Individualized brain biomarkers of late life depression: contributions to heterogeneity and resilience Project Summary/ Abstract Approximately 10% of people aged 60+ suffer from depression. Such late-life depression (LLD) is linked to broader adverse health outcomes such as stroke and dementia. Many brain correlates of LLD have been reported, but each explains only a small amount of interindividual variance in LLD symptoms, likely due to a many-to-one mechanistic mapping in which multiple neural mechanisms contribute to similar symptoms. Heterogeneity in clinical presentation arises from between-patient differences in acute severity, symptoms, chronicity, and age of onset. Few patients are matched in all clinical domains and therefore heterogeneity in conventional research samples is often unavoidable. Over and above clinical heterogeneity, additional risk/resilience factors may alter the experience of LLD at the individual level. Population data from the UK Biobank offers an unprecedented opportunity to fully disentangle clinical heterogeneity by curating clinically homogeneous subject groups. We will distinguish brain profiles, longitudinal changes, and resilience/vulnerability factors that are uniquely linked to LLD clinical domains of: acute severity, mood symptoms, somatic symptoms, chronicity, and late onset LLD. Sixty brain measures associated with LLD, including cortical thickness, gray matter volume, fractional anisotropy, white matter hyperintensities, and resting state connectivity will be used for all aims. In Aim 1, we will curate five homogeneous groups of UKB subjects with shared clinical presentation, focusing on: late onset LLD, acute severity, lifetime chronicity, mood symptoms, and somatic symptoms. Using normative models trained on never-depressed UKB subjects, we will distinguish normative brain deviation profiles associated with these different domains of clinical heterogeneity. In Aim 2, we will curate new groups of UKB subjects with shared longitudinal changes in acute severity, chronicity, mood symptoms, or somatic symptoms to test whether changes over time in brain measures are linked to longitudinal changes in clinical presentation. This aim therefore offers an independent validation of aim 1 and differentiates between state and trait markers of LLD. In Aim 3, we will test the hypothesis that cumulative environmental and psychological stressors alter the experience of LLD at the individual level. We will obtain individual-specific statistical estimates of resilience/vulnerability based on the difference between predicted and actual depression scores (‘brain depression gap’). The brain depression gap will be linked to stressors separately in each homogeneous subject group (same as aim 1) to determine factors that promote LLD resilience or vulnerability. Public health significance: this proposal is expected to move the field closer to a full understanding of LLD heterogeneity by combining theory-driven subject groups with data-driven population prediction models. Gaining a better understanding of LLD heterogeneity may inform improved strategies for treatment and prevention of LLD, which could positively influence broader health outcomes in older age.

Individualized brain biomarkers of late life depression: contributions to heterogeneity and resilience Project narrative About 1 in 10 people aged 60 and over experience depression, which puts them at higher risk for other health problems such as diabetes and stroke. In this proposal we will distinguish brain profiles linked to differences between people in terms of depression symptoms, severity, age of first depression, and number of depressed episodes they experienced. Furthermore, we will identify environmental and psychological stress factors that explain why some older people are more vulnerable or more resilient to depression than others.