Treatment Response In Late-life Depression Research Articles

Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex.

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

Change in Alzheimer's Disease Gray Matter Cortical Signature is Associated with Treatment Response in Late-Life Depression

Change in Alzheimer's Disease Gray Matter Cortical Signature is Associated with Treatment Response in Late-Life Depression

Treatment response in late-life depression: the absence of a relationship with white matter hyperintensity volume, executive functioning, and processing speed

Treatment response in late-life depression: the absence of a relationship with white matter hyperintensity volume, executive functioning, and processing speed

Machine Learning Prediction of Treatment Outcome in Late-Life Depression.

Background: Recent evidence suggests that integration of multi-modal data improves performance in machine learning prediction of depression treatment outcomes. Here, we compared the predictive performance of three machine learning classifiers using differing combinations of sociodemographic characteristics, baseline clinical self-reports, cognitive tests, and structural magnetic resonance imaging (MRI) features to predict treatment outcomes in late-life depression (LLD).Methods: Data were combined from two clinical trials conducted with depressed adults aged 60 and older, including response to escitalopram (N = 32, NCT01902004) and Tai Chi (N = 35, NCT02460666). Remission was defined as a score of 6 or less on the 24-item Hamilton Rating Scale for Depression (HAMD) at the end of 24 weeks of treatment. Features subsets were constructed from baseline sociodemographic and clinical features, gray matter volumes (GMVs), or both. Three classification algorithms were compared: (1) Support Vector Machine-Radial Bias Function (SVMRBF), (2) Random Forest (RF), and (3) Logistic Regression (LR). A repeated 5-fold cross-validation approach with a wrapper-based feature selection method was used for model fitting. Model performance metrics included Area under the ROC Curve (AUC) and Matthews correlation coefficient (MCC). Cross-validated performance significance was tested by permutation analysis. Classifiers were compared by Cochran's Q and post-hoc pairwise comparisons using McNemar's Chi-Square test with Bonferroni correction.Results: For the RF and SVMRBF algorithms, the combined feature set outperformed the clinical and GMV feature sets with a final cross-validated AUC of 0.83 ± 0.11 and 0.80 ± 0.11, respectively. Both classifiers passed permutation analysis. The LR algorithm performed best using GMV features alone (AUC 0.79 ± 0.14) but failed to pass permutation analysis using any feature set. Performance of the three classifiers differed significantly for all three features sets. Important predictive features of treatment response included anterior and posterior cingulate volumes, depression characteristics, and self-reported health-related quality scores.Conclusion: This preliminary exploration into the use of ML and multi-modal data to identify predictors of general treatment response in LLD indicates that integration of clinical and structural MRI features significantly increases predictive capability. Identified features are among those previously implicated in geriatric depression, encouraging future work in this arena.

Clinical and Cognitive Predictors of Response to Psychotherapy in Late Life Depression

<h3>Introduction</h3> Late life depression (LLD) is a common and heterogeneous condition that is associated with increased disability, cognitive impairment, and all-cause mortality in older adults. Anti-depressant medication and psychotherapy have been identified as effective treatments for LLD, though as many as 50% of patients do not respond to treatment. Several clinical (age, age of MDD onset, MDE severity, anxiety, perceived stress, social support, sleep quality) and cognitive (executive dysfunction, global cognitive impairment) factors have been identified as predictors of response to anti-depressant treatment. Less is known about predictors of psychotherapy treatment response in LLD, but cognitive dysfunction has been linked to poor treatment outcomes and may negatively impact the effectiveness of behavioral interventions that are subserved by various cognitive processes. <h3>Methods</h3> Participants included 83 individuals with LLD (HAM-D > 17) enrolled in a manualized 12-week psychotherapy with a licensed psychologist. All participants completed diagnostic interviews, comprehensive neuropsychological assessments and clinical evaluations before and after treatment. Separate multiple linear regression models were used to assess independent effects of baseline MDD features (age at onset, severity, treatment history, frequency and chronicity of MDEs), related clinical factors (comorbid anxiety and hoarding behaviors, perceived stress and health, social support, sleep disturbance), and cognitive performance (global cognition, executive functioning, episodic memory, processing speed, language, visuospatial skills, motor speed and dexterity) as predictors of treatment response, with percent change in HAM-D as the outcome variable. Cognitive performance was grouped by domain using composite Z-scores based on group means and standard deviations (all Chronbach's a's > .70). <h3>Results</h3> Forty-five percent (n=38) of participants showed treatment response (>50% reduction in HAM-D post-treatment). Responders were significantly younger (mean age = 69.76) than non-responders (mean age = 73.11, t = 7.10, <i>p</i> = .009). Level of education, gender distribution, and baseline depression characteristics (severity, length of episode, anti-depressant use) were equivalent (all <i>p</i>'s > .05). depression features accounted for 23.9% of the variance in HAM-D change, and showed a trend toward significance for older age of MDD onset associated with increased treatment response (t = 1.85, b = 0.38, <i>p =</i> .06) after accounting for age (t = 2.10, b = 0.31, <i>p = .</i>017). Non-depression clinical features accounted for 31.2% of the variance in HAM-D change, and greater sleep disturbance was associated with worse treatment response after accounting for age (t = 2.53, b = 0.34, <i>p = .</i>015). Cognitive performance accounted for 10.1% of the variance in HAM-D change, with no significant predictors after accounting for age (t = 2.36, b = 0.25, <i>p = .</i>021 <h3>Conclusions</h3> Our findings show that older age and sleep disturbance predict poorer response to treatment with 12 weeks of psychotherapy in a sample of individuals with LLD. Older age may negatively impact treatment response via increased risk for underlying neurodegenerative pathologies that are not affected by treatment with psychotherapy or medication. Similarly, sleep dysfunction in older adults has been implicated in the pathogenesis of Alzheimer's disease and related dementias and may reflect the presence of an underlying neurodegenerative process that is not targeted by psychiatric intervention. A preliminary exploration of cognitive factors suggests that cognitive dysfunction may play a more limited role in response to psychotherapeutic relative to pharmacologic intervention. Future research should assess the effect of neurodegenerative pathology on response to treatment with psychotherapy and medication in LLD. <h3>Funding</h3> This project was supported by the National Institute of Mental Health grant 1R01MH101472.

MEMORY COMPLAINTS AND DEPRESSION TREATMENT IN OLDER ADULTS

Introduction Older adults with major depression (or late-life depression) often complain about problems with thinking and memory. Some evidence suggests that subjective cognitive complaints may be a useful prognostic indicator of response to antidepressant medication. In one prior study, older adults with major depression and executive functioning complaints responded more slowly to escitalopram treatment over 12 weeks compared with older depressed adults with no executive functioning complaints. It is unclear whether the potential association between subjective cognitive complaints and treatment response generalizes to other cognitive domains and whether there is a longer-term relationship between treatment response and subjective cognitive complaints. The aim of the current study is to understand the relationship between subjective memory complaints and late-life depression treatment response at 12 weeks and one-year. The mechanism explaining the potential association between subjective cognitive complaints and treatment responses is unclear. Subjective memory complaints may represent subtle changes in objective memory test performance. Better objective story memory at baseline was associated with better depression outcomes one-year later in older adults with major depression. However, a large body of research also suggests subjective memory complaints in older adults are related to the severity of depression, anxiety, and/or personality traits (e.g., neuroticism), all factors that detrimentally influence depression treatment in older adults. Given these findings, we expected to find an association between subjective memory complaints and treatment response in late-life depression but hypothesized that the association would no longer be significant when controlling for depression severity, state anxiety, neuroticism, and objective memory performance. Methods The Neurobiology of Late-Life Depression (NBOLD) is a naturalistic longitudinal observation study of late-life depression. Upon enrollment, all patients were offered open label treatment with sertraline but this was not a requirement of participation. Instead, patients could have received other SSRIs/SNRIs and psychological treatment from non-study providers. Moreover, in some cases of mild major depression, patients may have elected not to receive treatment at all. All subjects underwent annual cognitive evaluations and depression monitoring with the Montgomery Asberg Depression Rating Scale (MADRS) as clinically indicated (and at least every three months). At baseline, subjective memory complaints were measured with the Memory Abilities Scale (MAB), state anxiety was measured with State-Trait Anxiety Inventory (STAI), and neuroticism was measured with the NEO-PI-R. Statistical Analyses: We conducted regression models testing the association between 12 week and one-year MADRS and baseline subjective memory complaints, objective memory performance (Logical Memory Delayed Recall), state anxiety, neuroticism, antidepressant usage, and relevant demographics. We tested both linear (continuous MADRS score) and logistic (yes-no presence of remission defined as MADRS Results The sample consisted of 90 patients at 12 weeks and 85 at one year. Regarding antidepressant treatment, 47.5% of LLD patients (n=57) began treatment with sertraline upon enrollment, 27.5% (n=33) were on some other SSRI and/or SNRI combination, and 25% were not receiving antidepressants. Contrary to our hypotheses, linear regression models revealed that baseline subjective memory complaints were a significant predictor of 12 week (Coefficient = -.087 +- .038, p = .025) and one-year MADRS (Coefficient = -.097 +- .039, p = .014) scores even when accounting for objective memory performance (Logical Memory Delayed Recall), state anxiety, neuroticism, antidepressant usage, and relevant demographics. Using the same covariates, subjective memory complaints also predicted remission at 12 weeks (OR[95%CI] = 1.07 (1.02, 1.11) p Conclusions Subjective memory complaints seem to be a useful indicator of depression treatment response in older adults with major depression. Notably the relationship between subjective memory complaints and treatment response was present even when accounting for other important factors shown to be related to subjective cognitive complaints and treatment outcome. Future work should investigate the biological and cognitive correlates of subjective memory complaints in older adults with major depression. This research was funded by: The research was supported by the Leo and Anne Albert Charitable Trust & NIMH Grant R01 MH108578.

Increased ventromedial prefrontal cortex activity and connectivity predict poor sertraline treatment outcome in late-life depression.

Previous studies of imaging predictors on acute treatment response in late-life depression (LLD) demonstrated that poor response to selective serotonin reuptake inhibitors (SSRIs) is associated with pre-treatment low functional connectivity (FC) within executive control network and high FC within default-mode network including the ventromedial prefrontal cortex (vmPFC). However, there is less research in regional resting-state functional activity that explains FC changes related to SSRI response. Thirty-six older major depressive disorder (MDD) patients not currently on antidepressant treatment had a baseline, pre-treatment resting-state functional magnetic resonance imaging scan, followed by sertraline treatment for 12weeks. Depression severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). Subjects whose MADRS score decreased less than 50% from baseline or who discontinued sertraline for any reason were classified as nonresponders (n=21). Subjects whose 12-week MADRS score dropped greater than or equal to 50% from baseline were defined as responders (n=15). We conducted the amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-to-ROI FC analyses independently. Significance threshold was set at P<0.05 with false discovery rate (FDR) correction for multiple comparisons. Relative to the responder group, the nonresponder group showed significantly less ALFF in the dorsomedial prefrontal cortex (dmPFC) and greater ALFF in the vmPFC/subgenual cingulate area. For ROI-to-ROI connectivity, there was significantly greater connectivity between the vmPFC and the cerebellar vermis in the nonresponder group. Our study highlighted the association of vmPFC resting-state activity and connectivity with SSRI response. Future studies are warranted for understanding the role of vmPFC-vermis connectivity in LLD.

Functional connectivity predictors of acute depression treatment outcome.

Few studies have examined functional connectivity (FC) patterns using functional magnetic resonance imaging (fMRI) to predict outcomes in late-life depression. We hypothesized that FC within and between frontal and limbic regions would be associated with 12-week depression outcome in older depressed adults. Seventy-one subjects with major depression were enrolled in the study. A study geriatric psychiatrist performed a clinical interview and completed a Montgomery-Åsberg Depression Rating Scale (MADRS). All study participants were free of medication at baseline and had a brain fMRI scan. Using a regions of interest (ROI) atlas (including 164 ROIs), we conducted ROI-to-ROI resting-state FC analyses for each participant. In terms of treatment participants were offered sertraline initially, although in this naturalistic study, other medications were also prescribed. Subjects were evaluated every 2 weeks up to 12 weeks by the study psychiatrist, who followed a flexible, clinically based medication dosing schedule. Multivariate regression analysis was used to examine correlation between change of MADRS score over 12 weeks and baseline FC between brain regions, controlling for age, gender, mean head motion, and baseline MADRS. We found greater FC between the left inferior frontal gyrus pars triangularis and the left frontal eye field and FC of these two regions with a number of brain regions related to reward, salience, and sensorimortor function were correlated with change in MADRS score over 12 weeks. Our results highlight the important role of between inner speech-reward, attention-salience, and attention-sensorimotor network synchronization in predicting acute treatment response in late-life depression.

Acute trajectories of neural activation predict remission to pharmacotherapy in late-life depression.

Pharmacological treatment of major depressive disorder (MDD) typically involves a lengthy trial and error process to identify an effective intervention. This lengthy period prolongs suffering and worsens all-cause mortality, including from suicide, and is typically longer in late-life depression (LLD). Our group has recently demonstrated that during an open-label venlafaxine (serotonin-norepinephrine reuptake inhibitor) trial, significant changes in functional resting state connectivity occurred following a single dose of treatment, which persisted until the end of the trial. In this work, we propose an analysis framework to translate these perturbations in functional networks into predictors of clinical remission. Participants with LLD (N = 49) completed 12-weeks of treatment with venlafaxine and underwent functional magnetic resonance imaging (fMRI) at baseline and a day following a single dose of venlafaxine. Data was collected at rest as well as during an emotion reactivity task and an emotion regulation task. Remission was defined as a Montgomery-Asberg Depression Rating Scale (MADRS) ≤10 for two weeks. We computed eigenvector centrality (whole brain connectivity) and activation during the emotion regulation and emotion reactivity tasks. We employed principal components analysis, Tikhonov-regularized logistic classification, and least angle regression feature selection to predict remission by the end of the 12-week trial. We utilized ten-fold cross-validation and Receiver Operator Curves (ROC) curve analysis. To determine task-region pairs that significantly contributed to the algorithm's ability to predict remission, we used permutation testing. Using the fMRI data at both baseline and after the first dose of treatment yielded a sensitivity of 72% and a specificity of 68% (AUC = 0.77), a 15% increase in accuracy over baseline MADRS. In general, the accuracy at baseline was further improved by using the change in activation following a single dose. Activation of the frontal cortex, hippocampus, parahippocampus, caudate, thalamus, medial temporal cortex, middle cingulate, and visual cortex predicted treatment remission. Acute, dynamic trajectories of functional imaging metrics in response to a pharmacological intervention are a valuable tool for predicting treatment response in late-life depression and elucidating the mechanism of pharmacological therapies in the context of the brain's functional architecture.

Poster Number: EI 42 - Immunological Markers Associated with Brain Health and Treatment Response in Late-Life Depression: Pilot Study

Poster Number: EI 42 - Immunological Markers Associated with Brain Health and Treatment Response in Late-Life Depression: Pilot Study

A Meta-Analysis of Executive Dysfunction and Antidepressant Treatment Response in Late-Life Depression.

Depressed older adults with executive dysfunction (ED) may respond poorly to antidepressant treatment. ED is a multifaceted construct and different studies have measured different aspects of ED, making it unclear which aspects predict poor response. Meta-analytic methods were used to determine whether ED predicts poor antidepressant treatment response in late-life depression and to determine which domains of executive functioning are responsible for this relationship. A Medline search was conducted to identify regimented treatment trials contrasting executive functioning between elderly responders and nonresponders; only regimented treatment trials for depressed outpatients aged 50 and older were included. Following the most recent PRISMA guidelines, 25 measures of executive functioning were extracted from eight studies. Six domains were identified: cognitive flexibility, planning and organization, response inhibition, selective attention, verbal fluency, and the Dementia Rating Scale Initiation/Perseveration composite score (DRS I/P). Hedge's g was calculated for each measure of executive functioning. A three-level Bayesian hierarchical linear model (HLM) was used to estimate effect sizes for each domain of executive functioning. The effect of planning and organization was significantly different from zero (Bayesian HLM estimate of domain effect size: 0.91; 95% CI: 0.32-1.58), whereas cognitive flexibility, response inhibition, selective attention, verbal fluency, and the DRS I/P composite score were not. The domain of planning and organization is meaningfully associated with poor antidepressant treatment response in late-life depression. These findings suggest that therapies that focus on planning and organization may provide effective augmentation strategies for antidepressant nonresponders with late-life depression.

Emotional Processing Functional Magnetic Resonance Imaging Is Associated with Treatment Response in Late Life Depression

Late-life depression (LLD) is a distinct clinical entity which has been estimated to affect 8-16% of elderly patients. Its disease burden is considerable with effects on mortality, development of dementia, functional status, and healthcare utilization. Research has established functional magnetic resonance imaging (fMRI) markers as reliable predictors of treatment in response in LLD, including differential activity and connectivity between various neural structures and networks. However, an underexplored area of previous fMRI studies is whether neural activity during affective tasks may be associated with treatment response in LLD.

Magnetic Resonance Imaging Predictors of Treatment Response in Late-Life Depression

In older adults, depression not only results in more years lived with disability than any other disease but it also carries additional risks of suicide, medical comorbidities, and family caregiving burden. Because it can take many months to identify an effective treatment regimen, it is of utmost importance to shorten the window of time and identify early on what medications and dosages will work effectively for individuals having depression. Late-life depression (LLD) has been associated with greater burden of age-related changes (eg, atrophy, white matter ischemic changes, and functional connectivity). Depression in midlife has been shown to alter affective reactivity and regulation, and functional magnetic resonance imaging (fMRI) studies in LLD have replicated the same abnormalities. Effective treatment can normalize these alterations. This article provides a review of the current literature using structural and functional neuroimaging to identify MRI predictors of treatment response in LLD. The majority of the literature on structural MRI has focused on the vascular depression hypothesis, and studies support the view that loss of brain volume and white matter integrity was associated with poorer treatment outcomes. Studies using fMRI have reported that lower task-based activity in the prefrontal cortex and limbic regions was associated with poorer outcome. These imaging markers may be integrated into clinical decision making to attain better treatment outcomes in the future.

Executive Functioning Complaints and Escitalopram Treatment Response in Late-Life Depression

Executive dysfunction may play a key role in the pathophysiology of late-life depression. Executive dysfunction can be assessed with cognitive tests and subjective report of difficulties with executive skills. The present study investigated the association between subjective report of executive functioning complaints and time to escitalopram treatment response in older adults with major depressive disorder (MDD). 100 older adults with MDD (58 with executive functioning complaints and 42 without executive functioning complaints) completed a 12-week trial of escitalopram. Treatment response over 12 weeks, as measured by repeated Hamilton Depression Rating Scale scores, was compared for adults with and without executive complaints using mixed-effects modeling. Mixed effects analysis revealed a significant group × time interaction, F(1, 523.34) = 6.00, p = 0.01. Depressed older adults who reported executive functioning complaints at baseline demonstrated a slower response to escitalopram treatment than those without executive functioning complaints. Self-report of executive functioning difficulties may be a useful prognostic indicator for subsequent speed of response to antidepressant medication.

Resting state functional connectivity and treatment response in late-life depression

Indices of functional connectivity in the default mode network (DMN) are promising neural markers of treatment response in late-life depression. We examined the differences in DMN functional connectivity between treatment-responsive and treatment-resistant depressed older adults. Forty-seven depressed older adults underwent MRI scanning pre- and post-pharmacotherapy. Forty-six never depressed older adults underwent MR scanning as comparison subjects. Treatment response was defined as achieving a Hamilton Depression Rating Scale of 10 or less post-treatment. We analyzed resting state functional connectivity using the posterior cingulate cortex as the seed region-of-interest. The resulting correlation maps were employed to investigate between-group differences. Additionally we examined the association between white matter hyperintensity burden and functional connectivity results. Comparison of pre- and post-treatment scans of depressed participants revealed greater post-treatment functional connectivity in the frontal precentral gyrus. Relative to treatment-responsive participants, treatment-resistant participants had increased functional connectivity in the left striatum. When adjusting for white matter hyperintensity burden, the observed differences lost significance for the PCC-prefrontal functional connectivity, but not for the PCC-striatum functional connectivity. The post-treatment “frontalization” of the DMN connectivity suggests a normalizing effect of antidepressant treatment. Moreover, our study confirms the central role of white matter lesions in disrupting brain functional connectivity.

Patterns of Reduced Cortical Thickness in Late-Life Depression and Relationship to Psychotherapeutic Response

Cortical atrophy has been associated with late-life depression (LLD) and recent findings suggest that reduced right hemisphere cortical thickness is associated with familial risk for major depressive disorder, but cortical thickness abnormalities in LLD have not been explored. Furthermore, cortical atrophy has been posited as a contributor to poor antidepressant treatment response in LLD, but the impact of cortical thickness on psychotherapy response is unknown. This study was conducted to evaluate patterns of cortical thickness in LLD and in relation to psychotherapy treatment outcomes. Participants included 22 individuals with LLD and 12 age-matched comparison subjects. LLD participants completed 12 weeks of psychotherapy and treatment response was defined as a 50% reduction in depressive symptoms. All participants underwent magnetic resonance imaging of the brain, and cortical mapping of gray matter tissue thickness was calculated. LLD individuals demonstrated thinner cortex than controls prominently in the right frontal, parietal, and temporal brain regions. Eleven participants (50%) exhibited positive psychotherapy response after 12 weeks of treatment. Psychotherapy nonresponders demonstrated thinner cortex in bilateral posterior cingulate and parahippocampal cortices, left paracentral, precuneus, cuneus, and insular cortices, and the right medial orbitofrontal and lateral occipital cortices relative to treatment responders. Our findings suggest more distributed right hemisphere cortical abnormalities in LLD than have been previously reported. In addition, our findings suggest that reduced bilateral cortical thickness may be an important phenotypic marker of individuals at higher risk for poor response to psychotherapy.

Dynamic Prediction of Treatment Response in Late-Life Depression

To identify actionable predictors of remission to antidepressant pharmacotherapy in depressed older adults and to use signal detection theory to develop decision trees to guide clinical decision making. We treated 277 participants with current major depression using open-label venlafaxine XR (up to 300 mg/day) for 12 weeks, in an NIMH-sponsored randomized, placebo-controlled augmentation trial of adjunctive aripiprazole. Multiple logistic regression and signal detection approaches identified predictors of remission in both completer and intent-to-treat samples. Higher baseline depressive symptom severity (odds ratio [OR]: 0.86, 95% confidence interval [CI]: 0.80-0.93; p<0.001), smaller symptom improvement during the first two weeks of treatment (OR: 0.96, 95% CI: 0.94-0.97; p<0.001), male sex (OR: 0.41 95% CI: 0.18-0.93; p= 0.03), duration of current episode≥2 years (OR: 0.26, 95% CI: 0.12-0.57; p<0.001) and adequate past depression treatment (ATHF≥3) (OR: 0.34, 95% CI: 0.16-0.74; p= 0.006) predicted lower probability of remission in the completer sample. Subjects with Montgomery Asberg (MADRS) decreasing by greater than 27% in the first 2 weeks and with baseline MADRS scores of less than 27 (percentile rank= 51) had the best chance of remission (89%). Subjects with small symptom decrease in the first 2 weeks with adequate prior treatment and younger than 75 years old had the lowest chance of remission (16%). Our results suggest the clinical utility of measuring pre-treatment illness severity and change during the first 2 weeks of treatment in predicting remission of late-life major depression.

Treatment Course With Antidepressant Therapy in Late-Life Depression

In order to assess the effect of gray matter volumes and cortical thickness on antidepressant treatment response in late-life depression, the authors examined the relationship between brain regions identified a priori and Montgomery-Åsberg Depression Rating Scale (MADRS) scores over the course of an antidepressant treatment trial. In a nonrandomized prospective trial, 168 patients who were at least 60 years of age and met DSM-IV criteria for major depression underwent MRI and were enrolled in a 12-week treatment study. Exclusion criteria included cognitive impairment or severe medical disorders. The volumes or cortical thicknesses of regions of interest that differed between the depressed group and a comparison group (N=50) were determined. These regions of interest were used in analyses of the depressed group to predict antidepressant treatment outcome. Mixed-model analyses adjusting for age, education, age at depression onset, race, baseline MADRS score, scanner, and interaction with time examined predictors of MADRS scores over time. Smaller hippocampal volumes predicted a slower response to treatment. With the inclusion of white matter hyper-intensity severity and neuropsychological factor scores, the best model included hippocampal volume and cognitive processing speed to predict rate of response over time. A secondary analysis showed that hippocampal volume and frontal pole thickness differed between patients who achieved remission and those who did not. These data expand our understanding of the prediction of treatment course in late-life depression. The authors propose that the primary variables of hippocampal volume and cognitive processing speed, subsuming other contributing variables (episodic memory, executive function, language processing) predict antidepressant response.

Late-Life Depression Research: Lessons Learned From the Metabolic Syndrome

Late-Life Depression Research: Lessons Learned From the Metabolic Syndrome

Relationship of endothelial function and atherosclerosis to treatment response in late‐life depression

Treatment response in late-life depression has been linked to cerebrovascular disease notably via the vascular depression hypothesis. This study investigated the relationship between endothelial function and atherosclerosis and treatment response to antidepressant monotherapy. Twenty five patients with late-life depression were compared with 21 non-depressed control subjects in a case control study. Nine of the depressed subjects were responders to antidepressant monotherapy and 16 were not. Vascular measures included assessment of carotid intima media thickness (IMT) representing atherosclerosis and biopsied small artery dilatation to acetylcholine to assess endothelial function in a subset of subjects. There were no group differences in vascular risks or sociodemographic variables. There was a significant group difference (responders versus non-responders versus controls) on both IMT and endothelial function (p < 0.01 and p < 0.05, respectively) with a significant difference between controls and non-responders (p < 0.001) on IMT and between controls and responders (p < 0.05) and control versus non-responders (p < 0.05) on endothelial function but no significant difference between responders and non-responders. On both IMT and endothelial function, there was a gradient across groups, with control subjects having best vascular structure or function, non-responders worse and responders in-between. The results are consistent with a hypothesis that poorer antidepressant response in later life depressive disorder may be linked to an underlying vascular dysfunction and pathology. The study is small, and the results require replication but if confirmed, trials with vasoprotective medication aimed at improving vascular function in order to alter the prognosis of late-life depression would be a rational development.