individuals as well as optimal patient care. One study using the SEER database found that Sjögren’s disease, rheumatoid arthritis, SLE, and autoimmune hemolytic anemia were associated with a 1.5- to 2-fold increased risk of three or more types of lymphomas, while psoriasis, pemphigus, and discoid lupus erythematosus were associated with a 3- to 6-fold increased risk of T-cell non-Hodgkin lymphoma (Anderson et al., 2009; Chiesa Fuxench et al., 2016).

Some autoimmune diseases are also associated with increased cancer risk at specific sites related to the disease. For example, people with IBD have an increased incidence of colorectal and other gastrointestinal cancers (Axelrad et al., 2016). The role of chronic inflammation, prolonged use of immunosuppressant agents, and common risk factors—as in the case of rheumatoid arthritis and lung cancer (Simon et al., 2015)—are important avenues for future research into cancer risk and autoimmune disease. In addition, much remains to be learned about how best to treat patients with autoimmune disease and cancer. Until recently, for example, patients with autoimmune disease and cancer were excluded from clinical trials of immunotherapy, which increases the immune system’s capability to detect and kill tumor cells, because of concerns that the drugs might increase autoimmunity and possibly cause severe and life-threatening complications (NLM, 2021).

Flare-ups of symptoms or disease activity, often requiring hospitalization, are common in many autoimmune diseases, including multiple sclerosis, rheumatoid arthritis, SLE, and IBD (Morales-Tisnes et al., 2021; Panopalis et al., 2012). The remitting-relapsing course of these diseases can be challenging to manage from a medical as well as a social and psychological perspective. In addition, the damage caused by some autoimmune diseases, such as vasculitis, SLE, and PBC, may require organ transplantation (Albuquerque et al., 2019; Carey et al., 2015; Jain et al., 2021).

Pain is a common symptom in many autoimmune diseases although the etiology varies. For example, owing to nerve involvement or damage in multiple sclerosis, individuals with the disease often experience spasticity with stiffness, flexor spasms, and uncontrollable muscle contractions as well as the burning sensations of dysesthesias and facial pain due to the severe stabbing-like tic douloureux (IOM, 2001). The chronic inflammation in rheumatoid arthritis causes progressive joint deterioration and secondary osteoarthritis, leading to pain and stiffness; while up to 90.4 percent of patients with the disease seek health care for severe pain, pain-management options remain limited (Sanchez-Florez et al., 2021). Persons with IBD often experience joint and spinal pain from inflammatory arthritis, in addition to abdominal and pelvic pain; in those with perianal disease from fistulae, pain can be severe. Moreover, pain is a risk factor for depression, anxiety, and disability in individuals with IBD (van der Valk et al., 2014a).

One of the most common complaints among individuals with autoimmune diseases is fatigue, which in this context is particularly complex and variable because it is likely linked to differing causal mechanisms. Multiple physiological processes may contribute to fatigue in autoimmune diseases including inflammatory activation of the immune system that affects the peripheral and central nervous systems (Lee and Giuliani, 2019b; Morris et al., 2015). Fatigue can be debilitating, impede performance of even simple daily tasks, and contribute to mental health problems such as depressed mood (Zielinski et al., 2019). When fatigue prevents people from fulfilling normal social roles or holding a job, it can cause isolation, impose financial burdens on them and their families, and decrease quality of life. There are currently no long-lasting interventions to effectively treat fatigue in persons with autoimmune diseases (Zielinski et al., 2019).

Autoimmune disease can have impacts on physical function. Neurological effects in multiple sclerosis include vision impairment and problems with balance and mobility, some being severe, and these effects are highly important to people living with this condition (Heesen et al., 2008). Blindness resulting from retinopathy is one of the most common complications of type 1 diabetes (James et al., 2014). In addition, the lesions and scarring that can result from skin manifestations of some diseases, such as psoriasis, can result in disfigurement and stigmatization (van Beugen et al., 2017). All of these effects can act to isolate a person physically and/or psychologically, impede social relationships, and restrict access to education and employment. Measures focusing on health care utilization may, in fact, overlook the significant effects of autoimmune diseases.

Children with autoimmune diseases are at risk for adverse impacts on growth and development as a result of the diseases and their treatment. Growth failure, as indicated by height velocity and final height that rank below age- and sex-expected percentile norms, can be caused by the effects on bone growth of chronic systemic inflammation as well as glucocorticoid therapy. Inflammation may also cause delayed puberty, which may adversely impact peak bone mass and linear growth (Kao et al., 2019). Studies in individuals with childhood-onset SLE have found that about 15 percent experience low height velocity (Bandeira et al., 2006; Gutierrez-Suarez et al., 2006), that the average final height is lower than target height, a calculation based on the heights of the parents (Heshin-Bekenstein et al., 2018), and that these effects are most marked in those experiencing pre-menarche disease onset (Sontichai et al., 2020). A recent large cohort study found that 10 percent of children with the systemic form of juvenile idiopathic arthritis had short stature (Guzman et al., 2017). However, some children with autoimmune disease experience a period of catch-up growth when their disease responds to treatment and/or glucocorticoid therapy is reduced (Gutierrez-Suarez et al., 2006; Guzman et al., 2017). Growth hormone therapy also may mitigate adverse growth effects (Simon and Bechtold, 2009). Development of new effective glucocorticoid-sparing medications may lessen adverse effects on growth and development for children with autoimmune diseases.

In young adults and during the reproductive years, autoimmune diseases can generate additional risks and complications (Sammaritano et al., 2020). Pregnancy or the post-partum period may worsen the course of autoimmune diseases, or the disease itself may result in increased risk of adverse pregnancy outcomes, including spontaneous abortion. This can lead to the need to make difficult choices regarding the use of disease-modifying medications during pregnancy. Those wishing to have children may have to consider the potential effects of treatments on fertility or carrying a pregnancy to term, and consider options for oocyte preservation.

Another effect of autoimmune diseases, particularly during the young and middle-aged adult years, is employment-related disability. Studies of people with IBD, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic sclerosis, and SLE report partial or full work disability, with one cohort study of persons with early rheumatoid arthritis observing a work disability rate of 28 percent at study start and 44 percent 15 years later (Eberhardt et al., 2007; Orbai et al., 2021; Raggi et al., 2016; Scofield et al., 2008; Sharif et al., 2011; van der Valk et al., 2014b). The relapsing-remitting nature of these diseases, as well as some of the features that contribute to disability such as fatigue and pain, may result in additional challenges to receiving disability benefits (Scofield et al., 2008). The indirect costs of lost productivity represent approximately 30 percent of the estimated total costs of rheumatoid arthritis (Birnbaum et al., 2010) and psoriasis (Vanderpuye-Orgle et al., 2015) in the United States, and approximately 50 percent of the total costs of IBD during the first year after diagnosis among working-age people in Sweden (KhaliLi et al., 2020).

Within the sphere of mental health, depression or depressive symptoms are common among people living with autoimmune diseases and can contribute to the risk of reduced employment (Eckert et al., 2017; Kurd et al., 2010; Moustafa et al., 2020; Vanderpuye-Orgle et al., 2015). In some diseases, research has not ruled out the possibility that the direct central nervous system effects of rheumatoid arthritis, SLE, and multiple sclerosis may play a role in inducing depression (Vallerand et al., 2018, 2019). In addition, difficulties with mobility, the challenges of working while coping with disease flares, and the physical effects of specific diseases that produce visible damage to skin or joints are consequences of autoimmune diseases that can significantly contribute to social isolation and affect quality of life. The directionality of effects of inflammation, depression, fatigue, and disease expression is an area requiring additional research (Lee and Giuliani, 2019a; Vallerand et al., 2018).

Finding: Autoimmune diseases are associated with an increased risk of cancer.

Conclusion: Additional research is needed to characterize the roles of chronic inflammation, prolonged use of immunosuppressant agents, and common risk factors in increased cancer risk in persons with autoimmune disease. In addition, there is a need for research to obtain a greater understanding of how best to treat patients with autoimmune disease and cancer.

Finding: Fatigue and depression or depressive symptoms commonly occur in individuals with autoimmune diseases; their etiology is unclear. There are no long-lasting treatments for fatigue. Both can greatly affect quality of life.

Conclusion: Additional research is needed to understand the directionality of effects of inflammation, depression, fatigue, and disease expression in persons with autoimmune diseases.

Estimates of Economic Impact

Few studies have estimated the direct and indirect costs of specific autoimmune diseases in the United States, and the committee is not aware of any studies attempting to estimate the overall costs of these conditions. The limited information that is available on the economic impact of specific autoimmune diseases is discussed above and in Chapter 3. The available evidence, while limited in scope, supports the notion that the direct and indirect costs of autoimmune diseases can be high (Adelman et al., 2013; Birnbaum et al., 2010; Vanderpuye-Orgle et al., 2015).

Finding: There are little data on the direct and indirect costs in the United States of specific autoimmune diseases and of autoimmune diseases overall.

THE LIFE-COURSE FRAMEWORK AND AUTOIMMUNE DISEASES

The life-course framework for health research is highly relevant for the study of autoimmune diseases. This framework emphasizes understanding how early life exposures—factors such as environmental toxicants or psychological stressors that are associated with an outcome—and timing of these exposures influence health along the life stages (Ben-Shlomo and Kuh, 2002; Jacob et al., 2017; Liu et al., 2010; Lynch and Smith, 2005), both at a population and individual patient level. This approach highlights the importance of conceptualizing autoimmune diseases as a result of social and environmental factors, or exposures, experienced at different points, from the in utero period, through childhood and adolescence, and on to young, mid-, and older adulthood (Figure 2-6).

FIGURE 2-6

Exposures across the lifespan impact life-long health, which highlights the importance of a life-course approach to health. SOURCE: Adapted with permission from National Institute of Environmental Health Sciences.

Examples of environmental exposures are toxicants and viruses, and examples of social exposures are stressors such as poverty, abuse, and discrimination. The multidisciplinary life-course framework enables examination of how these social and environmental determinants of health throughout the life stages can differentially affect biological processes to influence the development and the course of chronic diseases. For example, data from the longitudinal World Trade Center Health Registry show an increased risk for developing systemic autoimmune disease following exposure to dust and traumatic experiences from the September 11, 2001, terrorist attack (Miller-Archie et al., 2020). Additionally, data from the Nurses’ Health Study II, a large longitudinal cohort of U.S. female nurses, show an increased risk of developing SLE in those with exposure to childhood physical and emotional abuse (Feldman et al., 2019).

The epidemiologic study of autoimmune diseases using a life-course framework emphasizes a longitudinal approach inclusive of all life stages, linking a multiplicity of exposures across the life course to later health outcomes. It also emphasizes attention to the inter-relationships of these exposures and vulnerable developmental time periods. For example, findings from the National Institute of Environmental Health Sciences-funded Sister Study Cohort (Parks et al., 2016) showed that the early life factors of preterm birth and childhood pesticide exposure were associated with development of SLE in adulthood. Additional aspects for chronic autoimmune diseases in particular include the fluctuation of disease activity over periods of flare and remission, as well as the accumulation of permanent organ damage over time resulting from inflammation. Accounting for these complexities often presents methodological challenges for modeling repeat observations, hierarchical data, latent exposures, and multiple interactive effects (Kuh et al., 2003). Researchers have used complex analytic models, such as multi-level models, latent growth models, and Markov models in studying chronic diseases, and they are highly useful for understanding complex autoimmune diseases.

While researchers have applied the life-course framework to the epidemiologic study of populations, it is also useful for studying disease at the individual level (Halfon and Hochstein, 2002). Measuring the effect of socio-environmental factors on individuals with autoimmune disease across time and critical developmental periods increases the understanding of disease mechanisms, trajectories, and heterogeneity. This is of particular relevance to studying autoimmune diseases because they typically evolve over time, and a given disease can manifest differently from patient to patient. To understand the mechanisms underlying development and course of autoimmune diseases, it is important to characterize changes in biologic structure and function across the lifespan, and how genetic, social, and environmental factors cause deviation in expected biologic trajectories of typical development (Hardy and O’Neill, 2020). These trajectories may be non-linear, reflecting critical exposure periods, differential impacts across time and biologic structures, and the biologic impact of cumulative exposures. To increase knowledge of autoimmune disease and develop treatments, long-term systems for data collection and complex analytic approaches are necessary to model these aspects of disease mechanisms and trajectories within and across individuals and to elucidate the heterogeneity present within diseases.

Several implications arise from incorporating a life-course approach for studying autoimmune diseases:

• This approach requires longitudinal studies that incorporate children and adult populations, with particular attention to critical life periods for the effects of inflammation and disease damage.
• Methodological expertise is critical for modeling the issues of time, timing, and inter-relationship of exposures in relation to disease mechanisms and outcomes.
• A team science approach is key to bringing together multidisciplinary expertise in genetics and biology, social and environmental factors, life stages, and other relevant knowledge areas.
• Although the life-course approach involves epidemiology at the population level, it is also relevant to understanding disease processes at the individual patient level. It therefore provides understanding of opportunities for development of clinical treatments and behavioral interventions, as well as policy changes aimed at both prevention and provision of interventions.

Finding: A life-course approach to the epidemiological study of autoimmune disease could involve longitudinal studies that incorporate children and adult populations, enable modeling of the issues of time, timing, and inter-relationship of exposures in relation to disease mechanisms and outcomes, and engage multidisciplinary expertise in genetics and biology, social and environmental factors, life stages, and other relevant knowledge areas. Such an approach could better characterize the disease processes of autoimmune diseases, conditions that can affect individuals at any age and that are chronic, heterogeneous, and may involve flare and remission.

SUMMARY AND RESEARCH IMPLICATIONS

Autoimmunity arises when the immune system fails to distinguish self from non-self. This can result, over time, in disease conditions involving pathological tissue damage caused by autoreactive T cells and autoantibodies. Both the innate and adaptive immune systems are involved in promoting autoimmune disease, and genetics, social and environmental exposures, and sex differences may contribute to the development or exacerbation of autoimmune diseases.

There is no consensus definition of autoimmune disease. For more than 50 years, clinical criteria such as specific autoantibodies and symptoms have been used to characterize and classify autoimmune diseases. More recently, insights from research on biologic mechanisms have revealed commonalities between autoimmune diseases and autoinflammatory diseases, as well as other diseases that are not considered to be autoimmune diseases, making the definition less clear-cut. The two different approaches to characterize and understand autoimmune diseases each have advantages. Defining autoimmune diseases according to biological mechanisms may be useful in developing interventions and treatment, particularly when the mechanisms are shared across diseases. Characterizing autoimmune diseases by clinical phenotype alone, however, can impact patient care and impede research. An atypical presentation of an autoimmune disease, for example, could slow its diagnosis and treatment, or result in the person with the disease being excluded from a clinical trial when their inclusion might provide insight into the disease.

Incidence and prevalence data for autoimmune diseases in the United States are limited and not easily accessible. The last study that considered the prevalence of autoimmune diseases as a whole in the United States estimated a 7.6 to 9.4 percent prevalence of these conditions, but the study focused on just 29 autoimmune diseases and was published more than a decade ago (Cooper et al., 2009). Among the most common autoimmune diseases are celiac disease, rheumatoid arthritis, psoriasis, IBD, and type 1 diabetes. A critical limitation is the lack of population-based data from diverse populations that would enable researchers to accurately assess the incidence, prevalence, lifetime risk, and epidemiologic trends of autoimmune diseases in the U.S. population as well as extent of their impact.

Many, but not all, autoimmune diseases predominantly affect women, with some female-to-male incidence ratios equaling 6:1 or greater. Exceptions include type 1 diabetes and myocarditis, which occur more often in males (Coronado et al., 2019; Fairweather et al., 2013). No single pattern of racial and ethnic disparities is seen in incidence or prevalence among autoimmune diseases; for some conditions, the highest rates occur among Black, American Indian, and Alaska Native populations, while for others, the highest rates occur in White populations (Izmirly et al., 2021b). Researchers have also observed disparities in the severity and prognosis of autoimmune diseases according to race and ethnicity (Barton et al., 2011; Lim et al., 2019; Ventura et al., 2017). Research is needed to identify the reasons for these and other disparities. Autoimmune diseases display varied age-of-onset patterns, with some occurring primarily in children, teens, and young adults, such as type 1 diabetes, and others occurring more commonly through adulthood or reaching the highest incidence after age 60, such as primary Sjögren’s disease.

Autoimmune diseases are heterogeneous and long-lasting conditions. The impact on physical health—which can include pain and fatigue, an increased risk of developing a wide variety of other conditions, impaired growth and development, disfigurement, disability, functional impairment, and death—is substantial. Having an autoimmune disease may carry an increased risk of cancer (Anderson et al., 2009; Axelrad et al., 2016; Chiesa Fuxench et al., 2016); research is needed to establish how best to treat the patient. Autoimmune diseases can have adverse effects on social interaction and development, mental health, the capacity to have children, and education and employment.

Economic-impact research is inadequate, but available data indicate that the direct and indirect costs of autoimmune diseases can be high. Accurate mortality data are also lacking, one reason being that death certificates may not provide complete information on the autoimmune disease that contributed to death (Calvo-Alén et al., 2005; Molina et al., 2015).

The study of co-occurring autoimmune diseases in individuals has focused largely on multiple sclerosis, rheumatoid arthritis, autoimmune thyroiditis, type 1 diabetes, and IBD, with several combinations occurring at greater than expected rates. A broader understanding of the patterns of coexisting autoimmune diseases, as well as of their underlying biologic mechanisms, could inform strategies for the prevention, early diagnosis, and treatment of subsequent autoimmune diseases in individuals with one autoimmune disease.

Finally, applying a life-course, multidisciplinary framework to longitudinal epidemiologic studies that include children and adults could provide insight into issues involving exposures and timing that play a role in the etiology, mechanisms, and course and outcomes of these highly variable diseases.

REFERENCES

• AARDA (American Autoimmune Related Diseases Association). AARDA survey study. Eastpointe, MI: American Autoimmune Related Diseases Association; 2017. [July 8, 2021]. https://www​.aarda.org​/wp-content/uploads​/5yr-Survey-Study-REPORT-updated-2017​.pdf .
• Abbas AK, Lohr J, Knoechel B, Nagabhushanam V. T cell tolerance and autoimmunity. Autoimmunity Reviews. 2004;3(7-8):471–475. https://doi​.org/10.1016/j​.autrev.2004.07.004 . [PubMed: 15546793]
• Abramson O, Durant M, Mow W, Finley A, Kodali P, Wong A, Tavares V, McCroskey E, Liu L, Lewis JD, Allison JE, Flowers N, Hutfless S, Velayos FS, Perry GS, Cannon R, Herrinton LJ. Incidence, prevalence, and time trends of pediatric inflammatory bowel disease in northern California, 1996 to 2006. Journal of Pediatrics. 2010;157(2):233–239. e231. https://doi​.org/10.1016/j​.jpeds.2010.02.024 . [PubMed: 20400099]
• Adelman G, Rane SG, Villa KF. The cost burden of multiple sclerosis in the United States: A systematic review of the literature. Journal of Medical Economics. 2013;16(5):639–647. https://doi​.org/10.3111/13696998​.2013.778268 . [PubMed: 23425293]
• Aggarwal R, Anaya J-M, Koelsch KA, Kurien BT, Scofield RH. Association between secondary and primary Sjögren’s syndrome in a large collection of lupus families. Autoimmune Diseases. 2015a;2015:298506. https://doi​.org/10.1155/2015/298506 . [PMC free article: PMC4515287] [PubMed: 26246904]
• Aggarwal R, Ringold S, Khanna D, Neogi T, Johnson SR, Miller A, Brunner HI, Ogawa R, Felson D, Ogdie A, Aletaha D, Feldman BM. Distinctions between diagnostic and classification criteria? Arthritis Care & Research. 2015b;67(7):891–897. https://doi​.org/10.1002/acr.22583 . [PMC free article: PMC4482786] [PubMed: 25776731]
• Albuquerque BC, Salles VB, Tajra RDdP, Rodrigues CEM. Outcome and prognosis of patients with lupus nephritis submitted to renal transplantation. Scientific Reports. 2019;9(1):11611. https://doi​.org/10.1038​/s41598-019-48070-y . [PMC free article: PMC6690950] [PubMed: 31406264]
• American Board of Medical Specialties. Specialty and subspecialty certificates. [January 26, 2022]. n.d. https://www​.abms.org​/member-boards/specialty-subspecialty-certificates .
• American College of Rheumatology. Criteria. [January 26, 2022]. https://www​.rheumatology​.org/PracticeQuality​/Clinical-Support/Criteria .
• Anaya JM. Common mechanisms of autoimmune diseases (the autoimmune tautology). Autoimmunity Reviews. 2012;11(11):781–784. https://doi​.org/10.1016/j​.autrev.2012.02.002 . [PubMed: 22353402]
• Anderson LA, Gadalla S, Morton LM, Landgren O, Pfeiffer R, Warren JL, Berndt SI, Ricker W, Parsons R, Engels EA. Population-based study of autoimmune conditions and the risk of specific lymphoid malignancies. International Journal of Cancer. 2009;125(2):398–405. https://doi​.org/10.1002/ijc.24287 . [PMC free article: PMC2692814] [PubMed: 19365835]
• Asgari MM, Wu JJ, Gelfand JM, Salman C, Curtis JR, Harrold LR, Herrinton LJ. Validity of diagnostic codes and prevalence of psoriasis and psoriatic arthritis in a managed care population, 1996-2009. Pharmacoepidemiology and Drug Safety. 2013;22(8):842–849. https://doi​.org/10.1002/pds.3447 . [PMC free article: PMC3720770] [PubMed: 23637091]
• Autoimmune Association. Autoimmune disease list. 2021. [November 29, 2021]. https://autoimmune​.org/about-us .
• Autoimmune Registry Inc. The autoimmune diseases. 2020. [April 12, 2021]. https://www​.autoimmuneregistry​.org/autoimmune-diseases .
• Autoimmune Registry, Inc. About Autoimmune Registry, Inc. 2021. [June 22, 2021]. https://www​.autoimmuneregistry​.org/about-us .
• Axelrad JE, Lichtiger S, Yajnik V. Inflammatory bowel disease and cancer: The role of inflammation, immunosuppression, and cancer treatment. World Journal of Gastroenterology. 2016;22(20):4794–4801. https://doi​.org/10.3748/wjg.v22.i20.4794 . [PMC free article: PMC4873872] [PubMed: 27239106]
• Baer AN, Maynard JW, Shaikh F, Magder LS, Petri M. Secondary Sjögren’s syndrome in systemic lupus erythematosus defines a distinct disease subset. Journal of Rheumatology. 2010;37(6):1143–1149. https://doi​.org/10.3899/jrheum.090804 . [PubMed: 20360189]
• Bailey ZD, Feldman JM, Bassett MT. How structural racism works - racist policies as a root cause of U.S. racial health inequities. New England Journal of Medicine. 2021;384(8):768–773. https://doi​.org/10.1056/NEJMms2025396 . [PubMed: 33326717]
• Bandeira M, Buratti S, Bartoli M, Gasparini C, Breda L, Pistorio A, Grassi S, Alpigiani MG, Barbano G, Janz-Junior LL, Martini A, Ravelli A. Relationship between damage accrual, disease flares and cumulative drug therapies in juvenile-onset systemic lupus erythematosus. Lupus. 2006;15(8):515–520. https://doi​.org/10.1191​/0961203306lu2316oa . [PubMed: 16942004]
• Barnabe C, Joseph L, Belisle P, Labrecque J, Edworthy S, Barr SG, Fritzler M, Svenson LW, Hemmelgarn B, Bernatsky S. Prevalence of systemic lupus erythematosus and systemic sclerosis in the first nations population of Alberta, Canada. Arthritis Care & Research. 2012;64(1):138–143. https://doi​.org/10.1002/acr.20656 . [PubMed: 21972194]
• Barnado A, Casey C, Carroll RJ, Wheless L, Denny JC, Crofford LJ. Developing electronic health record algorithms that accurately identify patients with systemic lupus erythematosus. Arthritis Care & Research. 2017;69(5):687–693. https://doi​.org/10.1002/acr.22989 . [PMC free article: PMC5219863] [PubMed: 27390187]
• Barton JL, Trupin L, Schillinger D, Gansky SA, Tonner C, Margaretten M, Chernitskiy V, Graf J, Imboden J, Yelin E. Racial and ethnic disparities in disease activity and function among persons with rheumatoid arthritis from university-affiliated clinics. Arthritis Care & Research. 2011;63(9):1238–1246. https://doi​.org/10.1002/acr.20525 . [PMC free article: PMC3169768] [PubMed: 21671414]
• Bastard P, Rosen LB, Zhang Q, Michailidis E, Hoffmann HH, Zhang Y, Dorgham K, Philippot Q, Rosain J. Autoantibodies against type I IFNs in patients with life-threatening COVID-19. Science. 2020;370(6515):eabd4585. [PMC free article: PMC7857397] [PubMed: 32972996]
• Beck DB, Ferrada MA, Sikora KA, Ombrello AK, Collins JC, Pei W, Balanda N, Ross DL, Ospina Cardona D, Wu Z, Patel B, Manthiram K, Groarke EM, Gutierrez-Rodrigues F, Hoffmann P, Rosenzweig S, Nakabo S, Dillon LW, Hourigan CS, Tsai WL, Gupta S, Carmona-Rivera C, Asmar AJ, Xu L, Oda H, Goodspeed W, Barron KS, Nehrebecky M, Jones A, Laird RS, Deuitch N, Rowczenio D, Rominger E, Wells KV, Lee CR, Wang W, Trick M, Mullikin J, Wigerblad G, Brooks S, Dell’Orso S, Deng Z, Chae JJ, Dulau-Florea A, Malicdan MCV, Novacic D, Colbert RA, Kaplan MJ, Gadina M, Savic S, Lachmann HJ, Abu-Asab M, Solomon BD, Retterer K, Gahl WA, Burgess SM, Aksentijevich I, Young NS, Calvo KR, Werner A, Kastner DL, Grayson PC. Somatic mutations in uba1 and severe adult-onset autoinflammatory disease. New England Journal of Medicine. 2020;383(27):2628–2638. https://doi​.org/10.1056/NEJMoa2026834 . [PMC free article: PMC7847551] [PubMed: 33108101]
• Beko E, Pervaiz S, Nanda V, Dhawan S. Long-term follow-up of patients with diffuse fasciitis and eosinophilia associated with l-tryptophan ingestion. Cutis. 1993;51(4):266–270. [PubMed: 8477608]
• Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: Conceptual models, empirical challenges and interdisciplinary perspectives. International Journal of Epidemiology. 2002;31(2):285–293. https://doi​.org/10.1093/ije/31.2.285 . [PubMed: 11980781]
• Bewtra M, Kaiser LM, TenHave T, Lewis JD. Crohn’s disease and ulcerative colitis are associated with elevated standardized mortality ratios: A meta-analysis. Inflammatory Bowel Diseases. 2013;19(3):599–613. https://doi​.org/10.1097/MIB​.0b013e31827f27ae . [PMC free article: PMC3755276] [PubMed: 23388544]
• Birnbaum H, Pike C, Kaufman R, Maynchenko M, Kidolezi Y, Cifaldi M. Societal cost of rheumatoid arthritis patients in the US. Current Medical Research and Opinion. 2010;26(1):77–90. https://doi​.org/10.1185​/03007990903422307 . [PubMed: 19908947]
• Blomgren SE, Condemi JJ, Vaughan JH. Procainamide-induced lupus erythematosus. The American Journal of Medicine. 1972;52(3):338–348. https://doi​.org/10.1016​/0002-9343(72)90021-6 . [PubMed: 4536815]
• Boehmer TK, Kompaniyets L, Lavery AM, Hsu J, Ko JY, Yusuf H, Romano SD, Gundlapalli AV, Oster ME, Harris AM. Association between COVID-19 and myocarditis using hospital-based administrative data—United States, March 2020–January 2021. Morbidity and Mortality Weekly Report. 2021;70(35):1228–1232. [PMC free article: PMC8422872] [PubMed: 34473684]
• Brent L, Cohen IR, Doherty PC, Feldmann M, Matzinger P, Ghost L, Holgate ST, Lachmann P, Mitchison NA, Nossal G, Rose NR, Zinkernagel R. Crystal-ball gazing--the future of immunological research viewed from the cutting edge. Clinical & Experimental Immunology. 2007;147(1):1–10. https://doi​.org/10.1111/j​.1365-2249.2006.03234.x . [PMC free article: PMC1810455] [PubMed: 17177957]
• Broten L, Aviña-Zubieta JA, Lacaille D, Joseph L, Hanly JG, Lix L, O’Donnell S, Barnabe C, Fortin PR, Hudson M, Jean S, Peschken C, Edworthy SM, Svenson L, Pineau CA, Clarke AE, Smith M, Bélisle P, Badley EM, Bergeron L, Bernatsky S. Systemic autoimmune rheumatic disease prevalence in Canada: Updated analyses across 7 provinces. Journal of Rheumatology. 2014;41(4):673–679. [PubMed: 24584928]
• Bouman A, Heineman MJ, Faas MM. Sex hormones and the immune response in humans. Human Reproduction Update. 2005;11(4):411–423. [PubMed: 15817524]
• Bruno KA, Mathews JE, Yang AL, Frisancho JA, Scott AJ, Greyner HD, Molina FA, Greenaway MS, Cooper GM, Bucek A, Morales-Lara AC, Hill AR, Mease AA, Di Florio DN, Sousou JM, Coronado AC, Stafford AR, Fairweather D. BPA alters estrogen receptor expression in the heart after viral infection activating cardiac mast cells and T cells leading to perimyocarditis and fibrosis. Frontiers in Endocrinology. 2019;10:598. https://doi​.org/10.3389/fendo.2019.00598 . [PMC free article: PMC6737078] [PubMed: 31551929]
• Buskiewicz IA, Huber SA, Fairweather D. Sex hormone receptor expression in the immune system. In: Neigh G, Mitzelfelt M, editors. Sex differences in physiology. London, UK: Academic Press; 2016. pp. 45–60.
• Calvo-Alén J, Alarcón GS, Campbell JrR, Fernández M, Reveille JD, Cooper GS. Lack of recording of systemic lupus erythematosus in the death certificates of lupus patients. Rheumatology (Oxford, England). 2005;44(9):1186–1189. https://doi​.org/10.1093​/rheumatology/keh717 . [PubMed: 15956088]
• Carey EJ, Ali AH, Lindor KD. Primary biliary cirrhosis. Lancet. 2015;386:1565–1575. https://doi​.org/10.1016​/S0140-6736(15)00154-3 . [PubMed: 26364546]
• Carroll RJ, Thompson WK, Eyler AE, Mandelin AM, Cai T, Zink RM, Pacheco JA, Boomershine CS, Lasko TA, Xu H, Karlson EW, Perez RG, Gainer VS, Murphy SN, Ruderman EM, Pope RM, Plenge RM, Kho AN, Liao KP, Denny JC. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. Journal of the American Medical Informatics Association. 2012;19(e1):e162–169. https://doi​.org/10.1136​/amiajnl-2011-000583 . [PMC free article: PMC3392871] [PubMed: 22374935]
• Cartee AK, Owens LA, Lahr BD, Yawn BP, Murray JA, Kudva YC. Incidence of type 1 diabetes is not increasing in a population-based cohort in Olmsted County, Minnesota, USA. Mayo Clinic Proceedings. 2016;91(8):1066–1073. https://doi​.org/10.1016/j​.mayocp.2016.05.019 . [PMC free article: PMC5025795] [PubMed: 27492913]
• Castro-Correia C, Correia-Sa L, Norberto S, Delerue-Matos C, Domingues V, Costa-Santos C, Fontoura M, Calhau C. Phthalates and type 1 diabetes: Is there any link? Environmental Science and Pollution Research International. 2018;25(18):17915–17919. https://doi​.org/10.1007​/s11356-018-1997-z . [PMC free article: PMC6028856] [PubMed: 29680886]
• Chae DH, Martz CD, Fuller-Rowell TE, Spears EC, Smith TTG, Hunter EA, Drenkard C, Lim SS. Racial discrimination, disease activity, and organ damage: The Black women’s experiences living with lupus (BeWELL) study. American Journal of Epidemiology. 2019;188(8):1434–1443. https://doi​.org/10.1093/aje/kwz105 . [PMC free article: PMC6670046] [PubMed: 31062841]
• Chaplin DD. Overview of the immune response. Journal of Allergy and Clinical Immunology. 2010;125(2)(Suppl 2):S3–23. https://doi​.org/10.1016/j​.jaci.2009.12.980 . [PMC free article: PMC2923430] [PubMed: 20176265]
• Chen Y, Wang T, Liu X, Shankar RR. Prevalence of type 1 and type 2 diabetes among US pediatric population in the MarketScan Multi-State Database, 2002 to 2016. Pediatric Diabetes. 2019;20(5):523–529. https://doi​.org/10.1111/pedi.12842 . [PubMed: 30861241]
• Chiesa Fuxench ZC, Shin DB, Ogdie Beatty A, Gelfand JM. The risk of cancer in patients with psoriasis: A population-based cohort study in the health improvement network. JAMA Dermatology. 2016;152(3):282–290. https://doi​.org/10.1001/jamadermatol​.2015.4847 . [PMC free article: PMC5273859] [PubMed: 26676102]
• Cho JH, Feldman M. Heterogeneity of autoimmune diseases: Pathophysiologic insights from genetics and implications for new therapies. Nature Medicine. 2015;21(7):730–738. https://doi​.org/10.1038/nm.3897 . [PMC free article: PMC5716342] [PubMed: 26121193]
• Ciccarelli F, De Martinis M, Ginaldi L. An update on autoinflammatory diseases. Current Medicinal Chemistry. 2014;21(3):261–269. https://doi​.org/10.2174​/09298673113206660303 . [PMC free article: PMC3905709] [PubMed: 24164192]
• Cohen R, Robinson JrD, Paramore C, Fraeman K, Renahan K, Bala M. Autoimmune disease concomitance among inflammatory bowel disease patients in the United States, 2001-2002. Inflammatory Bowel Diseases. 2008;14(6):738–743. https://doi​.org/10.1002/ibd.20406 . [PubMed: 18300281]
• Cooper GS, Bynum MLK, Somers EC. Recent insights in the epidemiology of autoimmune diseases: Improved prevalence estimates and understanding of clustering of diseases. Journal of Autoimmunity. 2009;33(3–4):197–207. https://doi​.org/10.1016/j​.jaut.2009.09.008 . [PMC free article: PMC2783422] [PubMed: 19819109]
• Coronado MJ, Bruno KA, Blauwet LA, Tschöpe C, Cunningham MW, Pankuweit S, van Linthout S, Jeon E-S, McNamara DM, Krejčí J, Bienertová-Vašků J, Douglass EJ, Abston ED, Bucek A, Frisancho JA, Greenaway MS, Hill AR, Schultheiss H-P, Cooper LT Jr, Fairweather D. Elevated sera sST2 is associated with heart failure in men ≤50 years old with myocarditis. Journal of the American Heart Association. 2019;8(2):e008968. https://doi​.org/10.1161/jaha.118.008968 . [PMC free article: PMC6497352] [PubMed: 30638108]
• Crow YJ, Rehwinkel J. Aicardi-Goutieres syndrome and related phenotypes: Linking nucleic acid metabolism with autoimmunity. Human Molecular Genetics. 2009;18(R2):R130–R136. https://doi​.org/10.1093/hmg/ddp293 . [PMC free article: PMC2758706] [PubMed: 19808788]
• Crowson CS, Matteson EL, Myasoedova E, Michet CJ, Ernste FC, Warrington KJ, M. Davis J 3rd, Hunder GG, Therneau TM, Gabriel SE. The lifetime risk of adult-onset rheumatoid arthritis and other inflammatory autoimmune rheumatic diseases. Arthritis and Rheumatism. 2011;63(3):633–639. [PMC free article: PMC3078757] [PubMed: 21360492]
• Culpepper WJ, Marrie RA, Langer-Gould A, Wallin MT, Campbell JD, Nelson LM, Kaye WE, Wagner L, Tremlett H, Chen LH, Leung S, Evans C, Yao S, LaRocca NG., on behalf of the United States Multiple Sclerosis Prevalence Workgroup (MSPWG). Validation of an algorithm for identifying MS cases in administrative health claims datasets. Neurology. 2019;92(10):e1016–e1028. https://doi​.org/10.1212/WNL​.0000000000007043 . [PMC free article: PMC6442008] [PubMed: 30770432]
• Dabelea D, Mayer-Davis EJ, Saydah S, Imperatore G, Linder B, Divers J, Bell R, Badaru A, Talton JW, Crume T, Liese AD, Merchant AT, Lawrence JM, Reynolds K, Dolan L, Liu LL, Hamman RF., Search for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778–1786. https://doi​.org/10.1001/jama.2014.3201 . [PMC free article: PMC4368900] [PubMed: 24794371]
• Dahlhamer JM, Zammitti EP, Ward BW, Wheaton AG, Croft JB. Prevalence of inflammatory bowel disease among adults aged ≥18 years—United States, 2015. MMWR: Morbidity and Mortality Weekly Report. 2016;65(42):1166–1169. [PubMed: 27787492]
• Dall’Era M, Cisternas MG, Snipes K, Herrinton LJ, Gordon C, Helmick CG. The incidence and prevalence of systemic lupus erythematosus in San Francisco County, California: The California Lupus Surveillance Project. Arthritis & Rheumatology. 2017;69(10):1996–2005. [PubMed: 28891237]
• de Jonge H, Iamele L, Maggi M, Pessino G, Scotti C. Anti-cancer auto-antibodies: Roles, applications and open issues. Cancers. 2021;13(4) https://doi​.org/10.3390/cancers13040813 . [PMC free article: PMC7919283] [PubMed: 33672007]
• Desai MK, Brinton RD. Autoimmune disease in women: Endocrine transition and risk across the lifespan. Frontiers in Endocrinology. 2019;10:265. https://doi​.org/10.3389/fendo.2019.00265 . [PMC free article: PMC6501433] [PubMed: 31110493]
• Duarte-Garcia A, Pham MM, Crowson CS, Amin S, Moder KG, Pruthi RK, Warrington KJ, Matteson EL. The epidemiology of antiphospholipid syndrome: A population-based study. Arthritis & Rheumatology. 2019;71(9):1545–1552. https://doi​.org/10.1002/art.40901 . [PMC free article: PMC6717037] [PubMed: 30957430]
• Durante A, Bronzato S. The increased cardiovascular risk in patients affected by autoimmune diseases: Review of the various manifestations. Journal of Clinical Medicine Research. 2015;7(6):379–384. https://doi​.org/10.14740/jocmr2122w . [PMC free article: PMC4394909] [PubMed: 25883699]
• Eaton WW, Rose NR, Kalaydjian A, Pedersen MG, Mortensen PB. Epidemiology of autoimmune diseases in Denmark. Journal of Autoimmunity. 2007;29(1):1–9. https://doi​.org/10.1016/j​.jaut.2007.05.002 . [PMC free article: PMC2717015] [PubMed: 17582741]
• Eberhardt K, Larsson B-M, Nived K, Lindqvist E. Work disability in rheumatoid arthritis—development over 15 years and evaluation of predictive factors over time. Journal of Rheumatology. 2007;34(3):481–487. [PubMed: 17299844]
• Eckert L, Gupta S, Amand C, Gadkari A, Mahajan P, Gelfand JM. Impact of atopic dermatitis on health-related quality of life and productivity in adults in the United States: An analysis using the national health and wellness survey. Journal of the American Academy of Dermatology. 2017;77(2):274–279. e273. https://doi​.org/10.1016/j​.jaad.2017.04.019 . [PubMed: 28606711]
• Eder L, Widdifield J, Rosen CF, Cook R, Lee K-A, Alhusayen R, Paterson MJ, Cheng SY, Jabbari S, Campbell W, Bernatsky S, Gladman DD, Tu K. Trends in the prevalence and incidence of psoriasis and psoriatic arthritis in Ontario, Canada: A population-based study. Arthritis Care & Research. 2019;71(8):1084–1091. [PubMed: 30171803]
• Edwards M, Dai R, Ahmed SA. Our environment shapes us: The importance of environment and sex differences in regulation of autoantibody production. Frontiers in Immunology. 2018;9:478. https://doi​.org/10.3389/fimmu.2018.00478 . [PMC free article: PMC5890161] [PubMed: 29662485]
• Edwards MR, Dai R, Heid B, Cowan C, Werre SR, Cecere T, Ahmed SA. Low-dose 17α-ethinyl estradiol (EE) exposure exacerbates lupus renal disease and modulates immune responses to TLR7/9 agonists in genetically autoimmune-prone mice. Scientific Reports. 2020;10(1):5210. https://doi​.org/10.1038​/s41598-020-62124-6 . [PMC free article: PMC7090002] [PubMed: 32251357]
• Eriksson JK, Neovius M, Ernestam S, Lindblad S, Simard JF, Askling J. Incidence of rheumatoid arthritis in Sweden: A nationwide population-based assessment of incidence, its determinants, and treatment penetration. Arthritis Care & Research. 2013;65(6):870–878. https://doi​.org/10.1002/acr.21900 . [PubMed: 23281173]
• Fagundes CP, Glaser R, Kiecolt-Glaser JK. Stressful early life experiences and immune dysregulation across the lifespan. Brain, Behavior, and Immunity. 2013;27(1):8–12. https://doi​.org/10.1016/j​.bbi.2012.06.014 . [PMC free article: PMC3518756] [PubMed: 22771426]
• Fairweather D. Sex differences in inflammation during atherosclerosis. Clinical Medicine Insights: Cardiology. 2014;8(Suppl 3):49–59. https://doi​.org/10.4137/CMC.S17068 . [PMC free article: PMC4405090] [PubMed: 25983559]
• Fairweather D, Cooper LT Jr, Blauwet LA. Sex and gender differences in myocarditis and dilated cardiomyopathy. Current Problems in Cardiology. 2013;38(1):7–46. https://doi​.org/10.1016/j​.cpcardiol.2012.07.003 . [PMC free article: PMC4136454] [PubMed: 23158412]
• Feldman CH, Malspeis S, Leatherwood C, Kubzansky L, Costenbader KH, Roberts AL. Association of childhood abuse with incident systemic lupus erythematosus in adulthood in a longitudinal cohort of women. Journal of Rheumatology. 2019;46(12):1589–1596. https://doi​.org/10.3899/jrheum.190009 . [PMC free article: PMC6856423] [PubMed: 31092723]
• Gebhard C, Regitz-Zagrosek V, Neuhauser HK, Morgan R, Klein SL. Impact of sex and gender on COVID-19 outcomes in Europe. Biology of Sex Differences. 2020;11(1):29. https://doi​.org/10.1186​/s13293-020-00304-9 . [PMC free article: PMC7247289] [PubMed: 32450906]
• Gelpí E, de la Paz MP, Terracini B, Abaitua I, de la Cámara AG, Kilbourne EM, Lahoz C, Nemery B, Philen RM, Soldevilla L, Tarkowski S., WHO/CISAT Scientific Committee for the Toxic Oil Syndrome. The Spanish toxic oil syndrome 20 years after its onset: A multidisciplinary review of scientific knowledge. Environmental Health Perspectives. 2002;110(5):457–464. https://doi​.org/10.1289/ehp.110-1240833 . [PMC free article: PMC1240833] [PubMed: 12003748]
• Gianfrancesco MA, Dall’Era M, Murphy LB, Helmick CG, Li J, Rush S, Trupin L, Yazdany J. Mortality among minority populations with systemic lupus erythematosus, including Asian and Hispanic/Latino persons—California, 2007–2017. MMWR: Morbidity and Mortality Weekly Report. 2021;70(7):236–239. https://doi​.org/10.15585/mmwr.mm7007a2 . [PMC free article: PMC7891689] [PubMed: 33600382]
• Gokuladhas S, Schierding W, Golovina E, Fadason T, O’Sullivan J. Unravelling the shared genetic mechanisms underlying 18 autoimmune diseases using a systems approach. Frontiers in Immunology. 2021;12:693142. https://doi​.org/10.3389/fimmu​.2021.693142 . [PMC free article: PMC8415031] [PubMed: 34484189]
• Gutierrez-Suarez R, Ruperto N, Gastaldi R, Pistorio A, Felici E, Burgos-Vargas R, Martini A, Ravelli A. A proposal for a pediatric version of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index based on the analysis of 1,015 patients with juvenile-onset systemic lupus erythematosus. Arthritis and Rheumatism. 2006;54(9):2989–2996. [PubMed: 16947634]
• Guzman J, Kerr T, Ward LM, Ma J, Oen K, Rosenberg AM, Feldman BM, Boire G, Houghton K, Dancey P, Scuccimarri R, Bruns A, Huber AM, Watanabe Duffy K, Shiff NJ, Berard RA, Levy DM, Stringer E, Morishita K, Johnson N, Cabral DA, Larche M, Petty RE, Laxer RM, Silverman E, Miettunen P, Chetaille AL, Haddad E, Spiegel L, Turvey SE, Schmeling H, Lang B, Ellsworth J, Ramsey SE, Roth J, Campillo S, Benseler S, Chedeville G, Schneider R, Tse SML, Bolaria R, Gross K, Feldman D, Cameron B, Jurencak R, Dorval J, LeBlanc C, St Cyr C, Gibbon M, Yeung RSM, Duffy CM, Tucker LB. Growth and weight gain in children with juvenile idiopathic arthritis: Results from the reACCh-Out cohort. Pediatric Rheumatology Online Journal. 2017;15(1):68. https://doi​.org/10.1186​/s12969-017-0196-7 . [PMC free article: PMC5567720] [PubMed: 28830457]
• Halfon N, Hochstein M. Life course health development: An integrated framework for developing health, policy, and research. Milbank Quarterly. 2002;80(3):433–479. https://doi​.org/10.1111/1468-0009.00019 . [PMC free article: PMC2690118] [PubMed: 12233246]
• Hardy R, O’Neill D. Life course biological trajectories: Maximising the value of longitudinal studies. Annals of Human Biology. 2020;47(2):227–228. https://doi​.org/10.1080/03014460​.2020.1737732 . [PubMed: 32429757]
• Hargraves MM, Richmond H, Morton R. Presentation of two bone marrow elements; the tart cell and the l. E. Cell. Proceedings of the Staff Meetings of the Mayo Clinic. 1948;23(2):25–28. [PubMed: 18921142]
• Harrold LR, Salman C, Shoor S, Curtis JR, Asgari MM, Gelfand JM, Wu JJ, Herrinton LJ. Incidence and prevalence of juvenile idiopathic arthritis among children in a managed care population, 1996–2009. Journal of Rheumatology. 2013;40(7):1218–1225. https://doi​.org/10.3899/jrheum.120661 . [PMC free article: PMC5657479] [PubMed: 23588938]
• Harrold LR, Shan Y, Rebello S, Kramer N, Connolly SE, Alemao E, Kelly S, Kremer JM, Rosenstein ED. Prevalence of Sjögren’s syndrome associated with rheumatoid arthritis in the USA: An observational study from the Corrona registry. Clinical Rheumatology. 2020;39(6):1899–1905. https://doi​.org/10.1007​/s10067-020-05004-8 . [PMC free article: PMC7237400] [PubMed: 32130579]
• Haynes DC, Gershwin ME. The immunopathology of progressive systemic sclerosis (PSS). Seminars in Arthritis and Rheumatism. 1982;11(3):331–351. [PubMed: 6765289]
• Hedrich CM. Shaping the spectrum—from autoinflammation to autoimmunity. Clinical Immunology. 2016;165:21–28. [PubMed: 26948930]
• Heesen C, Böhm J, Reich C, Kasper J, Goebel M, Gold SM. Patient perception of bodily functions in multiple sclerosis: Gait and visual function are the most valuable. Multiple Sclerosis. 2008;14(7):988–991. https://doi​.org/10.1177/1352458508088916 . [PubMed: 18505775]
• Herrinton LJ, Liu L, Lafata JE, Allison JE, Andrade SE, Korner EJ, Chan KA, Platt R, Hiatt D, O’Connor S. Estimation of the period prevalence of inflammatory bowel disease among nine health plans using computerized diagnoses and outpatient pharmacy dispensings. Inflammatory Bowel Diseases. 2007;13(4):451–461. https://doi​.org/10.1002/ibd.20021 . [PubMed: 17219403]
• Herrinton LJ, Liu L, Lewis JD, Griffin PM, Allison J. Incidence and prevalence of inflammatory bowel disease in a northern California managed care organization, 1996–2002. The American Journal of Gastroenterology. 2008;103(8):1998–2006. https://doi​.org/10.1111/j​.1572-0241.2008.01960.x . [PubMed: 18796097]
• Heshin-Bekenstein M, Perl L, Hersh AO, von Scheven E, Yelin E, Trupin L, Yazdany J, Lawson EF. Final adult height of patients with childhood-onset systemic lupus erythematosus: A cross sectional analysis. Pediatric Rheumatology Online Journal. 2018;16(1):30. https://doi​.org/10.1186​/s12969-018-0239-8 . [PMC free article: PMC5913867] [PubMed: 29688869]
• Hou JK, Kramer JR, Richardson P, Mei M, El-Serag HB. The incidence and prevalence of inflammatory bowel disease among U.S. veterans: A national cohort study. Inflammatory Bowel Diseases. 2013;19(5):1059–1064. https://doi​.org/10.1097/MIB​.0b013e31828028ca . [PMC free article: PMC3972034] [PubMed: 23448789]
• Hussain YS, Hookham JC, Allahabadia A, Balasubramanian SP. Epidemiology, management and outcomes of Graves’ disease-real life data. Endocrine. 2017;56(3):568–578. https://doi​.org/10.1007​/s12020-017-1306-5 . [PMC free article: PMC5435772] [PubMed: 28478488]
• Icen M, Crowson CS, McEvoy MT, Dann FJ, Gabriel SE, Maradit Kremers H. Trends in incidence of adult-onset psoriasis over three decades: A population-based study. Journal of the American Academy of Dermatology. 2009;60(3):394–401. https://doi​.org/10.1016/j​.jaad.2008.10.062 . [PMC free article: PMC3028518] [PubMed: 19231638]
• Idée J-M, Fretellier N, Robic C, Corot C. The role of gadolinium chelates in the mechanism of nephrogenic systemic fibrosis: A critical update. Critical Reviews in Toxicology. 2014;44(10):895–913. https://doi​.org/10.3109/10408444​.2014.955568 . [PubMed: 25257840]
• IOM (Institute of Medicine). Multiple sclerosis: Current status and strategies for the future Washington. DC: National Academies Press; 2001. [PubMed: 25057543]
• Iwasaki A, Medzhitov R. Control of adaptive immunity by the innate immune system. Nature Immunology. 2015;16(4):343–353. https://doi​.org/10.1038/ni.3123 . [PMC free article: PMC4507498] [PubMed: 25789684]
• Izmirly PM, Wan I, Sahl S, Buyon JP, Belmont HM, Salmon JE, Askanase A, Bathon JM, Geraldino-Pardilla L, Ali Y, Ginzler EM, Putterman C, Gordon C, Helmick CG, Parton H. The incidence and prevalence of systemic lupus erythematosus in New York County (Manhattan), New York: The Manhattan Lupus Surveillance Program. Arthritis & Rheumatology. 2017;69(10):2006–2017. https://doi​.org/10.1002/art.40192 . [PMC free article: PMC11102806] [PubMed: 28891252]
• Izmirly PM, Buyon JP, Wan I, Belmont HM, Sahl S, Salmon JE, Askanase A, Bathon JM, Geraldino-Pardilla L, Ali Y, Ginzler EM, Putterman C, Gordon C, Helmick CG, Parton H. The incidence and prevalence of adult primary Sjögren’s syndrome in New York county. Arthritis Care & Research. 2019;71(7):949–960. https://doi​.org/10.1002/acr.23707 . [PMC free article: PMC6347539] [PubMed: 30044541]
• Izmirly PM, Ferucci ED, Somers EC, Wang L, Lim SS, Drenkard C, Dall’Era M, McCune WJ, Gordon C, Helmick C, Parton H. Incidence rates of systemic lupus erythematosus in the USA: Estimates from a meta-analysis of the Centers for Disease Control and Prevention National Lupus Registries. Lupus Science & Medicine. 2021a;8(1) https://doi​.org/10.1136​/lupus-2021-000614 . [PMC free article: PMC8685969] [PubMed: 34921094]
• Izmirly PM, Parton H, Wang L, McCune WJ, Lim SS, Drenkard C, Ferucci ED, Dall’Era M, Gordon C, Helmick CG, Somers EC. Prevalence of systemic lupus erythematosus in the United States: Estimates from a meta-analysis of the Centers for Disease Control and Prevention National Lupus Registries. Arthritis & Rheumatology. 2021b;73(6):991–996. https://doi​.org/10.1002/art.41632 . [PMC free article: PMC8169527] [PubMed: 33474834]
• Jacob CM, Baird J, Barker M, Cooper C, Hanson M. The importance of a life course approach to health: Chronic disease risk from preconception through adolescence and adulthood. Geneva, Switzerland: World Health Organization; 2017. [February 23, 2022]. https://www​.who.int/life-course​/publications​/life-course-approach-to-health.pdf .
• Jacobson DL, Gange SJ, Rose NR, Graham NMH. Epidemiology and estimated population burden of selected autoimmune diseases in the United States. Clinical Immunology and Immunopathology. 1997;84(3):223–243. https://doi​.org/10.1006/clin.1997.4412 . [PubMed: 9281381]
• Jain K, Jawa P, Derebail VK, Falk RJ. Treatment updates in antineutrophil cytoplasmic autoantibodies (anca) vasculitis. Kidney360. 2021;2(4):763–770. https://doi​.org/10.34067/kid.0007142020 . [PMC free article: PMC8177081] [PubMed: 34095854]
• James S, Gallagher R, Dunbabin J, Perry L. Prevalence of vascular complications and factors predictive of their development in young adults with type 1 diabetes: Systematic literature review. BMC Research Notes. 2014;7(1):593. https://doi​.org/10.1186/1756-0500-7-593 . [PMC free article: PMC4167503] [PubMed: 25182937]
• Jia L, Levine AB, Lockshin MD. American College of Rheumatology criteria for systemic lupus erythematosus exclude half of all systemic lupus erythematosus patients. Arthritis & Rheumatology. 2017;69(7):1502–1503. https://doi​.org/10.1002/art.40120 . [PubMed: 28388814]
• Johns Hopkins University. Definition of autoimmunity & autoimmune disease. 2022. [January 18, 2022]. https://pathology​.jhu​.edu/autoimmune/definitions/
• Johnson DB, Chandra S, Sosman JA. Immune checkpoint inhibitor toxicity in 2018. JAMA. 2018;320(16):1702–1703. https://doi​.org/10.1001/jama.2018.13995 . [PubMed: 30286224]
• Jorge AM, Lu N, Zhang Y, Rai SK, Choi HK. Unchanging premature mortality trends in systemic lupus erythematosus: A general population-based study (1999–2014). Rheumatology (Oxford). 2018;57(2):337–344. [PMC free article: PMC5850281] [PubMed: 29121273]
• Kanth R, Shrestha RB, Rai I, VanWormer JJ, Roy PK. Incidence of primary biliary cholangitis in a rural midwestern population. Clinical Medicine & Research. 2017;15(1–2):13–18. https://doi​.org/10.3121/cmr.2017.1351 . [PMC free article: PMC5573520] [PubMed: 28487448]
• Kao KT, Denker M, Zacharin M, Wong SC. Pubertal abnormalities in adolescents with chronic disease. Best Practice & Research Clinical Endocrinology & Metabolism. 2019;33(3):101275. [PubMed: 31047817]
• Kawatkar AA, Gabriel SE, Jacobsen SJ. Secular trends in the incidence and prevalence of rheumatoid arthritis within members of an integrated health care delivery system. Rheumatology International. 2019;39(3):541–549. [PubMed: 30656412]
• Ketelhuth DF, Hansson GK. Adaptive response of T and B cells in atherosclerosis. Circulation Research. 2016;118(4):668–678. [PubMed: 26892965]
• Khalili H, Everhov AH, Halfvarson J, Ludvigsson JF, Askling J, Myrelid P, Söderling J, Olen O, Neovius M., SWIBREG Group. Healthcare use, work loss and total costs in incident and prevalent Crohn’s disease and ulcerative colitis: Results from a nationwide study in Sweden. Alimentary Pharmacology and Therapeutics. 2020;52(4):655–668. [PMC free article: PMC7490827] [PubMed: 32902894]
• Kollert F, Fisher BA. Equal rights in autoimmunity: Is Sjögren’s syndrome ever ‘secondary’? Rheumatology (Oxford). 2020;59(6):1218–1225. [PubMed: 32025734]
• Kremers HM, Crowson CS, Therneau TM, Roger VL, Gabriel SE. High ten-year risk of cardiovascular disease in newly diagnosed rheumatoid arthritis patients: A population-based cohort study. Arthritis and Rheumatism. 2008;58(8):2268–2274. [PMC free article: PMC2929699] [PubMed: 18668561]
• Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C. Life course epidemiology. Journal of Epidemiology and Community Health. 2003;57(10):778–783. https://doi​.org/10.1136/jech.57.10.778 . [PMC free article: PMC1732305] [PubMed: 14573579]
• Kurd SK, Troxel AB, Crits-Christoph P, Gelfand JM. The risk of depression, anxiety and suicidality in patients with psoriasis: A population-based cohort study. Archives of Dermatology. 2010;146(8):891–895. https://doi​.org/10.1001/archdermatol​.2010.186 . [PMC free article: PMC2928071] [PubMed: 20713823]
• Kurmann RD, Sandhu AS, Crowson CS, Matteson EL, Osborn TG, Warrington KJ, Mankad R, Makol A. Cardiovascular risk factors and atherosclerotic cardiovascular events among incident cases of systemic sclerosis: Results from a population-based cohort (1980–2016). Mayo Clinic Proceedings. 2020;95(7):1369–1378. https://doi​.org/10.1016/j​.mayocp.2019.12.015 . [PMC free article: PMC9719716] [PubMed: 32622445]
• Langan D, Rose NR, Moudgil KD. Common innate pathways to autoimmune disease. Clinical Immunology. 2020;212:108361. https://doi​.org/10.1016/j​.clim.2020.108361 . [PMC free article: PMC8324042] [PubMed: 32058071]
• Langer-Gould A, Brara SM, Beaber BE, Zhang JL. Incidence of multiple sclerosis in multiple racial and ethnic groups. Neurology. 2013;80(19):1734–1739. https://doi​.org/10.1212/WNL​.0b013e3182918cc2 . [PubMed: 23650231]
• Lee C-H, Giuliani F. The role of inflammation in depression and fatigue. Frontiers in Immunology. 2019a;10:1696. https://doi​.org/10.3389/fimmu.2019.01696 . [PMC free article: PMC6658985] [PubMed: 31379879]
• Lee CH, Giuliani F. The role of inflammation in depression and fatigue. Frontiers in Immunology. 2019b;10:1696. https://doi​.org/10.3389/fimmu.2019.01696 . [PMC free article: PMC6658985] [PubMed: 31379879]
• Leese GP, Flynn RV, Jung RT, Macdonald TM, Murphy MJ, Morris AD. Increasing prevalence and incidence of thyroid disease in Tayside, Scotland: The thyroid epidemiology audit and research study (tears). Clinical Endocrinology. 2008;68(2):311–316. https://doi​.org/10.1111/j​.1365-2265.2007.03051.x . [PubMed: 17970771]
• Liao KP, Cai T, Gainer V, Goryachev S, Zeng-treitler Q, Raychaudhuri S, Szolovits P, Churchill S, Murphy S, Kohane I, Karlson EW, Plenge RM. Electronic medical records for discovery research in rheumatoid arthritis. Arthritis Care & Research. 2010;62(8):1120–1127. https://doi​.org/10.1002/acr.20184 . [PMC free article: PMC3121049] [PubMed: 20235204]
• Lim SS, Bayakly AR, Helmick CG, Gordon C, Easley KA, Drenkard C. The incidence and prevalence of systemic lupus erythematosus, 2002–2004: The Georgia Lupus Registry. Arthritis & Rheumatology. 2014;66(2):357–368. https://doi​.org/10.1002/art.38239 . [PMC free article: PMC4617771] [PubMed: 24504808]
• Lim SS, Helmick CG, Bao G, Hootman J, Bayakly R, Gordon C, Drenkard C. Racial disparities in mortality associated with systemic lupus erythematosus - Fulton and DeKalb Counties, Georgia, 2002-2016. MMWR: Morbidity and Mortality Weekly Report. 2019;68(18):419–422. https://doi​.org/10.15585/mmwr.mm6818a4 . [PMC free article: PMC6542193] [PubMed: 31071073]
• Lindestam Arlehamn CS, Dhanwani R, Pham J, Kuan R, Frazier A, Rezende Dutra J, Phillips E, Mallal S, Roederer M, Marder KS, Amara AW, Standaert DG, Goldman JG, Litvan I, Peters B, Sulzer D, Sette A. Α-synuclein-specific T cell reactivity is associated with preclinical and early Parkinson’s disease. Nature Communications. 2020;11(1):1875. https://doi​.org/10.1038​/s41467-020-15626-w . [PMC free article: PMC7171193] [PubMed: 32313102]
• Liu S, Jones RN, Glymour MM. Implications of lifecourse epidemiology for research on determinants of adult disease. Public Health Reviews. 2010;32(2):489–511. https://doi​.org/10.1007/BF03391613 . [PMC free article: PMC3955391] [PubMed: 24639598]
• Lockshin MD, Levine AB, Erkan D. Patients with overlap autoimmune disease differ from those with ‘pure’ disease. Lupus Science & Medicine. 2015;2(1):e000084. https://doi​.org/10.1136​/lupus-2015-000084 . [PMC free article: PMC4422903] [PubMed: 25973214]
• Lockshin MD, Barbhaiya M, Izmirly P, Buyon JP, Crow MK. SLE: Reconciling heterogeneity. Lupus Science & Medicine. 2019;6(1):e000280. https://doi​.org/10.1136​/lupus-2018-000280 . [PMC free article: PMC6485210] [PubMed: 31080630]
• Lockshin MD, Crow MK, Barbhaiya M. ACR Open Rheumatology 2021. Nov. 21, 2021. When a diagnosis has no name: Uncertainty and opportunity. https://doi​.org/10.1002/acr2.11368 . [PMC free article: PMC8916551] [PubMed: 34806330]
• Lu M, Zhou Y, Haller IV, Romanelli RJ, VanWormer JJ, Rodriguez CV, Anderson H, Boscarino JA, Schmidt MA, Daida YG, Sahota A, Vincent J, Bowlus CL, Lindor K, Zhang T, Trudeau S, Li J, Rupp LB, Gordon SC. for the Fibrotic Liver Disease Consortium Investigators. Increasing prevalence of primary biliary cholangitis and reduced mortality with treatment. Clinical Gastroenterology and Hepatology. 2018;16(8):1342–1350. e1341 https://doi​.org/10.1016/j​.cgh.2017.12.033. [PubMed: 29277621]
• Lynch J, Smith GD. A life course approach to chronic disease epidemiology. Annual Review of Public Health. 2005;26:1–35. https://doi​.org/10.1146/annurev​.publhealth.26.021304.144505 . [PubMed: 15760279]
• Maciel G, Crowson CS, Matteson EL, Cornec D. Incidence and mortality of physician-diagnosed primary Sjögren’s syndrome: Time trends over a 40-year period in a population-based cohort in the United States. Mayo Clinic Proceedings. 2017a;92(5):734–743. https://doi​.org/10.1016/j​.mayocp.2017.01.020 . [PMC free article: PMC5470777] [PubMed: 28389066]
• Maciel G, Crowson CS, Matteson EL, Cornec D. Prevalence of primary Sjögren’s syndrome in a population-based cohort in the United States. Arthritis Care & Research. 2017b;69(10):1612–1616. https://doi​.org/10.1002/acr.23173 . [PMC free article: PMC5478481] [PubMed: 27998024]
• Maggio M, Ceda GP, Lauretani F, Bandinelli S, Metter EJ, Artoni A, Gatti E, Ruggiero C, Guralnik JM, Valenti G, Ling SM, Basaria S, Ferrucci L. Estradiol and inflammatory markers in older men. Journal of Clinical Endocrinology & Metabolism. 2009;94(2):518–522. https://doi​.org/10.1210/jc.2008-0940 . [PMC free article: PMC2646519] [PubMed: 19050054]
• Man A, Zhu Y, Zhang Y, Dubreuil M, Rho YH, Peloquin C, Simms RW, Choi HK. The risk of cardiovascular disease in systemic sclerosis: A population-based cohort study. Annals of the Rheumatic Diseases. 2013;72(7):1188–1193. https://doi​.org/10.1136​/annrheumdis-2012-202007 . [PMC free article: PMC4386728] [PubMed: 22904260]
• Mardini HE, Westgate P, Grigorian AY. Racial differences in the prevalence of celiac disease in the US population: National Health and Nutrition Examination Survey (NHANES) 2009–2012. Digestive Diseases and Sciences. 2015;60(6):1738–1742. https://doi​.org/10.1007​/s10620-014-3514-7 . [PubMed: 25577269]
• Marshall JS, Warrington R, Watson W, Kim HL. An introduction to immunology and immunopathology. Allergy, Asthma, and Clinical Immunology. 2018;14(Suppl 2):49. https://doi​.org/10.1186​/s13223-018-0278-1 . [PMC free article: PMC6156898] [PubMed: 30263032]
• Martin-Pozo L, Gomez-Regalado MDC, Moscoso-Ruiz I, Zafra-Gomez A. Analytical methods for the determination of endocrine disrupting chemicals in cosmetics and personal care products: A review. Talanta. 2021;234:122642. https://doi​.org/10.1016/j​.talanta.2021.122642 . [PubMed: 34364451]
• Martz CD, Allen AM, Fuller-Rowell TE, Spears EC, Lim SS, Drenkard C, Chung K, Hunter EA, Chae DH. Vicarious racism stress and disease activity: The Black women’s experiences living with lupus (BeWELL) study. Journal of Racial and Ethnic Health Disparities. 2019;6(5):1044–1051. https://doi​.org/10.1007​/s40615-019-00606-8 . [PMC free article: PMC7302115] [PubMed: 31215018]
• Masters SL, Simon A, Aksentijevich I, Kastner DL. Horror autoinflammaticus: The molecular pathophysiology of autoinflammatory disease. Annual Review of Immunology. 2009;27:621–668. https://doi​.org/10.1146/annurev​.immunol.25.022106.141627 . [PMC free article: PMC2996236] [PubMed: 19302049]
• Mauldin J, Cameron HD, Jeanotte D, Solomon G, Jarvis JN. Chronic arthritis in children and adolescents in two Indian Health Service user populations. BMC Musculoskeletal Disorders. 2004;5(1):30. https://doi​.org/10.1186/1471-2474-5-30 . [PMC free article: PMC517923] [PubMed: 15333136]
• Mayer-Davis EJ, Dabelea D, Lawrence JM. Incidence trends of type 1 and type 2 diabetes among youths, 2002–2012. The New England Journal of Medicine. 2017;376(15):1419–1429. https://doi​.org/doi:10​.1056/NEJMoa1610187 . [PMC free article: PMC5592722] [PubMed: 28402773]
• Mayes MD, Lacey JV Jr, Beebe-Dimmer J, Gillespie BW, Cooper B, Laing TJ, Schottenfeld D. Prevalence, incidence, survival, and disease characteristics of systemic sclerosis in a large US population. Arthritis and Rheumatism. 2003;48(8):2246–2255. https://doi​.org/10.1002/art.11073 . [PubMed: 12905479]
• McGonagle D, McDermott MF. A proposed classification of the immunological diseases. PLOS Medicine. 2006;3(8) https://doi​.org/10.1371/journal​.pmed.0030297 . e297. [PMC free article: PMC1564298] [PubMed: 16942393]
• McMahon M, Hahn BH, Skaggs BJ. Systemic lupus erythematosus and cardiovascular disease: Prediction and potential for therapeutic intervention. Expert Review of Clinical Immunology. 2011;7(2):227–241. https://doi​.org/10.1586/eci.10.98 . [PMC free article: PMC3718673] [PubMed: 21426260]
• Mersha TB, Abebe T. Self-reported race/ethnicity in the age of genomic research: Its potential impact on understanding health disparities. Human Genomics. 2015;9(1):1. https://doi​.org/10.1186​/s40246-014-0023-x . [PMC free article: PMC4307746] [PubMed: 25563503]
• Miller-Archie SA, Izmirly PM, Berman JR, Brite J, Walker DJ, Dasilva RC, Petrsoric LJ, Cone JE. Systemic autoimmune disease among adults exposed to the September 11, 2001 terrorist attack. Arthritis & Rheumatology. 2020;72(5):849–859. https://doi​.org/10.1002/art.41175 . [PMC free article: PMC7216890] [PubMed: 31762219]
• Miller GE, Chen E, Parker KJ. Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychological Bulletin. 2011;137(6):959–997. https://doi​.org/10.1037/a0024768 . [PMC free article: PMC3202072] [PubMed: 21787044]
• Mitratza M, Klijs B, Hak AE, Kardaun JWPF, Kunst AE. Systemic autoimmune disease as a cause of death: Mortality burden and comorbidities. Rheumatology (Oxford). 2021;60(3):1321–1330. https://doi​.org/10.1093​/rheumatology/keaa537 . [PMC free article: PMC7937014] [PubMed: 32944773]
• Molina E, del Rincon I, Restrepo JF, Battafarano DF, Escalante A. Mortality in rheumatoid arthritis (RA): Factors associated with recording RA on death certificates. BMC Musculoskeletal Disorders. 2015;16:277. https://doi​.org/10.1186​/s12891-015-0727-7 . [PMC free article: PMC4595199] [PubMed: 26438345]
• Moores KG, Sathe NA. A systematic review of validated methods for identifying systemic lupus erythematosus (SLE) using administrative or claims data. Vaccine. 2013;31(Suppl 10):K62–73. https://doi​.org/10.1016/j​.vaccine.2013.06.104 . [PubMed: 24331075]
• Morales-Tisnes T, Quintero-Ortiz L, Quintero-Munoz E, Sierra-Matamoros F, AriasAponte J, Rojas-Villarraga A. Prevalence of hospital readmissions and related factors in patients with autoimmune diseases. Journal of Translational Autoimmunity. 2021;4:100121. https://doi​.org/10.1016/j​.jtauto.2021.100121 . [PMC free article: PMC8450261] [PubMed: 34585131]
• Morgan R, Baker P, Griffith DM, Klein SL, Logie CH, Mwiine AA, Scheim AI, Shapiro JR, Smith J, Wenham C, White A. Beyond a zero-sum game: How does the impact of COVID-19 vary by gender? Frontiers in Sociology. 2021;6(126):650729. https://doi​.org/10.3389/fsoc.2021.650729 . [PMC free article: PMC8239350] [PubMed: 34212026]
• Morris G, Berk M, Walder K, Maes M. Central pathways causing fatigue in neuro-inflammatory and autoimmune illnesses. BMC Medicine. 2015;13(28):28. https://doi​.org/10.1186​/s12916-014-0259-2 . [PMC free article: PMC4320458] [PubMed: 25856766]
• Moustafa AT, Moazzami M, Engel L, Bangert E, Hassanein M, Marzouk S, Kravtsenyuk M, Fung W, Eder L, Su J, Wither JE, Touma Z. Prevalence and metric of depression and anxiety in systemic lupus erythematosus: A systematic review and meta-analysis. Seminars in Arthritis and Rheumatism. 2020;50(1):84–94. https://doi​.org/10.1016/j​.semarthrit.2019.06.017 . [PubMed: 31303437]
• Munk Nielsen N, Corn G, Frisch M, Stenager E, Koch-Henriksen N, Wohlfahrt J, Magyari M, Melbye M. Multiple sclerosis among first- and second-generation immigrants in Denmark: A population-based cohort study. Brain. 2019;142(6):1587–1597. https://doi​.org/10.1093/brain/awz088 . [PubMed: 31081503]
• Myasoedova E, Crowson CS, Kremers HM, Therneau TM, Gabriel SE. Is the incidence of rheumatoid arthritis rising?: Results from Olmsted County, Minnesota, 1955–2007. Arthritis and Rheumatism. 2010;62(6):1576–1582. https://doi​.org/10.1002/art.27425 . [PMC free article: PMC2929692] [PubMed: 20191579]
• NCI (National Cancer Institute). Cancer stat facts: Cancer of any site. 2021a. [March 17, 2022]. https://seer​.cancer.gov​/statfacts/html/all.html .
• NCI. SEER is an authoritative source for cancer statistics in the United States. 2021b. [August 16, 2021]. https://seer​.cancer.gov/
• Nelson LM, Wallin MT, Marrie RA, Culpepper WJ, Langer-Gould A, Campbell J, Buka S, Tremlett H, Cutter G, Kaye W, Wagner L, Larocca NG., United States Multiple Sclerosis Prevalence Workgroup. A new way to estimate neurologic disease prevalence in the United States: Illustrated with MS. Neurology. 2019;92(10):469–480. https://doi​.org/10.1212/WNL​.0000000000007044 . [PMC free article: PMC6442012] [PubMed: 30770422]
• NHANES (National Health and Nutrition Examination Suvey). About NHANES. 2017. [July 1, 2021]. https://www​.cdc.gov/nchs​/nhanes/about_nhanes.htm .
• NIAID (National Institute of Allergy and Infectious Diseases). Autoimmune diseases. 2017. [January 18, 2021]. https://www​.niaid.nih​.gov/diseases-conditions​/autoimmune-diseases .
• Nielsen NM, Frisch M, Rostgaard K, Wohlfahrt J, Hjalgrim H, Koch-Henriksen N, Melbye M, Westergaard T. Autoimmune diseases in patients with multiple sclerosis and their first-degree relatives: A nationwide cohort study in Denmark. Multiple Sclerosis. 2008;14(6):823–829. https://doi​.org/10.1177/1352458508088936 . [PubMed: 18573841]
• NIH (National Institutes of Health). Report of the director—National Institutes of Health: Fiscal years 2014 and 2015. Bethesda, MD: National Institutes of Health; 2016.
• NIH. Report of the director—National Institutes of Health: Fiscal years 2016, 2017, and 2018. Bethesda, MD: National Institutes of Health; 2019.
• NLM (National Library of Medicine). Nivolumab in treating patients with autoimmune disorders and advanced, metastatic, or unresectable cancer. 2021. [October 8, 2021]. https://clinicaltrials.gov/ct2/show/NCT03816345 .
• Noah L. Confronting the inevitability of diagnostic uncertainty across multiple legal domains. In: Lockshin M, Crow MK, Barbhaiya M, editors. Diagnoses without names: Challenges for medical care, research, and policy. Switzerland: Springer Nature; 2022.
• Nusbaum JS, Mirza I, Shum J, Freilich RW, Cohen RE, Pillinger MH, Izmirly PM, Buyon JP. Sex differences in systemic lupus erythematosus: Epidemiology, clinical considerations, and disease pathogenesis. Mayo Clinic Proceedings. 2020;95(2):384–394. https://doi​.org/10.1016/j​.mayocp.2019.09.012 . [PubMed: 32029091]
• Orbai AM, Reddy SM, Dennis N, Villacorta R, Peterson S, Mesana L, Chakravarty SD, Lin I, Karyekar CS, Wang Y, Pacou M, Walsh J. Work absenteeism and disability associated with psoriasis and psoriatic arthritis in the USA-a retrospective study of claims data from 2009 to 2020. Clinical Rheumatology. 2021;40(12):4933–4942. https://doi​.org/10.1007​/s10067-021-05839-9 . [PMC free article: PMC8599387] [PubMed: 34287723]
• Paller AS, Singh R, Cloutier M, Gauthier-Loiselle M, Emond B, Guérin A, Ganguli A. Prevalence of psoriasis in children and adolescents in the United States: A claims-based analysis. Journal of Drugs in Dermatology. 2018;17(2):187–194. [PubMed: 29462227]
• Panopalis P, Clarke AE, Yelin E. The economic burden of systemic lupus erythematosus. Best Practice & Research: Clinical Rheumatology. 2012;26(5):695–704. https://doi​.org/10.1016/j​.berh.2012.08.006 . [PubMed: 23218432]
• Parks CG, D’Aloisio AA, Sandler DP. Early life factors associated with adult-onset systemic lupus erythematosus in women. Frontiers in Immunology. 2016;7:103. https://doi​.org/10.3389/fimmu.2016.00103 . [PMC free article: PMC4814765] [PubMed: 27064771]
• Pasvol TJ, Horsfall L, Bloom S, Segal AW, Sabin C, Field N, Rait G. Incidence and prevalence of inflammatory bowel disease in UK primary care: A population-based cohort study. BMJ Open. 2020;10(7):e036584. https://doi​.org/10.1136​/bmjopen-2019-036584 . [PMC free article: PMC7371214] [PubMed: 32690524]
• Patisaul HB. Endocrine disruption by dietary phyto-oestrogens: Impact on dimorphic sexual systems and behaviours. Proceedings of the Nutrition Society. 2017;76(2):130–144. https://doi​.org/10.1017​/S0029665116000677 . [PMC free article: PMC5646220] [PubMed: 27389644]
• Pinson RD. The Hospitalist. 2012. [August 28, 2012)]. [January 3, 2022]. Properly coding an uncertain diagnosis. https://www​.the-hospitalist​.org/hospitalist​/article/125124/properly-coding-uncertain-diagnosis .
• Popescu M, Feldman TB, Chitnis T. Interplay between endocrine disruptors and immunity: Implications for diseases of autoreactive etiology. Frontiers in Pharmacology. 2021;12:626107. https://doi​.org/10.3389/fphar​.2021.626107 . [PMC free article: PMC8021784] [PubMed: 33833678]
• Porta M. A dictionary of epidemiology (draft). Oxford: Oxford University Press; 2014.
• Potluri T, Fink AL, Sylvia KE, Dhakal S, Vermillion MS, Vom Steeg L, Deshpande S, Narasimhan H, Klein SL. Age-associated changes in the impact of sex steroids on influenza vaccine responses in males and females. NPJ Vaccines. 2019;4:29. https://doi​.org/10.1038​/s41541-019-0124-6 . [PMC free article: PMC6626024] [PubMed: 31312529]
• Quaglia M, Merlotti G, De Andrea M, Borgogna C, Cantaluppi V. Viral infections and systemic lupus erythematosus: New players in an old story. Viruses. 2021;13(2):277. [PMC free article: PMC7916951] [PubMed: 33670195]
• Raggi A, Covelli V, Schiavolin S, Scaratti C, Leonardi M, Willems M. Work-related problems in multiple sclerosis: A literature review on its associates and determinants. Disability and Rehabilitation. 2016;38(10):936–944. https://doi​.org/10.3109/09638288​.2015.1070295 . [PubMed: 26213244]
• Reifsnider E, Gallagher M, Forgione B. Using ecological models in research on health disparities. Journal of Professional Nursing. 2005;21(4):216–222. https://doi​.org/10.1016/j​.profnurs.2005.05.006 . [PubMed: 16061168]
• Rochester Epidemiology Project. 2012. [July 9, 2021]. https:​//rochesterproject​.org/wp-content/uploads​/2014/03/summary_tables_dec_2012​.pdf .
• Rose NR, Bona C. Defining criteria for autoimmune diseases (Witebsky’s postulates revisited). Immunology Today. 1993;14(9):426–430. https://doi​.org/10.1016​/0167-5699(93)90244-F . [PubMed: 8216719]
• Rose NR, Mackay IR. Autoimmune disease. In: Rose NR, Mackay IR, editors. The autoimmune diseases. 5th ed. San Diego, CA: Elsevier Inc; 2014. pp. 3–9.
• Rosenblum MD, Remedios KA, Abbas AK. Mechanisms of human autoimmunity. Journal of Clinical Investigation. 2015;125(6):2228–2233. https://doi​.org/10.1172/JCI78088 . [PMC free article: PMC4518692] [PubMed: 25893595]
• Rotstein DL, Chen H, Wilton AS, Kwong JC, Marrie RA, Gozdyra P, Krysko KM, Kopp A, Copes R, Tu K. Temporal trends in multiple sclerosis prevalence and incidence in a large population. Neurology. 2018;90(16):e1435–e1441. https://doi​.org/10.1212/WNL​.0000000000005331 . [PubMed: 29549225]
• Rubtsov AV, Rubtsova K, Kappler JW, Marrack P. Genetic and hormonal factors in female-biased autoimmunity. Autoimmunity Reviews. 2010;9(7):494–498. https://doi​.org/10.1016/j​.autrev.2010.02.008 . [PMC free article: PMC3171140] [PubMed: 20144912]
• Rusman T, van Vollenhoven RF, van der Horst-Bruinsma IE. Gender differences in axial spondyloarthritis: Women are not so lucky. Current Rheumatology Reports. 2018;20(6):35. https://doi​.org/10.1007​/s11926-018-0744-2 . [PMC free article: PMC5949138] [PubMed: 29754330]
• Sammaritano LR, Bermas BL, Chakravarty EE, Chambers C, Clowse MEB, Lockshin MD, Marder W, Guyatt G, Branch DW, Buyon J, Christopher-Stine L, Crow-Hercher R, Cush J, Druzin M, Kavanaugh A, Laskin CA, Plante L, Salmon J, Simard J, Somers EC, Steen V, Tedeschi SK, Vinet E, White CW, Yazdany J, Barbhaiya M, Bettendorf B, Eudy A, Jayatilleke A, Shah AA, Sullivan N, Tarter LL, Birru Talabi M, Turgunbaev M, Turner A, D’Anci KE. 2020 American College of Rheumatology guideline for the management of reproductive health in rheumatic and musculoskeletal diseases. Arthritis Care & Research. 2020;72(4):461–488. https://doi​.org/10.1002/acr.24130 . [PubMed: 32090466]
• Sánchez-Flórez JC, Seija-Butnaru D, Valero EG, Acosta Acosta CDP, Amaya S. Pain management strategies in rheumatoid arthritis: A narrative review. Journal of Pain & Palliative Care Pharmacotherapy Oct. 2021;8:1–9. https://doi​.org/10.1080/15360288​.2021.1973647 . [PubMed: 34623946]
• Sankar P, Cho MK, Condit CM, Hunt LM, Koenig B, Marshall P, Lee SS, Spicer P. Genetic research and health disparities. JAMA. 2004;291(24):2985–2989. https://doi​.org/10.1001/jama.291.24.2985 . [PMC free article: PMC2271142] [PubMed: 15213210]
• Scofield L, Reinlib L, Alarcón GS, Cooper GS. Employment and disability issues in systemic lupus erythematosus: A review. Arthritis and Rheumatism. 2008;59(10):1475–1479. https://doi​.org/10.1002/art.24113 . [PubMed: 18821664]
• Sedykh SE, Prinz VV, Buneva VN, Nevinsky GA. Bispecific antibodies: Design, therapy, perspectives. Drug Design, Development and Therapy. 2018;12:195–208. https://doi​.org/10.2147/DDDT.S151282 . [PMC free article: PMC5784585] [PubMed: 29403265]
• Sharif R, Mayes MD, Nicassio PM, Gonzalez EB, Draeger H, McNearney TA, Estrada-Y-Martin RM, Nair DK, Reveille JD, Arnett FC, Assassi S., the GENISOS Study Group. Determinants of work disability in patients with systemic sclerosis: A longitudinal study of the GENISOS cohort. Seminars in Arthritis and Rheumatism. 2011;41(1):38–47. https://doi​.org/10.1016/j​.semarthrit.2011.01.002 . [PMC free article: PMC3153604] [PubMed: 21429562]
• Shivashankar R, Tremaine WJ, Harmsen WS, Loftus EV Jr. Incidence and prevalence of Crohn’s disease and ulcerative colitis in Olmsted County, Minnesota from 1970 through 2010. Clinical Gastroenterology and Hepatology. 2017;15(6):857–863. https://doi​.org/10.1016/j​.cgh.2016.10.039 . [PMC free article: PMC5429988] [PubMed: 27856364]
• Simon D, Bechtold S. Effects of growth hormone treatment on growth in children with juvenile idiopathic arthritis. Hormone Research. 2009;72(Suppl 1):55–59. https://doi​.org/10.1159/000229765 . [PubMed: 19940497]
• Simon TA, Thompson A, Gandhi KK, Hochberg MC, Suissa S. Incidence of malignancy in adult patients with rheumatoid arthritis: A meta-analysis. Arthritis Research & Therapy. 2015;17(1):212. https://doi​.org/10.1186​/s13075-015-0728-9 . [PMC free article: PMC4536786] [PubMed: 26271620]
• Somers EC, Thomas SL, Smeeth L, Hall AJ. Autoimmune diseases co-occurring within individuals and within families: A systematic review. Epidemiology. 2006;17(2):202–217. https://doi​.org/10.1097/01​.ede.0000193605.93416.df . [PubMed: 16477262]
• Somers EC, Thomas SL, Smeeth L, Hall AJ. Are individuals with an autoimmune disease at higher risk of a second autoimmune disorder? American Journal of Epidemiology. 2009;169(6):749–755. https://doi​.org/10.1093/aje/kwn408 . [PubMed: 19224981]
• Somers EC, Marder W, Cagnoli P, Lewis EE, DeGuire P, Gordon C, Helmick CG, Wang L, Wing JJ, Dhar JP, Leisen J, Shaltis D, McCune WJ. Population-based incidence and prevalence of systemic lupus erythematosus: The Michigan Lupus Epidemiology and Surveillance Program. Arthritis & Rheumatology. 2014;66(2):369–378. https://doi​.org/10.1002/art.38238 . [PMC free article: PMC4198147] [PubMed: 24504809]
• Sontichai W, Liao F, Dominguez D, Levy DM, Al Mutairi M, Ng L, Silverio F, Silverman ED, Wasserman JD, Hiraki LT. Timing of childhood-onset systemic lupus erythematosus diagnosis relative to menarche impacts final height. Arthritis Care & Research. 2020;74(2):199–207. https://doi​.org/10.1002/acr.24461 . [PubMed: 32976694]
• Springer KW, Mager Stellman J, Jordan-Young RM. Beyond a catalogue of differences: A theoretical frame and good practice guidelines for researching sex/gender in human health. Social Science and Medicine. 2012;74(11):1817–1824. https://doi​.org/10.1016/j​.socscimed.2011.05.033 . [PubMed: 21724313]
• St. Sauver JL, Grossardt BR, Yawn BP, Melton J 3rd, Rocca WA. Use of a medical records linkage system to enumerate a dynamic population over time: The Rochester Epidemiology Project. American Journal of Epidemiology. 2011;173(9):1059–1068. [PMC free article: PMC3105274] [PubMed: 21430193]
• Stoffels M, Simon A. The concept of autoinflammatory diseases. In: Rose NR, Mackay IR, editors. The autoimmune diseases. 5th ed. Cambridge, MA: Elsevier Inc; 2014. pp. 39–50.
• Suntharalingam G, Perry MR, Ward S, Brett SJ, Castello-Cortes A, Brunner MD, Panoskaltsis N. Cytokine storm in a phase 1 trial of the anti-CD28 monoclonal antibody TGN1412. The New England Journal of Medicine. 2006;355(10):1018–1028. https://doi​.org/10.1056/nejmoa063842 . [PubMed: 16908486]
• Tager RE, Tikly M. Clinical and laboratory manifestations of systemic sclerosis (scleroderma) in Black South Africans. Rheumatology (Oxford). 1999;38(5):397–400. https://doi​.org/10.1093/rheumatology/38​.5.397 . [PubMed: 10371275]
• Tengstrand B, Carlström K, Felländer-Tsai L, Hafström I. Abnormal levels of serum dehydroepiandrosterone, estrone, and estradiol in men with rheumatoid arthritis: High correlation between serum estradiol and current degree of inflammation. Journal of Rheumatology. 2003;30(11):2338–2343. [PubMed: 14677174]
• Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Correale J, Fazekas F, Filippi M, Freedman MS, Fujihara K, Galetta SL, Hartung HP, Kappos L, Lublin FD, Marrie RA, Miller AE, Miller DH, Montalban X, Mowry EM, Sorensen PS, Tintoré M, Traboulsee AL, Trojano M, Uitdehaag BMJ, Vuku-sic S, Waubant E, Weinshenker BG, Reingold SC, Cohen JA. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. The Lancet Neurology. 2018;17(2):162–173. https://doi​.org/10.1016​/S1474-4422(17)30470-2 . [PubMed: 29275977]
• Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: Implications for understanding health and health services. Annals of Family Medicine. 2009;7(4):357–363. https://doi​.org/10.1370/afm.983 . [PMC free article: PMC2713155] [PubMed: 19597174]
• Vallerand IA, Lewinson RT, Frolkis AD, Lowerison MW, Kaplan GG, Swain MG, Bulloch AGM, Patten SB, Barnabe C. Depression as a risk factor for the development of rheumatoid arthritis: A population-based cohort study. RMD Open. 2018;4(2):e000670. https://doi​.org/10.1136​/rmdopen-2018-000670 . [PMC free article: PMC6045711] [PubMed: 30018804]
• Vallerand IA, Patten SB, Barnabe C. Depression and the risk of rheumatoid arthritis. Current Opinion in Rheumatology. 2019;31(3):279–284. https://doi​.org/10.1097/bor​.0000000000000597 . [PMC free article: PMC6455087] [PubMed: 30789849]
• van Beugen S, van Middendorp H, Ferwerda M, Smit JV, Zeeuwen-Franssen MEJ, Kroft EBM, de Jong EMGJ, Donders ART, van de Kerkhof PCM, Evers AWM. Predictors of perceived stigmatization in patients with psoriasis. British Journal of Dermatology. 2017;176(3):687–694. https://doi​.org/https://doi​.org/10.1111/bjd.14875 . [PubMed: 27436615]
• van der Valk M, Mangen M, Leenders M, Dijkstra G, van Bodegraven A, Fidder H, de Jong D, Pierik M, CJ VDW, MJ R-C, CH C, JM N, Pierik M, PC VDM, AE VDM-DJ, CY P, CJ B, JR V, PD S, MG VO, B. O. Coin study group; Dutch initiative on Crohn and colitis. Journal of Crohn’s & Colitis. 2014a;8:590–597. [PubMed: 24351733]
• van der Valk M, Mangen M, Leenders M, Dijkstra G, van Bodegraven AA, Fidder HH, de Jong DJ, Pierik M, Janneke van der Woude C, Romberg-Camps MJL, Clemens CHM, Jansen JM, Mahmmod N, van de Meeberg PC, van der Meulen-de Jong AE, Ponsioen CY, Bolwerk CJM, Reinoud Vermeijden J, Siersema PD, van Oijen MGH, Oldenburg B. Risk factors of work disability in patients with inflammatory bowel disease—A Dutch nationwide web-based survey. Journal of Crohn’s & Colitis. 2014a;8:590–597. https://doi​.org/10.1016/j​.crohns.2013.11.019 . [PubMed: 24351733]
• Vanderpuye-Orgle J, Zhao Y, Lu J, Shrestha A, Sexton A, Seabury S, Lebwohl M. Evaluating the economic burden of psoriasis in the United States. Journal of the American Academy of Dermatology. 2015;72(6):961–967. e965 https://doi​.org/10.1016/j​.jaad.2015.02.1099. [PubMed: 25882886]
• Ventura RE, Antezana AO, Bacon T, Kister I. Hispanic Americans and African Americans with multiple sclerosis have more severe disease course than Caucasian Americans. Multiple Sclerosis. 2017;23(11):1554–1557. https://doi​.org/10.1177/1352458516679894 . [PubMed: 27899551]
• Videm V, Thomas R, Brown MA, Hoff M. Self-reported diagnosis of rheumatoid arthritis or ankylosing spondylitis has low accuracy: Data from the Nord-Trøndelag Health Study. Journal of Rheumatology. 2017;44(8):1134–1141. https://doi​.org/10.3899/jrheum.161396 . [PubMed: 28412703]
• Wallin MT, Culpepper WJ, Campbell JD, Nelson LM, Langer-Gould A, Marrie RA, Cutter GR, Kaye WE, Wagner L, Tremlett H, Buka SL, Dilokthornsakul P, Topol B, Chen LH, LaRocca NG., US Multiple Sclerosis Prevalence Workgroup. The prevalence of MS in the United States: A population-based estimate using health claims data. Neurology. 2019;92(10):e1029–e1040. [PMC free article: PMC6442006] [PubMed: 30770430]
• Webber MP, Yip J, Zeig-Owens R, Moir W, Ungprasert P, Crowson CS, Hall CB, Jaber N, Weiden MD, Matteson EL, Prezant DJ. Post-9/11 sarcoidosis in WTC-exposed firefighters and emergency medical service workers. Respiratory Medicine. 2017;132:232–237. https://doi​.org/10.1016/j​.rmed.2017.06.004 . [PMC free article: PMC5720928] [PubMed: 28622920]
• Wei JC, Shi LH, Huang JY, Wu XF, Wu R, Chiou JY. Epidemiology and medication pattern change of psoriatic diseases in Taiwan from 2000 to 2013: A nationwide, population-based cohort study. Journal of Rheumatology. 2018;45(3):385–392. https://doi​.org/10.3899/jrheum.170516 . [PubMed: 29335350]
• Weng X, Liu L, Barcellos LF, Allison JE, Herrinton LJ. Clustering of inflammatory bowel disease with immune mediated diseases among members of a northern California-managed care organization. American Journal of Gastroenterology. 2007;102(7):1429–1435. https://doi​.org/10.1111/j​.1572-0241.2007.01215.x . [PubMed: 17437504]
• WHO (World Health Organization). Gender and health. 2021. [October 29, 2021]. https://www​.who.int/healthtopics​/gender#tab=tab_1 .
• Woodruff MC, Ramonell RP, Saini AS, Haddad NS, Anam FA, Rudolph ME, Bugrovsky R, Hom J, Cashman KS, Nguyen DC, Kyu S, Piazza M, Tipton CM, Jenks SA, Lee FE, Sanz I. medRxiv medRxiv. 2021. [Jul 27:2020]. Relaxed peripheral tolerance drives broad de novo autoreactivity in severe COVID-19. [Preprint] https://doi​.org/10.1101/2020​.10.21.20216192 .
• Wouters HJC M, Slagter SN, Muller Kobold AC, van der Klauw MM, Wolffenbuttel BHR. Epidemiology of thyroid disorders in the Lifelines Cohort Study (the Netherlands). PLOS ONE. 2020;15(11) https://doi​.org/10.1371/journal​.pone.0242795 . e0242795. [PMC free article: PMC7688129] [PubMed: 33237973]
• Xu F, Carlson SA, Liu Y, Greenlund KJ. Prevalence of inflammatory bowel disease among Medicare fee-for-service beneficiaries — United States, 2001−2018. Morbidity and Mortality Weekly Report. 2021;70(19) [PMC free article: PMC8118152] [PubMed: 33983913]
• Ye Y, Manne S, Treem WR, Bennett D. Prevalence of inflammatory bowel disease in pediatric and adult populations: Recent estimates from large national databases in the United States, 2007–2016. Inflammatory Bowel Diseases. 2020;26(4):619–625. https://doi​.org/10.1093/ibd/izz182 . [PubMed: 31504515]
• Yoshida EM, Riley M, Arbour LT. Autoimmune liver disease and the Canadian First Nations Aboriginal communities of British Columbia’s Pacific Northwest. World Journal of Gastroenterology. 2006;12(23):3625–3627. http://dx​.doi.org/10​.3748/wjg.v12.i23.3625 . [PMC free article: PMC4087452] [PubMed: 16773676]
• Yuen GJ. Autoimmunity in women: An examination of existing models. Clinical Immunology. 2020;210:108270. https://doi​.org/10.1016/j​.clim.2019.108270 . [PMC free article: PMC6989360] [PubMed: 31669190]
• Zielinski MR, Systrom DM, Rose NR. Fatigue, sleep, and autoimmune and related disorders. Frontiers in Immunology. 2019;10:1827. https://doi​.org/10.3389/fimmu.2019.01827 . [PMC free article: PMC6691096] [PubMed: 31447842]