Author
Listed:
- Kaidi Kang
(Vanderbilt University Medical Center)
- Jakob Seidlitz
(The Children’s Hospital of Philadelphia
University of Pennsylvania
Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine)
- Richard A. I. Bethlehem
(University of Cambridge)
- Jiangmei Xiong
(Vanderbilt University Medical Center)
- Megan T. Jones
(Vanderbilt University Medical Center)
- Kahini Mehta
(University of Pennsylvania
Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
University of Pennsylvania)
- Arielle S. Keller
(University of Connecticut
University of Connecticut)
- Ran Tao
(Vanderbilt University Medical Center
Vanderbilt University Medical Center)
- Anita Randolph
(University of Minnesota Medical School
University of Minnesota)
- Bart Larsen
(University of Minnesota Medical School
University of Minnesota)
- Brenden Tervo-Clemmens
(University of Minnesota
University of Minnesota Medical School)
- Eric Feczko
(University of Minnesota Medical School
University of Minnesota)
- Oscar Miranda Dominguez
(University of Minnesota Medical School
University of Minnesota)
- Steven M. Nelson
(University of Minnesota Medical School
University of Minnesota)
- Jonathan Schildcrout
(Vanderbilt University Medical Center)
- Damien A. Fair
(University of Minnesota Medical School
University of Minnesota
University of Minnesota)
- Theodore D. Satterthwaite
(University of Pennsylvania
Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
University of Pennsylvania)
- Aaron Alexander-Bloch
(The Children’s Hospital of Philadelphia
University of Pennsylvania
Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine)
- Simon Vandekar
(Vanderbilt University Medical Center)
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 BWAS1–3. 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.
Suggested Citation
Kaidi Kang & Jakob Seidlitz & Richard A. I. Bethlehem & Jiangmei Xiong & Megan T. Jones & Kahini Mehta & Arielle S. Keller & Ran Tao & Anita Randolph & Bart Larsen & Brenden Tervo-Clemmens & Eric Fecz, 2024.
"Study design features increase replicability in brain-wide association studies,"
Nature, Nature, vol. 636(8043), pages 719-727, December.
Handle:
RePEc:nat:nature:v:636:y:2024:i:8043:d:10.1038_s41586-024-08260-9
DOI: 10.1038/s41586-024-08260-9
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:636:y:2024:i:8043:d:10.1038_s41586-024-08260-9. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.