麻豆果冻传媒

Stanford researchers are devising ways to have computers help perform some of the intensive genetic analysis now performed manually when scientists study a patient's genome to diagnose a disease.

For Release: Aug. 15, 2016

Shayla Haddock's genome was analyzed in 2012 as her doctors searched for the cause of a condition that had resulted in club feet, deafness and shorter-than-normal limbs. Although the initial analysis didn't provide a diagnosis, a re-analysis in 2015 turned up an answer: Shayla had聽a rare genetic disease called Wiedemann-Steiner syndrome. The re-analysis made use of new computational tools developed at Stanford.

When Shayla Haddock was born in 1997, her parents immediately realized something was wrong. The sixth of seven children, Shayla had unusual facial features. She had club feet and shorter-than-normal limbs. She was smaller than most newborns. Hearing tests showed she was deaf.

As her parents, Cheryl and Levko Siloti, searched for answers about her condition, they worried: Had some preventable event during Cheryl鈥檚 pregnancy caused Shayla鈥檚 symptoms? Could identifying her diagnosis improve her treatment options? If Shayla鈥檚 siblings wanted to become parents someday, would their children be at risk for the same illness?

鈥淚t was kind of an emotional roller coaster,鈥� Cheryl Siloti said. Over the years, doctors suggested many diagnoses for Shayla, but medical tests repeatedly disproved their theories. 鈥淲e would get these possibilities and then hear 鈥楴ope, that鈥檚 not the answer.鈥欌��

The Stockton, California, family鈥檚 quest for answers illustrates the challenges of diagnosing rare genetic diseases, and illustrates how and why scientists at the are devising new approaches to help.

As much as Shayla鈥檚 parents longed for a diagnosis, they almost didn鈥檛 get one. On Aug. 10, 2012 鈥� only two weeks after Shayla鈥檚 doctors at Lucile Packard Children鈥檚 Hospital Stanford concluded that they could not match her genetic patterns and symptoms to a disease 鈥� a scientific report about a newly discovered link between a genetic defect and a rare disease was published that would have allowed them to diagnose her. But at the time, genetic-testing results were not routinely re-analyzed to take into account new knowledge. The family and doctors remained unaware that the answer was out there.

Genetic re-analysis

Last year, as part of a scientific study, Shayla鈥檚 parents agreed to have her genome re-analyzed. This time, Stanford computer scientists used new computational tools they had developed to compare Shayla鈥檚 gene sequences to the scientific literature. They found the 2012 scientific report and predicted that Shayla had a rare genetic disease called Wiedemann-Steiner syndrome, which her doctors confirmed.

鈥淲ith each passing month, more of the world鈥檚 genetic diversity is represented in scientific databases, and each time more information is there, it鈥檚 easier to interpret the next thing you see,鈥� said Jon Bernstein, MD, Shayla鈥檚 clinical geneticist at Packard Children鈥檚 and an author of the new report, which was published online July 21 in Genetics in Medicine. Ten percent of the patients in the study 鈥� four individuals, including Shayla, out of 40 who did not receive diagnoses after their first genetic analysis 鈥� were diagnosed with various rare diseases based on recent discoveries, even though the initial analyses had been conducted an average of only 20 months earlier.

These 鈥渘ear misses鈥� highlight a big challenge in the realm of precision health: Although the speed, cost and effort involved in obtaining individuals鈥� genetic sequences has dropped dramatically in recent years, it still requires about 20 to 40 hours of work by trained experts to match a patient鈥檚 rare mutations to information in the scientific literature that might reveal a diagnosis. Among patients suspected of having a rare genetic disease, 75 percent aren鈥檛 diagnosed the first time they have their DNA analyzed. And yet the knowledge base is growing fast. Each year, researchers discover the cause of about 250 genetic diseases and also find 9,200 links between specific gene variants and known diseases.

Too many to diagnose by hand

鈥淥ur study demonstrates that reanalysis of patients鈥� gene-testing results is useful because there鈥檚 a steady rate of discovery,鈥� said Bernstein, who is also an associate professor of pediatrics at the School of Medicine.

鈥淏ut there is no way we鈥檒l have enough manpower to continue to do all the analysis manually, as clinicians and scientists have done in the past,鈥� said , PhD, senior author of the study and associate professor of developmental biology, of computer science and of pediatrics.

Bejerano led the computer scientists who devised the automated approach used in the new research. Several million Americans may have some form of rare genetic disease, he noted 鈥� too many to diagnose by hand. 鈥淩ather than continuing to invest dozens of hours in each patient鈥檚 analysis, our team thought it made more sense to spend that time building computer science tools that can do much of the work for us,鈥� he said.

In the new study, the scientists tested whether automated comparisons between undiagnosed patients鈥� genomes and existing gene databases could accelerate diagnosis. The approach worked.

鈥淭he genome is ultimately a programming language,鈥� Bejerano said. 鈥淲e really would like to use machine learning and other approaches to build computer systems that leave as little as possible work for the human expert. A computer is going to be weaker than a human at doing this, but we think we can take the process 80 to 90 percent of the way by computer and provide a huge time savings for the human in the loop.鈥�

Comparing genes of patients, parents

Another key finding from the new research, according to Bernstein and Bejerano, is that comparing patients鈥� gene sequences to those of their parents greatly speeds the diagnostic process. Such comparisons help turn up new disease-causing mutations that occurred in the patients but are not present in their parents. 鈥淭hese things stand out more easily if you have the parents鈥� data in front you,鈥� Bernstein said.

In Shayla鈥檚 case, her diagnosis brought her family the answers they鈥檇 long been seeking. She doesn鈥檛 share her disease-causing mutation with her parents; instead, it occurred spontaneously in her. It wasn鈥檛 preventable, nor is there any expectation it would affect her siblings鈥� children. 鈥淚t really relieves a lot of worry to know that,鈥� Siloti said.

The diagnosis also has helped the Silotis find other families whose children have the same diagnosis. They share stories on a Facebook group and feel they鈥檝e found a new sense of support and community. 鈥淲e鈥檝e always believed that knowledge is power,鈥� Siloti said. 鈥淚t is wonderful to have some answers, especially after such a long search.鈥�

The co-lead authors of the new study are research scientists Aaron Wegner, PhD, and Harendra Guturu, PhD. The research was funded by , the Stanford Discovery Fund, the and the (grant U01MH105949).

Why it鈥檚 hard to diagnose a rare genetic disease, by the numbers:

• Size of the human genome: 3 billion bases, each a single letter in the 鈥渨ords鈥� that make up our genes and the genomic regions that control them.
• Number of Americans estimated to have some form of rare genetic disease: 25 million
• Annual number of single-gene diseases whose cause is newly identified: 250
• Annual number of genetic changes newly linked to existing diseases: 9,200
• Time required to analyze one person鈥檚 genetic information when a rare genetic disease is suspected: 20 to 40 hours
• Proportion of patients suspected of having a rare, single-gene disease who get a diagnosis the first time their genetic sequence is analyzed: 25 percent
• Typical frequency of re-analysis to help undiagnosed patients be matched to new discoveries: It has been rare, but is expected to become more common thanks to new, automated techniques for gene analysis.

麻豆果冻传媒 integrates research, medical education and health care at its three institutions - , , and Lucile Packard Children's Hospital Stanford. For more information, please visit the Office of Communication & Public Affairs site at .

Authors

Erin Digitale
(650) 724-9175
digitale@stanford.edu

Becky Bach
(530) 415-0507
retrout@stanford.edu