Zhu Jun-Ding, Chi I-Jou, Hsu Hui-Yun, Tsai Shih-Jen, Yang Albert C
Department of Occupational Therapy, https://ror.org/059ryjv25College of Medical Science and Technology, Chung Shan Medical University, Taichung, Taiwan.
Occupational Therapy Room, Chung Shan Medical University Hospital, Taichung, Taiwan.
Psychol Med. 2025 Aug 29;55:e253. doi: 10.1017/S0033291725101517.
Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic resonance imaging (MRI) to identify similarities and differences in abnormal aging between bipolar disorder (BD) and major depressive disorder (MDD) and pinpoint key brain regions of structural and functional change specific to each disorder.
Neuroimaging data from 340 healthy controls, 110 BD participants, and 68 MDD participants were included from the Taiwan Aging and Mental Illness cohort. We constructed 228 models using T1-weighted MRI, resting-state functional MRI, and diffusion tensor imaging data. Gaussian process regression was used to train models for estimating brain aging trajectories using structural and functional maps across various brain regions.
Our models demonstrated robust performance, revealing accelerated aging in 66 gray matter regions in BD and 67 in MDD, with 13 regions common to both disorders. The BD group showed accelerated aging in 17 regions on functional maps, whereas no such regions were found in MDD. Fractional anisotropy analysis identified 43 aging white matter tracts in BD and 39 in MDD, with 16 tracts common to both disorders. Importantly, there were also unique brain regions with accelerated aging specific to each disorder.
These findings highlight the potential of brain aging trajectories as biomarkers for BD and MDD, offering insights into distinct and overlapping neuroanatomical changes. Incorporating region-specific changes in brain structure and function over time could enhance the understanding and treatment of mental illness.
识别精神疾病中大脑功能障碍的关键区域对于精准诊断和治疗的发展至关重要。本研究旨在使用多模态磁共振成像（MRI）开发特定区域的脑老化轨迹预测模型，以识别双相情感障碍（BD）和重度抑郁症（MDD）之间异常老化的异同，并确定每种疾病特有的结构和功能变化的关键脑区。
纳入了来自台湾老龄化与精神疾病队列的340名健康对照者、110名BD参与者和68名MDD参与者的神经影像数据。我们使用T1加权MRI、静息态功能MRI和扩散张量成像数据构建了228个模型。使用高斯过程回归训练模型，以使用各个脑区的结构和功能图谱估计脑老化轨迹。
我们的模型表现出强大的性能，揭示了BD中66个灰质区域和MDD中67个灰质区域的加速老化，两种疾病共有13个区域。BD组在功能图谱上有17个区域加速老化，而MDD中未发现此类区域。分数各向异性分析确定了BD中43条老化的白质束和MDD中39条，两种疾病共有16条。重要的是，每种疾病也有特定的加速老化的独特脑区。
这些发现突出了脑老化轨迹作为BD和MDD生物标志物的潜力，为不同和重叠的神经解剖学变化提供了见解。纳入随时间变化的特定区域脑结构和功能变化可以增强对精神疾病的理解和治疗。
