A mathematical method to identify methylation signals in blood

Dr Andrew Fox

Florey Institute of Neuroscience and Mental Health, VIC

| Causes and Prevention | Genetics | Incubator | 2016 | Investigator Led Research |


Problems in controlling the level of activity of certain genes may be involved in the development and progression of MS. One way of controlling gene activity is through a process called DNA methylation. DNA methylation is where a chemical ‘tag’ is added to the DNA in the control area of the gene to switch the gene on or off in response to cues in the environment. For example smoking and vitamin D levels are known to affect methylation patterns.

Human blood contains a mixture of immune and other cells. Researchers have been collecting blood samples from people with MS over long periods of time and this blood has been stored (frozen) in its entirely for future use. Individual cell types were not separated out for storage. This makes it harder to identify exactly which cells in the blood have altered DNA methylation patterns in MS compared to healthy individuals. Dr Fox is developing a statistical analysis method which will allow methylation patterns from specific cell types to be identified from methylation data obtained from whole blood. Such an algorithm will be applicable on worldwide datasets of stored blood to obtain meaningful answers regarding changes in gene activity over time and in response to environmental stimuli.

Project Outcomes

Different cell types within a given tissue, in this case the blood, can and do exhibit different DNA methylation profiles. At the moment, separating and purifying different cell types from the larger mixture of cells in is time consuming and costly; and in certain diseases such as in MS, it is not known exactly which cell type is responsible for the disease.

Dr Fox and his colleagues have developed a statistical (mathematical) method that infers the proportion or percentage of each cell type in the whole blood. Upon initial testing, Dr Fox’s approach appears to be more accurate and simpler than the currently used methods. His team then used this method to determine the methylation patterns in specific cell populations from methylation data obtained from the entire blood. When comparing the cell type specific methylation data from people with and without MS, over 400 differences were identified. However, it should be noted that many of these differences were already known, and that this small short-term study used these results to assess the feasibility and accuracy of this new method.

Dr Fox and his colleagues have submitted this method and the findings for publication, and have demonstrated that these methods are extremely valuable for extracting cell type specific information from generalised blood data. In the future this method can be used to discover new gene changes and gene expression levels in specific cell types genuinely associated with the development and progression of MS and other diseases.

The development of this technique opens up an exciting and very important new avenue of research that will allow a much deeper understanding of how genes and the environment interact to contribute to the development of MS.


  • Field J, Fox A, Jordan MA, Baxter AG, Spelman T, Gresle M, Butzkueven H, Kilpatrick TJ, Rubio JP. Interleukin-2 receptor-α proximal promoter hypomethylation is associated with multiple sclerosis. Genes and Immunity, 2017 Jan 12. doi: 10.1038/gene.2016.50. PubMed PMID: 28077880.
  • Two more submitted and under review.

Updated 3 July 2017

Updated: 03 January, 2016


  • Dr Andrew Fox, Florey Institute of Neuroscience and Mental Health, VIC

Grant Awarded

  •  Incubator Grant

Total Funding

  • $20,000


  • 1 year

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A mathematical method to identify methylation signals in blood