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• What is the primary question addressed by this study ? We sought to determine whether self-reported symptom phenotypes in late-life depression were associated with cognitive presentation, disability, and antidepressant treatment outcomes. • What is the main finding of this study? Apathy/anhedonia and fatigue/insomnia symptom phenotypes were associated with greater disability, while fatigue/insomnia and rumination/worry were associated respectively with processing speed performance and episodic memory performance. Severity of symptom phenotypes did not influence the response to escitalopram, however only worry and overall rumination severity improved specifically to escitalopram above placebo. • What is the meaning of the finding? Deeper characterization of depressive symptoms in older adults may provide information about cognitive performance and overall disability, however escitalopram, when compared to placebo does not appear to robustly improve most of these symptoms beyond worry and overall rumination. Late-life depression is associated with substantial heterogeneity in clinical presentation, disability, and response to antidepressant treatment. We examined whether self-report of severity of common symptoms, including anhedonia, apathy, rumination, worry, insomnia, and fatigue were associated with differences in presentation and response to treatment. We also examined whether these symptoms improved during treatment with escitalopram. Eighty-nine older adults completed baseline assessments, neuropsychological testing and providing self-reported symptom and disability scales. They then entered an 8-week, placebo-controlled randomized trial of escitalopram, and self-report scales were repeated at the trial's end. Raw symptom scale scores were combined into three standardized symptom phenotypes and models examined how symptom phenotype severity was associated with baseline measures and depression improvement over the trial. While rumination/worry appeared independent, severity of apathy/anhedonia and fatigue/insomnia were associated with one another and with greater self-reported disability. Greater fatigue/insomnia was also associated with slower processing speed, while rumination/worry was associated with poorer episodic memory. No symptom phenotype severity score predicted a poorer overall response to escitalopram. In secondary analyses, escitalopram did not improve most phenotypic symptoms more than placebo, aside for greater reductions in worry and total rumination severity. Deeper symptom phenotype characterization may highlight differences in the clinical presentation of late-life depression. However, when compared to placebo, escitalopram did not improve many of the symptoms assessed. Further work is needed to determine whether symptom phenotypes inform longer-term course of illness, and which treatments may best benefit specific symptoms. [ABSTRACT FROM AUTHOR]

Objective: Late-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 Interventions: Following MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion.Participants: Ninety-five individuals with LLD.Measurements: A 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.Results: In 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.Conclusion: sMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial. [ABSTRACT FROM AUTHOR]

Objective: Amyloid accumulation, the pathological hallmark of Alzheimer's disease, may predispose some older adults to depression and cognitive decline. Deposition of amyloid also occurs prior to the development of cognitive decline. It is unclear whether amyloid influences antidepressant outcomes in cognitively intact depressed elders.Design: A pharmacoimaging trial utilizing florbetapir (18F) PET scanning followed by 2 sequential 8-week antidepressant medication trials.Participants: Twenty-seven depressed elders who were cognitively intact on screening.Measurements and Interventions: After screening, diagnostic testing, assessment of depression severity and neuropsychological assessment, participants completed florbetapir (18F) PET scanning. They were then randomized to receive escitalopram or placebo for 8 weeks in a double-blinded two-to-one allocation rate. Individuals who did not respond to initial treatment transitioned to a second open-label trial of bupropion for another 8 weeks.Results: Compared with 22 amyloid-negative participants, 5 amyloid-positive participants exhibited significantly less change in depression severity and a lower likelihood of remission. In the initial blinded trial, 4 of 5 amyloid-positive participants were nonremitters (80%), while only 18% (4 of 22) of amyloid-negative participants did not remit (p = 0.017; Fisher's Exact test). In separate models adjusting for key covariates, both positive amyloid status (t = 3.07, 21 df, p = 0.003) and higher cortical amyloid binding by standard uptake value ratio (t = 2.62, 21 df, p = 0.010) were associated with less improvement in depression severity. Similar findings were observed when examining change in depression status across both antidepressant trials.Conclusions: In this preliminary study, amyloid status predicted poor antidepressant response to sequential antidepressant treatment. Alternative treatment approaches may be needed for amyloid-positive depressed elders. [ABSTRACT FROM AUTHOR]

Introduction Subjective cognitive decline (SCD) is increasingly recognized as the initial outward sign of preclinical Alzheimer's disease. The ability to explore associations between individual domains (memory, language, executive function, and visuospatial processing) within SCD and pathological biomarkers of early Alzheimer's disease (AD) would provide an important tool to understand the pathological basis of SCD and the risk of developing AD. This study utilizes multiple data analysis strategies to characterize the severity of tau and amyloid burden in clinically normal elderly adults (CN) and early mild cognitive impairment (EMCI) subjects in association with their subjective cognitive decline. Methods All subject data were downloaded from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. These included [18F]flortaucipir tau and [18F]florbetapir amyloid positron emission tomography (PET) images as well as the subjects' SCD scores. For SCD, we used the self- and informant-reported individual items of Everyday Cognition questionnaire, including Everyday Memory, Everyday Language, Everyday Visuospatial abilities, Everyday Planning, Everyday Organization, and Everyday Divided Attention. The severity of the amyloid burden was calculated as the global PET standardized uptake value ratio (SUVR). The severity of the tau burden was assessed with both standard uptake-based approaches (tau SUVR in entorhinal, limbic, and isocortical Braak regions) and with a novel texture analysis tool, the weighted two-point correlation (wS2) analysis, which characterizes the spatial clustering of the tau-PET image as a sensitive early biomarker of abnormal tau accumulation and spread. Using a series of backward-elimination regression models, we identified the combination of predictors (from tau PET, global amyloid-PET, sex, APOE, and age) that constructed the best model to predict each Everyday Cognition item. Results Across the different cognitive tests, the wS2-based tau measures explained more variability, as indicated by p-values and elevated R-squared values, than standardized uptake value ratios from different anatomical regions, including the entorhinal cortex which is believed to be among the first regions to show signs of tau pathology. Our backward-elimination regression analyses (figure 1) suggested that the strongest models for predicting some of the subjective cognitive items (Everyday Memory, Everyday Language, Everyday Organization) were more likely amyloid-related whereas other items (Everyday Visuospatial, Everyday Planning) were more tau-related (together with age and sex). Conclusions Different pathological pathways may influence the manifestation of different subjective cognitive items. In vivo texture analysis techniques may be used as sensitive tools to explore these pathological pathways in association with the earliest signs of cognitive changes. [ABSTRACT FROM AUTHOR]