Segal Ashlea, Smith Robert E, Chopra Sidhant, Oldham Stuart, Parkes Linden, Aquino Kevin, Kia Seyed Mostafa, Wolfers Thomas, Franke Barbara, Hoogman Martine, Beckmann Christian F, Westlye Lars T, Andreassen Ole A, Zalesky Andrew, Harrison Ben J, Davey Christopher G, Soriano-Mas Carles, Cardoner Narcís, Tiego Jeggan, Yücel Murat, Braganza Leah, Suo Chao, Berk Michael, Cotton Sue, Bellgrove Mark A, Marquand Andre F, Fornito Alex
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia.
Monash Biomedical Imaging, Monash University, Melbourne, Australia.
bioRxiv. 2024 Aug 6:2024.08.04.606523. doi: 10.1101/2024.08.04.606523.
Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.
We applied Warped Bayesian Linear Regression normative models to T1-weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter-regional connections, specific brain regions, and spatially extended brain networks.
The specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large-scale networks in up to 35% of individuals.
The prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.
精神疾病中神经生物学和临床特征的个体间变异性常被经典的组均值病例对照研究忽视。使用规范模型推断灰质体积个体特异性偏差的研究表明，组均值并不能代表大多数个体。对白质形态计量学（这对脑功能至关重要）中这种变异性的存在程度仍不清楚。
我们将扭曲贝叶斯线性回归规范模型应用于T1加权磁共振成像数据，并绘制了1294例（58%为男性）被诊断患有六种疾病（注意力缺陷多动障碍、自闭症、双相情感障碍、重度抑郁症、强迫症和精神分裂症）之一的患者以及在25个扫描点招募的1465名匹配对照（54%为男性）的个体特异性白质体积偏差的个体间变异性。我们开发了一个框架，以在多个空间尺度上表征偏差异质性，从单个体素，到区域间连接、特定脑区以及空间扩展的脑网络。
白质体积偏差的具体位置在参与者之间高度异质，在相同诊断的个体中，影响相同体素的个体少于8%。对于自闭症和精神分裂症，负偏差（即体积低于正常预期的区域）在高达35%的个体中聚集到共同的束、区域和大规模网络中。
白质体积偏差的患病率低于先前在灰质中观察到的情况，并且在考虑体素级空间分辨率时，这些偏差的具体位置高度异质。在精神分裂症和自闭症中，共同通路和网络内聚集的证据明显，但在其他疾病中则不明显。
