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Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI.

Alyssa H ZhuTalia M NirShayan JavidJulio E Villalon-ReinaAmanda L RodrigueLachlan T StrikeGreig I de ZubicarayKatie L McMahonMargaret J WrightSarah E MedlandJohn E BlangeroDavid C GlahnPeter V KochunovAsta K HåbergPaul M ThompsonNeda Jahanshad
Published in: bioRxiv : the preprint server for biology (2024)
Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan with a unique trajectory in the brain, complementing the process of gray matter development and degeneration. Normative modeling can establish lifespan reference curves for typical WM microstructural aging patterns by pooling data from many independent studies that span different age ranges. Here, we create such reference curves by harmonizing and pooling diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three ComBat harmonization methods to create normative curves for regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a widely used metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with neuroscientific knowledge regarding WM maturation peaks. Harmonized FA metrics were used to create lifespan reference curves, which were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Within-study associations were not affected by normative harmonization, ensuring that large-scale harmonized studies can be conducted across the lifespan, even from distinct age-restricted studies, without compromising individual study findings. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are available through our new Python package, eHarmonize (https://github.com/ahzhu/eharmonize).
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