In this competing renewal (Year 11) of our R01 using fMRI to study late-life depression (LLD) pharmacotherapy (R01MH076079), the primary aim is to characterize functional connectivity changes associated with initial medication exposure (12-hour challenge). Our preliminary data suggests that these initial fMRI changes reflect monoaminergic engagement, regardless of monoaminergic class (serotonergic or noradrenergic), and predict later treatment response. In the proposed study we test a neural systems level model that response in LLD is mediated by acute pharmacologically-induced changes in cognitive and affective large scale network. Depression in older adults is frequently disabling and is often resistant to first-line treatments, requiring more prolonged treatment trials than in younger adults, mainly due to its heterogeneous pathophysiology (e.g. vascular and degenerative brain changes). Currently, there is little neurobiological data to guide changing or augmenting antidepressant medications. Thus, there has been a heightened focus on tailoring treatment to optimize outcome as described in the 2015 NIMH draft strategic plan (strategy 3.2). While antidepressant clinical response may take up to 8 weeks, recent studies suggest that physiologic changes, as measured with pharmacologic fMRI (phMRI) are seen within 24 hours of starting a new monoaminergic antidepressant1. For this proposal, we focus on three major Cognitive and Affective Networks (CAN): the Default Mode Network (DMN), the Salience Network (SN) and the Executive Control Network (ECN). The proposed model suggests that monoaminergic engagement leads to core CAN changes, changes that subsequently are related to overall clinical response as well as response in specific symptom clusters such as negative bias, somatizations/ anxiety and cognitive control. The same networks that are functionally connected while individuals are at rest, are also selectively engaged during tasks. Our prior work shows that pharmacotherapy ? regardless of type of antidepressant used - engages these specific networks at rest and during standard cognitive and affective tasks. Given the role of cerebrovascular disease in LLD treatment response, we will also explore the moderating role of vascular burden on the proposed association between CAN engagement and treatment response. We will recruit 100 older adults with LLD who will be randomized to receive treatment with either a very specific serotonin reuptake inhibitor (escitalopram) or a norepinephrine reuptake inhibitor (levomilnacipram). A pair of fMRI scans one day apart will be used to measure FC associated with medication titration. We propose to use a very early (12 hours after initiation of treatment) biomarker of treatment response, which, when validated, would decrease substantially the waiting time between medication changes. Additionally, our study will further our understanding of the acute neural system changes associated with monoaminergic antidepressants; this knowledge of mechanism is essential for both guiding LLD treatment research, and serving as an engagement target in LLD treatment research.

Public Health Relevance

This is a neuroimaging study that tests a mechanistic model describing the treatment-related dynamic changes of the core cognitive and affective networks at rest and during standard behavioral tasks. The results will further our understanding about the neural systems changes associated with pharmacotherapy in late-life depression.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZMH1)
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Rowland, Laura Marie
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University of Pittsburgh
Schools of Medicine
United States
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Wei, Wenjing; Karim, Helmet T; Lin, Chemin et al. (2018) Trajectories in Cerebral Blood Flow Following Antidepressant Treatment in Late-Life Depression: Support for the Vascular Depression Hypothesis. J Clin Psychiatry 79:
Karim, Helmet T; Wang, Maxwell; Andreescu, Carmen et al. (2018) Acute trajectories of neural activation predict remission to pharmacotherapy in late-life depression. Neuroimage Clin 19:831-839
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
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; 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
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
Andreescu, Carmen; Tudorascu, Dana; Sheu, Lei K et al. (2017) Brain structural changes in late-life generalized anxiety disorder. Psychiatry Res Neuroimaging 268:15-21
Smagula, Stephen F; Karim, Helmet T; Lenze, Eric J et al. (2017) Gray matter regions statistically mediating the cross-sectional association of eotaxin and set-shifting among older adults with major depressive disorder. Int J Geriatr Psychiatry 32:1226-1232
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
Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J (2016) Studying depression using imaging and machine learning methods. Neuroimage Clin 10:115-23

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