INTERVIEW – LA NACION

Alzheimer’s disease is a growing concern in world public health. According to the Centers for Disease Control and Prevention (CDC) of the United States, it is estimated that about 55 million people suffer from dementia throughout the planet, a figure that could triple around 2050 if effective methods are not implemented for their prevention and early detection. In Argentina, more than 500,000 people live with some type of dementia, with Alzheimer’s as a more frequent cause. Faced with this panorama, the current great challenge is to diagnose the disease long before its symptoms seriously impact everyday life.

There the innovative technological and scientific proposal of Jason Hassestab, director of the Cognitive Technology Research Laboratory (CTRLAB) at the University of Washington In St. Louis, United States. He is the principal investigator of the Multicentric International Study Ambulatory Research in Cognition-Down Syndromewho investigates Alzheimer’s disease associated with Down’s syndrome, and It specializes in the development and application of technologies to optimize cognitive evaluations in Alzheimer’s disease and other neurodegenerative disorders.

Hassestab spoke with La Nacion during a visit to Argentina Invited by Fleni, in which he participated in the Neuroscience Next, which is a hybrid international conference with global reach, sponsored by the Alzheimer’s Association – one of the most influential organizations in the research in neurosciences worldwide – and carried out from February 24 to 27 in the city.

The expert proposes to use digital technologies, as cognitive evaluations carried out by smartphones, to detect subtle changes in memory and reasoning In initial stages of Alzheimer’s. As noted, traditional evaluation methods, which are usually carried out in a single clinical session, do not reflect the true fluctuation of mental performance in real life, thus limiting their effectiveness to capture the earliest signals of the disease.

Hassestab comments in this interview how repeated digital evaluations offer enormous advantages to detect Alzheimer’s early. It emphasizes that evaluating multiple times per day for a week allows to capture real fluctuations of memory and other cognitive functions, providing extremely precise data on how you learn or how you forget a person in different daily contexts. These digital methods, called «momentary ecological evaluation» (EMA)they are revolutionizing scientific research and clinical trials, offering more reliable results and close to reality than those obtained by traditional evaluations, he says.

However, he warns that there are still important challenges for the mass implementation of these methods in habitual clinical practice. The economic cost and the need for specialized technical support for older adults are some important obstacles that should be overcome so that these technologies are available in clinics and hospitals. Despite this, Hassestab anticipates a scenario where advanced, adaptive and accessible cognitive evaluations from any smartphone will detect Alzheimer’s long before it significantly impacts the quality of life.

– What exactly is a cognitive test and what are the main challenges to detect Alzheimer’s disease early?

–A cognitive test seeks to quantify our mental world: memory, attention, visual understanding, language or mathematical capacity. Generally, these tests begin easy and the difficulty is increasing until the person cannot complete them. The great challenge is that traditional tests are not designed to detect very subtle changes in the initial stage of Alzheimer’s. In addition, when being carried out in a single visit, they can give deceptive results, influenced by circumstantial factors such as stress or tiredness. That is why we need more creative and sensitive methods, such as repeated digital tests in everyday environments.

– What advantages do digital cognitive evaluations offer in their laboratory on traditional tests in office?

–The main advantage is to perform short evaluations on multiple occasions for a week. Our participants complete tests on their mobile phone four times per day, which allows us to measure averages, observe learning and oblivion curves, and record daily or momentary fluctuations. These data, impossible to obtain with traditional methods, considerably increase the precision of early diagnosis.

– How do you guarantee the precision and reliability of the tests performed by smartphones or web platforms?

– The repetition of short tests up to 28 times a week ensures a reliability superior to traditional methods. Although we are concerned that participants can be distracted or that someone else performs the test, in practice we observe very little this. We carry out controls, asking about the environment and possible interruptions. In studies with thousands of people, there is practically no consistent evidence of interference that affects precision.

–Your laboratory uses a methodology called Momentan Ecological Evaluation (EMA). What is and what are your advantages to investigate Alzheimer’s?

–Ama implies performing repeated evaluations in real time to reduce biases. Originally it was used to register moods or physical symptoms, but in our laboratory we adapt it to measure cognition. Its main advantage is to provide reliable and novel data, impossible to obtain with traditional evaluations. This deeply transforms the quality of the data into research on Alzheimer’s.

– What role does the Ambulatorly Research In Cognition (ARC) application in international studies such as Dian and how did the quality of data collected?

–The ARC application, a technological platform developed by the Cognitive Technology Research Laboratory, is central in our international Alzheimer’s studies, including the Dian Network (an international network that is specifically dedicated to the study of the dominant hereditary Alzheimer’s study, a rare and genetic form of the disease) and preventive clinical trials. It was designed from the beginning for international use and is already translated into ten languages. Soon we will publish results that demonstrate that ARC is significantly more sensitive than traditional methods to detect early cognitive changes, an exciting achievement that confirms its clinical utility.

– Do you think these technologies could be massively implemented in clinical practice to improve the early diagnosis of Alzheimer’s? What are the current barriers?

–This is the great current challenge. Although I firmly believe that these technologies will be fundamental in the future, we are not yet ready. The main barrier is economical: developing and maintaining these tools is expensive. In addition, older adults usually need additional technical support. Mass adoption will depend on overcoming these technical and financial obstacles.

– How can the future of Alzheimer’s early detection imagine? Is an accessible detection possible through intelligent devices and advanced algorithms possible?

–Imagino a future in which interactive and adaptive evaluations evaluate cognitive processes through advanced technologies, including speech analysis and personalized learning. It is currently missing more scientific theory that supports certain methods, but I see a promising future in which advanced technologies can detect alzheimer’s precision in very early stages, from any intelligent device.