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Published on: July 19, 2019
Plasma lipidomic patterns associated with disease activity in chronic inflammatory demyelinating
Kristina Auf dem Brinke1, Lisa-Marie Borsch1, Christian Klose2
1Department of Neurology, University Medical Center Göttingen, Göttingen, Germany.
None:
Chronic inflammatory demyelinating polyneuropathy (CIDP) is an immune-mediated neuropathy that causes significant disability in patients. Although pathogenic mechanisms remain unclear, it is known that inflammation results in segmental demyelination. This study aims to investigate the plasma lipidomic profile of patients with CIDP to identify lipid patterns associated with disease activity. Using high-throughput shotgun lipidomics, we analyzed and compared the plasma lipidome of 30 patients with CIDP (mean age ± SD: 60.7 ± 12.2 years) with that of 30 individuals diagnosed with non-demyelinating neurological disorders (OND; mean age ± SD: 52.8 ± 10.3 years). Lipids were quantified in absolute [pmol] and relative concentrations [mol%], and their levels were correlated with CIDP disease activity and clinical disability scores (R-ODS, INCAT and MRC). To control for confounders such as age and weight, strongly correlated lipids were excluded. The analysis identified 669 molecular lipid species across 15 lipid classes, revealing a significant elevation in the diacylglycerol (DAG) class in CIDP patients. Furthermore, specific lipid subspecies, including triacylglycerol (TAG), DAG, and ether-linked phosphatidylcholine (PC O-), were significantly correlated with disease activity. A set of distinct lipid subspecies, including phosphatidylcholine (PC), lyso-phosphatidylcholine (LPC), phosphatidylinositol (PI), sphingomyelin (SM), and cholesterol ester (CE), showed strong associations with clinical disability scores. These findings suggest that CIDP is characterized by distinct lipidomic profiles modulated by disease activity. This dataset could pave the way for future studies in larger cohorts evaluating the potential of plasma lipid profiles to serve as biomarkers for disease activity and severity, aiding in informing clinical management.

