New gene technique identifies hidden causes of brain malformation.
Howard Hughes Medical Institute (HHMI) scientists have developed a strategy for finding disease-causing mutations that lurk in only a small fraction of the body’s cells. Such mutations can cause significant problems, but cannot be detected with traditional methods of genetic testing, as well as newer, more costly genome sequencing technologies.
The scientists report in the New England Journal of Medicine, that they used the technique to find disease-causing mutations in patients with brain malformations whose genetic causes were unknown despite previous testing.
By sequencing hundreds of copies of the genes in a panel of candidate genes the team identified somatic mutations, gene mutations present in diploid but not haploid germ line cells, in more than a quarter of patients that could be successfully diagnosed genetically.
The team was surprised to discover so many somatic mutations in patients who had already undergone genetic testing, showing just how poorly other methods perform in detecting somatic mutations. They state that researchers are not going to find these things unless they go looking for them, unless they have a clinical test that is set up to detect them in a sensitive way.
Somatic mutations are not inherited from parents, but instead, arise sometime after fertilization. They are most often seen in some forms of cancer, in which genetic differences between tumor cells and the rest of the body drive tumour growth and metastasis. But they’ve been implicated in other diseases, as well.
Somatic mutations have been discovered to cause milder forms of a wide range of diseases, especially neuropsychiatric ones, the team cite Rett syndrome and tuberous sclerosis as examples here, two disorders that cause seizures and intellectual disability. The team had found that some of their patients with double cortex syndrome, a brain malformation that can cause some of the same kinds of neurological problems, have somatic mutations. And in a new study published in Cell Reports, the team analyzed the genomes of individual cells in healthy and diseased brains and found that large segments of DNA had been duplicated or deleted in most cells. A lot of variability was observed with some of these mutations having occurred at a stage where they were present in more than one cell.
The team summise that these somatic mutations are probably more common as causes of intellectual disability, and maybe even some psychiatric conditions, than people have generally realized. A genetic diagnosis is important for counselling patients and their parents about risks to future children, and can, in some cases, influence treatment decisions. But many patients who had come to the lab with neurodevelopmental problems were still without answers. The team had successfully identified causative mutations in many families. But there remained a subset where, even after 10 or more years of searching, the researchers had been unable to identify the causative genes. This made the group question whether there might be certain kinds of mutations not well discovered by present methods.
The team questioned whether it had missed somatic mutations in those patients by using traditional methods of genetic testing? It seemed possible. Those techniques are not designed to find mutations that occur only in a small fraction of cells. Even if researchers are looking at the right gene, the mutation can still be missed.
Most diagnostic gene testing is done by sequencing specific genes using a traditional DNA sequencing technique known as the Sanger method. When this strategy fails, the search for mutations is sometimes broadened to all of the protein-coding regions of the genome, the exome, or further, to the entire genome. Both approaches have limitations
Whole-exome sequencing tends to sample the genome about 30 or 50 times over. But if a mutation is only in five or 10 percent of the cells, then it’s only going to be in a very small fraction of the data, and it’s hard to separate from the noise. The same is true of Sanger sequencing, it has not been optimized to detect a mutation that’s present in a small fraction of the reads.
To find the kinds of mutations they were looking for the team knew they would have to deepen their search. They devised a strategy in which they would use next-generation sequencing technology to sequence a panel of genes known or suspected to be associated with brain malformations. The team shot to sequence them a thousand times over, ergo, even if a mutation is only present in five percent of the cells, it will be obvious that it’s a mutation, because the researchers saw that mutation 50 times.
The team set up a test to screen blood samples from 158 patients whose brain malformations remained unexplained. For each patient, a panel of 14 or 54 genes (depending on the patient’s condition) was sequenced hundreds or thousands of times. The design of the panel and sequencing took about 2-3 months to carry out. They then fine-tuned existing bioinformatics algorithms to search for somatic mutations in the sequences. Though the initial sequencing was fast, follow-up validation of potential somatic mutations took additional months because it remains labour-intensive.
In this way, the team uncovered mutations likely to cause disease, either because their role was already known or because they disrupted protein function, in 27 of the 158 patients in their study. Eight of these were somatic mutations, present in just five to 35 percent of the sequenced DNA. The team confirmed these sequencing findings with laboratory experiments in which the patients’ DNA was replicated in bacterial cells and analyzed by Sanger sequencing.
Thus the patients have a genetic diagnosis, ending the diagnostic odyssey for these eight individuals.
Five of the eight somatic mutations that they identified would never have been found with traditional sequencing methods, the scientists say. All of the mutations that were present at less than about 15 percent of the reads were completely undetectable by Sanger sequencing. One of them had been missed by whole-exome sequencing, as well.
The gold standard of clinical diagnosis is Sanger sequencing. But researchers will be missing a big chunk of patients with mutations in these genes, because they’re using a test that’s not designed to look for them.
Now that they have demonstrated their method’s sensitivity in detecting somatic mutations, the team say medical geneticists should consider using the approach before turning to more costly whole-exome sequencing. Neither offers a single solution for all patients, but their complementary strengths give geneticists a more complete set of tools.