David C. Steffens, M.D., M.H.S.
Professor and Chair
Department of Psychiatry
My research focuses on long-term mood and cognitive outcomes of late-life depression, including trajectories of recovery from depression and risks related to cognitive decline and subsequent development of Alzheimer’s disease and other dementias. I have examined a variety of biological, psychological and social variables in my studies. From a biological standpoint, we have found two structural neuroimaging markers of cognitive decline in depression: smaller hippocampal volumes and larger volumes of white matter hyperintense lesions. More recently, I have also used functional MRI to study both resting state functional connectivity and task-based activation patterns. Genetic markers related to late-life depression outcomes we have studied include APOE, COMT and 5HTT-LPR.
My current NIH-supported study, Neurobiology of Late-life Depression (NBOLD), seeks to examine the role of neuroticism in mood and cognitive outcomes of depression in older adults, as well as functional imaging correlates of neuroticism. Preliminary work demonstrated that depressed older adults scoring high in neuroticism, particularly those with vulnerability to stress, have limited response to antidepressants and are at higher risk of cognitive decline. Other psychological factors involve measures of optimism and resilience. Key social variables relevant to depression outcomes include objective and subjective social support, recent psychosocial stressors and adverse childhood experiences.
My research attempts to examine the complexity of geriatric depression and its outcomes through comprehensive longitudinal clinical and neuropsychological assessment, neuroimaging, genetics, and a variety of psychological, functional and social measures. The resulting data sets are large and lend themselves to a variety of interesting secondary questions that can be examined to advance understanding of this common and clinically significant disorder. I have had the pleasure of working with many students, trainees and faculty members to develop focused projects using these data.