Multimodal MRI markers support a model of small vessel ischemia for depressive symptoms in very old adults

Highlights

• This study examined brain magnetic resonance imaging (MRI) features associated with late-life depressive symptoms in a community sample.

• MRI variables examined were: white matter hyperintensity burden, fractional anisotropy and gray matter volume.

• Each whole-brain variable showed loss of integrity associated with higher depression score on the CES-D.

• Findings support a cerebrovascular pattern for depressive symptoms in older adults.

Abstract

In older adults, depressive symptoms are associated with lower quality of life, high morbidity and mortality. This study aims to identify brain magnetic resonance imaging (MRI) features associated with late-life depressive symptoms in the population. Older community-dwelling adults (n=314) from the Health ABC study underwent brain MRI. Logistic regression was used to characterize the relationships between depressive symptoms (Center for Epidemiologic Studies of Depression scale, CES-D) and the following whole-brain variables: white matter hyperintensity (WMH) burden, fractional anisotropy (FA), and gray matter volume (GMV). Analyses examining possible regional differences between the CES-D groups controlled for Modified Mini-Mental State Examination score and diabetes status. The relative importance of localization of the markers was examined by comparing the distribution of significant peaks across the brain. Each whole-brain variable showed loss of integrity associated with high CES-D. For GMV, the odds ratio (OR)=0.84 (95% confidence interval (CI) 0.74, 0.96); for FA, OR=0.714 (95% CI 0.57, 0.88); for WMH, OR=1.89 (95%CI 1.33, 2.69). Voxel-wise analyses and patterns of peak significance showed non-specific patterns for white matter measures. Loss of GMV was most significant in the bilateral insula and anterior cingulate cortex. This study supports a cerebrovascular pattern for depressive symptoms in older adults. The localization of gray matter changes to the insula, a watershed area and a hub of affective circuits, suggests an etiological pathway from ischemia to increased depressive burden.

Introduction

Depressive symptoms in the elderly, which are common and associated with increased morbidity, have been identified as one of the leading causes of decreased quality of life in older individuals (Blazer, 2003). Brain-imaging correlates of these depressive symptoms would be helpful in understanding the biological mechanisms of depressive symptoms later in life, including major depression (often referred to in older adults as late-life depression, LLD). Magnetic resonance imaging (MRI) markers of brain integrity, including measures of gray matter volume, white matter lesion load, and myelin integrity, have all been associated with LLD (Bell-McGinty et al., 2002, Ballmaier and Toga, 2004, Wu et al., 2006, Andreescu et al., 2008, Sheline and Price, 2008, Butters and Aizenstein, 2009, Shimony et al., 2009). However, uncertainty remains about the primary pattern(s) of changes, and their causal implications, if any, for LLD. Is LLD due to damage from cerebrovascular insults, as posited by the vascular depression hypothesis (Alexopoulos and Meyers, 1997)? Does the pattern represent ‘toxic stress’ (Sheline and Wang, 1996) from cumulative lifetime depression burden? Or is depression part of the Alzheimer׳s disease prodrome (Steffens and Plassman, 1997)? Studies support each of these models, and a single pattern has not emerged. Likely the failure to find definitive answers reflects the fact that LLD is itself heterogeneous and contains multiple patterns.

However, LLD is not necessarily the best model for studying depressive symptoms in the elderly. Several studies suggest that meeting full criteria for a major depressive episode is less common in older individuals than it is mid-life. Rather, it is the subsyndromal depressive symptom burden that appears to be more characteristic in the elderly (Lyness et al., 1999). Subsyndromal depression can be readily studied with epidemiological sampling methods. It may be that subsyndromal (or minor) depression in older adults represents a distinct disorder, related to major depressive disorder (MDD), but also similar to other geriatric syndromes (Lavretsky and Kumar, 2002). The current study aims to identify whether there is a pattern of structural and microstructural changes associated with subsyndromal depressive symptoms that may point to a predominant pathway, with potential prevention and treatment targets.

The current study of 314 participants from the Health, Aging and Body Composition (Health ABC) Study uses multiple MRI sequences to quantify brain abnormalities at the macro-structural and micro-structural level including T1-weighted imaging, T2-weighted fluid-attenuated inversion recovery (FLAIR) imaging and diffusion tensor imaging (DTI). An aim of the study, which is based on a large epidemiologic sample, is to characterize the brain-imaging variables that are independently associated with depressive has long been recognized that in the depressive symptoms in the elderly are often associated with cognitive deficits (Sheline et al., 2006). Thus, in studying brain-imaging variables associated with depressive symptoms, it is important to relate these changes to the individual׳s cognitive performance; otherwise, the brain changes found to be associated with depression might be primarily indicators of cognitive decline. We also included global cognitive performance, an additional independent variable, to distinguish the extent to which brain changes are primarily associated with the mood (and not cognitive) symptoms.

In this report, we examine the relationship of relevant MRI variables to depressive symptoms. In addition to examining the association of whole-brain markers of brain integrity, we also examine the regional distribution within the brain of these associations, using voxel-wise analyses. Further, to explore the relative regional specificity of these brain markers, we generate plots of the peak regional significance across the whole brain. This technique is used to visualize whether the markers show relatively similar effects across brain, or whether the plot shows distinct peaks, indicative of regional specificity.