grant

1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt)

Organization VANDERBILT UNIVERSITY MEDICAL CENTERLocation NASHVILLE, UNITED STATESPosted 15 Jan 2020Deadline 30 Nov 2026
NIHUS FederalResearch GrantFY2024AccelerationAffectAffectiveAutoregulationBehavioralCell Communication and SignalingCell SignalingClinicalCognitiveCognitive DisturbanceCognitive ImpairmentCognitive declineCognitive function abnormalDataDepressed moodDevelopmentDisease remissionDisturbance in cognitionEarly DiagnosisEcologic MonitoringEcological MonitoringEcological momentary assessmentElderlyElderly depressionEmotional DepressionEnvironmental MonitoringEquilibriumExhibitsFunctional MRIFunctional Magnetic Resonance ImagingFutureGoalsHistoryHomeostasisImpaired cognitionIndividualIntracellular Communication and SignalingLaboratoriesLongitudinal StudiesMeasuresMental DepressionMonitorMoodsNeurobiologyNoiseParticipantPerformancePhysiological HomeostasisPredictive FactorPreventionProcessRecording of previous eventsRecoveryRecurrenceRecurrentRegulationRemissionReportingResidualResidual stateRiskRisk MarkerSeveritiesSignal TransductionSignal Transduction SystemsSignalingSingle major depressionSingle major depressive episodeSiteSleepStressSubgroupSymptomsTestingTherapeutic InterventionTimeTranslatingactigraphactigraphyadult youthadvanced ageaged brainaging brainanti-depressant agentanti-depressant drugsanti-depressantsanti-depressive agentsbalancebalance functionbiological signal transductionclinical practicecognitive burdencognitive dysfunctioncognitive functioncognitive loadcognitive losscognitive performancedepresseddepressiondepression symptomdepressivedepressive symptomsdevelopmentalearly detectionenvironmental testingexecutive controlexecutive functionexperiencefMRIgeriatricgeriatric depressionhigh riskhistoriesintervention therapylate life depressionlong-term studylongitudinal outcome studieslongterm studymajor depressive episodemood symptomnegative affectnegative affectivitynetwork modelsneuralneural imagingneural networkneuro-imagingneurobiologicalneuroimagingneurological imagingolder adultolder adulthoodpredictive biomarkerspredictive markerpredictive molecular biomarkerprospectiverecurrent depressionrisk predictorrisk predictorsruminateruminationruminativesadnesssenior citizensingle episode Major Depressionsingle episode major depressive disorderstress reactivityyoung adultyoung adulthood
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Full Description

PROJECT SUMMARY
Repeated major depressive episodes are particularly problematic for older adults who have a more brittle

recovery than younger adults. Our data show that, despite antidepressant treatment, almost 60% of remitted

older adults experience recurrence within four years. Beyond simply relying on past history and reported

current stress, it is unclear what neurobiological factors are prospectively associated with recurrence risk,

when these factors trigger recurrence, and how they contribute to the high rates of cognitive impairment

observed in late-life depression (LLD). Using a model of network homeostasis, we posit that depressive

episodes are characterized by disrupted homeostasis in key neural networks involved in affect regulation and

cognitive function. Our preliminary data indicate that treatment non-remitters have residual functional network

alterations and high network instability (higher fluctuations in temporal signal-to-noise ratio). We hypothesize

that remitters with residual functional network alterations and greater instability remain at high risk of

recurrence with subsequent stress exposure. This disequilibrium contributes to subsyndromal symptoms

followed by full recurrence. These processes may also contribute to the higher rate of cognitive impairment and

decline observed in LLD. Our groups have reported elevated rates of cognitive decline in remitted LLD and an

association of recurrence with accelerated brain aging. We hypothesize that greater neural reactivity to stress

may accelerate brain aging and cognitive decline and that deficits/variability in performance on tasks

dependent on ECN may serve as markers of network alterations and signal increased recurrence risk. The

goals of this study are to A) identify neurobiological factors that predict recurrence risk, and B) examine how

cognitive performance changes are both influenced by these same neurobiological factors and also predict

recurrence risk. Our approach is to conduct a three-site, two-year longitudinal study of remitted LLD and

never-depressed elders. Every 8 months we will conduct laboratory assessments, including clinical, cognitive

and neuroimaging assessments and an in-scanner stress paradigm, along with burst ecological momentary

assessments (EMA) of mood variability, stress exposure, cognitive performance, and passive actigraphy. As

an exploratory goal, we will examine whether continuous ecological monitoring of mood and activity can

provide early detection of recurrence. A subgroup will be continuously monitored by EMA and actigraphy for

state shifts (persistent worsening) or variance shifts (increased variability) in symptom severity. When shifts in

mood symptoms are identified, they will engage in ad-hoc clinical and neuroimaging testing. Results from this

study may be translated in clinical practice through the future development of easy-to-use platforms (e.g. apps)

that signal to clinicians increased risk of impending recurrence, thus allowing for swift therapeutic intervention.

Grant Number: 5R01MH121620-05
NIH Institute/Center: NIH

Principal Investigator: Patricia Andrews

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