Conventional treatment of late-life depression (LLD) often requires long trials of several antidepressants before an effective regimen can be found for an individual. This can take many months and is associated with persistent depressive symptoms, an increased risk of suicide, patients dropping out of care, and worsening of medical co-morbidities. This long response time in LLD is one of the most challenging clinical features of LLD. Thus, in the elderly it is particularly important to shorten this window, and to identify as early as possible what medication regimen will be the most effective for an individual. With the recent development of Pharmacologic Functional MRI (phMRI), it has become possible to track cerebral blood flow patterns (as proxies of regional brain activity) in response to a medication. The primary aims of the proposed LLD phMRI study are 1). To characterize the trajectories of the phMRI brain responses over the course of initiation and titration of an antidepressant, and 2). To use these trajectories to identify the earliest time-point when functional brain changes predict treatment response. As an exploratory aim, the phMRI trajectories will be related to other prominent markers of treatment response in LLD, cognition and structural brain changes. The proposed study is a continuation of R01MH076079, now in its 5th year, which has successfully achieved its aims of characterizing the functional neuroanatomy of LLD, using a model of altered connectivity. The hypotheses for this continuation follow from an observation in the current study that the 12-week change in functional MRI (fMRI) activity was more predictive of treatment response, than was baseline fMRI activity. The proposed study follows-up on this observation by measuring fMRI activity at 5 different time-points over the course of treatment to identify the earliest point at which brain activity in LLD can be used to predict treatment response. The fMRI paradigm includes affective reactivity and affective regulation tasks designed to highlight the ventral limbic affective processing circuits (including the rostral cingulate, anterior insula, and amygdala), which are implicated in LLD treatment. Novel image analysis methods, including resting-state calibration of task-related fMRI, will be used to optimize scan-rescan reliability. One hundred LLD subjects will participate. The proposed study leverages the resources of a recently funded large NIH clinical treatment trial of Venlafaxine XR to treat geriatric depression (IRLGREY, PI: Reynolds, R01MH083648). The imaging component of this study is integrated with the ongoing IRLGREY study, and thus initial subject recruitment, characterization, and treatment will be covered by IRLGREY. This study is designed to impact both ends of the translational research path, from characterizing the pharmacologic effects in the brain to the potential clinical use of MRI for personalized treatment of LLD. As far as we are aware, this will be the first study to systematically characterize the trajectory of fMRI limbic activity to an SRI. The study focuses on the elderly because the importance of predicting treatment response in that group has added urgency due to their prolonged response to treatment and high suicide risk.

Public Health Relevance

This is a functional MRI study of antidepressant medication treatment of late-life depression. The study aims to identify functional brain changes in the first days of treatment that can be used to predict whether an individual will ultimately respond to an antidepressant.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH076079-08
Application #
8494692
Study Section
Adult Psychopathology and Disorders of Aging Study Section (APDA)
Program Officer
Evans, Jovier D
Project Start
2006-04-01
Project End
2016-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
8
Fiscal Year
2013
Total Cost
$474,064
Indirect Cost
$154,160
Name
University of Pittsburgh
Department
Psychiatry
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Smagula, Stephen F; Lotrich, Francis E; Aizenstein, Howard J et al. (2017) Immunological biomarkers associated with brain structure and executive function in late-life depression: exploratory pilot study. Int J Geriatr Psychiatry 32:692-699
Karim, H T; Tudorascu, D L; Butters, M A et al. (2017) In the grip of worry: cerebral blood flow changes during worry induction and reappraisal in late-life generalized anxiety disorder. Transl Psychiatry 7:e1204
Andreescu, Carmen; Tudorascu, Dana; Sheu, Lei K et al. (2017) Brain structural changes in late-life generalized anxiety disorder. Psychiatry Res 268:15-21
Karim, Helmet T; Perlman, Susan B (2017) Neurodevelopmental maturation as a function of irritable temperament: Insights From a Naturalistic Emotional Video Viewing Paradigm. Hum Brain Mapp 38:5307-5321
Edelman, Kathryn; Tudorascu, Dana; Agudelo, Christian et al. (2017) Amyloid-Beta Deposition is Associated with Increased Medial Temporal Lobe Activation during Memory Encoding in the Cognitively Normal Elderly. Am J Geriatr Psychiatry 25:551-560
Karim, H T; Andreescu, C; Tudorascu, D et al. (2017) Intrinsic functional connectivity in late-life depression: trajectories over the course of pharmacotherapy in remitters and non-remitters. Mol Psychiatry 22:450-457
Khalaf, Alexander; Karim, Helmet; Berkout, Olga V et al. (2016) Altered Functional Magnetic Resonance Imaging Markers of Affective Processing During Treatment of Late-Life Depression. Am J Geriatr Psychiatry 24:791-801
Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J (2016) Studying depression using imaging and machine learning methods. Neuroimage Clin 10:115-23
Smagula, Stephen F; Aizenstein, Howard J (2016) Brain structural connectivity in late-life major depressive disorder. Biol Psychiatry Cogn Neurosci Neuroimaging 1:271-277
Karim, Helmet T; Andreescu, Carmen; MacCloud, Rebecca L et al. (2016) The effects of white matter disease on the accuracy of automated segmentation. Psychiatry Res 253:7-14

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