Brain connections predict the likelihood of dementia

Last month, ZonMw shared an interesting interview about the research of Betty Tijms, psychologist, neuroinformatician, and associate professor at the VUmc Alzheimer's Center (Dementia Research Spotlight ZonMw). She developed an algorithm that can predict the progression of dementia based on brain connections in individuals. The research is supported by a grant from ZonMw.


ZonMw is a government agency in the Netherlands that supports scientific research to promote good health through knowledge. The themes revolve around innovation in health, care, well-being, healthy living, preventing illness, new treatments and medications, and delivering the right care in the right place. In short, many themes intertwined with broader societal issues (ZonMw).

Early detection of Alzheimer's

An aging population and an increase in the number of people with dementia pose broader societal challenges. Despite knowing more about dementia and Alzheimer's disease, there is still no cure. Therefore, more research is focusing on early detection of the disease as well as its prevention.

Betty Tijms' research, highlighted by ZonMw, contributes to the early detection and prediction of dementia. A crucial feature of the disease is the deterioration of brain connections, often occurring long before visible changes in behavior (such as memory problems and confusion) manifest. Preventing and possibly curing the disease necessitates detecting these early processes to intervene before dementia develops.

Predicting dementia

The research followed patients to map the decline of brain connections. Based on these measurements, Betty Tijms developed an algorithm that predicts how quickly the brain deteriorates in people with Alzheimer's disease. In 65% of cases, the algorithm could correctly predict who would develop dementia within 2 years! It was also found that people with poorer brain connections experienced a faster progression of the disease.

A follow-up study then examined whether the state of brain networks can be a clinical measure for the progression of the disease in individual patients (Disease progression in clinical practice). Information about the size of the hippocampus and the presence of the harmful Alzheimer's protein Tau was added to the algorithm. This increased the accuracy of the algorithm's prediction to 72%. Protein measurements (proteomics) in cerebrospinal fluid are now being investigated to see if there are other proteins besides Tau that are associated with the loss of brain connections and clinical decline in Alzheimer's disease (Tijms 2024).

The researchers highlight as the most significant result that this knowledge can directly benefit patients, their caregivers, and healthcare providers because they can now have a better understanding and more certainty about the progression of the disease. With this knowledge, decisions can then be made that focus on well-being and adequate care for people with dementia, ultimately resulting in personalized care and an improved quality of life.