Babikian, T. | bioRxiv Science

bioRxiv2023

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individuals latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences. TeaserWe present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.

neuroscience↗

bioRxiv2020

White Matter Disruption in Pediatric Traumatic Brain Injury: Results from ENIGMA Pediatric msTBI

Annually, approximately 3 million children around the world experience traumatic brain injuries (TBIs), of which up to 20% are characterized as moderate to severe (msTBI) and/or have abnormal imaging findings. Affected children are vulnerable to long-term cognitive and behavioral dysfunction, as injury can disrupt or alter ongoing brain maturation. Post-injury outcomes are highly variable, and there is only limited understanding of how inter-individual differences in outcomes arise. Small sample sizes have also complicated efforts to better understand factors influencing the impact of TBI on the developing brain. White matter (WM) disruption is a critical aspect of TBI neuropathology and diffusion MRI (dMRI) is particularly sensitive to microstructural abnormalities. Here we present the results of a coordinated analysis of dMRI data across ten cohorts from three countries. We had three primary aims: (1) to characterize the nature and extent of WM disruption across key post-injury intervals (acute/subacute - within 2 months, post-acute - 2-6 months, chronic - 6+ months); (2) evaluate the impact of age and sex on WM in the context of injury; and (3) to examine associations between WM and neurobehavioral outcomes. Based on data from 507 children and adolescents (244 with complicated mild to severe TBI and 263 control children), we report widespread WM disruption across all post-injury intervals. As expected, injury severity was a significant contributor to the pattern and extent of WM degradation, but explained less variance in dMRI measures with increasing time since injury, supporting other research indicating that other factors contribute increasingly to outcomes over time. The corpus callosum appears to be particularly vulnerable to injury, an effect that persists years post-TBI. We also report sex differences in the effect of TBI on the uncinate fasciculus (UNC), a structure with a key role in emotion regulation. Females with a TBI had significantly lower fractional anisotropy (FA) in the UNC than those with no TBI, and this phenomenon was further associated with more frequent parent-reported behavioral problems as measured by the Child Behavior Checklist (CBCL). These effects were not detected in males. With future harmonization of imaging and neurocognitive data, more complex modeling of factors influencing outcomes will be possible and help to identify clinically-meaningful patient subtypes.

neuroscience↗