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Research Continues to Link Genes to Autoimmune Disease

Research Continues to Link Genes to Autoimmune Disease

Close to 24 million Americans have been diagnosed with an autoimmune disease,1 and Functional Medicine clinicians typically look at a patient’s health history, intestinal symptoms, environment, and genetic makeup to form a diagnosis. In the realm of genetics, a number of significant advances have been made through genome-wide association studies and through the use of omics technologies to inform patient treatment. Research findings are helping scientists move toward a more personalized treatment approach for patients with autoimmune disease.

This rising interest in genetics isn’t contained to the medical community; DNA testing services are gaining popularity. Patients can obtain a wealth of information on anything from lactose intolerance to proclivity to certain diseases and even access a raw, uninterpreted genetic data file.

Autoimmune diseases are marked by their complexity, and the heterogeneity of many of these diseases has made them difficult to define and treat.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

Many autoimmune diseases, including lupus, disproportionately affect women.5 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.5 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.5

Autoimmune diseases also run in families, but inheritance is not Mendelian.6 Familial autoimmunity does not cluster by condition, but rather diverse autoimmune conditions can run in families.7,8 Generally, the families of these individuals have a heightened incidence of systemic autoimmune diseases, such as lupus erythematosus 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.9

Genome-wide association studies have identified hundreds of susceptibility genes among autoimmune diseases, largely affecting adults. A 2015 study focused on the pediatric population. Researchers discovered many of the autoimmune-related gene signals were on biological pathways functionally linked to cell activation, cell proliferation, and signaling systems important in immune processes.10

One recent evaluation of shared genetic autoimmune loci suggests that autoimmunity may result from specific and 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 Fasano’s triad takes the connection even further, supporting a new paradigm in which genetic susceptibility, coupled with increased intestinal permeability, sets the stage for a specific environmental trigger. The trigger then causes a break in immunological tolerance and the onset of an autoimmune cascade.11

In addition to specific genes that indicate risk for autoimmunity, gene expression changes 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 or to monitor change in gene expression over time from multiple samples.2 This suggests that in the future, individual risk for autoimmunity can 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. Omics research is developing at a rapid rate and is helping scientists move toward a more personalized treatment approach for patients with autoimmune disease.2

Although genetics play a key role in autoimmune risk, environmental factors are known to have a much larger effect on the emergence of autoimmune conditions.12 Functional Medicine looks at all of the factors that shape the immune system—hereditary, environmental, and intestinal—that together cause the cascade that leads to the development of autoimmune disease.

View the Solving the Puzzle of Autoimmunity: The Interplay of Gut, Genes, and Environment Conference Proceedings to explore clinical topics from IFM’s 2018 Annual International Conference on autoimmunity.

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References

  1. Fairweather D, Frisancho-Kiss S, Rose NR. Sex differences in autoimmune disease from a pathological perspective. Am J Pathol. 2008;173(3):600-609. doi:10.2353/ajpath.2008.071008.
  2. Albert H. A new approach to autoimmunity: using multi-omic technology to reclassify and improve treatment for autoimmune disease. Genetic Engineering & Biotechnology News. https://www.genengnews.com/gen-exclusives/a-new-approach-to-autoimmunity/77901039. Published January 22, 2018. Accessed January 30, 2018.
  3. Ramos P, Shedlock A, Langefeld C. Genetics of autoimmune diseases: insights from population genetics. J Hum Genet. 2015;60(11):657-664. doi:10.1038/jhg.2015.94.
  4. Ceccarelli F, Agmon-Levin N, Perricone C. Genetic factors of autoimmune diseases. J Immunol Res. 2016;2016:3476023. doi:10.1155/2016/3476023.
  5. Souyris M, Cenac C, Azar P, et al. TLR7 escapes X chromosome inactivation in immune cells. Sci Immunol. 2018;3(19):eaap8855. doi:10.1126/sciimmunol.aap8855.
  6. 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:10.1155/2015/572353.
  7. 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:10.1186/1741-7015-11-73.
  8. 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.
  9. Rose NR, Burek CL. Genetic predisposition to thyroid autoimmune disease: introduction. Mt Sinai J Med. 1986;53(1):3-5.
  10. 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:10.1038/nm.3933.
  11. Fasano A. Leaky gut and autoimmune diseases. Clin Rev Allergy Immunol. 2012;42(1):71-78. doi:10.1007/s12016-011-8291-x.
  12. Anaya J-M, Ramirez-Santana C, Alzate MA, Molano-Gonzalez N, Rojas-Villarraga A. The autoimmune ecology. Front Immunol. 2016;7:139. doi:10.3389/fimmu.2016.00139.

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