A new study found that analyzing written language samples may help predict future Alzheimer’s disease in people who are cognitively normal. Researchers assessed the writing samples of 270 older adults to develop a set of linguistic markers and test their ability to predict the disease.
Language patterns such as writing short and simple phrases, repeating, and misspelling words, and skipping punctuation were associated with future onset of Alzheimer’s. The language pattern analysis was about 70% accurate in predicting who would go on to develop Alzheimer’s disease — several years before the diagnosis.
Study findings suggest that language patterns may be a detectable biomarker for the disease. Further exploration could inform advancements in non-invasive tests for the early detection of Alzheimer’s.
Learn more about the recent study on language analysis for Alzheimer’s prediction on NIA’s website.
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