抑郁症高家族风险个体的默认模式网络连通性增加。
Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression.
作者信息
Posner Jonathan, Cha Jiook, Wang Zhishun, Talati Ardesheer, Warner Virginia, Gerber Andrew, Peterson Bradley S, Weissman Myrna
机构信息
Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA.
New York State Psychiatric Institute, New York, NY, USA.
出版信息
Neuropsychopharmacology. 2016 Jun;41(7):1759-67. doi: 10.1038/npp.2015.342. Epub 2015 Nov 23.
Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11-60 years, at high and low familial risk for depression. Study participants were part of a three-generation longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD.
对重度抑郁症(MDD)病理生理学的研究主要集中在已经受MDD影响的个体上。因此,这些研究在区分由MDD产生的影响与该疾病的先兆方面能力有限。通过研究具有高家族性MDD风险的个体,我们旨在识别出可能指示MDD发病风险的潜在生物标志物,这是推进预防和早期干预的关键一步。我们使用静息态功能连接MRI(rs-fcMRI)和扩散MRI(纤维束成像),对111名年龄在11至60岁之间、有高或低家族性抑郁风险的个体,检查了默认模式网络(DMN)内以及DMN与中央执行网络(CEN)之间的连接性。研究参与者是一项三代家族性抑郁症纵向队列研究的一部分。基于rs-fcMRI,高家族性抑郁风险个体与低家族性抑郁风险个体相比,DMN连接性增加,同时DMN-CEN负连接性降低。在排除有当前或终生抑郁病史的个体后,这些发现仍然显著。基于纤维束成像的扩散MRI测量结果支持了DMN-CEN负连接性降低的发现。路径分析表明,DMN-CEN负连接性降低介导了家族风险与冲动性神经心理学测量之间的关系。我们的研究结果表明,DMN和DMN-CEN连接性在高抑郁风险个体和低抑郁风险个体中存在差异,因此提示了识别有MDD发病风险个体的潜在生物标志物。