Spatial lipidomics reveals altered lipid profiles in TMEM63A mutant rats with hypomyelination
Abstract
Abstract Hypomyelinating leukodystrophies (HLDs) are genetic disorders characterized by deficient myelination. While TMEM63A variants are associated with HLD19, the specific lipid alterations in affected brain regions remain to be fully characterized. This study aimed to investigate the spatial distribution of lipid changes in a Tmem63a mutant rat model of hypomyelination. A homozygous Tmem63a c.500G > A p.(G167E) knock-in rat model ( Tmem63a G167E/G167E ) was established. Brain sections from Tmem63a G167E/G167E and Tmem63a WT rats ( n = 3/group) were analyzed using MALDI-MSI for lipid profiling across nine distinct brain regions. Myelin structure was characterized by transmission electron microscopy (TEM) and g-ratio quantification. Statistical analyses included Mann-Whitney U tests for g-ratio distributions and ROC analysis for feature screening. Out of 702 analyzed features, 124 were differentially expressed. Lipids constituted the most altered class (43 features), including 22 glycerophospholipid, 9 fatty acid, 5 sphingolipid, 5 sterol lipid, and 2 prenol lipid species. These alterations were predominantly observed in white matter-rich regions and gray-white matter junctions. TEM revealed thinner and less dense myelin sheaths in Tmem63a G167E/G167E rats, with a reduced proportion of optimal g-ratios. This study provides a comprehensive spatial lipidomic characterization in a Tmem63a mutant rat model, revealing significant lipid alterations associated with hypomyelination. These findings offer new insights into the pathology of hypomyelination and highlight specific lipid species for future investigation.
Article Details
Authors (12)
Junyu Wang
Liang Wang
Yu Zhang
Xiangya Hospital, Central South University Changsha China
Kai Gao
Jiangxi Xiao
Lin Nie
Jihang Luo
Shiqi Yang
State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics, School of Physics
Ye Wu
School of Medicine
Yuwu Jiang
Huifang Yan
Jingmin Wang