The research proposal for this K23 grant application uses imaging with positron emission tomography (PET) to quantify brain serotonin 1A receptors in bipolar depression to determine whether the imaging signal is associated with a clinical response to the selective serotonin receptor inhibitor (SSRI) antidepressant fluoxetine when added to a mood stabilizer. An association with clinical outcome may be a first step to identifying a biomarker that can predict clinical response. This goal is important because not all bipolar patients respond to SSRI's and there are risks associated with the treatment, making personalized medicine options for the disorder a needed tool. Bipolar disorder is common, is one of the top 10 sources of disability, and is associated with an increased risk for suicide. Moreover, treatment is trial and error, a problematic clinical process, and there are only three medications FDA approved for the depressed phase. A recent paper showed that PET signal of brain serotonin 1A receptor was associated with clinical remission after three months of unstructured treatment. A different paper showed that the PET signal was associated with clinical response to SSRI's in major depressive disorder. Another aim of the study is to determine whether the PET signal is associated with the symptoms of anxiety or aggression in bipolar depression. If there is a correlation, this may be the first step to redefining the diagnoss along biological, serotonin signaling. The project utilizes a new radiotracer [11C] CUMI-101 that is a significant advance over other radiotracers. It also utilizes a new statistical approach to correlate clinical outcome with imaging data. This is a training grant, and the research project will provide an opportunity for its principal investigator, Martin Lan, MD, PhD, to develop into an independent neuroimaging researcher. He has previous research background in basic science techniques, and this grant will allow him to gain patient oriented research skills to use his clinial training as a psychiatrist in his research. He will receive mentorship from experts in the field during the project, including his primary mentor, Dr. J John Mann, co-mentor, Dr. R. Todd Ogden, collaborator, Dr. Patrick McGrath and consultant, Dr. Jeffrey Meyer. This mentorship, and a curriculum of classes to increase his knowledge, will provide the necessary skills in image processing, PET radiotracer kinetic modeling, general statistics, and basic and translational neuroscience.
This grant aims to determine whether brain imaging using positron emission tomography in patients with bipolar depression to measure a molecule involved with serotonin signaling is associated with clinical response to antidepressant treatment, or with patient symptoms of anxiety and agitation. These results may be a first step to identify a biomarker to predict who will respond to antidepressants or to redefine the diagnosis on biological terms, thereby reducing the public health burden of this common and disabling condition. It also aims to train its principle investigator to become an independent neuroimaging scientist, a role that is needed in the field.
| Rubin-Falcone, Harry; Zanderigo, Francesca; Thapa-Chhetry, Binod et al. (2018) Pattern recognition of magnetic resonance imaging-based gray matter volume measurements classifies bipolar disorder and major depressive disorder. J Affect Disord 227:498-505 |
| Lan, Martin J; Ogden, R Todd; Kumar, Dileep et al. (2017) Utility of Molecular and Structural Brain Imaging to Predict Progression from Mild Cognitive Impairment to Dementia. J Alzheimers Dis 60:939-947 |
| Lan, Martin J; Rubin-Falcone, Harry; Motiwala, Fatima et al. (2017) White matter tract integrity is associated with antidepressant response to lurasidone in bipolar depression. Bipolar Disord 19:444-449 |
| Lan, Martin J; Chhetry, Binod Thapa; Liston, Conor et al. (2016) Transcranial Magnetic Stimulation of Left Dorsolateral Prefrontal Cortex Induces Brain Morphological Changes in Regions Associated with a Treatment Resistant Major Depressive Episode: An Exploratory Analysis. Brain Stimul 9:577-83 |
