1. Study design features increase replicability in brain-wide association studies.
- Author
-
Kang K, Seidlitz J, Bethlehem RAI, Xiong J, Jones MT, Mehta K, Keller AS, Tao R, Randolph A, Larsen B, Tervo-Clemmens B, Feczko E, Dominguez OM, Nelson SM, Schildcrout J, Fair DA, Satterthwaite TD, Alexander-Bloch A, and Vandekar S
- Subjects
- Humans, Reproducibility of Results, Aged, Longitudinal Studies, Male, Female, Adolescent, Middle Aged, Cross-Sectional Studies, Alzheimer Disease diagnostic imaging, Cognition physiology, Organ Size, Genome-Wide Association Study, Adult, Neuroimaging, Aged, 80 and over, Age Factors, Brain diagnostic imaging, Magnetic Resonance Imaging, Research Design
- Abstract
Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behaviour associations
1,2 . Several recent studies have shown that thousands of study participants are required for good replicability of BWAS1-3 . Here we performed analyses and meta-analyses of a robust effect size index using 63 longitudinal and cross-sectional MRI studies from the Lifespan Brain Chart Consortium4 (77,695 total scans) to demonstrate that optimizing study design is critical for increasing standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger variability of the covariate and longitudinal studies have larger reported standardized effect size. Analysing age effects on global and regional brain measures from the UK Biobank and the Alzheimer's Disease Neuroimaging Initiative, we showed that modifying study design through sampling schemes improves standardized effect sizes and replicability. To ensure that our results are generalizable, we further evaluated the longitudinal sampling schemes on cognitive, psychopathology and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset. We demonstrated that commonly used longitudinal models, which assume equal between-subject and within-subject changes can, counterintuitively, reduce standardized effect sizes and replicability. Explicitly modelling the between-subject and within-subject effects avoids conflating them and enables optimizing the standardized effect sizes for each separately. Together, these results provide guidance for study designs that improve the replicability of BWAS., Competing Interests: Competing interests: J.Seidlitz and R.A.I.B. are directors and hold equity in Centile Bioscience. A.A.-B. holds equity in Centile Bioscience and received consulting income from Octave Bioscience in 2023. S.M.N. consults for Turing Medical, which commercializes FIRMM. This interest has been reviewed and managed by the University of Minnesota in accordance with its conflict of interest policies. All other authors declare no competing interests., (© 2024. The Author(s).)- Published
- 2024
- Full Text
- View/download PDF