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Digital Biomarkers Reveal Alzheimer’s Gender Differences

Artificial intelligence graphic
(Gerd Altmann, Pixabay)

16 June 2022. A study of people with and without Alzheimer’s disease found differences between women and men in their state of cognitive decline with data from mobile devices. Results of the study, conducted by the Women’s Brain Project, a not-for-profit organization based in Switzerland, and digital brain health diagnostics company Altoida Inc. in Washington, D.C. appear in the 6 June 2022 issue of EPMA Journal that publishes research on predictive and personalized medicine.

The researchers are seeking faster, less expensive, yet still reliable ways of diagnosing degenerative neurological disorders, such as Alzheimer’s disease and other forms of dementia, that also predict future declines in cognitive performance. In addition, the study team aims to identify differences in indicators of cognitive decline for women and men, since rates and symptoms of decline differ between sexes, which suggests a single set of overall indicators may not be helpful.

The Women’s Brain Project seeks to generate scientific evidence of gender differences in brain health, including mental health disorders and neurodegenerative diseases, with the aim of encouraging more precise diagnostics and treatments recognizing and addressing those differences. The project’s members are researchers who collaborate on studies investigating differences between the sexes in cognitive health.

For the study, the Women’s Brain Project teamed with Altoida Inc. that offers tools for assessing cognitive health as smartphone and tablet apps. The company’s technology employs exercises with immersive augmented reality that feature activities in daily life. Altoida says the games on its mobile apps take only about 10 minutes, and measure cognitive and functional abilities with scores on cognitive and motor skill indicators. The company says it uses artificial intelligence algorithms to correlate these indicators to clinical and real-world data on brain health. A founder of Women’s Brain Project, Antonella Santuccione Chadha, is also Altoida’s chief medical officer.

Function of gender and disease stage

The study analyzed data collected by Altoida in a clinical trial to evaluate the company’s technology in diagnosing Alzheimer’s disease in real-world settings, from 438 participants age 50 and older in Italy, Greece, and Spain, including their results of cognitive and biological brain health indicators. The clinical trial participants included individuals with mild cognitive impairment and Alzheimer’s disease, as well as healthy individuals. The team also recruited 130 participants in Japan, age 20 to 50, with no known cognitive disorders, who performed the Altoida mobile app exercises.

As part of the study, Altoida developed, trained, and tested an algorithm to detect the sex of individuals based on responses to the company’s mobile apps. Findings from the study, say the researchers, show the algorithm accurately identifies the gender of cognitively healthy participants 75 percent of the time. However, the algorithm’s ability to identify gender declines as indicators of cognitive decline increase.

Those findings, say the authors, suggest differences between men and women in cognitive performance may be a function of their gender, as well as the stage of the disease. And as a result, separate digital biomarker signatures for men and women may help identify more precise states of cognitive decline.

“Our research shows how digital biomarkers can detect sex-based differences,” says Chadha in a Women’s Brain Project statement, “which are often overlooked when using standardized cognitive neuropsychological assessment. These findings support the need for researchers and drug developers to account for sex-based characteristics in investigating prospective treatments for Alzheimer’s disease.”

Travis Bond, CEO of Altoida adds, “By integrating sex with risk stratification based on genetics and individual risk factors with the use of digital biomarker monitoring applications, this will enable the early detection and treatment of symptoms, when a patient has [mild cognitive impairment], before development into Alzheimer’s.”

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