Genetic overlap between type 1 diabetes and other autoimmune diseases

Bidirectional association between inflammatory bowel disease and type 1 diabetes: a nationwide matched cohort and case-control study

Background

Co-occurrence of inflammatory bowel disease (IBD) and type 1 diabetes (T1D) has been linked to poor clinical outcomes, but evidence on their bidirectional associations remain scarce. This study aims to investigate their bidirectional associations.

Methods

A nationwide matched cohort and case-control study with IBD patients identified between 1987 and 2017. The cohort study included 20,314 IBD patients (≤28 years; Crohn's disease [CD, n = 7277], ulcerative colitis [UC, n = 10,112], and IBD-unclassified [IBD-U, n = 2925]) and 99,200 individually matched reference individuals, with a follow-up until December 2021. The case-control study enrolled 87,001 IBD patients (no age restriction) and 431,054 matched controls. We estimated adjusted hazard ratio (aHR) of incident T1D in the cohort study with flexible parametric survival model and adjusted odds ratio (aOR) of having a prior T1D in the case-control study with conditional logistic regression model, with 95% confidence intervals (CI).

Findings

During a median follow-up of 14 years, 116 IBD patients and 353 reference individuals developed T1D. Patients with IBD had a higher hazard of developing T1D (aHR = 1.58 [95% CI = 1.27-1.95]). The hazard was increased in UC (aHR = 2.02 [1.51-2.70]) but not in CD or IBD-U. In the case-control study, a total of 1018 (1.2%) IBD patients and 3496 (0.8%) controls had been previously diagnosed with T1D. IBD patients had higher odds of having prior T1D (aOR = 1.36 [1.26-1.46]). Such positive association was observed in all IBD subtypes. The sibling comparison analyses showed similar associations between IBD and T1D (aHR = 1.44 [0.97-2.15] and aOR = 1.32 [1.18-1.49]).

Interpretation

Patients with IBD had a moderately increased hazard of developing T1D and higher odds of having prior T1D. Their bidirectional associations may be partially independent of shared familial factors.

Funding

European Crohn's and Colitis Organisation, Stiftelsen Professor Nanna Svartz Fond, SSMF (project#: PG-23-0315-H-02), Ruth and Richard Julin Foundation; and FORTE (project#: 2016-00424).

Auto-immuno-deficiency syndromes

Autoimmune diseases constitute a broad, heterogenous group with many diverse and often overlapping symptoms. Even so, they are traditionally classified as either systemic, rheumatic diseases or organ-directed diseases. Several theories exist about autoimmune diseases, including defective self-recognition, altered self, molecular mimicry, bystander activation and epitope spreading. While there is no consensus about these theories, it is generally accepted that genetic, pre-disposing factors in combination with environmental factors can result in autoimmune disease. The relative contribution of genetic and environmental factors varies between diseases, as does the significance of individual contributing factors within related diseases. Among the genetic factors, molecules involved in antigen (Ag) recognition, processing, and presentation stand out (e.g., MHC I and II) together with molecules involved in immune signaling and regulation of cellular interactions (i.e., immuno-phenotypes). Also, various immuno-deficiencies have been linked to development of autoimmune diseases. Among the environmental factors, infections (e.g., viruses) have attracted most attention, but factors modulating the immune system have also been the subject of much research (e.g., sunlight and vitamin D). Multiple sclerosis currently stands out due to a very strong and proven association with Epstein-Barr virus infection, notably in cases of late infection and in cases of EBV-associated mononucleosis. Thus, a common picture is emerging that both systemic and organ-directed autoimmune diseases may appropriately be described as auto-immuno-deficiency syndromes (AIdeSs), a concept that emphasizes and integrates existing knowledge on the role of immuno-deficiencies and chronic infections with development of overlapping disease syndromes with variable frequencies of autoantibodies and/or autoreactive T cells. This review integrates and exemplifies current knowledge on the interplay of genetically determined immuno-phenotypes and chronic infections in the development of AIdeSs.

Deciphering Autoimmune Diseases: Unveiling the Diagnostic, Therapeutic, and Prognostic Potential of Immune Repertoire Sequencing

Autoimmune diseases (AIDs) are immune system disorders where the body exhibits an immune response to its own antigens, causing damage to its own tissues and organs. The pathogenesis of AIDs is incompletely understood. However, recent advances in immune repertoire sequencing (IR-seq) technology have opened-up a new avenue to study the IR. These studies have revealed the prevalence in IR alterations, potentially inducing AIDs by disrupting immune tolerance and thereby contributing to our comprehension of AIDs. IR-seq harbors significant potential for the clinical diagnosis, personalized treatment, and prognosis of AIDs. This article reviews the application and progress of IR-seq in diseases, such as multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, and type 1 diabetes, to enhance our understanding of the pathogenesis of AIDs and offer valuable references for the diagnosis and treatment of AIDs.

Pleiotropic Bias and Study Design Considerations in Genetic Association Studies

Background

Case-control studies are efficient designs for investigating gene-disease associations. A discovery of genome-wide association studies (GWAS) is that many genetic variants are associated with multiple health outcomes and diseases, a phenomenon known as pleiotropy. We aimed to discuss about pleiotropic bias in genetic association studies.

Methods

The opinions of the researchers on the basis of the literature were presented as a critical review.

Results

Pleiotropic effect can bias the results of gene-disease association studies if they use individuals with pre-existing diseases as the control group, while the disease in cases and controls have shared genetic markers. The idea supports the conclusion that when the exposure of interest in a case-control study is a genetic marker, the use of controls from diseased cases that share similar genetic markers may increase the risk of pleiotropic effect. However, not manifesting the disease symptoms among controls at the time of recruitment does not guarantee that the individual will not develop the disease of interest in the future. Age-matched disease-free controls may be a better solution in similar situations. Different analytical techniques are also available that can be used to identify pleiotropic effects. Known pleiotropic effects can be searched from various online databases.

Conclusion

Pleiotropic effects may result in bias in genetic association studies. Suggestions consist of selecting healthy yet age-matched controls and considering diseases with independent genetic architecture. Checking the related databases is recommended before designing a study.