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Lipidomics unveils lipid dyshomeostasis and low circulating plasmalogens as biomarkers in a monogenic mitochondrial disorder
Matthieu Ruiz, Alexanne Cuillerier, Caroline Daneault, Sonia Deschênes, Isabelle Robillard Frayne, Bertrand Bouchard, Anik Forest, Julie Thompson Legault, The LSFC Consortium, Frederic M. Vaz, John D. Rioux, Yan Burelle, Christine Des Rosiers
Matthieu Ruiz, Alexanne Cuillerier, Caroline Daneault, Sonia Deschênes, Isabelle Robillard Frayne, Bertrand Bouchard, Anik Forest, Julie Thompson Legault, The LSFC Consortium, Frederic M. Vaz, John D. Rioux, Yan Burelle, Christine Des Rosiers
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Research Article Cell biology Metabolism

Lipidomics unveils lipid dyshomeostasis and low circulating plasmalogens as biomarkers in a monogenic mitochondrial disorder

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Abstract

Mitochondrial dysfunction characterizes many rare and common age-associated diseases. The biochemical consequences, underlying clinical manifestations, and potential therapeutic targets, remain to be better understood. We tested the hypothesis that lipid dyshomeostasis in mitochondrial disorders goes beyond mitochondrial fatty acid β-oxidation, particularly in liver. This was achieved using comprehensive untargeted and targeted lipidomics in a case-control cohort of patients with Leigh syndrome French-Canadian variant (LSFC), a mitochondrial disease caused by mutations in LRPPRC, and in mice harboring liver-specific inactivation of Lrpprc (H-Lrpprc–/–). We discovered a plasma lipid signature discriminating LSFC patients from controls encompassing lower levels of plasmalogens and conjugated bile acids, which suggest perturbations in peroxisomal lipid metabolism. This premise was reinforced in H-Lrpprc–/– mice, which compared with littermates recapitulated a similar, albeit stronger peroxisomal metabolic signature in plasma and liver including elevated levels of very-long-chain acylcarnitines. These mice also presented higher transcript levels for hepatic markers of peroxisome proliferation in addition to lipid remodeling reminiscent of nonalcoholic fatty liver diseases. Our study underscores the value of lipidomics to unveil unexpected mechanisms underlying lipid dyshomeostasis ensuing from mitochondrial dysfunction herein implying peroxisomes and liver, which likely contribute to the pathophysiology of LSFC, but also other rare and common mitochondrial diseases.

Authors

Matthieu Ruiz, Alexanne Cuillerier, Caroline Daneault, Sonia Deschênes, Isabelle Robillard Frayne, Bertrand Bouchard, Anik Forest, Julie Thompson Legault, The LSFC Consortium, Frederic M. Vaz, John D. Rioux, Yan Burelle, Christine Des Rosiers

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Figure 3

Untargeted lipidomics in plasma from H-Lrpprc–/– mice identifies multiple lipid changes including lower levels of plasmalogens and docosahexaenoic acid (DHA).

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Untargeted lipidomics in plasma from H-Lrpprc–/– mice identifies multipl...
(A) Volcano plot of LC-QTOF–based untargeted lipidomics from plasma of fed H-Lrpprc–/– mice (n = 13) and their littermate controls (n = 8) depicting the 1,295 features obtained following MS data processing. Using a P-corr threshold of 0.05 (corresponding to an uncorrected P value of 0.01; horizontal red dotted line) and a FC >2 or <0.5 (vertical red dotted lines), 98 features significantly discriminated H-Lrpprc–/– mice vs. controls, of which 32 were increased (red dots) and 66 were decreased (green dots). See also Supplemental Table 2 for the list of lipids identified by MS/MS with FCs and P values (2-tailed unpaired Student’s t test and with Benjamini-Hochberg correction). (B–D) Dot plots of selected lipids significantly discriminating H-Lrpprc–/– mice from controls and identified by MS/MS using LC-QTOF. Each dot represents a log2-transformed signal intensity ratio for the indicated lipid (sub)classes with their acyl side chain(s): (B) 1 AC: AC18:0 and 15 glycerolipids (TGs); (C) 6 CEs; (D) 9 glycerophospholipids: 2 LPC, 5 PC, and 2 PE-plasmalogens (PE-O). The underscore symbol “_” beside the acyl side chain for TGs and glycerophospholipids refers to acyl chains for which the sn position remains to be ascertained. (E and F) Box plots of (E) plasmalogens and (F) DHA identified through manual alignment of this mouse plasma data set with human and mouse reference data sets for which the various plasmalogens had been previously identified by MS/MS. Statistics using 2-tailed unpaired Student’s t test: *P < 0.05; **P < 0.01, ***P < 0.001 before and $P < 0.05, $$P < 0.01 after Benjamini-Hochberg correction.

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