Two distinc neuroanatomica subtypes of schizophrenia revealed using machine learning
Two distinc neuroanatomica subtypes of schizophrenia revealed using machine learning
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DOI：
10.1093/brain/awaa025
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发表时间：
2020-03-01
期刊：
影响因子：
14.5
通讯作者：
Davatzikos, Christos
中科院分区：
文献类型：
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作者：
Chand, Ganesh B.;Dwyer, Dominic B.;Davatzikos, Christos
精神分裂症的神经生物学异质性知之甚少，并与目前的分析相混淆。我们在一个多机构、多种族的队列中研究了神经解剖亚型，使用了新的半监督机器学习方法，旨在发现与疾病相关的模式，而不是正常的解剖变异。对已确诊的精神分裂症患者(307例)和健康对照组(364例)的结构MRI和临床测量进行了分析。灰质、白质和脑脊液的局部体积测量被用来识别精神分裂症独特的和可重复的神经解剖亚型。发现了两种不同的神经解剖学亚型。亚型1灰质体积普遍降低，以丘脑、伏隔核、内侧颞叶、内侧前额叶/额叶和岛叶皮质最为明显。亚型2表现为基底节和内囊体积增大，其余脑体积正常。灰质体积与病程呈负相关(r=-0.201，P=0.016)，而与病程无关(r=-0.045，P=0.652)，提示可能存在不同的神经病理过程。年龄(t=-1.603，df=305，P=0.109)、性别(卡方=0.013，df=1，P=0.910)、病程(t=-0.167，df=277，P=0.868)、抗精神病药物用量(t=-0.439，df=210，P=0.521)、起病年龄(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)或抗精神病剂型(卡方=6.670，df=3，P=0.083)。亚型1的文化程度低于亚型2(卡方=6.389，df=2，P<0.041)。总而言之，我们发现了两种截然不同且高度重复性的神经解剖学亚型。亚型1表现出与病程相关的广泛性音量减少，以及较差的病前功能。亚型2具有正常和稳定的解剖结构，除了较大的基底节和内囊，不能用抗精神病药物剂量解释。这些亚型挑战了脑容量丧失是精神分裂症的一般特征的概念，并提示了不同的病因。它们可以促进临床试验丰富和分层以及精确诊断的策略。
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.