Subtypes and Trajectories of Depression in Older Adults

描述(由申请人提供)：老年人的抑郁症状与认知和身体功能低下、医学共病、卫生服务使用增加和生活满意度下降有关，并已被证明可以预测认知和功能下降、持续的抑郁症状和死亡率。随着老年人数量预计在未来几十年内增加，更多地了解晚年抑郁症状的亚型及其不同的轨迹可以帮助公共卫生和精神病学领域。这项拟议的研究的目标是确定老年人抑郁症状的亚型和轨迹。这项拟议的研究将利用在NIH支持的研究中收集的纵向数据的二次分析，这些研究1)来自具有代表性的社区样本的老年人和2)被诊断为严重抑郁症(MD)的老年患者。重要的是要确定抑郁症的哪些亚型会导致不良后果或持续存在，以及独特的轨迹是否与特定的亚型有关。简而言之，晚年抑郁症的亚型可以通过其症状集和随时间推移的病程来区分。这项研究的具体目的是：1)确定在接受MD治疗的老年人的临床样本和社区样本中观察到的晚年抑郁的类别或亚型，并确定与这些亚型相关的人口、临床、社会、心理和共病因素；2)确定哪些亚型的晚年抑郁与不良后果相关，即持续性抑郁症状、认知衰退、功能衰退和死亡率；3)确定社区居住的老年人和接受MD治疗的患者抑郁症状的轨迹，并确定与这些轨迹相关的人口、临床、社会、心理和共病因素；以及4)制定策略，进一步检查随着时间的推移症状认可的模式。为了达到这些目的，我们将使用潜在类别和潜在类别轨迹分析来区分抑郁症状的类别和症状组的轨迹。拟议的分析将利用杜克老年流行病学研究(EPESE)(使用耶鲁大学EPESE验证的发现)、高龄老年人资产和健康动态研究(AHEAD)的数据，以及杜克临床研究中心晚年抑郁症研究的两个纵向队列的数据。这项研究可以为精神病学领域做出独特的贡献，并导致识别老年人抑郁症的亚型，然后将其映射到遗传和生物学成分，并对抑郁症的预防和治疗进行干预。这项研究的发现也可能有助于识别晚年抑郁症的过渡性表型，这种表型反映了继发于遗传异常或与年龄相关的病理性脑变化的神经退行性变化。

DESCRIPTION (provided by applicant): Depressive symptoms in older adults have been associated with poor cognitive and physical functioning, medical comorbidity, increased health service use, and decreased life satisfaction, and have been shown to predict cognitive and functional decline, persistent depressive symptoms, and mortality. With the number of older adults expected to increase in the coming decades, a greater understanding of subtypes of late life depressive symptoms and their varying trajectories can help the field of public health as well as psychiatry. The goal of the proposed research is to identify subtypes and trajectories of depressive symptoms in older adults. The proposed research will utilize secondary analysis of longitudinal data collected in NIH supported studies of 1) elders from representative community samples and 2) older patients diagnosed with major depression (MD). It is important to identify which subtypes of depression lead to adverse outcomes or persist, and whether unique trajectories can be linked to specific subtypes. In short, subtypes of late life depression may be distinguished both by their set of symptoms and by their course over time. The specific aims of the proposed research are to: 1) Identify classes or subtypes of late life depression observed in clinical samples of older adults treated for MD and in community samples of older adults, and to identify demographic, clinical, social, psychological, and comorbidity factors associated with these subtypes; 2) Identify which subtypes of late life depression are associated with adverse outcomes, i.e., persistent depressive symptomatology, cognitive decline, functional decline, and mortality; 3) Identify trajectories of depressive symptoms in community dwelling older adults and in patients treated for MD, and identify demographic, clinical, social, psychological, and comorbidity factors associated with these trajectories; and 4) Develop strategies to further examine patterns of symptom endorsement over time. To address these aims, we will use latent class and latent class trajectory analyses in order to discern classes of depressive symptoms and trajectories of symptom groups. The proposed analysis will utilize data from the Duke Established Populations for Epidemiologic Studies of the Elderly (EPESE) (with findings validated using the Yale EPESE), the Study of Assets and Health Dynamics Among the Oldest Old (AHEAD), and two longitudinal cohorts from the Duke Clinical Research Center for the Study of Depression in Late Life. This research can provide a unique contribution to the field of psychiatry, and lead to identification of subtypes of depression in older adults which can then be mapped to genetic and biological components and to prevention of depression and treatment interventions. Findings from this study may also assist in the process of identifying a transitional phenotype of late life depression that reflects neurodegenerative changes secondary to genetic abnormalities or pathologic age-associated brain changes.