EDITORIAL
Neuroimaging Studies of Depression, Dementia, and Mobility in Older Adults Lisa T. Eyler, Ph.D., Howard Aizenstein, M.D., Ph.D.
S
tructural and functional neuroimaging techniques are increasingly used to answer questions of relevance to the geriatric psychiatrist and geriatrician. The current issue of The American Journal of Geriatric Psychiatry contains six articles illustrating how a better understanding of brain size, shape, response, and presence of amyloid may aid in diagnosis and prognosis in addition to giving further clues in the search for causes of late-life mental and neurological disorders. A challenge in treating older adults with major depressive disorder is the limited guidance for initial treatment choice. Standard of care for late-life depression (LLD) is to start with a first-line selective serotonin reuptake inhibitor and wait for a clinical response, which can take 4 to 6 weeks, even longer in older adults.1 Unfortunately, many older adults fail initial treatment, and do not respond until after multiple trials. Identifying the most effective treatment for an individual before treatment can significantly improve outcomes. A central goal of much of clinical neuroimaging research is to identify treatment-predictive imaging markers. These markers promise to deepen our understanding of depression treatment and response, as well as add to our clinical toolbox. Two papers in the current issue of The American Journal of Geriatric Psychiatry significantly expand the literature on treatment-predictive imaging markers for LLD. The paper by Marano et al.2 examines whether there are pre-treatment neuroanatomic regions in gray matter that distinguish those who will respond well to citalopram. Data were included from
34 older adults (17 with LLD: age 66.9 6.4 years, and 17 comparison subjects: age 66.0 7.9 years). Participants were scanned (T1-weighted MPRAGE) at baseline then LLD participants underwent 12 weeks of open-label treatment with citalopram. Treatment response was considered separately for mood (measured as change in Hamilton Depression Rating Scale score), memory (California Verbal Learning Test), and verbal (letter) fluency. A whole brain (voxel-wise) approach to see if regionally specific gray matter differences (i.e., selective regional atrophy) were associated with mood or cognitive response was also carried out. They found that both mood and cognitive improvement was generally associated with less atrophy (i.e., greater regional gray matter volume) throughout the brain. The Gallagher Thompson et al. report3 in the current issue also addresses treatment response in LLD. This paper uses functional neuroimaging to predict response to cognitive behavioral therapy (CBT). Forty-four older adults (age: 68.86 7.21 years) were included. Individuals underwent functional MRI while performing an executive control task (the Wisconsin Card Sorting Task [WCST]). Cognitive function was also assessed outside the scanner with the WCST. Participants then underwent 12 weeks of CBT. Sixty-seven percent responded (based on structured interview criteria) to treatment. The functional signal, but not the cognitive performance, was predictive of CBT response. The observation that the functional imaging signal is more predictive of clinical response than cognitive performance highlights the potential of functional imaging as a biomarker.
Received October 27, 2014; accepted October 28, 2014. From the University of California, San Diego, La Jolla, CA. Send correspondence and reprint requests to Lisa T. Eyler, Ph.D., Department of Psychiatry, University of California, San Diego, Mail Code 9151B, 9500 Gilman Dr., La Jolla, CA 92093-9151. e-mail: [email protected] Ó 2015 American Association for Geriatric Psychiatry http://dx.doi.org/10.1016/j.jagp.2014.10.008
Am J Geriatr Psychiatry 23:1, January 2015
1
Editorial One of the most significant neuroimaging advances in the last 10 years has been the emergence of amyloid PET imaging. With amyloid imaging it is possible to assess, in vivo, one of the most prominent neuropathological features of Alzheimer disease (AD): amyloid plaques. Previously, these could only be assessed post mortem. The development of amyloid imaging, as well as other imaging and cerebrospinal fluid biomarkers, has led to the emergence of a new diagnostic entity, pre-clinical AD,4 which is used to describe individuals who show the brain changes associated with AD, but do not have the clinical syndrome. These individuals are at particularly high risk of developing AD. The paper by Donaghy et al.5 reviews how amyloid imaging has been used in studies of Lewy body disorders. These disorders are on a continuum from Parkinson disease (PD), to Parkinson dementia (PDD) and dementia with Lewy bodies (DLB). The literature reviewed is consistent with a pattern across these disorders showing greatest cortical amyloid in DLB, followed by PDD, and essentially no amyloid deposition in PD without dementia. Another important clinical challenge addressed using neuroimaging methods in the current issue of The American Journal of Geriatric Psychiatry is differential diagnosis between DLB and AD. Watson et al.6 investigated differences in cortical thickness between those diagnosed with probable AD versus DLB versus those without dementia, and found that thinning in the entorhinal cortex and parahippocampal gyri was uniquely pronounced in AD compared with DLB, when group differences were mapped at points across the whole cortex. Although there was less thinning overall in DLB compared with AD, region of interest analyses also showed some regions where thinning was greater in DLB than AD—namely, in the transverse temporal and right precentral gyri. These initial findings point to the possible usefulness of cortical thickness measures for clinically distinguishing AD from DLB, but the authors point out that further work will be needed to make these methods practical for use in diagnostic evaluations. Advances in analytic techniques for examining the structure of subcortical brain regions now allow for millimeter resolution investigations of shape and size based on MRI images. Although these techniques
2
have been applied before to young adult samples of people with schizophrenia, Prestia et al.7 are the first to use these methods to compare hippocampal and amygdalar size and shape between elderly schizophrenia patients and matched comparison participants. Widespread tissue reduction was seen in both hemispheres of the hippocampus and amygdala in the elderly patients with schizophrenia, with greater than 30% tissue reduction in the basolatero-ventromedial amygdala. Patients with more negative symptoms had greater tissue reductions in both structures. Greater spatial specificity regarding alterations in hippocampus and amygdala could help advance our understanding of the aging process in schizophrenia, in particular if these techniques could be applied to longitudinal MRI scans in future studies. In addition to its role in diagnosis and prognosis for mental and neurological disorders of late life, neuroimaging may also serve to inform the geriatrician about neural systems underlying disturbances of physical function, such as gait and balance, in individuals who may be at risk for physical instability due to presence of white matter hyperintensities (WMH). In this issue, Macfarlane et al.8 examine a subset of data from a large prospective study of individuals with WMH seen on MRI at baseline, which had previously shown that greater WMH predicted poorer physical performance. In the current analysis, the role of basal ganglia size and shape in deficits of gait and balance was tested. The results indicated that lower caudate volume and inward deformation of the left caudate in regions of known inputs/ outputs to dorsolateral prefrontal, premotor, and motor regions were associated with poorer physical performance at baseline. It will be of additional interest to understand if these relationships are replicable and how they may add to or interact with the severity of WMH in prediction of risk for falls. In conclusion, the six neuroimaging papers in this issue of The American Journal of Geriatric Psychiatry give a sampling of new and emerging approaches for studying geriatric mental health disorders. Continued research in this area will undoubtedly further our understanding of the neural mechanisms underlying mental illnesses in older adults, and promises to enhance prevention and treatment strategies in this population.
Am J Geriatr Psychiatry 23:1, January 2015
Eyler and Aizenstein References 1. Andreescu C, Reynolds CF 3rd: Late-life depression: evidence-based treatment and promising new directions for research and clinical practice. Psychiatr Clin North Am 2011; 34:335e355; viieiii 2. Marano CM, Workman CI, Lyman CH, et al: Structural imaging in late-life depression: association with mood and cognitive responses to antidepressant treatment. Am J Geriatric Psychiatry 2015; 23:4e12 3. Thompson DG, Kesler SR, Sudheimer K, et al: fMRI activation during executive function predicts response to cognitive behavioral therapy in older, depressed adults. Am J Geriatric Psychiatry 2015; 23:13e22 4. Sperling RA, Aisen PS, Beckett LA, et al: Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on
Am J Geriatr Psychiatry 23:1, January 2015
5. 6.
7.
8.
diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7:280e292 Donaghy P, Thomas AJ, O’Brien JT: Amyloid PET imaging in Lewy body disorders. Am J Geriatric Psychiatry 2015; 23:23e37 Watson R, Colloby SJ, Blamire AM, et al: Assessment of regional gray matter loss in dementia with Lewy bodies: a surface-based MRI analysis. Am J Geriatric Psychiatry 2015; 23:38e46 Prestia A, Cavedo E, Boccardi M, et al: Hippocampal and amygdalar local structural differences in elderly patients with schizophrenia. Am J Geriatric Psychiatry 2015; 23:47e58 Macfarlane MD, Looi JCL, Walterfang M, et al: Shape abnormalities of the caduate nucleus correlate with poorer gait and balance: results from a subset of the LADIS study. Am J Geriatric Psychiatry 2015; 23:59e71
3
Neuroimaging Studies of Depression, Dementia, and Mobility in Older Adults Lisa T. Eyler, Ph.D., Howard Aizenstein, M.D., Ph.D.
S
tructural and functional neuroimaging techniques are increasingly used to answer questions of relevance to the geriatric psychiatrist and geriatrician. The current issue of The American Journal of Geriatric Psychiatry contains six articles illustrating how a better understanding of brain size, shape, response, and presence of amyloid may aid in diagnosis and prognosis in addition to giving further clues in the search for causes of late-life mental and neurological disorders. A challenge in treating older adults with major depressive disorder is the limited guidance for initial treatment choice. Standard of care for late-life depression (LLD) is to start with a first-line selective serotonin reuptake inhibitor and wait for a clinical response, which can take 4 to 6 weeks, even longer in older adults.1 Unfortunately, many older adults fail initial treatment, and do not respond until after multiple trials. Identifying the most effective treatment for an individual before treatment can significantly improve outcomes. A central goal of much of clinical neuroimaging research is to identify treatment-predictive imaging markers. These markers promise to deepen our understanding of depression treatment and response, as well as add to our clinical toolbox. Two papers in the current issue of The American Journal of Geriatric Psychiatry significantly expand the literature on treatment-predictive imaging markers for LLD. The paper by Marano et al.2 examines whether there are pre-treatment neuroanatomic regions in gray matter that distinguish those who will respond well to citalopram. Data were included from
34 older adults (17 with LLD: age 66.9 6.4 years, and 17 comparison subjects: age 66.0 7.9 years). Participants were scanned (T1-weighted MPRAGE) at baseline then LLD participants underwent 12 weeks of open-label treatment with citalopram. Treatment response was considered separately for mood (measured as change in Hamilton Depression Rating Scale score), memory (California Verbal Learning Test), and verbal (letter) fluency. A whole brain (voxel-wise) approach to see if regionally specific gray matter differences (i.e., selective regional atrophy) were associated with mood or cognitive response was also carried out. They found that both mood and cognitive improvement was generally associated with less atrophy (i.e., greater regional gray matter volume) throughout the brain. The Gallagher Thompson et al. report3 in the current issue also addresses treatment response in LLD. This paper uses functional neuroimaging to predict response to cognitive behavioral therapy (CBT). Forty-four older adults (age: 68.86 7.21 years) were included. Individuals underwent functional MRI while performing an executive control task (the Wisconsin Card Sorting Task [WCST]). Cognitive function was also assessed outside the scanner with the WCST. Participants then underwent 12 weeks of CBT. Sixty-seven percent responded (based on structured interview criteria) to treatment. The functional signal, but not the cognitive performance, was predictive of CBT response. The observation that the functional imaging signal is more predictive of clinical response than cognitive performance highlights the potential of functional imaging as a biomarker.
Received October 27, 2014; accepted October 28, 2014. From the University of California, San Diego, La Jolla, CA. Send correspondence and reprint requests to Lisa T. Eyler, Ph.D., Department of Psychiatry, University of California, San Diego, Mail Code 9151B, 9500 Gilman Dr., La Jolla, CA 92093-9151. e-mail: [email protected] Ó 2015 American Association for Geriatric Psychiatry http://dx.doi.org/10.1016/j.jagp.2014.10.008
Am J Geriatr Psychiatry 23:1, January 2015
1
Editorial One of the most significant neuroimaging advances in the last 10 years has been the emergence of amyloid PET imaging. With amyloid imaging it is possible to assess, in vivo, one of the most prominent neuropathological features of Alzheimer disease (AD): amyloid plaques. Previously, these could only be assessed post mortem. The development of amyloid imaging, as well as other imaging and cerebrospinal fluid biomarkers, has led to the emergence of a new diagnostic entity, pre-clinical AD,4 which is used to describe individuals who show the brain changes associated with AD, but do not have the clinical syndrome. These individuals are at particularly high risk of developing AD. The paper by Donaghy et al.5 reviews how amyloid imaging has been used in studies of Lewy body disorders. These disorders are on a continuum from Parkinson disease (PD), to Parkinson dementia (PDD) and dementia with Lewy bodies (DLB). The literature reviewed is consistent with a pattern across these disorders showing greatest cortical amyloid in DLB, followed by PDD, and essentially no amyloid deposition in PD without dementia. Another important clinical challenge addressed using neuroimaging methods in the current issue of The American Journal of Geriatric Psychiatry is differential diagnosis between DLB and AD. Watson et al.6 investigated differences in cortical thickness between those diagnosed with probable AD versus DLB versus those without dementia, and found that thinning in the entorhinal cortex and parahippocampal gyri was uniquely pronounced in AD compared with DLB, when group differences were mapped at points across the whole cortex. Although there was less thinning overall in DLB compared with AD, region of interest analyses also showed some regions where thinning was greater in DLB than AD—namely, in the transverse temporal and right precentral gyri. These initial findings point to the possible usefulness of cortical thickness measures for clinically distinguishing AD from DLB, but the authors point out that further work will be needed to make these methods practical for use in diagnostic evaluations. Advances in analytic techniques for examining the structure of subcortical brain regions now allow for millimeter resolution investigations of shape and size based on MRI images. Although these techniques
2
have been applied before to young adult samples of people with schizophrenia, Prestia et al.7 are the first to use these methods to compare hippocampal and amygdalar size and shape between elderly schizophrenia patients and matched comparison participants. Widespread tissue reduction was seen in both hemispheres of the hippocampus and amygdala in the elderly patients with schizophrenia, with greater than 30% tissue reduction in the basolatero-ventromedial amygdala. Patients with more negative symptoms had greater tissue reductions in both structures. Greater spatial specificity regarding alterations in hippocampus and amygdala could help advance our understanding of the aging process in schizophrenia, in particular if these techniques could be applied to longitudinal MRI scans in future studies. In addition to its role in diagnosis and prognosis for mental and neurological disorders of late life, neuroimaging may also serve to inform the geriatrician about neural systems underlying disturbances of physical function, such as gait and balance, in individuals who may be at risk for physical instability due to presence of white matter hyperintensities (WMH). In this issue, Macfarlane et al.8 examine a subset of data from a large prospective study of individuals with WMH seen on MRI at baseline, which had previously shown that greater WMH predicted poorer physical performance. In the current analysis, the role of basal ganglia size and shape in deficits of gait and balance was tested. The results indicated that lower caudate volume and inward deformation of the left caudate in regions of known inputs/ outputs to dorsolateral prefrontal, premotor, and motor regions were associated with poorer physical performance at baseline. It will be of additional interest to understand if these relationships are replicable and how they may add to or interact with the severity of WMH in prediction of risk for falls. In conclusion, the six neuroimaging papers in this issue of The American Journal of Geriatric Psychiatry give a sampling of new and emerging approaches for studying geriatric mental health disorders. Continued research in this area will undoubtedly further our understanding of the neural mechanisms underlying mental illnesses in older adults, and promises to enhance prevention and treatment strategies in this population.
Am J Geriatr Psychiatry 23:1, January 2015
Eyler and Aizenstein References 1. Andreescu C, Reynolds CF 3rd: Late-life depression: evidence-based treatment and promising new directions for research and clinical practice. Psychiatr Clin North Am 2011; 34:335e355; viieiii 2. Marano CM, Workman CI, Lyman CH, et al: Structural imaging in late-life depression: association with mood and cognitive responses to antidepressant treatment. Am J Geriatric Psychiatry 2015; 23:4e12 3. Thompson DG, Kesler SR, Sudheimer K, et al: fMRI activation during executive function predicts response to cognitive behavioral therapy in older, depressed adults. Am J Geriatric Psychiatry 2015; 23:13e22 4. Sperling RA, Aisen PS, Beckett LA, et al: Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on
Am J Geriatr Psychiatry 23:1, January 2015
5. 6.
7.
8.
diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7:280e292 Donaghy P, Thomas AJ, O’Brien JT: Amyloid PET imaging in Lewy body disorders. Am J Geriatric Psychiatry 2015; 23:23e37 Watson R, Colloby SJ, Blamire AM, et al: Assessment of regional gray matter loss in dementia with Lewy bodies: a surface-based MRI analysis. Am J Geriatric Psychiatry 2015; 23:38e46 Prestia A, Cavedo E, Boccardi M, et al: Hippocampal and amygdalar local structural differences in elderly patients with schizophrenia. Am J Geriatric Psychiatry 2015; 23:47e58 Macfarlane MD, Looi JCL, Walterfang M, et al: Shape abnormalities of the caduate nucleus correlate with poorer gait and balance: results from a subset of the LADIS study. Am J Geriatric Psychiatry 2015; 23:59e71
3
