Researchers identified the beneficial changes that occur naturally in the immune system during pregnancy.
The study was published in 'Journal of Neuroinflammation'
From an immunological standpoint, pregnancy is a very unique condition. The immune system protects us from foreign substances. Despite the fact that half of the foetus' genetic material comes from the father, it is not rejected by the mother's immune system. One reason this balancing act is almost always successful is that the mother's immune system is adapted to become more tolerant during pregnancy.
Multiple sclerosis (MS) impairs nerve function because the immune system attacks the fat that acts as an insulating sheath around the nerve fibres. Inflammation of the nerves can result in nerve damage. Despite the availability of new and more effective treatment options, the majority of MS patients deteriorate over time.
Researchers believe that the temporary suppression of the immune response may explain why pregnant women with MS improve. Symptoms, or relapses, are reduced by 70% during the last third of pregnancy. Other autoimmune diseases, such as rheumatoid arthritis, also temporarily improve during pregnancy. However, the reason for this has not been revealed. This is why the researchers behind this study wanted to look into what mechanisms might be important for the decrease in symptoms during pregnancy, as a first step towards developing future treatment strategies that have the same effect in MS and possibly other similar diseases.
T cells, which play an important role in the immune system, piqued the researchers' interest. Furthermore, T cells are important during pregnancy and play an important role in MS. The researchers compared 11 women with MS to 7 healthy women who had blood drawn before, during, and after pregnancy.
The researchers identified the genes used in T cells at various points during pregnancy to better understand what happens in immune cells. They also looked into changes that control how genes are turned on and off, known as epigenetic changes. The researchers focused their investigation on one such regulation mechanism known as DNA methylation.
"What was possibly most striking is that we couldn't find any real differences between the groups during pregnancy, as it seems that the immune system of a pregnant woman with MS looks roughly like that of a healthy pregnant woman, said Sandra Hellberg, assistant professor at the Department of Biomedical and Clinical Sciences at Linkoping University and one of the researchers behind the study.
The researchers found networks of interacting genes that are affected during pregnancy. Their study found that these genes are to a large extent linked to the disease and to important processes in the immune system.
"We can see that the changes in the T cells mirror the amelioration in relapse frequency. The biggest changes happen in the last third of pregnancy, and this is where women with MS improve the most. These changes are then reversed after pregnancy at the point in time when there is a temporary increase in disease activity. It is important to stress that disease activity thereafter goes back to what it was prior to the pregnancy," said Sandra Hellberg.
The network of genes affected during pregnancy also included genes regulated by pregnancy hormones, mainly progesterone. The researchers are now testing various hormones in the lab in an attempt to mimic the effects observed in the study, to see if these can be part of a possible future treatment strategy.
This research is the result of a long-standing collaboration between researchers in medicine and bioinformatics. A key part of the project has been understanding the large amount of data by analysing it using what is known as network analysis, developed over many years by, among others, a research group led by Mika Gustafsson at Linkoping University. Network analysis is a tool for finding genes that interact extensively with the genes the researchers are interested in. It often turns out that other genes in the network are regulated in an abnormal manner and indirectly affect key processes in disease.
"Such insights can be used to find alternative medication and find new biomarkers to be able to differentiate between subgroups of a disease. We have used this strategy successfully for analysis in research into for instance allergy and multiple sclerosis", said Mika Gustafsson, professor of Bioinformatics, who is now making the analysis available to other researchers through a newly founded company.
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