After suffering two pulmonary embolisms in 2003, Cupertino, Calif. resident John West began to wonder if he had passed any blood clotting risks to his children. A direct-to-consumer genetics test revealed that his teenage daughter, Anne, had inherited the same risks. So the enterprising high school student calculated the frequency of genetic recombination in her family, first with snippets of genetic information from the genomics company data and then with the family’s full genome sequences from biotechnology company Illumina.
While Anne successfully identified the origin and implications of some disease variants in the family’s genomes, the family, as my colleague notes in a release, "wanted to know more than one busy teenager armed with Excel spreadsheets could manage." That's when John West approached Stanford cardiologist Euan Ashley, MD, and colleagues for help.
With the DNA sequences of both parents and children, the team of researchers was able to better check for sequencing errors and more accurately predict how individual genetic variants affect each family member's risk for disease. More from our release:
With a family of genomes, the researchers could determine exactly which parent had donated a given copy of a gene to their offspring, allowing them to better calculate the severity of health risks when many variants were found together.
The related set of genome sequences also allowed the scientists to locate, with the most precision reported to date, where along the DNA strand the parents’ chromosomes had mixed together before being passed to the next generation — a diversity-generating process known as genetic recombination
Specifically for the Wests, the team identified multiple variants in genes related to clotting. They also identified the exact physician-determined dosage of anticoagulants that John West was already taking, and predicted the dosage that Anne West may one day need.
The researchers' work is described in a study published today in PLoS Genetics. Their findings are the second reported analysis of a four-person family of genomes, but the first to include a whole-genome interpretation of a family’s medical risks.