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

晚年抑郁症的个体化大脑生物标志物：对异质性和复原力的贡献

基本信息

批准号：
10676995
负责人：
Janine Diane Bijsterbosch
金额：
$ 46.44万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-05 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10676995
关键词：
Acute Address Adopted Adult Age Age of Onset Anisotropy Biological Markers Blood Vessels Brain Chronic Clinical Data Data Set Dementia Depressed mood Diabetes Mellitus Diet Elderly Family Family history of Health Heterogeneity Hippocampus Individual Individual Differences Link Major Depressive Disorder Maps Matched Group Measures Mental Depression Mental Health Modeling Nature Outcome Patients Persons Physical Exercise Population Prevention Process Psychiatry Psychological Stress Public Health Recording of previous events Regression Analysis Reporting Research Rest Risk Sampling Scanning Severities Social support Stress Stroke Symptoms Testing Thick Time Training Trauma Validation White Matter Hyperintensity aged allostatic load biobank biological adaptation to stress clinical heterogeneity cognitive reserve comparison group demographics depressive symptoms environmental stressor experience follow-up geriatric depression gray matter high risk human old age (65+)improved individual patient innovation mood symptom multimodality neuromechanism novel pediatric trauma predictive modeling promote resilience psychological stressor resilience resilience factor stressor theories trait treatment strategy

项目摘要

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.

老年抑郁症的个体化脑生物标志物：对异质性和韧性的贡献项目摘要/摘要在60岁以上的人中，大约有10%患有抑郁症。这种晚年抑郁(LLD)与更广泛的不良健康后果，如中风和痴呆症。许多与LLD相关的大脑因素已经被报道过，但每一种都只解释了LLD症状的少量个体间差异，可能由于多对一机制映射，其中多个神经机制对类似的症状。临床表现的异质性源于患者之间急性严重程度的差异，症状、慢性病和发病年龄。很少有患者在所有临床领域都匹配，因此常规研究样本的异质性往往是不可避免的。高于临床异质性，额外的风险/复原力因素可能会在个体层面上改变LLD的体验。来自英国生物库的人口数据提供了一个前所未有的机会来完全理清临床通过管理临床上相同的受试者群体来实现异质性。我们将区分大脑的轮廓，与LLD临床领域唯一相关的纵向变化和恢复力/脆弱性因素特点：急性严重程度、情绪症状、躯体症状、慢性化和迟发性LLD。六十个大脑与LLD相关的测量，包括皮质厚度、灰质体积、各向异性分数、白质高强度和静息状态连通性将用于所有目标。在目标1中，我们将主持具有相同临床表现的五组相同的UKB受试者，重点是：迟发性LLD，急性严重性、终生慢性病、情绪症状和躯体症状。使用标准模型在从未抑郁的UKB受试者上进行训练，我们将区分相关的标准脑偏差轮廓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主题组在急性严重性、慢性病、情绪症状或躯体症状方面有共同的纵向变化检验脑部测量指标随时间的变化是否与临床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，并区分状态和LLD的性状标记。在目标3中，我们将检验以下假设：累积环境和心理压力源会在个体层面上改变LLD的体验。我们将获得特定于个人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(“大脑抑郁差距”)。大脑抑郁的差距将与压力因素单独相关。在每个同类受试组(与目标1相同)中，确定促进LLD复原力或脆弱性。公共卫生意义：这项提议有望使该领域更接近于充分了解将理论驱动的受试组与数据驱动的人口预测相结合的LLD异质性模特们。更好地了解LLD的异质性可能有助于改进治疗策略以及预防LLD，这可能会对老年人的更广泛的健康结果产生积极影响。