Study design features increase replicability in brain-wide association studies

• 成果类型: Article
• 署名作者: 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 F.; Vandekar, Simon
• 署名单位: Vanderbilt University; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; Pennsylvania Medicine; University of Cambridge; University of Pennsylvania; University of Connecticut; University of Connecticut; Vanderbilt University; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: Nature
• ISSN/ISSBN: 0028-6215
• DOI: 10.1038/s41586-024-08260-9
• 发表日期: 2024-12-19
• 关键词: inference; models

摘要

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 BWAS1-3. 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. Optimizing study design is critical for increasing standardized effect sizes and replicability, and the features that increase replicability in cross-sectional and longitudinal brain-wide association studies are explored.