insights

Autoimmune diseases, including rheumatic diseases, affect 3-10% of the world population.¹ Most autoimmune diseases are defined as a complex trait disorder where multiple genetic and environmental factors interact.¹ Functional medicine looks at everything that shapes the immune system, including hereditary, environmental, and intestinal factors that together cause the cascade of events leading to autoimmune disease. Recently, a number of significant advances in our understanding of the genetics of autoimmunity have been made through genome-wide association studies and the use of omics technologies. Research findings are helping scientists move toward a more personalized treatment approach for patients with autoimmune disease.

Key Features of Autoimmune Disease

Autoimmune diseases are marked by their complexity, and the heterogeneity of many of these diseases has made them difficult to define and treat.² A number of confirmed gene coding regions predispose an individual to autoimmunity; for instance, the human leukocyte antigen (HLA) region is associated with all autoimmune disease.³ Other loci associated with multiple autoimmune diseases are IL23R, TNFAIP3, and IL2RA.³ Yet despite these commonalities, the genetic heritability of autoimmune diseases is exceedingly variable, ranging from very high in Crohn’s disease and ankylosing spondylitis to almost negligible in systemic sclerosis.³ One estimate is that less than 15% of genes related to autoimmune risk have been identified.⁴ Over the past decade, many studies investigating the genetics of autoimmunity have found a common genetic feature: TYK2, which has been associated with over 20 different autoimmune diseases.⁵

Many autoimmune diseases, including systemic lupus erythematosus (SLE), disproportionately affect women.⁶ Scientists recently looked at blood cells from healthy women and men with Klinefelter syndrome (who carry one or more supernumerary X chromosomes and are also at an increased risk of lupus) and found that the gene that codes for toll-like receptor 7 (TLR7) escapes X-inactivation, a process that occurs during embryonic development and switches off one of the two X chromosomes to prevent the overexpression of genes. TLR7 binds single-stranded RNA and activates type I interferon signaling, a pathway that is also activated in SLE patients. The authors concluded that biallelic expression of TLR7 contributes to greater risk of lupus in individuals with two X chromosomes.⁶

Autoimmune diseases tend to run in families, but inheritance is often not Mendelian.⁷ Generally, familial autoimmunity does not cluster by condition, but rather, diverse autoimmune conditions can run in families.^8,9 The relatives of individuals with a specific autoimmune disease have a heightened incidence of systemic autoimmune diseases, such as SLE and rheumatoid arthritis, or organ-specific autoimmune diseases, such as chronic thyroiditis, Graves’ disease, insulin-dependent diabetes mellitus, and related autoimmune endocrinopathies. Only a few families have been shown to exhibit both systemic and organ-specific autoimmune diseases.¹⁰

Genetic Factors

Genome-wide association studies (GWAS) have identified hundreds of susceptibility genes among autoimmune diseases, largely affecting adults. One study of the pediatric population found that many of the autoimmune-related gene signals were in biological pathways functionally linked to cell activation, cell proliferation, and signaling systems important in immune processes.¹¹

One recent evaluation of shared genetic autoimmune loci suggests that autoimmunity may result from multiple different pleiotropic effects.³ This suggests that different population genetic factors (for example, natural selection and coevolution with pathogens, random mutation, isolations, etc.) led to the current loci that predispose an individual to autoimmunity, pointing to a potential interplay between population genetic factors and environmental factors.³ Alessio Fasano’s famed triad takes the connection even further, suggesting that genetic susceptibility, coupled with increased intestinal permeability, sets the stage for a specific environmental trigger to precipitate autoimmune disease. The trigger causes a break in immunological tolerance leading to the onset of an autoimmune cascade.¹²

In April 2021, research from Spain suggested that certain genetic variants that alter the binding ability of the protein PU.1 in neutrophils may also be associated with autoimmune disease susceptibility.¹³ This new study builds upon research called BLUEPRINT, which revealed how variation in blood cells’ characteristics and numbers can affect a person’s risk of developing autoimmune diseases, including rheumatoid arthritis, asthma, celiac disease, and type 1 diabetes. The current study suggests that variants associated with PU.1 differential binding (PU.1 tfQTLs) are enriched for genetic associations with cell count and susceptibility to multiple autoimmune and inflammatory diseases. While further research is needed to see if this change in the ability of PU.1 to bind directly causes certain autoimmune diseases, this research provides further understanding about the impact of these genetic variants on the cells in the body. Additionally, this research has illuminated a list of potential genes that could hold further information about the genetic causes of autoimmune disease.¹³

Also in April 2021, researchers in Japan compiled a first-of-its-kind genetic database for autoimmune and autoinflammatory diseases, sequencing the full genomes of 79 healthy volunteers and 337 patients diagnosed with any of 10 different categories of immune-mediated diseases, including rheumatoid arthritis, SLE and systemic sclerosis.¹⁴ Researchers isolated 28 different types of immune-related cells from volunteers’ blood samples and measured gene expression in those cells. The new resource will allow experts to more deeply understand how immune disorders develop. Scientists also hope this atlas of immune-related genome data may eventually be applied to investigations of infectious diseases like COVID-19.¹⁴

Emerging Research

In addition to specific genes that indicate risk for autoimmunity, gene expression affects disease risk and progression.² Transcriptomics, or RNA sequencing, allows scientists to study gene expression in a sample from a patient at a given time and monitor changes in gene expression over time from multiple samples.² Since 2007, rapid advances in GWAS have enhanced the identification of hundreds of genetic risk factors for many complex diseases.¹ This suggests that in the future, individual risk for autoimmunity may be measured over time, allowing tailored interventions.

Proteomics is also being widely used in autoimmune research to analyze molecules secreted by a variety of immune cells, including autoantibodies, cellular metabolites, and cytokines.² A team of scientists at Stanford University School of Medicine are using bead-based multiplex arrays to better diagnose, subtype, and treat patients with autoimmune diseases. They are also studying how the epigenome influences the immune system and have discovered a significant epigenetic difference between the immune system of elderly individuals versus the young.

Epigenetic mechanisms, which include DNA methylation, histone modification, and microRNA (miRNA), can produce heritable phenotypic changes without a change in DNA sequence.¹⁵ Recent research suggests that disruption of gene expression patterns that are governed by epigenetics may result in autoimmune diseases, including multiple sclerosis,¹⁶ primary Sjögren’s syndrome,¹⁷ type 1 diabetes,¹⁸ psoriasis,¹⁹ and lupus erythematosus.²⁰

Omics (e.g., genomics, proteomics, and metabolomics) data-processing tools have also been successful in revealing mechanisms underlying autoimmune pathogenesis and in identifying novel therapeutic targets.²¹ This research is helping scientists move toward a more personalized prevention and treatment approach for patients at risk for autoimmune disease.^2,22

Conclusion

Although genetics play a key role in autoimmune risk, environmental factors are known to have a large impact on the emergence of autoimmune conditions.²³ IFM’s Immune Advanced Practice Module provides an in-depth understanding of underlying immune mechanisms, which helps clinicians to develop effective interventions, even in the absence of a conventional diagnosis.

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References

1. Yamamoto K, Okada Y. Shared genetic factors and their causality in autoimmune diseases. Ann Rheum Dis. 2019;78(11):1449-1451. doi:1136/annrheumdis-2019-215099
2. Albert H. A new approach to autoimmunity: using multi-omic technology to reclassify and improve treatment for autoimmune disease. Genetic Engineering & Biotechnology News. Published January 22, 2018. Accessed December 10, 2021. https://www.genengnews.com/gen-exclusives/a-new-approach-to-autoimmunity/77901039
3. Ramos PS, Shedlock AM, Langefeld CD. Genetics of autoimmune diseases: insights from population genetics. J Hum Genet. 2015;60(11):657-664. doi:1038/jhg.2015.94
4. Ceccarelli F, Agmon-Levin N, Perricone C. Genetic factors of autoimmune diseases. J Immunol Res. 2016;2016:3476023. doi:1155/2016/3476023
5. Cortes A, Albers PK, Dendrou CA, Fugger L, McVean G. Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. Nat Genet.2020;52(1):126-134. doi:1038/s41588-019-0550-4
6. Souyris M, Cenac C, Azar P, et al. TLR7 escapes X chromosome inactivation in immune cells. Sci Immunol. 2018;3(19):eaap8855. doi:1126/sciimmunol.aap8855
7. Castiblanco J, Sarmiento-Monroy JC, Mantilla RD, Rojas-Villarraga A, Anaya J-M. Familial aggregation and segregation analysis in families presenting autoimmunity, polyautoimmunity, and multiple autoimmune syndrome. J Immunol Res. 2015;2015:572353. doi:1155/2015/572353
8. Cárdenas-Roldán J, Rojas-Villarraga A, Anaya J-M. How do autoimmune diseases cluster in families? A systematic review and meta-analysis. BMC Med. 2013;11:73. doi:1186/1741-7015-11-73
9. Mariani SM. Genes and autoimmune diseases—a complex inheritance: highlights of the 54th Annual Meeting of the American Society of Human Genetics; October 26-30, 2004; Toronto, Ontario, Canada. MedGenMed. 2004;6(4):18.
10.  Rose NR, Burek CL. Genetic predisposition to thyroid autoimmune disease: introduction. Mt Sinai J Med. 1986;53(1):3-5.
11.  Li YR, Li J, Zhao SD, et al. Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases. Nat Med. 2015;21(9):1018-1027. doi:1038/nm.3933
12.  Fasano A. Leaky gut and autoimmune diseases. Clin Rev Allergy Immunol. 2012;42(1):71-78. doi:1007/s12016-011-8291-x
13.  Watt S, Vasquez L, Walter K, et al. Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease. Nat Commun. 2021;12(1):2298. doi:1038/s41467-021-22548-8
14.  Ota M, Nagafuchi Y, Hatano H, et al. Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases. 2021;184(11):P3006-3021. doi:1016/j.cell.2021.03.056
15.  Zhang L, Lu Q, Chang C. Epigenetics in health and disease. Adv Exp Med Biol. 2020;1253:3-55. doi:1007/978-981-15-3449-2_1
16.  Chan VS. Epigenetics in multiple sclerosis. Adv Exp Med Biol. 2020;1253:309-374. doi:1007/978-981-15-3449-2_12
17.  Bordron A, Devauchelle-Pensec V, Le Dantec C, Capdeville A, Brooks WH, Renaudineau Y. Epigenetics in primary Sjögren’s syndrome. Adv Exp Med Biol. 2020;1253:285-308. doi:1007/978-981-15-3449-2_11
18.  Xie Z, Chang C, Huang G, Zhou Z. The role of epigenetics in type 1 diabetes. Adv Exp Med Biol. 2020;1253:223-257. doi:1007/978-981-15-3449-2_9
19.  Shao S, Gudjonsson JE. Epigenetics of psoriasis. Adv Exp Med Biol. 2020;1253:209-221. doi:1007/978-981-15-3449-2_8
20.  Wu H, Chang C, Lu Q. The epigenetics of lupus erythematosus. Adv Exp Med Biol. 2020;1253:185-207. doi:1007/978-981-15-3449-2_7
21.  Langan D, Rose NR, Moudgil KD. Common innate pathways to autoimmune disease. Clin Immunol. 2020;212:108361. doi:1016/j.clim.2020.108361
22.  Bae RH, Leung PSC, Hodge DL, et al. Multi-omics: differential expression of IFN-? results in distinctive mechanistic features linking chronic inflammation, gut dysbiosis, and autoimmune disease. J Autoimmun. 2020;111:102436. doi:1016/j.jaut.2020.102436
23.  Anaya J-M, Ramirez-Santana C, Alzate MA, Molano-Gonzalez N, Rojas-Villarraga A. The autoimmune ecology. Front Immunol. 2016;7:139. doi:3389/fimmu.2016.00139