The IONA® test is a non-invasive prenatal test (NIPT) for pregnant women which estimates the risk of a fetus having Down’s syndrome (Trisomy 21), Edwards’ syndrome (Trisomy 18) and Patau’s syndrome (Trisomy 13). The test is performed by analysing cell-free placental-fetal DNA from a maternal blood sample. The test is suitable for women who are at least 10 weeks pregnant, prior to ten weeks there is a risk that there would be insufficient placental-fetal cell free DNA to allow a reliable test.
Although IONA® is suitable for most pregnancies there are some exclusions listed within the test information. These include cases where the mother has cancer or where she has received an organ transplant, or any treatment involving the transfusion of heterologous cells in the last 12 months, or where she carries a chromosomal imbalance. This short article explores the reasoning behind these exclusions and explains why they have been put in place.
To understand the reason for these exclusions we have to go back a step and understand exactly how the IONA® test works and the assumptions built into it. It has been known for a long time that during pregnancy a small amount of cell free DNA leaks out from the fetoplacental unit into the mother’s blood. The mother’s blood also contains her own cell free DNA so when she is pregnant her blood contains a mixture of maternal and fetal cell free DNA. Typically, the amount of fetal cell free DNA is about 10% of the total. This figure is known as the fetal fraction
The cell free DNA in the blood is highly fragmented but significantly the relative proportion of DNA derived from each chromosome is maintained. For example, chromosome 1 is the largest human chromosome and comprises 249,000,000 base pairs, equivalent to about 7.54% of the human genome. When cell free DNA is extracted and analysed the fragments derived from chromosome 1 also comprise 7.54% of the total. This pattern is repeated for all the other human chromosomes.
Because the chromosomal ratios are maintained in cell free DNA, we can now see how an NIPT test like IONA® works. Imagine the situation where a woman is pregnant with a fetus carrying trisomy 21. Chromosome 21 is 46,709,983 bp long so in a normal individual represents 46.7Mb /3.3Gb (the size of the human genome) or 1.41% of the genome. In an individual affected by Down’s syndrome there is an extra copy of chromosome 21. As a result of this, the proportion of chromosome 21 derived DNA is increased 1.5-fold to 2.1%. In the case of the pregnant woman the increase of chromosome 21 DNA in her cell free DNA is about 1.47% (the actual increase depends on the fetal fraction in the particular pregnancy).
Now an increase from 1.41% of DNA from chromosome 21 in an unaffected pregnancy to 1.47% in a pregnancy affected by Down’s syndrome is admittedly not a large difference but it is this small difference that forms the basis of the IONA® test. Throughout the test workflow, many millions of DNA fragments are sequenced and mapped back to their chromosome of origin and this allows a very accurate and precise measurement of the proportion of chromosome 21 DNA in the bloodstream. If the measured percentage of chromosome 21 DNA is significantly increased from the background of 1.41% then this is indicative of a pregnancy affected by Down’s syndrome.
The key take home message from this section is that the IONA® test works because the increase in DNA from a fetus with trisomy 21 can be detected as a difference from the expected amount of chromosome 21 derived DNA in the blood sample.
Clearly any factor that alters the expected amount of a particular chromosome could have an impact on test performance. For example, if the mother carried a partial duplication of chromosome 21 then this would manifest itself as a positive signal for trisomy 21 quite independent of the status of the fetus.
Now as we go and look back at the exclusions, we can understand them in the context of how the test works. Cancer is known to generate significant chromosome imbalances within a tumour. If sufficient cancer derived cell free DNA is released into the bloodstream this can affect the measured ratios of all of the chromosomes, potentially making the test unreliable. In the case of a transplanted organ or a transfusion of white blood cells there is a small but not zero chance that the donor was affected with Down’s syndrome and if this were the case then it could lead to false positive results.
In the case of transplants and transfusions the actual chance of a trisomy affected donor is clearly very low but there is a second more subtle reason as to why a transplant could lead to an inaccurate result.
As mentioned above an important parameter in NIPT is the fetal fraction – the amount of fetal derived DNA in the blood stream. The IONA® test estimates fetal fraction and uses this figure to set the expectation of the size of the increase associate with a fetus affected by a trisomy. For example, if the fetal fraction was 10%, the increase of the chromosome ratio associated with trisomy 21 is 0.06% but if the fetal fraction were 20% this change would be 0.14%. It is important for the IONA® test performance that the fetal fraction is measured accurately, and this leads us to the second reason why transplants and/or white cell transfusions could confound the test result.
One of the methods the IONA® test uses to estimate fetal fraction is based on the level of male derived DNA in the fetus. In the case of a transplant, it is quite possible that we could have donors and recipients which are not matched for sex and in these cases the fetal fraction estimate could be confused by the presence of a background level of male DNA. This is prevented from happening by the exclusion of test subjects who have had an organ transplant.
In summary the IONA® test is a very accurate and reliable method of assessing the risk of a pregnancy being affected by a trisomy. As we have seen, the IONA® algorithms make several assumptions regarding background chromosome ratios in the pregnant woman and hopefully this article has explained why certain conditions are excluded from testing to ensure that samples that may have slightly different background chromosome ratios do not lead to inaccurate test results.
All numbers used in this article are approximations for illustrative purposes only.
