Mechanistic underpinnings of cognitive and actiography-based biomarkers in individuals with depression
Approved Research ID: 77362
Approval date: September 23rd 2021
There are currently many challenges in mental healthcare, including the high failure rate of current psychiatric medications and a lack of development of new antidepressant medications. Therefore, it is important to identify individuals that are likely to benefit from existing treatment and, for the individuals that are not predicted to respond well to existing antidepressants, identify new mechanisms for future development.
One way to predict whether an individual with depression is likely to respond well to an existing treatment is by integrating additional clinical and biological data. For example, data from cognitive task performance is a useful predictor of whether someone with depression is likely to respond well to existing medication or not. That is, individuals with depression who also had poorer cognitive task performance had poorer treatment outcomes than those patients with depression with better cognitive task performance. This result indicates that cognitive task performance is associated with clinical outcome for existing medications and could assist in personalizing psychiatric treatment. It also highlights the need for developing antidepressants with different mechanisms of action that may better target processes relevant to patients with poorer cognition.
It is currently difficult to determine which mechanisms should be explored when developing new antidepressants. Analyzing genetic, cognitive, and activity data from UK Biobank can help. For example, previous studies of the UK Biobank have found that depression, cognitive performance, and activity are genetically influenced. Therefore, first, we will analyze differences in the genetics of individuals as a function of cognitive performance. These differences will generate hypotheses to help guide the development of new antidepressants. Finally, we will also see if the predicted gene expression levels are correlated with sleep or activity features, which help us understand the broader picture that comes with poorer cognitive performance (as this too is poorly understood). The project duration will be up to 3 years.
Overall, this project seeks to improve mental healthcare by contributing to personalized psychiatry and new directions for treating depression.