Individualized brain biomarkers of late life depression: contributions to heterogeneity and resilience

晚年抑郁症的个体化脑生物标志物：对异质性和弹性的贡献 项目总结/摘要 大约10%的60岁以上的人患有抑郁症。这种晚年抑郁症（LLD）与 更广泛的不良健康后果，如中风和痴呆症。LLD的许多脑相关因素 已经报道，但每一个都只能解释LLD症状中的少量个体间差异，可能 由于多对一的机制映射，其中多个神经机制有助于类似的 症状临床表现的异质性源于患者间急性严重程度的差异， 症状、慢性和发病年龄。很少有患者在所有临床领域都匹配，因此 传统研究样本的不均匀性往往是不可避免的。超过临床 异质性，额外的风险/弹性因素可能会改变LLD在个人层面的经验。 英国生物库的人口数据为充分理清临床问题提供了前所未有的机会 通过管理临床同质的受试者组来实现异质性。我们将区分大脑的轮廓， 纵向变化，以及与LLD临床领域唯一相关的弹性/脆弱性因素 急性严重程度、情绪症状、躯体症状、慢性和迟发性LLD。六十脑 与LLD相关的测量，包括皮质厚度、灰质体积、各向异性分数， 白色物质高强度和静息状态连接将用于所有目标。在目标1中，我们将 5个具有相同临床表现的同质UKB受试者组，重点关注：晚发型LLD， 急性严重性、终生慢性性、情绪症状和躯体症状。使用规范模型 通过对从未抑郁过的UKB受试者进行培训，我们将区分与抑郁症相关的规范性大脑偏差特征， 这些不同领域的临床异质性。在目标2中，我们将策划新的UKB科目组 在急性严重程度、慢性、情绪症状或躯体症状方面有共同的纵向变化， 测试大脑测量值随时间的变化是否与临床指标的纵向变化有关。 演示文稿.因此，该目标提供了对目标1的独立验证，并区分了各州 和LLD的特征标记。在目标3中，我们将检验累积环境和 心理压力改变LLD在个人层面的经验。我们将获得个人特定的 根据预测和实际之间的差异对复原力/脆弱性进行统计估计 抑郁评分（“脑抑郁间隙”）。大脑抑郁的差距将分别与压力源联系起来 在每个同质受试者组中（与目标1相同），以确定促进LLD恢复力的因素， 易损性. 公共卫生意义：该提案有望使该领域更接近于全面了解 通过结合理论驱动的受试者群体和数据驱动的人群预测，研究LLD异质性 模型更好地了解LLD异质性可能有助于改善治疗策略 和预防LLD，这可能对老年人的更广泛健康结果产生积极影响。

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.