A0340
Title: Region-based functional genome-wide association detection for imaging response
Authors: Wenliang Pan - Academy of Mathematics and Systems Science, Chinese Academy of Sciences (China) [presenting]
Abstract: Advancements in data acquisition technology have fueled the growth of brain imaging genetic studies, which seek to uncover connections between brain images and genetic markers. Nevertheless, persistent challenges such as misalignment, region heterogeneity, and registration errors necessitate innovative solutions. The region-based functional genome-wide association detection (rfGWAS) method is introduced to address these issues. Focusing on small regions rather than individual voxels, rfGWAS streamlines computation while preserving the detection of meaningful associations. Theoretical analysis confirms that rfGWAS adheres to the independence-zero equivalence principle and reliably identifies significant region sets. Moreover, its test statistic effectively controls Type-I errors under null hypotheses and attains a probability of 1 for rejecting alternative hypotheses. Simulation results underscore the method's effectiveness, and its application to hippocampus surface data from the ADNI study demonstrates its potential. rfGWAS emerges as a promising solution for uncovering region-based associations in brain imaging studies, mitigating critical shortcomings of existing approaches.
