Detecting and Repairing DNA Errors
Elaine Mardis, Ph.D., agrees that genetic engineering therapy for people is not arriving anytime soon. Dr. Mardis, the co-director at The Genome Institute of Washington University and a professor of genetics, believes that researchers will probably have the ability to detect and repair DNA errors at the preimplantation embryo stage in about ten years.
“We can genotype embryos right now that do or don’t carry mutations such as in cystic fibrosis. But mutation repair is still far off,” she says. “And trying to repair DNA mutations in a grown adult is even more problematic.”
She points out that we know that BRCA1 and BRCA2 are prognostic for women to develop breast and ovarian cancer.
“But there is a mystery here in that if the same mutated form of DNA is carried in every cell, why does cancer only appear in breast and ovarian tissues?” asks Dr. Mardis. “We still don’t fundamentally understand how to specifically target the appropriate tissues in adults with, for example, gene therapy or with another gene repair technique.”
Dr. Mardis strongly believes that next-gen sequencing is the major driver of clinical genomics.
“Baseline research in the basic science arena is establishing methodologies for up-front preparation of libraries for next-gen sequencing and for downstream analytical processes that are critical for coming to more precise genomic interpretation in the clinic,” she explains. “This constitutes 99% of the battle for clinical translation of genomic data.”
Dr. Mardis adds that supporting technologies such as computer science and computational pipelines are also necessary for the successful integration of clinical omics into standard medical practice.
Dr. Mardis notes that another key clinical genomics driver is the fact that many children who currently come to a medical genetics clinic with an uncertain diagnosis immediately undergo some type of sequencing, primarily exome sequencing to aid in the diagnosis. Establishing clinical utility, i.e., how fast you can get an answer about the child’s condition, is enhanced by exome sequencing rather than single gene-by-gene testing, according to Dr. Mardis.
“Exome sequencing is less expensive than multiple single gene tests and insurance companies recognize that,” said Dr. Mardis. “The burden of clinical utility falls on the clinical genomics lab. Payers want to know if they pay for a genomics test, will the patient have a path to a solution that is better than the current standard of care? They [the payers] ask questions like how much does this test cost in comparison to another test? If it costs more why is the new test better?”
Dr. Mardis stresses that big data analytics will address some of the cost equation. “Most of the cost is not in the DNA sequencing process but in analyzing the data,” she points out. In general, she finds no problem with data standardization as currently practiced. “Most large-scale sequencing teams use the bam file format to align reads to the genome. You can run bam files through any predictor program to come up with your own variant calls,” she says.
In storing variant calls, you might run into trouble because definitions about what you consider and call variants and actually put into a variant file can themselves vary, according to Dr. Mardis.
“We either need to warehouse genomic data as bam format files or throw all the data away and keep the biological samples in a biobank,” she says. “Data storage is becoming more expensive than data production. And regarding data production, competition will come in the future with new DNA sequencing platforms that will drive the costs down further.
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