Moodie Joanna E, Harris Sarah E, Harris Mathew A, Buchanan Colin R, Davies Gail, Taylor Adele, Redmond Paul, Liewald David, Del C Valdés Hernández Maria, Shenkin Susan, Russ Tom C, Muñoz Maniega Susana, Luciano Michelle, Corley Janie, Stolicyn Aleks, Shen Xueyi, Steele Douglas, Waiter Gordon, Sandu-Giuraniuc Anca, Bastin Mark E, Wardlaw Joanna M, McIntosh Andrew, Whalley Heather, Tucker-Drob Elliot M, Deary Ian J, Cox Simon R
Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK.
Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.
bioRxiv. 2023 Sep 20:2023.03.16.532915. doi: 10.1101/2023.03.16.532915.
Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (; 3 cohorts, total meta-analytic = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of , beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
基因表达在整个大脑中存在差异。这种空间模式表示对特定脑功能的专门支持。然而,给定基因的表达在大脑中波动的方式可能受一般规则支配。量化基因间的空间共变模式将有助于深入了解支持例如复杂认知功能的脑区的分子特征。在这里,我们使用主成分分析来分离与认知的皮质底物相关的一般和独特的基因调控关联。我们发现,8235个基因的皮质表达谱在区域间的变化与两个主要主成分共变:基因本体分析表明,这些维度的特征是细胞信号传导/修饰和转录因子的下调和上调。我们在样本外和不同的数据处理选择中验证了这些模式。在一般认知功能中牵连更强的脑区(3个队列,总荟萃分析n = 39,519)往往在两个主要成分的下调和上调之间更加平衡(由区域成分得分表示)。然后,我们确定了另外41个基因,作为除两个主要成分的模式之外的认知的候选皮质空间相关基因(|β|范围 = 0.15至0.53)。这些基因中的许多先前已与临床神经退行性疾病和精神疾病或其他与健康相关的表型相关联。结果为基因表达的皮质组织及其与认知功能个体差异的关联提供了见解。