Matt Might: Genetic testing and ‘crowdscreening’ enabling precision medicine, faster research

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Matt Might: Genetic testing and ‘crowdscreening’ enabling precision medicine, faster research

At the intersection of Big Data, online communities, genomics and precision medicine, you’ll find Matt Might, a professor of computer science, who has taken a leading role advocating for patients with undiagnosed or rare diseases. Advances in genetic testing are revealing crucial details about these patients. One of them is his own son, Bertrand, who endured years of seizures and treatments until the cause was identified.

Might found his calling, and joined Seven Bridges for its weekly Journal Club to discuss the ways patients are helping each other to identify and treat rare genetic diseases. Families are becoming activists and scientists, armed with personal genomics data, analytics and a community formed using social media.

“As soon as you get a diagnosis, you can start doing science. And I argue that science itself becomes medicine in the absence of any other course of action,” he said. “Science becomes the actionable component when you get a diagnosis like this and if we’re going to make precision medicine work we have to scale up science in a big way.”

Whole exome sequencing determined that Bertrand had N-glycanase (NGLY1) deficiency, medically described among Congenital Disorders of Glycosylation. His was the first recorded case, but Might calculated that there would be other undiagnosed patents around the world.

Two years after defining the condition genetically, 16 cases have been identified worldwide – though symptoms can differ even within families.

“We went from accurate genotyping to really accurate phenotyping,” he said, describing how he used precise descriptions to find other families searching online for similar patient conditions such as “lack of tears when crying.” The discovery was one most doctors hadn’t considered: decreased glycosolation in cells – where previously they looked for hyper-glycosolation or unrelated disorders.

Matt Might and family: users of genetic testing
Matt and Cristina Might, with two of their children, Bertrand and Victoria.

Defining the details of his son’s condition took persistence and his knowledge of online research and resources. His provocative blog post titled “Hunting Down My Son’s Killer” went viral worldwide thanks largely to his understanding of search engines and social media. His tweets, blog and media exposure used key words and search terms that he knew other families would use to identify symptoms — connecting them to the Mights.

The power of online search and popularity of social media now yields groups of patients instead of ‘n-of-1’ single-instance medical mysteries.

“In the past year, we had 12 patients and well over half the known patients were phenotyped and got some statistically significant information,” he said. “So there is now a large enough population of patients to do experiments and gain insight into the diagnosis.”

Might got early help from lab scientist Hudson Freeze, a glycobiologist at Sanford-Burnham Medical Research Institute. Then, as more related cases were found, the National Institutes of Health set up a protocol to study affected patients.

‘Crowd-screening’ and ‘blognosis’ are two ways Might describes patient families checking PubMed and Internet search for symptoms, possible triggers and treatment options. Moms trading messages and photos often yields more specific details than a doctor with limited time and expertise, he said.

Might and his wife, Cristina, also are building political support in their home state of Utah for rare disease research and patient rights. They also participated at ASHG15 in Baltimore, working with NIH on undiagnosed conditions.

The hashtag #patientsaspartners helps spread the word along with their website,

“If you keep asking the Internet, eventually people will step forward and do something,” he said. “We’re moving into an era where the people that effectively discover this disorder are Moms by exchanging pictures and (comparing) phenotypes and looking to see they had common ground.”