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

Venlafaxine XR treatment for older patients with major depressive disorder: decision trees for when to change treatment

BackgroundPredictors of antidepressant response in older patients with major depressive disorder (MDD) need to be confirmed before they can guide treatment.ObjectiveTo create decision trees for early identification of older patients...

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

Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression

ObjectiveLate-life depression (LLD) is characterized by accelerated biological aging. Accelerated brain aging, estimated from structural magnetic resonance imaging (sMRI) data by a machine learning algorithm, is associated with LLD diagnosis, poorer cognitive performance, and disability. We hypothesized that accelerated brain aging moderates the antidepressant response. Design and InterventionsFollowing MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion. ParticipantsNinety-five individuals with LLD. MeasurementsA machine learning algorithm estimated each participant's brain age from sMRI data. This was used to calculate the brain-age gap (BAG), or how estimated age differed from chronological age. Secondary sMRI measures of aging pathology included white matter hyperintensity (WMH) volumes and hippocampal volumes. Mixed models examined the relationship between sMRI measures and change in depression severity. Initial analyses tested for a moderating effect of MRI measures on change in depression severity with escitalopram. Subsequent analyses tested for the effect of MRI measures on change in depression severity over time across trials. ResultsIn the blinded initial phase, BAG was not significantly associated with a differential response to escitalopram over time. BAG was also not associated with a change in depression severity over time across both arms in the blinded phase or in the subsequent open-label bupropion phase. We similarly did not observe effects of WMH volume or hippocampal volume on change in depression severity over time. ConclusionsMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial.

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.

Greater baseline subjective attentional complaints predict poorer 8-week antidepressant response in late-life depression

<h3>Introduction</h3> Late-life depression (LLD) is characterized by both subjective cognitive complaints and objective cognitive deficits, most notably in executive functions. Worse cognitive performance, including in the executive function domain, is associated with poor antidepressant treatment outcomes. While executive-based cognitive complaints are similarly associated with poor treatment outcomes, the relationship between other subjective cognitive complaints and antidepressant response is not as clear. This may be particularly relevant for subjective attentional complaints, a common finding and clinical diagnostic criterion for Major Depressive Disorder. <h3>Methods</h3> Eighty-eight adults with LLD were recruited (mean age = 66.07 ± 4.49, 61% female, baseline mean Montgomery-Asberg Depression Rating Scale (MADRS) = 26.38 ± 5.46) and underwent an 8-week antidepressant trial. Subjective cognitive complaints were assessed with the following scales: Attentional Control Scale (ACS, focusing in-depth on attention), the WHODAS 2.0, domain 1 (focusing largely on attentional abilities), and the PROMIS Cognitive Abilities and Concerns (focusing on general / broad-based cognitive abilities). Antidepressant response was determined via the change in MADRS scores from baseline to week 8. Separate linear regressions examined the relationship between subjective cognitive complaints and change in MADRS scores, controlling for age, sex, baseline MADRS, and treatment arm. <h3>Results</h3> After covariate adjustment, ACS and WHODAS scores significantly predicted antidepressant response (<i>ß =</i> -0.42<i>, p=</i> 0.02 and <i>ß =</i> 0.57<i>, p=</i> 0.03, respectively), such that greater subjective attentional complaints at baseline were related to less improvement in MADRS scores. General cognitive complaints via the PROMIS were not significantly associated with antidepressant response. Follow-up analyses decomposing the ACS into its two subscales found that the change in MADRS scores was significantly related to attentional shifting (<i>ß = -</i>0.79, <i>p</i> = 0.01), but not focusing (<i>ß =</i> -0.57, <i>p</i> = 0.06), complaints. <h3>Conclusions</h3> Results highlight the importance of assessing for subjective cognitive complaints in LLD, particularly in the domain of attention, as their presence at baseline may be related to treatment response. Further research is needed to better understand the relationship between subjective and objective cognition in LLD, their relationship with treatment response and other outcomes, as well as underlying mechanisms. <h3>Funding</h3> R01MH102246

The Effects of Accelerated Brain Aging on the Antidepressant Response in Late-Life Depression

Introduction Late-Life Depression (LLD) is characterized by functional and structural brain alterations and accelerated brain aging. Our past work utilized a brain-based marker of accelerated aging to examine LLD and demonstrated a cross-sectional association between accelerated brain aging and impaired cognitive ability (poor episodic memory, slow processing speed, and poor executive function) as well as disability (measured by WHODAS). However, it is unclear whether or not accelerated brain aging influences the antidepressant response in depressed elders. Methods We examined depressed adults over 60 years-old with current Major Depressive Disorder (MDD) without psychotic features (N=95) randomized to receive either escitalopram up to 20mg daily or identical placebo (2:1 subject ratio) for 8 weeks. Subjects underwent baseline depression assessment (MADRS) and MRI prior to randomization. After using an automated deep learning tool to estimate brain age from cranial MRI, the brain age gap (BAG) was calculated by subtracting the participant's chronological age from his or her calculated brain age estimation. The brain MRI estimating tool uses ROI volumes derived from multiple atlases and the BrainAGE algorithm - the algorithm applies a deep convolutional neural network regression model trained on 5000 healthy controls. For statistical analysis, the dependent outcome variable was change in MADRS over 8 weeks. Initial models examined the effects of BAG with baseline MADRS, age, sex, and treatment assignment as covariates. Subsequent models tested for a statistical interaction between treatment assignment and BAG to observe whether or not the effects of brain aging on change in MADRS differed between arms. Results In the primary effects model examining change in MADRS, although there was a strong effect of treatment assignment (t = -3.75, p = 0.0003), there was no significant relationship between BAG and antidepressant response (t = -0.02, p = 0.9819). In the subsequent model, we observed a statistical interaction between BAG and treatment assignment on change in MADRS (t = -2.38, p = 0.0196). Analysis of subgroup data demonstrated that a larger BAG (indicating an older appearing brain) was associated with less change in MADRS for those who received placebo. In contrast, a larger BAG (indicating an older appearing brain) was associated with greater change in MADRS for those who received escitalopram. Conclusions The effect of accelerated brain aging, measured with the BAG, on change in MADRS have opposite patterns based on treatment assignment. Although a larger BAG is associated with poorer cognitive performance and greater disability, a larger BAG was associated with greater change in MADRS in the active treatment arm of our study. This is somewhat discrepant with prior work that associates poor cognitive performance with worse antidepressant response. As a global brain metric, BAG is not specific to discrete functional and/or structural brain impairments. Therefore, the elements that jointly contribute to the brain age metric may act in discrete, separate ways, with some influencing cognitive performance, and with others having less of a functional impact, serving as a marker of positive response to antidepressant medication. Further work must examine the complex relationships between accelerated brain aging, cognition, and response to antidepressants. Funding R01 MH102246, K24 MH110598

Amyloid Burden: A Reason for Poor Antidepressant Response in Late-Life Depression?

Accumulation of cortical amyloid-β (Aβ) has been associated with greater depressive symptoms in cognitively intact older adults. Higher cortical Aβ

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.

Screening for Executive Dysfunction in Late-Life Depression: Utility of Trail Making Test and Self-Report Measures

Prior work suggests executive dysfunction (ED) on the Stroop Color and Word Test (SCWT) and the Mattis Dementia Rating Scale-2 Initiation/Perseveration subscale (DRS IP) predicts poor antidepressant response in late-life depression. This study examined if either patient perception of ED or the Trail Making Test Part B (TMT-B) could identify patients with impairment on the SCWT or DRS IP. Patients were 65 or older and had a diagnosis of major depression without dementia. Cognition was assessed with the TMT-B, the SCWT, and the DRS IP. A self-reported Perceived Deficits Questionnaire (PDQ) subscale assessed patients' perceptions of ED. In 247 participants (mean age 71.3 years), the PDQ subscale was not associated with test performance. The sensitivity of the TMT-B in identifying impairment on the SCWT or DRS IP was low (35% and 23%, respectively). Neither the TMT-B nor self-reports are useful screening tools for ED on the SCWT or DRS IP.

S138. White Matter Integrity Predicts Anti-Depressant Response in Late-Life Depression

White matter integrity in fronto-limbic-striatal circuits are frequently reduced in depression. We investigated the effect of local tract integrity on antidepressant outcome in geriatric depression. Regions of interest (ROIs) comprised the callosal genu (GCC), anterior and posterior internal capsule (ALIC, PLIC), cingulum (CGC), inferior and superior fronto-occipital and superior longitudinal fasciculi (IFO, SFO, SLF).

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.

The role of late life depressive symptoms on the trajectories of insomnia symptoms during antidepressant treatment

ObjectiveSleep disturbances are common in late life depression; however, changes in insomnia symptoms during antidepressant treatment need to be characterized further. The objective of this study was two-fold: 1) to describe longitudinal trajectories of insomnia symptoms in older adults receiving antidepressant treatment and 2) to examine whether baseline depressive symptoms were associated with trajectories of sleep over time. MethodsData was obtained from 680 older adults (aged ≥ 60) with major depression who participated in one of two protocolized open-label antidepressant treatment clinical trials (Maintenance Therapies in Late Life Depression [MTLD-3]; Incomplete Response in Late Life Depression: Getting to Remission [IRL-GRey]). Depression (total score minus sleep items) and sleep (sum of sleep items) outcomes were derived from the Hamilton Depression Rating Scale in the MLTD-3 and Montgomery-Asberg Depression Rating Scale in the IRL-GRey. ResultsBoth datasets identified 5 possible trajectories of insomnia symptoms with about half of the older adults having clinically significant baseline sleep disturbances and minimal improvement following a course of antidepressant treatment (i.e., sub-optimal sleep trajectory). Furthermore, across both datasets, worse baseline depression severity was associated with sub-optimal sleep trajectories. ConclusionIn older adults receiving antidepressant treatment, those with clinically significant baseline sleep disturbances and greater depression severity may require adjunctive sleep-focused treatment to ameliorate sleep symptoms.

55. Intrinsic and Internetwork Connectivity, Negative Self Referential Processing, and Antidepressant Response in Late-Life Depression

55. Intrinsic and Internetwork Connectivity, Negative Self Referential Processing, and Antidepressant Response in Late-Life Depression

Frontocingulate cerebral blood flow and cerebrovascular reactivity associated with antidepressant response in late-life depression

BackgroundVascular pathology is common in late-life depression (LLD) and may contribute to alterations in cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). In turn, such hemodynamic deficits may adversely affect brain function and clinical course. The goal of this study was to examine whether altered cerebral hemodynamics in depressed elders predicted antidepressant response. Methods21 depressed elders completed cranial 3T MRI, including a pseudo-continuous Arterial Spin Labeling (pcASL) acquisition on both room air and during a hypercapnia challenge. Participants then completed 12 weeks of open-label sertraline. Statistical analyses examined the relationship between regional normalized CBF and CVR values and change in Montgomery-Asberg Depression Rating Scale (MADRS) and tested for differences based on remission status. Results10 participants remitted and 11 did not. After controlling for age and baseline MADRS, greater change in MADRS with treatment was associated with lower pre-treatment normalized CBF in the caudal anterior cingulate cortex (cACC) and lateral orbitofrontal cortex (OFC), as well as lower CVR with hypercapnia in the caudal medial frontal gyrus (cMFG). After controlling for age and baseline MADRS score, remitters exhibited lower CBF in the cACC and lower CVR in the cMFG. LimitationsOur sample was small, did not include a placebo arm, and we examined only specific regions of interest. ConclusionsOur findings suggest that increased perfusion of the OFC and the ACC is associated with a poor antidepressant response. They do not support that vascular pathology as measured by CBF and CVR negatively affects acute treatment outcomes.

Predictors and Moderators of Remission With Aripiprazole Augmentation in Treatment-Resistant Late-Life Depression: An Analysis of the IRL-GRey Randomized Clinical Trial.

Safe, efficacious, second-line pharmacological treatment options exist for the large portion of older adults with major depressive disorder who do not respond to first-line pharmacotherapy. However, limited evidence exists to aid clinical decision making regarding which patients will benefit from which second-line treatments. To test the moderating role of pretreatment executive function, severity of anxiety, and severity of medical comorbidity in remission of treatment-resistant late-life depression after aripiprazole augmentation. As follow-up to a 12-week randomized clinical trial of aripiprazole augmentation for first-line treatment-resistant late-life depression (Incomplete Response in Late-Life Depression: Getting to Remission [IRL-GRey]), we evaluated the effects of the following potential moderators and their interactions with treatment: baseline assessments of executive function (set shifting measured by the Trail Making Test) and response inhibition control (measured by a Color-Word Interference task), anxiety symptoms, and medical comorbidity. Analyses were conducted in May and June 2015. Aripiprazole or placebo tablets were started at 2 mg daily and titrated as tolerated, to a maximal dose of 15 mg daily. Remission of treatment-resistant late-life depression (defined as a Montgomery-Åsberg Depression Rating Scale score of ≤10 at both of the last 2 consecutive visits). Of 181 trial participants (103 female [56.9%]) who were 60 years of age or older and whose major depression had failed to remit with venlafaxine hydrochloride monotherapy, 91 received aripiprazole and 90 received placebo. Remission occurred in 40 (43%) who received aripiprazole and 26 (29%) who received placebo. Baseline set shifting moderated the efficacy of aripiprazole augmentation (odds ratio [OR], 1.66 [95% CI, 1.05-2.62]; P = .03 for interaction with treatment). Among participants with a Trail Making Test scaled score of 7 or higher, the odds of remission were significantly higher with aripiprazole than with placebo (53% vs 28%; number needed to treat, 4; OR, 4.11 [95% CI, 1.83-9.20]). Among participants with a Trail Making Test scaled score of less than 7, aripiprazole and placebo were equally efficacious (OR, 0.64 [95% CI, 0.15-2.80]). Greater severity of anxiety at baseline predicted a lower remission rate but did not moderate aripiprazole efficacy; each standard deviation greater anxiety severity was associated with 50% reduced odds of remission in both aripiprazole and placebo arms. Medical comorbidity and Color-Word Interference test performance were neither general predictors nor treatment-moderating factors. Set-shifting performance indicates which older adults with treatment-resistant depression may respond favorably to augmentation with aripiprazole and thus may help to personalize treatment. clinicaltrials.gov Identifier: NCT00892047.