Charting brain growth and aging at high spatial precision.
Charting brain growth and aging at high spatial precision.
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DOI：
10.7554/elife.72904
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发表时间：
2022-02-01
期刊：
影响因子：
7.7
通讯作者：
Marquand AF
中科院分区：
文献类型：
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作者：
Rutherford S;Fraza C;Dinga R;Kia SM;Wolfers T;Zabihi M;Berthet P;Worker A;Verdi S;Andrews D;Han LK;Bayer JM;Dazzan P;McGuire P;Mocking RT;Schene A;Sripada C;Tso IF;Duval ER;Chang SE;Penninx BW;Heitzeg MM;Burt SA;Hyde LW;Amaral D;Wu Nordahl C;Andreasssen OA;Westlye LT;Zahn R;Ruhe HG;Beckmann C;Marquand AF
定义群体变异的参考模型以及研究个体偏差的能力对于理解个体间变异及其与疾病发作和进展的关系至关重要。在这项工作中，我们收集了来自82个站点（N= 58，836;年龄2-100）的神经影像学数据的参考队列，并使用规范建模来表征皮质厚度和皮质下体积的寿命轨迹。模型根据手动质量检查的子集（N= 24，354）进行验证，我们提供了一个接口，用于传输到新的数据源。我们通过将模型应用于跨诊断精神病样本（N=1985）来展示临床价值，表明它们可用于量化多种疾病的变异性，同时还可以改进病例对照推断。这些模型将随着更多样本和成像模式的可用而得到增强。这提供了一个通用的参考平台来绑定来自不同研究的结果，并最终为个性化临床决策铺平道路。
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2–100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.