Journal Article

Reproducible brain-wide association studies require thousands of individuals

Uriarte, Johnny, Fair, Damien A., Hatoum, Alexander S., Hendrickson, Timothy J., Thompson, Wesley K., Doyle, Olivia, Tervo-Clemmens, Brenden, Chen, Jianzhong, Garavan, Hugh, Newbold, Dillan J., Dosenbach, Nico U. F., Metoki, Athanasia, Kay, Benjamin P., Laumann, Timothy O., Donohue, Meghan Rose, Earl, Eric A., Zheng, Annie, Cordova, Michaela, Malone, Stephen M., Moore, Lucille A., Petersen, Steven E., Calabro, Finnegan J., Van, Andrew N., Luna, Beatriz, Perrone, Anders J., Lynch, Benjamin J., Foran, William, Miller, Ryland L., Kandala, Sridhar, Montez, David F., Feczko, Eric, Yeo, B. T. Thomas, Seider, Nicole A., Miranda-Dominguez, Oscar, Nichols, Thomas E., Marek, Scott, Conan, Gregory M., Tam, Angela, Barch, Deanna M., Wilgenbusch, James C., Graham, Alice M., Snider, Kathy, Chauvin, Roselyne J., Pengo, Thomas, Greene, Deanna J.

2022

Overview

Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions 1 – 3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping 4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain–behavioural phenotype associations 5 , 6 . Here we used three of the largest neuroimaging datasets currently available—with a total sample size of around 50,000 individuals—to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain–phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals. Combined data from three large studies, with a total sample size of around 50,000 individuals, indicate that many previous studies linking the brain to complex phenotypes have been statistically underpowered, producing inflated and irreproducible effects.

• Publisher: Nature Publishing Group UK,Nature Publishing Group
• Subject: 59/36 / 59/57 / 631/378/2649 / 631/477 / Age / Bivariate analysis / Brain / Brain mapping / Brain Mapping - methods / Brain research / Cognition / Cognition & reasoning / Cognitive ability / Datasets / Datasets as Topic / Functional magnetic resonance imaging / Genotype & phenotype / Humanities and Social Sciences / Humans / Magnetic resonance imaging / Magnetic Resonance Imaging - methods / Medical imaging / Mental health / multidisciplinary / Neural networks / Neuroimaging / Phenotype / Population / Psychopathology / Reproducibility / Reproducibility of Results / Sample size / Scanners / Science / Science (multidisciplinary) / Structure-function relationships