Abstract

The Functional Brain Imaging Core will provide the scientific environment, imaging resources, and data analysis support to conduct three novel pilot investigators of late-life mood disorders using functional imaging. Each imaging study will examine a specific biological hypotheses related to late-life mood disorders using functional imaging method that share two or more of the following innovative attributes: a) measurement of the change in regional brain function during a pharmacological or sensory probe; b) examination of the remitted patient to allow focus on potential trait- related attributes; or c) examination of a specific receptor system putatively related to the manifestion of mood disorders in the elderly. Objectives of the three proposed pilot projects are; Study 1: Identify circadian timing system abnormalities in remitted late-life depressed patients using a bright light stimulus. Study 2: Determine the relationships between the regional brain serotonin-mediated responses to a serotonergic challenge, CSF 5-HIAA as a measure of overall serotonin innervation, and suicidality and hopelessness in late-life depressed patients. Study 3; Identify changes in regional serotonin reuptake )serotonin transporter) sites in elderly depressed patients.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Center Core Grants (P30)
Project #
2P30MH052247-06
Application #
6302644
Study Section
Project Start
1995-03-01
Project End
2005-02-28
Budget Start
Budget End
Support Year
6
Fiscal Year
2000
Total Cost
Indirect Cost

  Institution

Name
University of Pittsburgh
Department
Type
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213

  Publications

Smagula, Stephen F; Beach, Scott; Rosso, Andrea L et al. (2017) Brain Structural Markers and Caregiving Characteristics as Interacting Correlates of Caregiving Strain. Am J Geriatr Psychiatry 25:582-591
Smagula, Stephen F; Wallace, Meredith L; Anderson, Stewart J et al. (2016) Combining moderators to identify clinical profiles of patients who will, and will not, benefit from aripiprazole augmentation for treatment resistant late-life major depressive disorder. J Psychiatr Res 81:112-8
Patel, Meenal J; Andreescu, Carmen; Price, Julie C et al. (2015) Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction. Int J Geriatr Psychiatry 30:1056-67
Khalaf, Alexander; Edelman, Kathryn; Tudorascu, Dana et al. (2015) White Matter Hyperintensity Accumulation During Treatment of Late-Life Depression. Neuropsychopharmacology 40:3027-35
Joel, Ian; Begley, Amy E; Mulsant, Benoit H et al. (2014) Dynamic prediction of treatment response in late-life depression. Am J Geriatr Psychiatry 22:167-76
Diniz, Breno S; Reynolds 3rd, Charles F; Butters, Meryl A et al. (2014) The effect of gender, age, and symptom severity in late-life depression on the risk of all-cause mortality: the Bambuí Cohort Study of Aging. Depress Anxiety 31:787-95
Andreescu, Carmen; Teverovsky, Esther; Fu, Bo et al. (2014) Old worries and new anxieties: behavioral symptoms and mild cognitive impairment in a population study. Am J Geriatr Psychiatry 22:274-84
Chisholm, Denise; Toto, Pamela; Raina, Ketki et al. (2014) Evaluating capacity to live independently and safely in the community: Performance Assessment of Self-care Skills. Br J Occup Ther 77:59-63
Gallo, Joseph J; Morales, Knashawn H; Bogner, Hillary R et al. (2013) Long term effect of depression care management on mortality in older adults: follow-up of cluster randomized clinical trial in primary care. BMJ 346:f2570
Sherer, Eric A; Sale, Mark E; Pollock, Bruce G et al. (2012) Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building. J Pharmacokinet Pharmacodyn 39:393-414

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