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It’s only natural
06-05-2015
EDIT CONNECT
SHARING OPTIONS:
BETHESDA, Md.—A new study by National Institutes of Health (NIH) researchers has turned
traditional genomics research on its head. Instead of trying to find a mutation in the genomic sequence of a person with a genetic disease, they sequenced
the genomes of healthy participants, then analyzed the data to find “putative,” or presumed, mutations that would almost certainly lead to a
genetically induced condition.
Out of almost 1,000 volunteers whose genomes were examined, about 100 had genomic
variants predicting that they would have a rare disease. Almost half of them indeed had the disease when researchers went back and carefully evaluated them,
said Leslie G. Biesecker, M.D., chief of the Medical Genomics and Metabolic Genetics Branch (MGMGB) at the National Human Genome Research Institute (NHGRI) and corresponding author of the study published June 4, 2015, in the American Journal of Human Genetics.
“We were
surprised that this many individuals had positive findings in a group of individuals that is basically healthy,” said Jennifer Johnston, Ph.D., lead
author and staff scientist with the Clinical Genetics Section of the MGMGB. The research is part of ClinSeq, a large-scale, NIH research study that explores the fundamental medical, molecular and bioinformatic challenges facing individualized
genome sequencing in a clinical research setting.
Once they identified participants with genomic mutations,
researchers called them back to the clinic to give them a customized work-up. They called this method of looking at the person after looking at the genomic
data “iterative phenotyping.” Researchers sifted through more than 100,000 variants per participant—nearly all harmless—and studied
only potentially harmful mutations that were found in about 100 of the 951 participants. Among those patients, 79 were followed up, and they confirmed that
34 had the specific condition linked to their genetic mutation. These findings indicate that 3 percent or more of the U.S. population may have a genetic
condition compared to previous estimates of less than 0.02 percent.
“We achieved about a 50 percent accuracy
of predicting disease in people not knowing anything about their health status beforehand,” Dr. Biesecker said. In other words, the
researchers changed the odds of these patients having one of these diseases from something like 1 in 50,000 to 1 in 2.
Given this accuracy, Dr. Biesecker is upbeat about the future of genomic medicine. “These results show that you can dramatically improve your
predictions based on genome sequence information.”
NHGRI Director Eric Green, M.D., Ph.D, agreed, adding: “Today, we tend to deliver medical care based on the expected response of the average patient, and yet we know that this is far
from perfect. Eventually, we want to deliver medical care based on individual genomic differences that enable more precise ways to prevent and treat disease.
These findings move us closer to that reality.”
The team also found that having a mutation did not always
lead to a condition that looked like a textbook case. Indeed, 20 of the 79 participants with harmful mutations and an associated physical change
didn’t know they might have a genetic condition. Sometimes these physical changes were so mild that the participant had neither sought a diagnosis nor
reported them to the research team during enrollment in the study. While it may seem unnecessary to find these mild cases, one key aspect of genomics is that
the same mutation can affect family members with different levels of severity.
“A couple of the participants
with LDLR (low density lipoprotein receptor) mutations thought they just had garden variety high cholesterol, when in fact they had familial
hypercholesterolemia,” said Dr. Biesecker. This led to more aggressive cholesterol screening in other family members, including children as young as
eight, because early treatment can delay heart attacks and prolong life.
Researchers found other evidence that
genetic conditions are underestimated. That is because, until now, knowledge about genetic conditions has mostly been based on family health history or ill
people who walk into a clinic. This has led researchers to study only those who are more severely affected and not those who are mildly affected or not
affected at all, which eventually leads to an overestimation of the condition’s severity and an underestimation of its prevalence. The problem
(ascertainment bias) has long been known and acknowledged by genetics researchers. They have only recently been able to address it as DNA sequencing costs
have plummeted.
At this rate, just above 9 million people, about the population of New Jersey, may be living with
some sort of genetic condition. The authors caution that not all healthy people need to have their genomes sequenced, emphasizing that this is a proof-of-
concept study that may lead to a better understanding of how these mutations affect health. “We want to add DNA sequencing to the physician’s
toolbox,” Dr. Biesecker said. “It is fine to take care of patients once they are sick and that’s appropriate, but wouldn’t it be
better to find some patients before they are sick and take care of them?”
Other co-authors include: Katie
Lewis, Sc.M., David Ng, M.D., Larry Singh, Ph.D., Jamila Wynter, Steven Gonsalves, Suzanne Hart, Ph.D., Robert Sokolic, M.D., Benjamin Solomon, M.D., NHGRI;
Carmen Brewer, Ph.D., National Institute on Deafness and Other Communication Disorders; Brian Brooks, M.D., Ph.D., Wadih Zein, M.D., National Eye Institute;
Isaac Brownell, M.D., Ph.D., Heidi Kong, M.D., National Cancer Institute; Kristina Rother, M.D., National Institute of Diabetes and Digestive and Kidney
Diseases; David Cooper, Ph.D., Peter Stenson, Cardiff University, U.K.; James Mullikin, Ph.D., NIH Intramural Sequencing Center; and Fabio Candotti, M.D.,
Universite de Lausanne, Switzerland.
The research was supported by the intramural research programs at NHGRI, the
National Eye Institute (NEI), the National Institute on Deafness and Other Communication Disorders (NIDCD), the National Cancer Institute, and the National
Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).
Code: E06051501 Back |
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