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Study design features increase replicability in brain-wide association studies

Authors :
Kang, Kaidi
Seidlitz, Jakob
Bethlehem, Richard A. I.
Xiong, Jiangmei
Jones, Megan T.
Mehta, Kahini
Keller, Arielle S.
Tao, Ran
Randolph, Anita
Larsen, Bart
Tervo-Clemmens, Brenden
Feczko, Eric
Dominguez, Oscar Miranda
Nelson, Steven M.
Schildcrout, Jonathan
Fair, Damien A.
Satterthwaite, Theodore D.
Alexander-Bloch, Aaron
Vandekar, Simon
Source :
Nature; December 2024, Vol. 636 Issue: 8043 p719-727, 9p
Publication Year :
2024

Abstract

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain–behaviour associations1,2. Several recent studies have shown that thousands of study participants are required for good replicability of BWAS1, 2–3. 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.

Details

Language :
English
ISSN :
00280836 and 14764687
Volume :
636
Issue :
8043
Database :
Supplemental Index
Journal :
Nature
Publication Type :
Periodical
Accession number :
ejs68129698
Full Text :
https://doi.org/10.1038/s41586-024-08260-9