Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
Brain. 2020 Mar 1;143(3):1027-1038. doi: 10.1093/brain/awaa025.
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.
精神分裂症的神经生物学异质性理解不足,这混淆了当前的分析。我们使用旨在发现与疾病相关而非正常解剖变异模式的新型半监督机器学习方法,在多机构多民族 PHENOM(通过维度神经影像学评估精神分裂症)联盟的队列中研究了神经解剖亚型。对来自三个 PHENOM 研究地点的已确诊精神分裂症(n=307)和健康对照者(n=364)的结构磁共振成像和临床测量数据进行了分析。对灰质、白质和脑脊液的区域容积测量进行了分析,以确定精神分裂症的独特且可重复的神经解剖亚型。发现了两种截然不同的神经解剖亚型。亚型 1 表现为广泛的灰质体积减少,在丘脑、伏隔核、内侧颞叶、内侧前额叶/额叶和脑岛皮质中最为明显。亚型 2 则表现为基底节和内囊体积增加,而其他脑区体积正常。灰质体积与亚型 1 患者的疾病持续时间呈负相关(r=-0.201,P=0.016),而与亚型 2 患者无相关性(r=-0.045,P=0.652),这可能表明存在不同的潜在神经病理学过程。在年龄(t=-1.603,df=305,P=0.109)、性别(卡方=0.013,df=1,P=0.910)、疾病持续时间(t=-0.167,df=277,P=0.868)、抗精神病药物剂量(t=-0.439,df=210,P=0.521)、发病年龄(t=-1.355,df=277,P=0.177)、阳性症状(t=0.249,df=289,P=0.803)、阴性症状(t=0.151,df=289,P=0.879)或抗精神病药物类型(卡方=6.670,df=3,P=0.083)方面,两种亚型间无显著差异。与亚型 2 相比,亚型 1 的受教育程度更低(卡方=6.389,df=2,P=0.041)。总之,我们发现了两种独特且高度可重复的神经解剖亚型。亚型 1 表现为广泛的体积减少,与疾病持续时间相关,且认知功能障碍更为严重。亚型 2 的解剖结构正常且稳定,仅基底节和内囊体积较大,而这与抗精神病药物剂量无关。这些亚型挑战了脑容量减少是精神分裂症的普遍特征这一观点,并提示了不同的病因。它们可以促进临床试验的富集和分层,并实现精准诊断。