At the Oxford Biomedical Research Center (BRC), scientists used Ingenuity Variant Analysis from QIAGEN Bioinformatics in a family study to pinpoint unknown mutations causing abnormal brain development. Now, a family with a history of conceiving babies with severe brain malformations has a new path toward having a healthy child. And the program that helped them could make a difference for many other families in similar situations as well.
Alistair Pagnamenta, a postdoc who has focused on neurological disorders since joining the center in 2010, was the lead author on a recent paper in Human Molecular Genetics reporting results for this family. They had had three pregnancies terminated due to the detection of abnormalities including polymicrogyria, a brain anomaly where poor organization of neurons results in an increased number of small folds in the cortex, instead of a smaller number of large folds to maximize the brain’s surface area. The condition can lead to intellectual disability, muscle weakness or paralysis, seizures, and more.
One challenge Pagnamenta and his colleagues faced early on was limited access to DNA samples from the three fetuses. With those precious samples as well as DNA from the parents, the team performed exome sequencing on all five individuals. Using Ingenuity Variant Analysis, they generated a list of genes already known to be associated with polymicrogyria and quickly determined that in this family, none of them was faulty. They would have to search for a novel gene.
But whole exome data from five people is a lot of DNA to comb through, so the team focused the search for a causal variant on genomic regions where all three fetuses had inherited the same chromosome segments from each parent. Targeting these identical-by-descent regions allowed the scientists to narrow their search to just 8.6 percent of the genome. “Then we searched within those regions and looked at all the variants present — how many of them were rare, how many were predicted deleterious,” Pagnamenta says. Within that subset of variants, they scanned for homozygous and compound heterozygous mutations.
The inheritance pattern for the variant of interest was unknown going into the project, Pagnamenta notes. “We thought it was most likely to be a recessive condition because there were multiple affected fetuses and the parents were unaffected,” he says. “But we couldn’t be absolutely sure. It could also have been germline mosaicism — a de novo mutation that was present in all three fetuses but not in DNA from the parents’ blood.”
Testing both modes of inheritance was another way that Ingenuity Variant Analysis proved to be a handy tool. “Having this software was quite useful because you can change the order that all the filtering is performed, and you can very quickly switch from the recessive mechanism to this de novo parental mosaicism model,” Pagnamenta says.
The team’s analysis turned up one very strong candidate that matched the expected autosomal recessive inheritance mode — compound heterozygous mutations in PI4KA on chromosome 22, one causing a premature stop and the other a missense substitution at a conserved location. The variants affect “an enzyme that’s part of a well-known signaling pathway,” Pagnamenta says. “Mutations in other components of this pathway were known to cause related brain malformations.”
To learn more about this study and BRC’s exome sequencing efforts, check out our full case study of Alistair Pagnamenta’s work.