General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Joanna E. Moodie* (Corresponding Author), Sarah E. Harris, Mathew A. Harris, Colin R. Buchanan, Gail Davies, Adele Taylor, Paul Redmond, David C. M. Liewald, Maria del C. Valdés Hernández, Susan Shenkin, Tom C. Russ, Susana Muñoz Maniega, Michelle Luciano, Janie Corley, Aleks Stolicyn, Xueyi Shen, Douglas Steele, Gordon Waiter, Anca-Larisa Sandu, Mark E. BastinJoanna M. Wardlaw, Andrew McIntosh, Heather Whalley, Elliot M. Tucker-Drob, Ian J. Deary, Simon R. Cox* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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 (g; 3 cohorts, total meta-analytic N?=?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 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|?| range?=?0.18 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.
Original languageEnglish
Pages (from-to)e26641
Number of pages21
JournalHuman Brain Mapping
Volume45
Issue number4
Early online date15 Mar 2024
DOIs
Publication statusPublished - Mar 2024

Bibliographical note

We thank the participants of the three cohorts (UKB, Generation Scotland (STRADL) and LBC1936) for their participation and the research teams for their work in collecting, processing and giving access to these data for analysis. We are also thankful to the brain donors to the Allen Human Brain Atlas, BrainSpan Atlas and Human Brain Transcriptome Project, and to the people who collected and processed the data and made it openly available
For the purpose of open access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

Data Availability Statement

Supporting scripts for this manuscript are available here https://github.com/JoannaMoodie/moodie-geneexpression-cognition. All UKB data analysed herein (including IDPs) were provided under project reference 10279. A guide to access UKB data are available from http://www.ukbiobank.ac.uk/register-apply/. To access data from the STratifying Resilience and Depression Longitudinally (STRADL) study, which is part of the Generation Scotland study, see https://www.research.ed.ac.uk/en/datasets/stratifying-resilience-and-depression-longitudinally-stradl-a-dep, and to access the Lothian Birth Cohort data, see https://www.ed.ac.uk/lothian-birth-cohorts/data-access-collaboration.

Keywords

  • biological processes
  • cognition
  • gene expression
  • meta-analysis
  • neuroanatomy
  • neurostructural correlations

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