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Home / Science-tech / Tongues Tell: Linguistic performance can predict onset of Alzheimer’s

Tongues Tell: Linguistic performance can predict onset of Alzheimer’s

A recent study indicates that it may be possible to predict whether a person will get neurological diseases by his or her speech patterns

Gina Kolata   |   Published 15.02.21, 12:30 AM

Is it possible to predict who will develop Alzheimer’s disease simply by looking at writing patterns years before there are symptoms?

According to a new study by IBM researchers, the answer is yes.

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And, they and others say that Alzheimer’s is just the beginning. People with a wide variety of neurological illnesses have distinctive language patterns that, investigators suspect, may serve as early warning signs of their diseases.

For the Alzheimer’s study, the researchers looked at a group of 80 men and women in their 80s — half had Alzheimer’s and the others did not. But, seven-and-a-half-years earlier, all of them had been cognitively normal.

The men and women were participants in the Framingham Heart Study, a long-running US federal research effort that requires regular physical and cognitive tests. As part of it, they took a writing test before any of them had developed Alzheimer’s that asks subjects to describe a drawing of a boy standing on an unsteady stool and reaching for a cookie jar on a high shelf while a woman, her back to him, is oblivious to an overflowing sink.

The researchers examined the subjects’ word usage with an artificial intelligence programme that looked for subtle differences in language. It identified one group of subjects who were more repetitive in their word usage at that earlier time when all of them were cognitively normal. These subjects also made errors, such as spelling words wrong or inappropriately capitalising them, and they used telegraphic language, meaning language that has a simple grammatical structure and is missing subjects and words like “the”, “is” and “are”.

The members of that group turned out to be the people who developed Alzheimer’s disease.

The AI programme predicted, with 75 per cent accuracy, who would get Alzheimer’s disease, according to results published recently in The Lancet journal EClinicalMedicine.

“We had no prior assumption that word usage would show anything,” said Ajay Royyuru, vice-president of healthcare and life sciences research at IBM Thomas J. Watson Research Center in Yorktown Heights, New York, US, where the AI analysis was done.

Alzheimer’s researchers were intrigued, saying that when there are ways to slow or stop the illness — a goal that so far remains elusive — it will be important to have simple tests that can warn, early on, that without intervention a person will develop the progressive brain disease.

“What is going on here is very clever,” said Dr Jason Karlawish, an Alzheimer’s researcher at the University of Pennsylvania, US. “Given a large volume of spoken or written speech, can you tease out a signal?”

For years, researchers have analysed speech and voice changes in people who have symptoms of neurological diseases — Alzheimer’s, amyotrophic lateral sclerosis, Parkinson’s, frontotemporal dementia, bipolar disease and schizophrenia, among others.

But, said Dr Michael Weiner, who researches Alzheimer’s disease at the University of California, San Francisco, US, the IBM report breaks new ground.

“This is the first report I have seen that took people who are completely normal and predicted with some accuracy who would have problems years later,” he said.

The hope is to extend the Alzheimer’s work to find subtle changes in language used by people with no obvious symptoms but who will go on to develop other neurological diseases.

Each neurological disease produces unique changes in speech, which probably occur long before the time of diagnosis, said Dr Murray Grossman, professor of neurology at University of Pennsylvania and director of the university’s frontotemporal dementia centre.

He has been studying speech in patients with a behavioural form of frontotemporal dementia, a disorder caused by progressive loss of nerves in the brain’s frontal lobes. These patients exhibit apathy and declines in judgment, self-control and empathy that have proved difficult to objectively quantify. Speech is different, Dr Gross-man said, because changes can be measured.

Early in the course of that disease, there are changes in the pace of the patients’ speech, with pauses distributed seemingly at random. Word usage changes, too — patients use fewer abstract words. These alterations are directly linked to changes in the frontotemporal parts of the brain, Dr Grossman said. And they appear to be universal, not unique to English.

Dr Adam Boxer, director of the neurosciences clinical research unit at UC San Francisco, is also studying frontotemporal dementia. His tool is a smartphone app. His subjects are healthy people who have inherited a genetic predisposition to develop the disease. His method is to show subjects a picture and ask them to record a description of what they see.

“We want to measure very early changes, five to 10 years before they have symptoms,” he said. “The nice thing about smartphones is that you can do all kinds of things.”

Researchers can ask people to talk for a minute about something that happened that day, he said, or to repeat sounds like tatatatata.

Dr Boxer said he and others were focussing on speech because they wanted tests that were noninvasive and inexpensive.

NYTNS



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