An Energy Deficit in MS Lesions, and in Tissue Before It Demyelinates

The lipids got the title of this paper, but the same dataset carries a second signal that reads as bioenergetics rather than membrane chemistry. Energy metabolites were among the most significantly changed modules in multiple sclerosis (MS) lesions, and they were one of only three to change in tissue that is not demyelinated and looks normal. Ladakis and colleagues measured 783 metabolites in brain tissue from the edge and core of chronic active and chronic inactive lesions, from periplaque white matter and from control white matter, across 17 samples from 5 people with secondary progressive MS and 8 samples from 6 controls. This post follows the energy and nitrogen side of what they found, which behaves differently from the lipid side and points at a different kind of problem.

Energy Metabolites Fall, and Nucleotides With Them
Grouping the panel into modules by correlation network analysis put 30 metabolites into an energy module, led by guanosine, pyridoxamine phosphate from vitamin B6 metabolism, and glutamate gamma-methyl ester. Against control white matter that module came in at a standardized mean difference of −0.31 (95% CI −0.48 to −0.15, q = 0.001), one of the largest shifts in the study. A separate nucleotide metabolism module of 13 metabolites, led by 5′-GMP, AMP and UMP, moved the same way at −0.28 (95% CI −0.5 to −0.07, q = 0.05). Both were reduced most profoundly in the lesion cores. One module that might have been expected to follow did not: the acylcarnitines, 40 metabolites led by palmitoleoylcarnitine and oleoylcarnitine and the standard readout of mitochondrial fatty acid oxidation, showed no significant difference at −0.12 (p = 0.41).

The Deficit Reaches Tissue That Is Not Demyelinated
Periplaque white matter sits beside the lesion, shows no previous or current demyelination by immunostaining, and resembles normal white matter in cell composition. Energy metabolites were reduced there as well, at a standardized mean difference of −0.29 (95% CI −0.46 to −0.11, q = 0.01), which is close to the figure inside the lesions themselves. The nucleotide module did not reach significance in periplaque tissue (q = 0.18), so the two signals do not travel the same distance from the lesion. The authors read the periplaque energy reduction as evidence of an existing pathology that could contribute to lesion expansion, which makes it a finding about what happens before a lesion forms rather than after.

The Nitrogen Pools Run the Other Way
While energy carriers and nucleotides fall, the nitrogen-containing pools rise. The dipeptide module, 81 metabolites led by glycylleucine, came in at a standardized mean difference of 0.19 (p = 0.04), and in the five-group comparison across tissue types dipeptides were significantly higher in lesion cores than in control white matter. The same direction appeared in the factor analysis, where dipeptides were among the metabolic pathways enriched in MS lesions (q = 1.5×10⁻⁶). The amino acid metabolism module, the largest in the study at 115 metabolites and led by serine, lysine and gamma-glutamylleucine, ran borderline upward at 0.17 (p = 0.03, q = 0.08). The paper reports the direction and where it is strongest without proposing a mechanism for the dipeptide rise.

What the Authors Put Forward as Causes
Three candidate contributors are offered for the energy and nucleotide reductions, and the authors mark them as speculation rather than findings. Inflammatory cells may have altered nucleotide metabolism. The increased numbers of apoptotic or necroptotic cells, especially in the core, could explain the decreased nucleotide and energy metabolites seen in MS lesions against control white matter. And the impaired mitochondrial function already documented in MS lesions could be a contributor. Each of these would produce the same measured result through a different route, and the design does not separate them.

Where This Side of Metabolism Meets Cell Composition
Pairing metabolites with single-nucleus cell counts from the same tissue sorted the panel into two opposing blocks, and the coenzyme A chemistry landed on the side that might not be expected. Pantothenate and coenzyme A metabolites, which sit at the entry to coenzyme A chemistry and therefore upstream of most energy production, grouped with endocannabinoids, long-chain fatty acids, monoacylglycerols and lysophospholipids as the set that correlated negatively with astrocyte and immune cell subpopulations and positively with oligodendrocytes and premyelinating oligodendrocyte precursor cells. The opposing block, sphingolipids, diacylglycerols and cell membrane lipid metabolites, tracked the inflammatory side, correlating positively with astrocytes and immune cells and negatively with the oligodendrocyte lineage. So the energy-related pool sits with the promyelinating and anti-inflammatory cell profile rather than with the inflammatory one.

What the Design Cannot Settle About Direction
Several of the stated limitations bear directly on this reading. Homogenizing brain tissue for metabolomic analysis limits the ability to distinguish metabolite concentrations inside cells from those outside, or to assign cellular origin, information the authors say could help validate some of their hypotheses. It is not known whether changes in the metabolomic profile of the different lesions are the main drivers of a subsequent inflammatory reaction that leads to demyelination, or rather the byproduct of demyelination and myelin breakdown. Correlating metabolite levels with cell populations does not imply causation, and definite conclusions cannot be drawn about the origin of these metabolites. The sample size is small and larger cohorts are required to validate the findings. Patients were untreated for MS within the three months before death and most were never treated with a disease-modifying therapy, but interactions between other drugs and the metabolomic profile cannot be completely excluded. The conclusion the authors settle on keeps lipids as the most dysregulated class while placing the energy result alongside them: lesion cores showed increased sphingolipids and decreased unsaturated fatty acids, endocannabinoids and energy metabolites compared with other MS tissues, which they read as marking the severe pathology in those areas.

Disclaimer: This blog post is based on the cited study and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.

Reference:
Ladakis, D. C., Pedrini, E., Reyes-Mantilla, M. I., Sanjayan, M., Smith, M. D., Fitzgerald, K. C., Pardo, C. A., Reich, D. S., Absinta, M., & Bhargava, P. (2024). Metabolomics of multiple sclerosis lesions demonstrates lipid changes linked to alterations in transcriptomics-based cellular profiles. Neurology: Neuroimmunology & Neuroinflammation, 11(3), e200219. https://doi.org/10.1212/NXI.0000000000200219