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Could –omics hold the key to MS?

Multiple Sclerosis (MS) is a tricky disease, which is why scientists have found themselves delving deeper and deeper in a bid to shed light on the mechanisms behind it. In labs across the world, experts are using new technologies to “zoom in” and take a peek at what’s going on inside our cells.

One particular form of scientific study, known as molecular research has made incredible strides in the last years. The field of genomics in particular has opened up a whole new understanding of the different molecular pathways that give rise to changes seen in autoimmune diseases like MS1. This in turn has given us a better understanding of how drugs affect the body, and could one day be used to reverse the effects of this complex condition.

Here’s a look at some of the so-called “-omics” fields of research that are changing lives, molecule by molecule.

Genomics

Nearly every disease is related in some way or another to our genes2. Unlike genetics, which looks at how single genes affect the body, genomics is the study of genomes – the complete set of DNA of an organism2.

Thanks to the Human Genome Project, a ground-breaking international initiative that set out to sequence the entire set of human genes2  (around 25,000 genes, or so!2), we now have access to a wealth of information. The completion of this project set the stage for many more research projects to come. Because knowing the “code” of the human DNA is not enough, we also need to understand what this code actually means and how our bodies use this information. In the past few years, we have learned a great deal about how certain genes act together, and the health consequences changes in these genes can cause.

Though there is no single gene that causes MS 3, genomics allows scientists to look for variations that are more common in people with the condition than in healthy people. What’s more, genome-based research is enabling scientists to develop improved ways of diagnosing the disease, as well as coming up with more effective treatments2.

In the future, for example, it’s likely that treatments will be tailored to a person’s particular genes (pharmacogenomics), as we know that people with different genetic make-ups respond in different ways to treatment4.

Transcriptomics

The human genome is made up of DNA, which is then converted in the cell into a messenger form called mRNA. It’s this transcript of the original DNA that is then “read” by the ribosomes, molecular machines in the cell. The ribosomes use the chemical transcript as instructions for creating different arrangements of amino acids to form specific proteins5. Analyzing the entire collection of mRNA sequences in a cell (the transcriptome),5 allows researchers to work out the amount of gene activity – otherwise known as gene expression – in a certain cell or tissue type5.

Studying the transcriptomes of people with MS has helped highlight processes that trigger T cells to go rogue, and cause the inflammation seen in MS. Not only have these helped scientists to understand the workings of the immune system, this additional knowledge might also lead to new possibilities for treatments that target these pathways6.

Proteomics

This is the study of (you guessed it), the proteins produced by our cells’ ribosomes7. By studying these proteins, scientists can identify particular molecules or “biomarkers” in the blood or tissues that can be used to detect abnormal processes.

Proteomics is helping researchers to understand the various immune pathways at play in MS8.  With the help of this specific field of research, the hope is to find and define specific biomarkers that will not only allow an earlier diagnosis but also predict disease progression and response to treatments9.

Metabolomics

Okay, this one’s a bit trickier. Metabolites are basically the end products of chemical processes that occur within a cell. So a cell’s metabolome (the collection of these chemical end products) can tell scientists a great deal about the processes that are taking place in the cell10. Again, certain metabolites can be used as biomarkers of disease. One study, for example, compared metabolites in the cerebrospinal fluid of people with MS and people without the condition and found differences that suggest that certain metabolic pathways are altered in MS11.

Lipidomics

Another important component of our cells are fats (or lipids). One study, for example, found people with MS had altered levels of two lipids Lysophosphatidylcholine (lysoPC and PC, for short), specifically a lower ratio of lysoPC to PC than people with other neurological diseases12. Again it’s possible that lipidomics could be used as a way to diagnose the disease in future, as well as providing insight into alternative biochemical pathways of the disease13.

So what does all this mean for people with MS?

If the technical terms haven’t completely bamboozled you, then hopefully they’ve given you a good idea of just how seriously researchers are taking MS. The guys and gals in lab coats are basically leaving no cell unturned. Already, these fields are changing the way in which scientists are approaching MS, with many more breakthroughs on the horizon.

By understanding what’s going on at a cellular level, scientists have a much better chance of finding ways to intervene, and block the harmful processes that lead to the destruction of myelin. In time, the data from each of these fields will begin to overlap, providing an even clearer picture of what causes MS and how we can stop it in its tracks. Yes, MS is a sneaky condition – but the researchers are doing their utmost to outsmart it. Bring it on.

References:

  1. Rapid progress in our understanding of immune function promises more effective treatments for autoimmune disorders. Nature Biotechnology 18, IT7 - IT9 (2000). http://www.nature.com/nbt/journal/v18/n10s/full/nbt1000_IT7.html
  2. National Human Genome Research Institute. A Brief Guide to Genomics. DNA, Genes and Genomes. https://www.genome.gov/18016863 
  3. Website “Multiple Sclerosis Society” – Causes of MS. Last accessed: 05.04.16. https://www.mssociety.org.uk/what-is-ms/information-about-ms/causes
  4. National Library of Medicine. Genetics Home Reference. https://ghr.nlm.nih.gov/handbook/genomicresearch/pharmacogenomics
  5. NIH. National Human Genome Research Institute. Transcriptome. https://www.genome.gov/13014330
  6. The multiple sclerosis whole blood mRNA transcriptome and genetic associations indicate dysregulation of specific T cell pathways in pathogenesis. Gandhi KS1, McKay FC, Cox M, Riveros C, Armstrong N, et al. ANZgene Multiple Sclerosis Genetics Consortium. Hum Mol Genet. 2010 Jun 1;19(11):2134-43. http://www.ncbi.nlm.nih.gov/pubmed/20190274
  7. Website “Human Proteome Organization” – What is Proteomics? Last accessed: 06.04.16. https://www.hupo.org/background/proteomics/
  8. Ten years of proteomics in multiple sclerosis. Farias AS, Pradella F, Schmitt A, Santos LM, Martins-de-Souza D. Proteomics. 2014 Mar;14(4-5):467-80. http://www.ncbi.nlm.nih.gov/pubmed/24339438
  9. Cerebrospinal fluid proteomics in multiple sclerosis. Kroksveen AC, Opsahl JA, Guldbrandsen A, Myhr KM, Oveland E, Torkildsen Ø, Berven FS. Biochim Biophys Acta. 2015 Jul;1854(7):746-56. http://www.ncbi.nlm.nih.gov/pubmed/25526888
  10. New Medical. Life Sciences & Medicine. http://www.news-medical.net/life-sciences/What-are-Metabolites.aspx 
  11. Metabolomic profiling in multiple sclerosis: insights into biomarkers and pathogenesis.Reinke SN1, Broadhurst DL, Sykes BD, Baker GB, Catz I, Warren KG, Power C. Mult Scler. 2014 Sep;20(10):1396-400. http://www.ncbi.nlm.nih.gov/pubmed/?term=24468817
  12. Lipidomic investigations for the characterization of circulating serum lipids in multiple sclerosis. Del Boccio P, Pieragostino D, Di Ioia M, Petrucci F, Lugaresi A, De Luca G, Gambi D, Onofrj M, Di Ilio C, Sacchetta P, Urbani A. J Proteomics. 2011 Nov 18;74(12):2826-36. http://www.ncbi.nlm.nih.gov/pubmed/21757039
  13. Nat Rev Drug Discov. 2005 Jul;4(7):594-610. The emerging field of lipidomics. Wenk MR. Nat Rev Drug Discov. 2005 Sep;4(9):725. http://www.ncbi.nlm.nih.gov/pubmed/16052242
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