基于弥散张量成像的抑郁症生物学亚型研究

Investigation on biological subtypes of depression based on diffusion tensor imaging

背景 抑郁症病因复杂且临床表现异质性高,神经影像学研究为抑郁症生物学亚型的探索提供了新契机。目前,采用结构磁共振数据(MRI)进行抑郁症亚型划分的研究十分有限。目的 使用弥散张量成像(DTI)和机器学习方法探索抑郁症的生物学亚型。方法 纳入2017年9月-2021年8月于北京安定医院就诊的、符合《精神障碍诊断与统计手册(第4版)》(DSM-IV)抑郁症诊断标准的患者127例,同期在医院附近社区通过广告招募与患者性别和年龄相匹配的80例健康对照组。采集所有受试者的DTI图像、人口学信息和临床资料。使用纤维束追踪空间统计(TBSS)方法和约翰霍普金斯大学(JHU)脑白质概率图谱提取纤维束各向异性分数(FA),采用半监督学习方法划分抑郁症亚型,并比较不同亚型的患者组与健康对照组全脑白质纤维束FA值的差异。结果 抑郁症患者被划分为两种亚型,亚型I患者胼胝体、放射冠等广泛的纤维束FA值低于健康对照组(P<0.01,FDR校正),亚型II患者在小脑中脚、左侧小脑上脚和左侧大脑脚的FA值高于健康对照组(P<0.01,FDR校正)。亚型I和亚型II患者基线期HAMD-17总评分差异无统计学意义(P>0.05);治疗12周后,亚型Ⅰ患者组HAMD-17总评分低于亚型Ⅱ患者组(t=2.410,P<0.05)。结论 抑郁症患者存在两种具有不同白质损伤模式的生物学亚型,不同亚型的患者对药物的治疗反应存在差异。

Background Being complex and highly heterogeneous with regard to the etiology and clinical manifestations of depression,neuroimaging studies make a breakthrough for exploring the biological subtypes of depression,while the current data-driven approach for the identification of subtyping depression using structural magnetic resonance imaging(MRI)data is insufficient. Objective To explore the biological subtypes of depression using diffusion tensor imaging (DTI) and machine learning methods. Methods A total of 127 patients with depression who attended Beijing Anding Hospital from September 2017 to August 2021 and met the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) diagnostic criteria were included, and another 80 healthy individuals matched for gender and age were recruited through advertisements in surrounding communities during the same period. DTI findings, demographic characteristics and clinical data were collected from all participants. Tract-based spatial statistics (TBSS) and the Johns Hopkins University (JHU) white matter probability maps were used to extract fractional anisotropy (FA) values of white matter tracts. A semi-supervised machine learning technique was used to identify the subtypes, and the FA values for whole brain white matter of patients and controls were compared. Results Patients with depression were classified into two biological subtypes. FA values in multiple tracts including corpus callosum and corona radiata of subtype I patients were smaller than those of healthy controls (P<0. 01, FDR corrected), and FA values in middle cerebellar peduncle, left superior cerebellar peduncle and left cerebral peduncle of subtype II patients were larger than those of healthy controls (P<0. 01, FDR-corrected). Baseline Hamilton Depression Scale-17 item (HAMD-17) score yielded no statistical difference between subtype I and subtype II patients (P>0. 05), while subtype I patients scored lower on HAMD-17 than subtype II patients after 12 weeks of treatment (t=2. 410, P<0. 05). Conclusion Depression patients exhibit two biological subtypes with distinct patterns of white matter damage. Furthermore, the subtypes respond differently to the medication treatment.