More than 6 million Americans are living with Alzheimer’s disease, costing the nation $321 billion in 2022, according to the Alzheimer’s Association. A variety of studies and pilot programs are underway to improve the diagnosing of or to lessen the effects of the disease.
For instance, a Journal of Alzheimer’s Disease study indicates that a willingness to give away money may be an early sign of Alzheimer’s. Sixty-seven older adult participants completed neuropsychological assessments and altruistic choice paradigms in which they made decisions about allocating money between themselves and an anonymous person.
The goal of the study was to understand why some older adults might be more susceptible than others to scams, fraud or financial exploitation.
The researchers found that financial altruism was associated with worse performance on cognitive assessments known to be sensitive to Alzheimer’s disease. They said that the results of the study point to a potential link between financial exploitation risk and Alzheimer’s disease in older age.
The findings could improve screening for Alzheimer’s disease and help people protect their loved ones from financial exploitation, according to the investigators. They also could help researchers distinguish between healthy giving behavior and an action that could signify underlying problems.
A blood test for Alzheimer’s?
At the University of South Florida recently received $3.2 million from the National Institute on Aging to investigate whether a simple blood test can detect Alzheimer’s. The new funding follows a $44.4 million, five-year grant that the National Institutes of Health awarded to the university last year to research whether brain games can reduce the risk of dementia in older adults.
The Preventing Alzheimer’s with Cognitive Training, or PACT, study, is a prevention trial launched in 2021 to test the effectiveness of computer-based training. The university is recruiting 7,600 older adults.
At the end of the PACT trial, scientists will examine the blood samples from willing participants and determine which specific blood-based biomarkers predict Alzheimer’s, the severity of disease and / or the responsiveness to treatment.
Improving medication adherence
Another NIH grant is funding a study of a medication reminder app to help older adults with mild cognitive impairment improve their medication adherence. A team of researchers at the University of Arizona Health Sciences and the University of Illinois will use a $2.5 million grant to study the effectiveness of digital technology on medication adherence among older adults with hypertension and at risk of cognitive decline.
Prior research found that as many as 50% of people with mild cognitive impairment do not take their medications as prescribed.
“We want to preserve quality of life and living well as long as possible, co-principal investigator Kathleen Insel, Ph.D., RN, interim dean and professor at the University of Arizona College of Nursing, said in a release. “We know that uncontrolled and undertreated hypertension has a deleterious effect on people’s organs, including the brain, even in the absence of stroke. If we can protect people’s ability to think and remember, they have the option tf staying independent.”
The goal of the study is to adapt and evaluate the digital health intervention Medical Education, Decision Support, Reminding and Monitoring System, or MEDSReM, to improve hypertension medication adherence and support self-management of hypertension medication for people with mild cognitive impairment.
Researchers are soliciting feedback from people who have mild cognitive impairment, and their family caregivers. They plan to conduct multiple rounds of usability testing to optimize the app.
Using AI to diagnose dementia
Another study from Nature Communications suggests that artificial intelligence could help diagnose dementia with clinician-level accuracy.
Researchers used machine learning to create computer models that collected large datasets collected during a typical work-up of a patient with suspected dementia. This work-up included neuropsychological and functional testing, a medical history, physical exams, the collection of demographic information and magnetic resonance imaging scans of people from the United States and Australia.
The study compared the results to diagnoses from 24 neurologists and neuroradiologists using the same information. Researchers said that the model performed better at differentiating the type of dementia among patients in whom dementia had been diagnosed.
Researchers hope to conduct an observational study in memory care clinics to confirm the model’s ability to assess dementia status at the same level as the expert clinician involved in dementia care.
If confirmed, the investigators said, the approach could expand the scope of machine learning for Alzheimer’s detection and management, ultimately creating an assistive screening tool for healthcare practitioners.
