Region-Specific Lipidomic Profiling in Brain and Spinal Cord Tissue of X-Linked Adrenoleukodystrophy Mice

Background/Purpose: X-linked adrenoleukodystrophy (X-ALD) is an inherited peroxisomal disorder caused by ABCD1 mutations, leading to accumulation of very long chain fatty acids (VLCFA) in blood and tissue. Clinical presentation includes cerebral ALD, adrenomyeloneuropathy and asymptomatic carriers. VLCFA accumulation and subsequent disproportion of other lipids has a multitude of consequences that are still elusive and might contribute significantly to the course of disease. This study aims to investigate lipid metabolism via lipidomic analysis in the X-ALD mouse model.

Methods: Brain and spinal cord tissue from male ABCD1^-/0 mice and wild-type (wt) litter mates at 3 and 12 months was objected to quantitative shotgun lipidomics. Mass spectrometry-based analysis was performed by Lipotype GmbH. KNIME Analytics Platform was used for data processing. R Statistical Software, MetaboAnalystR, lipidr, and mixOmics were used for statistical analyses. Lipid species and subspecies are annotated according to their molecular composition as described by LIPID-MAPS.

Results: Lipidomic analysis included over 700 lipid species and revealed region specific clustering for both age groups. Significant differences between X-ALD and wt tissues were found in a series of lipid classes, more profound in white matter opposed to gray matter. Differences were intensified in the older cohort.

Conclusion: Regions and age groups revealed distinct lipidomic profiles with increase of incorporated VLCFA over time. The largest discrepancy between X-ALD and wt was found in spinal cord tissue of 12-month-old mice, matching the X-ALD mouse model characteristics of an AMN phenotype. Findings provide insight into lipidomic profiles in X-ALD mouse brain and spinal cord tissue and show the impact of VLCFA accumulation on composition of complex lipids. Our results have implications for further lipidomic analysis in patient derived material and deliver insights about possible pathophysiological processes in X-ALD.

Publikationsverlauf

Artikel online veröffentlicht:
13. November 2023