NIH Awards $1.9 million to Find Genetic Markers to Explain How White Blood Cells Cause Damage in MS
The Benaroya Research Institute at Virginia Mason (BRI) was awarded a $1.9 million grant from the National Institutes of Health (NIH) to study molecular changes in the human genome which may be responsible for damage to the central nervous system as seen in multiple sclerosis.
Researchers aim to explain how and why certain white blood cells contribute to the development of MS. “We want to understand the factors that make these cells target the spinal cord and brain to cause disease,” said Estelle Bettelli, PhD, BRI Assistant Member and co-principal investigator of the study in the August 4, 2013 press release.
"With Dr. Bettelli's research advances and with the new technological innovations in genome research, we can look at specific marks present in the genome of these cells and understand how they are generated and how they can be controlled," says co-principal investigator Steven Ziegler, PhD, Director of the BRI Immunology Research Program.
“Several factors, including the cell types involved, are believed to dictate the clinical progression of MS,” says Dr. Betelli. “The understanding of how and which cell populations of the immune system participate in the autoimmune attack is very important for determining current treatments and designing new therapeutics tailored to the different forms of MS. We hope to find ways to significantly inhibit these dangerous cells with new targeted medicines with fewer side effects.”
Since the completion of the Human Genome Project in 2003, significant research has looked more closely to our genes as contributing factors to developing MS. The first three studies which identified genetic variations associated with MS in the human leukocyte antigen (HLA) region of the human genome were published in 2007.
To date, there have been at least seven genome-wide association studies (GWAS) and one meta-analysis which have identified an additional 57 non-HLA genetic variations. Twenty-nine of those variations were identified in the largest collaborative GWAS involving nearly 10,000 MS patients of European descent and 23 research groups working in 15 different countries published in the journal Nature in August 2011.
A study of genetic variations can also explain why some treatments may or may not work well in patients living with multiple sclerosis. In a study published in 2012, researchers from Oxford University identified a genetic variant linked to MS which is not only associated with developing the disease, but is also responsible for blocking the effectiveness of anti-TNF medications. It is believed that this gene, TNFRSF1A, is the reason patients who use TNF-inhibitors (such as Humira or Enbrel) for other diseases may experience a worsening of MS or other demyelinating disease.
If you are interested in reading more about advances in genomic research in MS and other autoimmune diseases, please refer to the resources section below for select publications.
Benaroya Research Institute at Virginia Mason (Sept 4, 2013). First study to investigate the human genome in multiple sclerosis [press release]. Retrieved from http://www.eurekalert.org/pub_releases/2013-09/itn-fst090313.php
BBC News: Health (Jul 9, 2012). Gene flaw explains why drugs failed to treat MS. Retrieved from http://www.bbc.co.uk/news/health-18738785
Yale News (Aug 10, 2011). New Genetic Links to MS Also Play Roles In Other Autoimmune Diseases. Retrieved from http://news.yale.edu/2011/08/10/new-genetic-links-ms-also-play-roles-other-autoimmune-diseases
Regal C. (Aug 1, 2012). MS and the Human Genome: A HealthCentral Explainer. Retrieved from http://www.healthcentral.com/multiple-sclerosis/c/215658/154979/human/
Disanto G, Sandve GK, Berlanga-Taylor AJ, Morahan JM, Dobson R, et al. Genomic Regions Associated with Multiple Sclerosis Are Active in B Cells. PLoS ONE. 2012; 7(3): e32281. doi:10.1371/journal.pone.0032281. Retrieved from http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032281
International Multiple Sclerosis Genetics Consortium. Network-Based Multiple Sclerosis Pathway Analysis with GWAS Data from 15,000 Cases and 30,000 Controls. Am J Hum Genet. 2013 June 6;92(6);854-865. pii: S0002-9297(13)00180-8. doi: 10.1016/j.ajhg.2013.04.019. Epub 2013 May 22. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23731539
International Multiple Sclerosis Genetics Consortium & Wellcome Trust Case Control Consortium 2. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011 Aug 10;476(7359):214–219. doi:10.1038/nature10251. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21833088
Katsavos S, Anagnostouli M. Biomarkers in Multiple Sclerosis: An Up-to-Date Overview. Mult Scler Int. 2013;2013:340508. doi: 10.1155/2013/340508. Epub 2013 Jan 22. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564381/
Baranzini SE, Mudge J, van Velkinburgh JC, et al. Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis. Nature. 2010 April 29; 464(7293): 1351–1356. doi:10.1038/nature08990. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20428171
Ebers GC, Kukay K, et al. A full genome search in multiple sclerosis. Nature Genetics. 1996;13:472-476. doi:10.1038/ng0896-472. Retrieved from http://www.nature.com/ng/journal/v13/n4/abs/ng0896-472.html
International Multiple Sclerosis Genetics Consortium. Comprehensive follow-up of the first genome-wide association study of multiple sclerosis identifies KIF21B and TMEM39A as susceptibility loci. Hum Mol Genet. 2010 Mar 1;19(5):953-62. doi: 10.1093/hmg/ddp542. Epub 2009 Dec 9. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2816610/
International Multiple Sclerosis Genetics Consortium. Genome-wide association study of severity in multiple sclerosis. Genes Immun. 2011 Dec;12(8):615-25. doi: 10.1038/gene.2011.34. Epub 2011 Jun 9. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21654844
Kemppinen A, Sawcer S, Compston A. Genome-wide association studies in multiple sclerosis: lessons and future prospects. Brief Funct Genomics. 2011 Mar;10(2):61-70. doi: 10.1093/bfgp/elr004. Epub 2011 Feb 10. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21310812
Leone MA, Barizzone N, Esposito F, Lucenti A, Harbo HF, et al. Association of Genetic Markers with CSF Oligoclonal Bands in Multiple Sclerosis Patients. PLoS ONE. 2013;8(6): e64408. doi:10.1371/journal.pone.0064408. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0064408
Mechelli R, Umeton R, Policano C, Annibali V, Coarelli G, et al. A ‘‘Candidate-Interactome’’ Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis. PLoS ONE. 2013;8(5): e63300. doi:10.1371/journal.pone.0063300. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3655974/
Patsopoulos NA. Genomewide meta-analysis identifies novel multiple sclerosis susceptibility loci. Ann Neurol. 2011 December ; 70(6): 897–912. doi:10.1002/ana.22609. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22190364
Ramagopalan SV, Dyment DA. What is Next for the Genetics of Multiple Sclerosis?. Autoimmune Dis. 2011 Mar 28;2011:519450. doi:10.4061/2011/519450. Retrieved from http://www.hindawi.com/journals/ad/2011/519450/
Sawcer S, Jones HB, et al. A genome screen in multiple sclerosis reveals susceptibility loci on chromosome 6p21 and 17q22. Nature Genetics. 1996;13:464-468. doi:10.1038/ng0896-464. Retrieved from http://www.nature.com/ng/journal/v13/n4/abs/ng0896-464.html
Simon Fraser University (Oct 25, 2012). Scientists deepen genetic understanding of multiple sclerosis. ScienceDaily. Retrieved from http://www.sciencedaily.com/releases/2012/10/121025161757.htm
Watson CT, Disanto G, Breden F, Giovannoni G, Ramagopalan SV. Estimating the proportion of variation in susceptibility to multiple sclerosis captured by common SNPs. Scientific Reports. 2012;2 doi: 10.1038/srep00770. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23105968