How much information can we extract from a five–minute recording of someone talking? Enough to tell whether that individual may be genetically predisposed to some health complications, according to researchers at the University of Wisconsin–Madison’s Waisman Center and Wisconsin Institute for Discovery.

In a new study published in the journal Scientific Reports, the researchers used machine learning to analyze hundreds of voice recordings and accurately identify individuals with a genetic condition known as fragile X premutation, which increases the risk of developing neurodegenerative disorders, infertility or having a child with fragile X syndrome.

While fragile X syndrome – characterized by intellectual disability and behavioral, physical and learning challenges — is relatively rare, millions of people across the world have fragile X premutations. “But the premutations remain underdiagnosed, and people are often unaware of their increased health risks,” says Marsha Mailick, professor of social work and UW­Â–Madison vice chancellor for research and graduate education. Mailick is a co–author of the study.

Part of the challenge in diagnosis is that the genetic testing to identify fragile X premutations can be time–consuming and resource–intensive. “Our group of researchers wanted to develop a method to quickly and cost–effectively screen for this condition,” says Mailick.

That led them to machine learning — artificial intelligence computer programs that can be “trained” using existing data sets and then used to analyze new information.

“We can go from taking hours to analyze and annotate each recording to needing less than a second,” says Kris Saha, assistant professor of biomedical engineering at UW–Madison and the study’s senior author.

The researchers focused on voice recording analysis because Mailick and her colleagues have shown in prior studies that this can yield valuable information about the families of individuals with fragile X premutations.

For instance, in 2012, a study led by the UW’s Jan Greenberg, professor of social work and associate vice chancellor for research and graduate education, analyzed five–minute recordings of mothers talking about their children with fragile X syndrome. The study showed that parental warmth and a positive family atmosphere were associated with fewer behavioral problems in their children. Greenberg is a co–author of the new study.

Another co–author, Audra Sterling, an assistant professor of communication sciences and disorders at UW–Madison, used the same recordings to show a strong correlation between age and specific speech difficulties in middle–aged and older women with fragile X premutations. These findings indicated that voice recordings could be used to track the development of cognitive challenges faced by many older individuals with fragile X premutations.

But according to Mailick, coding the speech characteristics was time consuming and required clinical expertise, neither of which are needed with the method reported in the new study.