Objectives Late-life depression is associated with cognitive deficits and increased risk for cognitive decline. The purpose of the study was to determine whether clinical characteristics could serve as phenotypes informative of subsequent cognitive decline. We examined age of depression onset and antidepressant remission at 3 months (acute response) and 12 months (chronic response). Design A longitudinal study of late-life depression in an academic center. Participants 273 depressed and 164 never-depressed community dwelling elders aged 60 years or older were followed on average for over five years. Measurements Participants completed annual neuropsychological testing. Neuropsychological measures were converted to z-scores derived from the baseline performance of all participants. Cognitive domain scores at each time were then created by averaging z-scores across tests, grouped into domains of episodic memory, attention-working memory, verbal fluency, and executive function. Results Depressed participants exhibited poorer performance at baseline and greater subsequent decline in all domains. Early-onset depressed individuals exhibited a greater decline in all domains than the late-onset or nondepressed groups. For remission, remitters and nonremitters at both 3- and 12-months exhibited greater decline in episodic memory and attention-working memory than nondepressed subjects. 3-month remitters also exhibited a greater decline in verbal fluency and executive function, while 12-month nonremitters exhibited greater decline in executive function than other groups. Conclusions Consistent with past studies, depressed elders exhibit greater cognitive decline than nondepressed subjects, particularly individuals with early depression onset. This supports that repeated depressive episodes may contribute to decline. Clinical remission is not associated with less cognitive decline.

Background: Late Life Depression (LLD) has been associated with alterations in intrinsic functional networks, best characterized in the Default Mode Network (DMN), the Cognitive Control Network (CCN), and the Salience Network (SN). However these findings often derive from small samples and it is not well understood how network findings relate to clinical and cognitive symptomatology. Methods: We studied 100 older adults (n=79 with LLD, n=21 nondepressed) and collected resting state functional MRI, clinical measures of depression, and performance on cognitive tests. We selected canonical network regions for each intrinsic functional network (DMN, CCN, and SN) as seeds in seed-to-voxel analysis. We compared connectivity between depressed and nondepressed groups and correlated connectivity with depression severity among depressed subjects. We then investigated whether the observed connectivity findings were associated with greater severity of common neuropsychiatric symptoms or poorer cognitive performance. Results: LLD was characterized by decreased DMN connectivity to the frontal pole, a CCN region (Wald χ 2 =22.33, P<0.001). No significant group differences in connectivity were found for the CCN or SN. However, in the LLD group increased CCN connectivity was associated with increased depression severity (Wald χ 2 >20.14, p<0.001), greater anhedonia (Wald χ 2 =7.02,

Over half of the depressed elders who remitted experienced recurrence, mostly within 2 years. Multiple clinical and environmental measures predict recurrence risk. Work is needed to develop instruments that stratify risk.

Alzheimer’s disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes—aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)—are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau.

Background Depression in late life is a risk factor for cognitive decline. Depression is also associated with increased disability and social support deficits; these may precede conversion to dementia and inform risk. In this study, we examined if baseline or one-year change in disability and social support predicted later cognitive deterioration. Methods 299 cognitively intact depressed older adults were followed for an average of approximately seven years. Participants received antidepressant treatment according to a standardized algorithm. Neuropsychological testing and assessment of disability and social support were assessed annually. Cognitive diagnosis was reviewed annually at a consensus conference to determine if participants remained cognitively normal, or if they progressed to either dementia or cognitively impaired, no dementia (CIND). Results During study participation, 167 individuals remained cognitively normal (56%), 83 progressed to CIND (28%), and 49 progressed to dementia (16%). Greater baseline instrumental activities of daily living (IADL) deficits predicted subsequent conversion to a cognitive diagnosis (CIND or dementia). However, neither baseline measures nor one-year change in basic ADLs (BADLs) and social support predicted cognitive conversion. In post-hoc analyses, two IADL measures (managing finances, preparing meals) significantly increased the odds of cognitive conversion. Conclusions Greater IADL deficits predicted increased risk of cognitive conversion. Assessment of IADL deficits may provide clues about risk of later cognitive decline.