Using Digital Technology to Study Relationship of Depression and Dementia

Project Details


Background Studies have shown that depression may increase one's risk of developing Alzheimer's and other dementia. However, scientists remain unclear about the biology by which depression and dementia may be potentially linked. One reason for this lack of knowledge could be that people experience depression in different ways and with different symptoms. Some may have feelings of sadness, while others may feel apathy (defined as being indifferent or having lack of motivation). Studies show that individuals with certain types of depressive symptoms may be at a greater risk for developing dementia than others. In earlier research, Dr. Laili Soleimani and colleagues studied the role of depression in two large groups of older adults at risk for dementia. First, they collected smartphone conversations from their participants over a period of time. Then the researchers used a novel method of analysis called MYNDYOU, which is designed to identify subtle differences in speech quality that may help understand which of the depressive symptoms an individual might be experiencing. Research Plan Building on their preliminary work, Dr. Soleimani and colleagues will conduct a larger study of MYNDYOU using machine learning, an advanced computer science technique. The researchers will leverage the infrastructure at the Mount Sinai Alzheimer's Disease Research Center (Mount Sinai ADRC). From the Mount Sinai ADRC, over a period of six months, the researchers will collect smartphone conversations from 225 older adults with dementia, with mild cognitive impairment (MCI, a condition of subtle memory loss that may precede dementia) or with no cognitive impairment. The researchers will also leverage the ADRC datasets that includes cognitive tests, brain scans (Positron Emission Tomography) as well as biomarkers (such as cerebrospinal fluid samples- the biological fluid surrounding the brain and spinal cord) to study brain changes associated with Alzheimer's in the participants. Dr. Soleimani's team will then study whether the MYNDYOU technique may be better able to predict cognitive decline in comparison to the cognitive test results and scans. Further, the researchers will study whether predictions using MYNDYOU may be associated with brain changes such as levels of beta-amyloid and tau measured using the biomarkers; beta-amyloid and tau accumulate to form plaques and tangles, the two main hallmark brain changes observed in Alzheimer's. Impact The study results could help us further understand the potential impact of depression in the risk of developing dementia. If successful, the project could offer a novel method of detecting Alzheimer's at an early stage. Families facing Alzheimer's now and in future will benefit greatly from early detection, allowing for important care and planning. Furthermore, when we have new therapies, we will be in a better position to know who needs treatment at the earliest time point.
Effective start/end date1/01/21 → …


  • Alzheimer's Association


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.