Delineating the role of monocarboxylate transporter 8 (MCT8) in the context of neuroinflammation–mediated oligodendrocytopathy

Delineating the role of monocarboxylate transporter 8 (MCT8) in the context of neuroinflammation–mediated oligodendrocytopathy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Delineating the role of monocarboxylate transporter 8 (MCT8) in the context of neuroinflammation–mediated oligodendrocytopathy Steven Petratos, Rahimeh Emamnejad, Paschalis Theotokis, Jae Young Lee, and 23 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8429369/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Oligodendrocytes (OLs) myelinate central nervous system (CNS) axons and provide metabolic support to maintain axonal integrity. Thyroid hormone (TH) is a mitogen for oligodendroglial precursor cells (OPCs) maturation into myelinating OLs. Cellular uptake of TH is mediated by monocarboxylate transporter 8 (MCT8; encoded by slc16a2 ), and its dysfunction results in intracellular triiodothyronine (T3) deprivation, leading to hypomyelination and myelin degeneration during neuroinflammation. We showed that MCT8 expression is maintained in OPCs residing within the sub–ventricular zone (SVZ) throughout CNS development, suggesting a role during OL development. We identified MCT8 deficiency during neuroinflammatory and cuprizone demyelination models, as well as in secondary progressive multiple sclerosis (SPMS). These conditions were associated with dysregulated AKT–mTOR–PANK2 signaling and abrogated Co Enzyme A and lipid synthesis pathways in the CNS during myelin degeneration. Hence, neuroprotection during SPMS maybe achieved by overcoming MCT8 deficiencies in OLs. Biological sciences/Neuroscience/Diseases of the nervous system/Multiple sclerosis Health sciences/Neurology/Neurological disorders/Multiple sclerosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction The loss of oligodendrocytes (OLs) or specific developmental defects in oligodendrogenesis results in denudement of axons, potentiating the brain’s vulnerability to further neurodegeneration. 1 Central nervous system (CNS) neurons and their axons receive the structural and metabolic support of OLs, 1 and failure of this support results in severe neurological disorders, as manifest in multiple sclerosis (MS) or during inherited forms of leukoencephalopathy. 2 In adult CNS disorders, oligodendrogenesis and repair can be limited by the availability and stalled maturation of oligodendroglial progenitor cells (OPCs). 3 In MS, this is partially due to a lack of trophic support, including thyroid hormone (TH) within demyelinated lesions. 4 Furthermore, the accumulation of “disease–associated” oligodendroglia (DOLs) is associated with cognitive decline in tauopathy, neurodegeneration and autoimmune–mediated neuroinflammation. 5 Providing trophic support to OLs may limit inflammatory damage, including the transition to DOLs, to combat neurodegeneration. The neuroactive TH, tri-iodothyronine (T 3 ), supports OL differentiation in vitro and in vivo . It plays a central role in OL development and myelination in vivo by regulating OPC replication, and the expression of genes required for myelin production and OL survival. 6 – 8 Although THs stimulate OL differentiation, 9–11 the mechanism of TH transport into OLs is not well known. THs are shuttled across the plasma membrane by transporters including the monocarboxylate transporter (MCT)8, 12 MCT10, 13 organic anion transporting polypeptide 1C1 (OATP1C1), 14 and SLC17A4. 15 MCT8 encoded by the SLC16A2 gene, facilitates the uptake of T3 across the blood brain barrier (BBB). 16 Mutations in the SLC16A2 gene locus cause a severe congenital X–linked psychomotor dysfunction, known as Allan–Herndon–Dudley syndrome (AHDS). 17 , 18 This disease is associated with increased serum levels of free–T 3 , developmentally delayed/incomplete myelination, and persistent neurological deficits, which suggests that MCT8 is required for normal OL development and myelination. 19 – 21 The MCT10, encoded by the gene slc16a10 , transports TH in addition to performing its common T–type amino acid transporter function. 22 MCT10 shows overlapping expression with MCT8 particularly in mature white matter tracts, suggesting a functional role in differentiated OLs. 23 We recently demonstrated that TH transporters are expressed by human oligodendroglia and support their differentiation and myelination in vitro. 24 When MCT8 expression was downregulated in human OPCs (hOPCs), OPC survival and OL maturation was impaired. 24 However, the TH analog, 3,5-diiodothyropropionic acid (DITPA), preserved hOPCs, promoted oligodendroglial maturation, and increased their myelination of co-cultured retinal ganglion neurons. 24 In this study we report that MCT8 expression is essential for normal mouse brain and spinal cord development but is reduced during inflammatory demyelination, coinciding with OL loss and impaired TH–dependent non-genomic signaling. Using archival human brain white matter samples, we identified that impaired TH transport into the CNS and its altered metabolism, alongside dysfunctional aspects of the AKT–mTOR–PANK2 signaling pathway, may represent common features of neurodegeneration. Metabolomic profiling further revealed disruption of the pantothenic acid and coenzyme A (CoA) biosynthesis pathway. This dysregulated pathway stems from disruptions in the AKT–mTOR–PANK2 pathway. In parallel, Fourier transform infrared imaging (FTIR) and photothermal optical infrared spectroscopy (OPTIR) imaging demonstrated pronounced lipid degradation, reflecting the downstream effects of these molecular and metabolic disturbances. Together, these findings reveal that metabolic disruptions in the pantothenic acid and CoA biosynthesis pathway in progressive MS can be therapeutically targeted by overcoming the dysregulated TH–dependent signalling within white matter of progressive MS lesions. Results To characterize the MS tissue utilized in this study, post–mortem CNS specimens from SPMS were evaluated by histopathology and immunofluorescence to confirm the presence of chronic active demyelinating plaques exhibiting ongoing OL dystrophy (supplementary Fig. 1). Detailed histopathological classification of lesions is provided in the Supplementary Information. Chronic active plaques demonstrating pronounced axonopathy were subsequently selected for analysis of OL–specific MCT8 and MCT10 expression, as well as for metabolic and proteomic profiling. Abrogated MCT8 and MCT10 expression levels are evident in OLs throughout neurodegenerative lesions. To initially assess if there exists TH resistance in neuropathological lesions with active degeneration, we performed a qualitative immunofluorescence analysis of MCT8 and MCT10 expression comparing acquired neuroinflammation–mediated demyelination, as seen in MS, control (NNDC), and other primary neurodegenerative diseases, including Alzheimer’s disease (AD), Fronto–temporal dementia (FTD), Huntington’s disease (HD) (Fig. 1 A–G; supplementary Fig. 1S). MCT8 and MCT10 were detected in mature OLs (CC1⁺ or Olig2⁺ cells), but their expression was markedly reduced within degenerative lesions, particularly in chronic active demyelinating white matter of SPMS. This reduction indicates impaired TH transporter function consistent with TH resistance in mature OLs resident in chronic active MS lesions. Further immunofluorescence analysis assessing downstream OLs survival signaling revealed decreased co–localization of phosphorylated AKT (p–AKT) with MCT8 in glial cells including astrocytes and OLs within SPMS white matter chronic active lesions compared with AD and non–neurological disease controls (supplementary Fig. 1T). FTIR and OPTIR imaging identified pronounced lipid degradation within chronic active lesion in SPMS. FTIR imaging revealed disrupted lipid spectral profiles within chronic active demyelinating lesions of SPMS tissue, characterized by decreased CH₂:CH₃, CH 2 : lipid, Olefin: lipid ratios and increased OH: lipid ratios (Fig. 2 ). The decrease in CH 2 :CH 3 and CH 2 : lipid ratios reflects acyl chain shortening and structural lipid degradation, consistent with lipid peroxidation and oxidative stress–induced myelin damage. 25 In contrast, the increase of OH: lipid ratio suggests accumulation of lipid peroxidation end products, 26 while the decreased olefin: lipid ratio further indicates oxidative damage to double bonds, leading to loss of unsaturation. 27 Together, these findings are consistent with ongoing myelin degeneration linked to impaired mitochondrial acetyl–CoA metabolism [for review, see 28 – 30 ]. The Aromatic: lipid ratio may suggest that the neurotransmitter tryptophan is a significant contributor to the changes observed in the lesion (Fig. 2 ). Complementary OPTIR measurements confirmed these lipid alterations, showing reduced CH stretching related to lipids (3000–2800 cm⁻¹) in lesion regions compared with adjacent non–lesioned white matter, while protein–associated Amide I and II bands (1710–1500 cm⁻¹) remained comparable (Fig. 2 ). The complementary capabilities of FTIR and OPTIR imaging—restricted spectral range in FTIR (4000–2600 cm⁻¹, due to the use of glass slides as the sample substrate) versus extended coverage by OPTIR (3000–800 cm⁻¹)—together support the presence of lesion–specific lipid degradation within SPMS white matter. Human post–mortem tissue demonstrates dysregulated metabolic pathways in chronic active and degenerative demyelinating lesions. We first conducted an untargeted metabolomic analysis to profile metabolites in archival chronic active white matter lesions from people with MS (pwMS), and compared these with frontal white matter tissue from individuals with AD, FTD, or NNDC as the control (CTR) tissue group. After performing multiple student's t–tests on the metabolite databases we identified a compilation of 89 significant changes occurring in SPMS, 67 in AD, and 62 in FTD, when compared to CTR frontal white matter. We generated volcano plots based on significant t–test results, using a threshold of 1·5–fold change (FC), which revealed that 30 metabolites were increased, while 28 showed decreased levels in MS relative to CTR white matter (supplementary Fig. 2A, supplementary table 3). Following metabolic pathway analysis of dysregulated metabolites (adjusted p 1·5) identified between MS and CTR, we tabulated the alterations that affect 20 metabolic pathways (supplementary table 4). Among these, four pathways were significantly enriched, including Pantothenate and Coenzyme A (CoA) biosynthesis (KEGG pathway ID: hsa00770; P = 0·001), Histidine metabolism (hsa00340, p = 0·01), beta–Alanine metabolism (hsa00410, P = 0·02), Pentose and glucuronate interconversions (hsa00040, P = 0·02), as detailed in supplementary Fig. 2F and supplementary table 4. Within the Pantothenate and CoA biosynthesis, the major dysregulated pathway, three key metabolites were altered: pantothenic acid, pantetheine 4'–phosphate, and dephospho–CoA were significantly downregulated (adjusted p = 0·004, 0·03, 0·003; FC = 0·56, 0·47, 0·51, respectively; Fig. 3 B). Similarly, beta–Alanine metabolism exhibited notable perturbations, characterized by decreased levels of beta–alanyl–L–lysine and carnosine (adjusted p = 0·002, 0·03 and FC = 0·48, 0·61, respectively), this pathway is also involved in the biosynthesis of pantothenate and CoA biosynthesis (Fig. 3 D). In histidine metabolism, an increase in 1–methylhistidine (adjusted p = 0·004, FC = 2·6) and decrease in carnosine levels contributed to pathway dysregulation (Fig. 3 D). In addition, the upregulated levels of glucuronate and ribulose (adjusted p = 0·02 and 0·02, FC = 1·89 and 1·98, respectively) were involved in dysregulation of pentose and glucuronate interconversions (Fig. 3 E). Although some pathways did not reach statistical significance, the dysregulated metabolites involved are biologically meaningful and suggest functionally relevant metabolic alterations. Several of these metabolites were associated with antioxidant defence mechanisms. Specifically, gamma–glutamylcysteine, alpha–aminobutyric acid, and glucuronate (adjusted p = 0·03, 0·004, 0·02, and FC = 0·57, 1·76, and 1·89 respectively) are implicated in glutathione metabolism (hsa00480), cysteine and methionine metabolism (hsa00270), and ascorbate and aldarate metabolism (hsa00053), respectively — pathways that play central roles in maintaining redox homeostasis and neutralizing ROS (Fig. 3 E-F). These metabolites are aligned with a downregulation in carnosine levels in MS, 31 consistent with its consumption during oxidative or carbonyl stress and a decreased availability of this non–enzymatic antioxidant dipeptide. 32 Similarly, β–alanyl–L–lysine was decreased, suggesting increased utilization of β–alanine–containing dipeptides (carnosine) with potential antioxidant and buffering roles. These reductions indicate a loss of small–molecule dipeptide defences, which may shift the burden of redox protection toward the glutathione system and other enzymatic antioxidant pathways. Elevated levels of kynurenine (adjusted p = 0·004, FC = 2·7) indicate potential activation of tryptophan metabolism, which has been linked to neurotoxicity and immunomodulation (Fig. 3 G). Uric acid and UMP were altered (adjusted p = 0·04, 0·01; FC = 2·43, 0·58), with participation in nucleotide metabolism (Fig. 3 G). Moreover, 2–hydroxybutyric acid—a metabolite associated with the propanoate metabolism pathway — was markedly elevated (adjusted p = 0·004; FC = 3·37; Fig. 3 G), underscoring links between altered CoA biosynthesis and energy metabolism. Finally, altered levels of glyceric acid and ethanolamine phosphate (adjusted p = 0·002, and 0·01, FC = 1·61, and 0·64 respectively) mapped to lipid–related pathways, including glycerolipid metabolism, glycerophospholipid metabolism, sphingolipid metabolism, and GPI–anchored lipid biosynthesis (Fig. 3 G). Broader analysis revealed additional dysregulated metabolites across various amino acid metabolic routes. Subsequent comparisons between MS and AD revealed a total of 50 significantly altered metabolites, with 33 upregulated and 10 downregulated (volcano plot analysis, adjusted p 1·5; supplementary Fig. 2D, supplementary table 5). These dysregulated metabolites were mapped to ten metabolic pathways, with statistically significance observed in three: D–amino acid metabolism ( p = 0·05), nicotinate and nicotinamide metabolism ( p = 0·05), and histidine metabolism ( p = 0·05) (supplementary Fig. 2I, supplementary table 6). The primary metabolites contributing to these pathway perturbations were serine (adjusted p = 0·01, FC = 1·6), nicotinic acid (p = 0·01, FC = 1·6), and 1–methylhistidine (adjusted p = 0·03, FC = 0·57), respectively (Fig. 4 ). Additionally, several metabolites exhibited biologically meaningful roles within key metabolic pathways, although they did not reach statistical significance for pathway–level disruption. These included (6R)-6-(L-Erythro-1,2-Dihydroxypropyl)-5,6,7,8-tetrahydro-4a-hydroxypterin (adjusted p = 0·02, FC = 2·5) involved in folate biosynthesis, and guanosine diphosphate (adjusted p = 0·02, FC = 0·53) within purine metabolism (Fig. 4 ). Finally, comparison of frontal white matter tissues between MS and FTD revealed only seven significantly altered metabolites, of which two were upregulated and two downregulated based on volcano plot analysis (supplementary Fig. 2E, supplementary table 7). The metabolomic analysis for comparison between AD and CTR, or FTD and CTR are provided in Supplementary Information. These data suggest that SPMS chronic active MS lesions display dysregulated metabolic pathways that are depicted in the white matter of brain tissue from primary neurodegenerative disorders. Human post–mortem tissue demonstrates dysregulated TH–dependent signaling in chronic active demyelinating lesions. To investigate whether dysregulated metabolites seen in MS are related to changes in TH–dependent signaling, post–mortem human white matter lysates from four different neurological diseases (AD, FTD, HD, and SPMS with chronic active lesions) and NNDC as control, were assessed for the expression of TH transporters, TH–converting enzymes, and components of the non–genomic TH signalling pathway (AKT–mTOR–PANK2) using western blotting and immunoprecipitation (IP) (Fig. 5 A-D). Analysis of 10% input human tissue lysates revealed a marked downregulation of the TH transporters MCT8, MCT10, and OATP1C1 in SPMS frontal white matter tissue compared with NNDC (Fig. 5 A–B; p < 0·01, p < 0·0001, and p < 0·001, respectively), indicating profoundly altered TH transport during progressive demyelination. Although MCT8 expression in FTD exceeded that seen in AD and HD, MCT10 expression was significantly reduced relative to NNDC (Fig. 5 A–B; p < 0·001), demonstrating TH–resistance, since ~ 25% of circulating thyroxine (T4) binds to this plasma membrane transporter for its intracellular uptake. 33 Furthermore, we demonstrated that both deiodinase–2 (DIO2) and deiodinase–3 (DIO3) expression significantly reduced in SPMS white matter (Fig. 5 A-B, p < 0·01 and 0·0001, respectively), while remaining unchanged in AD compared with NNDC (Fig. 5 A-B). Collectively, these data may suggest that the deficiencies identified in the plasma membrane TH transporters along with both T4 to T3 and T3 to rT3/T2 converting enzymes clearly contribute to a chronic impairment of TH signalling in SPMS demyelinating and neurodegenerative lesions. Further analysis of non–genomic TH signalling in frontal white matter lesions from SPMS tissue revealed a significant reduction in phosphorylated AKT (p–AKT at T308 and S473) levels and in the p–AKT/AKT ratio compared with NNDC (Fig. 5 C–D, p = 0·05), as shown by pulling down with an anti–total AKT antibody. IP pulling down with anti–total mTOR also demonstrated decreased level of phosphorylated mTOR in SPMS samples. Western blot analysis of 10% input confirmed decreased levels of both total and phosphorylated–forms of AKT along with total mTOR, in MS tissue compared with NNDC (Fig. 5 C-D, p < 0·01, 0·01 and 0·05, respectively). However, these non–genomic mechanisms downstream of TH–dependent signaling required further investigation in cell culture and animal models. From human frontal lobe white matter lysates, the levels of key mitochondrial enzymes downstream of AKT–mTOR signalling, fundamental for the conversion of pantothenic acid to acetyl CoA for lipid synthesis were assessed. Consistent with metabolomic analysis that showed a significant dysregulated pantothenate metabolism in SPMS (supplementary Fig. 2A and F). PANK2 was markedly reduced in SPMS compared to NNDC, with substantive reductions in both mature (mPANK2) and precursor (pPANK2) forms (Fig. 5 C–D; p < 0·05 for both). These data may identify the mechanisms by which the phosphorylated–proteins are dysregulated downstream of TH–dependent nongenomic signalling during SPMS that may lead to profound deficits in myelin lipid synthesis pathways during mature OL dystrophy. The expression of MCT8 in OLs during CNS development in naïve C57BL/6 mice As in vitro MCT8 expression was identified in oligodendroglial lineage cells derived from hESCs, 24 we investigated the in vivo expression of MCT8 during postnatal C57BL/6 mouse brain development. MCT8 expression was prominently localized to developing OLs defined on PDGFRα + OPCs during brain and white matter development were clearly identified within the SVZ and CC tracts (supplementary Fig. 3A-C). Expression peaked at P21 in the developing CC, highlighting a critical role for MCT8 in OPC-mediated myelinogenesis, as previously reported. 24 Hence re–establishing this signalling role would be of great importance in limiting myelin degeneration. For details, see the Supplementary Information. Expression of the TH–transporters, MCT8 and MCT10, in mature OLs present in white matter tracts of the naïve PLP – YFP transgenic adult mouse spinal cord. To understand the TH–dependent mechanisms operative in mature OLs across CNS white matter prior to neuroinflammatory challenge, we initially utilized the Plp–CreER T2 ::ROSA26–stop–EYFP transgenic mouse model for fate mapping of mature OLs. The quantitative analysis of MCT8 or MCT10 expression in mature OLs (PLP + /CC1 + ) (supplementary Fig. 3D-P), demonstrated the presence of both transporters within the white matter of the spinal cord. Comparable numbers of MCT8⁺ and MCT10⁺ OLs were detected in white matter regions, whereas MCT10⁺ OLs were markedly reduced in the grey matter (supplementary Fig. 3L and P), where myelinated fibers are sparse. These findings suggest potential differential T₃ versus T₄ transport dynamics between spinal white and grey matter, warranting further investigation. For details, see the Supplementary Information. The optic nerve and lumbo–sacral spinal cord of EAE–induced C57BL/6 mice and the corpus callosum of cuprizone–induced mice demonstrate significantly reduced TH–transporter expression with profound OL dystrophy. To assess the MCT8–dependent signalling mechanisms during neuroinflammatory processes within the CNS, we analysed lumbo–sacral spinal cord and optic nerve tissues from EAE–induced adult C57BL/6 female mice at pre–onset, onset and peak disease (up to 30 days post–induction). At peak disease, pronounced white matter inflammation coincided with reduced amplitude and conduction velocity of dorsal column compound action potentials (Fig. 6 A). Expression of full-length MCT8 declined approximately five-fold compared with naïve controls ( p ≤ 0·001; Fig. 6 C). This may demonstrate the persistent MCT8 degradation throughout EAE progression, leading to reduced transporter expression and impaired TH dependent signalling. MCT10 expression was similarly reduced, by about two-fold ( p < 0·05; Fig. 6 C). OL loss and dystrophic morphology were evident at the peak of neuroinflammation of EAE, predominantly within inflammatory regions of the lumbo–sacral spinal cord and optic nerve white matter, coinciding with reduced MCT8 expression (Fig. 6 D-E; supplementary Fig. 4C-D). A comparable loss of MCT8–deficient SOX10⁺ mature OLs was also identified in the cuprizone model of demyelination (supplementary Fig. 5). Downregulation of MCT8 in mature CC1⁺ OLs was associated with cleaved caspase–3 expression, indicating apoptosis as a key contributor to OL loss (supplementary Fig. 4H-J) possibly resulting from deprivation of trophic support by T3 due to impaired MCT8 function. In the optic nerve, axonal integrity was evaluated by rAAV2–GFP transduction of retinal ganglion cells (~ 40% of temporal retina) before EAE induction in C57Bl/6 mice. At disease peak, dystrophic GFP⁺ axons were frequently located near apoptotic (caspase–3⁺) mature OLs (CC1⁺), representing 27·7% of CC1⁺ OLs near inflammatory lesions (supplementary Fig. 4F-I). The optic nerve showed greater susceptibility to neuroinflammatory damage than the spinal cord, likely reflecting its compact architecture and dense myelination. Refer to Supplementary Information for more detail. Concomitant with MCT8 loss, deiodinase expression declined at all disease stages. DIO2 levels decreased three-fold from naïve to clinical scores 1–2 ( p < 0·05) and score 3 ( p < 0·01), while DIO3 expression decreased two–fold at scores 1–2 ( p < 0·01) and ten–fold at score 3 ( p < 0·0001), with an additional five–fold reduction between clinical score of 1–2 and 3 diseases ( p < 0·05; Fig. 6 C). This highlights a progressive decline in DIO2 and DIO3 expression correlating with the severity of EAE. DIO3 expression was particularly diminished in dystrophic PLP⁺ mature OLs (Fig. 6 F-H). Collectively, these data support the hypothesis that neuroinflammatory demyelination is associated with a progressive decline in MCT8, DIO2, and DIO3 expression, leading to impaired TH transport and metabolism in mature OLs. This likely contributes to localized TH resistance, disrupting TH–dependent metabolic and homeostatic processes critical for OL survival and axonal maintenance during active neuroinflammation. Modulation of MCT8 expression in spinal cord and peripheral immune cell populations following EAE induction in wildtype C57BL/6 mice. To determine MCT8 expression modulation during neuroinflammatory demyelination, we examined its distribution in peripheral blood cells from naïve and EAE–induced wild–type C57BL/6 mice at a clinical score of 3. Flow cytometric analysis revealed a marked upregulation of MCT8 in cells of the monocytic lineage, suggesting an enhanced metabolic demand associated with the inflammatory state (supplementary Fig. 6B). Within the spinal cord white matter of EAE mice at peak disease, MCT8 expression was broadly increased in inflammatory regions but showed minimal overlap with immune cells, including CD3e + T cells, B220 + B cells and CD206 + macrophages. These findings suggest that MCT8 upregulation during neuroinflammation occurs mainly in non-lymphoid, non-macrophage populations within the CNS (supplementary Fig. 6C-F). Detailed information is provided in the Supplementary Information. TH signaling is altered in the spinal cord of EAE–induced C57BL/6 mice. Given the decreased MCT8 expression in OLs at peak neuroinflammation, suggesting impaired T3 transport and trophic deprivation contributing to OL loss, we next examined non–genomic TH signaling in spinal cord lysates across disease stages [figure 7 A-B]. Lumbo–sacral spinal cords from EAE–induced adult female C57BL/6 mice were analysed at pre–onset, onset, and peak disease (day 30 post–induction; Fig. 7 A-B). Western blot analysis revealed progressive decreases in AKT, mTOR and PANK2 protein levels at peak disease ( p < 0·001, 0·01, and 0·0001 respectively; Fig. 7 B). Co-immunoprecipitation (co–IP) using total AKT demonstrated dynamic AKT–mTOR interactions, with binding at clinical scores 0–1, with dissociation evident from score 2 onwards. Notably, bound mTOR levels transiently increased at score 1, coinciding with reduced p–AKT relative to score 0 (Fig. 7 A). Reciprocal co–IP using mTOR confirmed these findings, showing maximal AKT–mTOR interaction at onset of neurological deficits (clinical score 1; Fig. 7 A), highlighting a stage–specific dysregulation of TH–dependent non–genomic signalling, potentially mediated via αvβ3 integrin complexes, during neuroinflammation (Fig. 7 C). Collectively, these findings indicate that neuroinflammation disrupts the AKT–mTOR–PANK2 signalling axis and its multimeric complex, correlating with disease severity and myelin damage. We next evaluated whether MCT8⁺ OLs at peak EAE were protected from apoptosis through p-AKT signalling, as suggested by our previous in vitro findings. 24 In the spinal cord, 50·4% of PLP⁺/MCT8⁺ OLs co-expressed p–AKT in normal appearing white matter (NAWM), compared with 45·1% in periplaque white matter (PPWM), showing a 32·8% PLP + OL reduction (Fig. 7 D-E). These data suggest that OLs adjacent to inflammatory lesions are particularly vulnerable to reduced MCT8 expression and diminished p–AKT, implicating p–AKT signalling as a compensatory pro–survival mechanism in mature OLs under neuroinflammatory stress. Reduced MCT8 expression and AKT signaling drive oligodendrocyte loss during peak–stage EAE in PLP–YFP transgenic mice despite MCT8–positive OPC mobilization. To investigate how reduced MCT8 expression in mature OLs contributes to cell death, as previously observed in human OL cultures, 24 cleaved caspase–3 was quantified in PLP–YFP + mice at peak EAE (supplementary Fig. 7A–C). Among MCT8⁺ cells within and around inflammatory lesions, only ~ 18.3% co–expressed cleaved caspase–3 (supplementary Fig. 7B). In PPWM, ~ 17% of mature PLP–YFP + OLs exhibited cleaved caspase–3–dependent apoptosis (supplementary Fig. 7C), suggesting partial resistance to apoptosis in MCT8 + OLs. However, OL loss remained significant (~ 23%; Fig. 8D–E), indicating additional death pathways, possibly ferroptosis but need appropriate validation. We next investigated whether MCT8–deficient OL apoptosis near inflammatory lesions promotes expansion of MCT8⁺ OPCs, a lineage previously shown to activate in the optic nerve. MCT8⁺/PDGFRα⁺ OPCs were increased in inflamed optic nerves compared with non–lesion and showed elevated p–AKT expression (supplementary Fig. 8A-B). Similar findings were observed in the spinal cord, where PDGFRα⁺/P-AKT⁺ cells were sparse in the PPWM (~ 95 cells/mm²), but 66.9% expressed MCT8 (supplementary Fig. 8C). To further characterize remyelinating populations, BCAS1⁺ pro-myelinating OPCs, enriched near MS lesions and mice that lack this gene display hypomyelination, were examined. These cells were more abundant (~ 638 cells/mm²) in PPWM, with 34.4% co–expressing MCT8 (supplementary Fig. 8D-F). Among BCAS1⁺/p–AKT⁺ cells, 58.4% were MCT8⁺, suggesting a link between MCT8 expression and p–AKT signalling in viable OPCs near lesions. As mTOR signalling upstream of AKT is known to regulate OPC-mediated remyelination, we examined p-mTOR in BCAS1⁺ OPCs. Approximately 52.1% were p-mTOR⁺ (supplementary Fig. 8G-H), suggesting additional upstream regulators of AKT activation in BCAS1⁺/p-AKT⁺ OPCs (41.3%) within PPWM (supplementary Fig. 8F). Whether these p-mTOR⁺ OPCs are directly regulated by MCT8-dependent signalling during neuroinflammation remains to be clarified. A detailed quantitative analysis of OL apoptosis, OPC activation, and associated MCT8–AKT–mTOR signalling is provided in the Supplementary Information. Discussion MS is a debilitating neurological disorder of the CNS that involves axonal demyelination and neurodegeneration. Over the past two decades, several disease modifying therapies (DMTs) have been developed for the treatment of the multiphasic representations of MS. 34 Despite the major advancements, most drugs are only suitable for the treatment of the relapsing–remitting multiple sclerosis phase but not its progressive form. 35 Therefore, there is an immediate unmet medical need for patients transitioning to the progressive form of disease. 35 Prior to addressing this, we need to establish the pathogenic mechanisms that are driving CNS injury during active neuroinflammation, both in its acute and chronic active (or indeed inactive) phases of the disease. Therefore, this study addresses key mechanistic aspects of OL damage and demyelination during active neuroinflammation. In this study, we identified in vivo MCT8 expression in OLs during normal mouse brain development, co–expressed with oligodendroglial markers. Persistent MCT8 expression in precursor cells within and around the SVZ throughout development suggests a key role in regulating metabolism, as intracellular T3 is essential for OPC proliferation, myelin synthesis, and mature OL survival. 8 This is consistent with the proposed function for transportation of TH across the BBB but we report for the first time, utilizing the PLP–YFP + transgenic model the importance of TH metabolism in spinal cord of OLs. We demonstrated oligodendroglial expression of MCT8 and MCT10 is reduced during neuroinflammatory–driven demyelination. Both transporters were downregulated during peak–chronic stages of EAE which may be related to oligodendrogliopathy, as tissue destruction occurs leading to progressive neurologic symptoms and myelin degeneration. This aligns with previous reports of cellular hypothyroidism during EAE, which disrupts TH–dependent processes essential for OPC maturation into myelinating OLs. 36 Moreover, our recent in vitro study has demonstrated the specific MCT8–deficiency in human OPCs promoted their cell death. 24 This may indicate that OL apoptosis results from downregulated MCT8 expression causing an acute deprivation in TH–dependent metabolic support for these cells. However, co–expression of these cells with cleaved caspase–3 indicated that only a subset of mature MCT8 + OLs undergo apoptosis. Whether this reflects secondary pro–inflammatory mechanisms causing MCT8 deprivation through OLs loss in the white matter requires further elucidation. This also calls into question if the remaining subset of detectable OLs which do not show the expression of MCT8 may be undergoing alternative cell death pathways, such as necrosis (uncontrolled cell death) and ferroptosis (oxidative stress–induced cell death). 37 , 38 Further work is required to resolve some of these fundamental scientific questions and understand how TH support can indeed protect the CNS OLs from cell death in the context of neuroinflammation. To abrogate oligodendroglial cell death, we need to be able to regulate downstream p–AKT and mTOR signaling. 39 , 40 Indeed, these pathways are activated during OPC differentiation and thereby support OL survival and CNS repair in demyelinating conditions. Many extracellular signals that regulate OL survival converge on AKT phosphorylation. 41 Experimental inhibition of AKT induces OL apoptosis even in the presence of mitogens such as neuregulin, whereas constitutively active AKT enhances CNS myelination in transgenic models. 41 Our data suggest that MCT8 + mature OLs may be protected from apoptotic cell death during neuroinflammation through the downstream activation of p–AKT. These data suggest that MCT8–mediated TH transport is critical for OL survival, likely through non–genomic p–AKT activation. Beyond maintaining mature OL viability and myelin integrity, p-AKT signaling may drive remyelination by promoting OPC differentiation from anatomical areas in the CNS where they can be expanded from. We demonstrated here that the 58% of p–AKT + OPCs co–expressed MCT8 in the PPWM spinal cord. This may suggest that in the presence of MCT8, TH is able to enter OPCs (PDGFRα + and BCAS1 + ) and stimulate the downstream signalling of p–AKT via genomic and non–genomic signalling pathways for cell growth and survival. 42 Importantly, the upregulation mTOR signalling upstream of the PI3K–AKT pathway is critical for OPC survival and proliferation, as its loss reduces myelin protein synthesis and causes hypomyelination. 43 The AKT and mTOR pathway has also been shown to promote the differentiation of OPCs in vitro and in vivo . 40 Our findings further suggest that mTOR may act in concert with p-AKT, but further experiments may allow us to establish direct mechanistic evidence that identify MCT8 as a key driver of remyelination. Human chronic active demyelinating lesions of frontal lobe white matter from pwMS, demonstrated metabolic and proteomic alterations. The key TH transporters and metabolic enzymes—MCT8, MCT10, OATP1C1, DIO2, and DIO3—as well as components of the AKT–mTOR–PANK2 signalling pathway, were dysregulated in MS frontal white matter lysates. These proteomic alterations were supported by untargeted metabolomic analysis, which revealed disruption of the pantothenic acid and CoA biosynthesis pathway in progressive MS—a mitochondrial pathway previously shown to be downstream of AKT–mTOR–PANK2. 44 Complementary FTIR and OPTIR imaging confirmed pronounced lipid degradation within lesions, evidenced by reduced CH stretching associated with lipids, while protein-related Amide I and II bands remained largely unchanged. These FTIR and OPTIR features are consistent with lipid peroxidation and oxidative stress–induced myelin damage, supporting ongoing myelin degeneration linked to impaired mitochondrial acetyl-CoA metabolism. By understanding the potential molecular mechanisms of MCT8 deficiency during different neuroinflammatory challenges within the CNS, we were able to incorporate these findings in a large–scale preclinical study that has utilized MCT8–independent TH analogues to rescue OL dystrophy during progressive neuroinflammation and to limit neurological decline. Such interventions may hold promise to limit further degeneration and enhance remyelination in conditions such as progressive MS. Materials and Methods Human post-mortem tissue Human research was approved by the Monash University Human Research Ethics Committee (HREC) (#34474 and #CF13/1646-2013000831) and met the requirements of the National Statement on Ethical Conduct in Human Research (NHMRC). Post–mortem CNS tissue (frontal lobe white matter), provided by the Victorian Brain Bank Network (VBBN), included tissue from: NNDC donors (n = 10); other neurological disease control donors, including AD (n = 6), FTD (n = 16), HD (n = 4), and MS donors with chronic–active lesions (n = 40). Participant de–identified details of sex, age, weight, post–mortem interval (PMI) and disease type were provided with the archival donor tissue (See supplementary table 1 ). Post–mortem interval did not exceed 73 hours h. All samples were fixed with 10% formalin and blocked using optical cutting temperature (OCT) –mounting medium and transferred to a Leica cryo–microtome at − 18°C, to generate 20 µm cryosections that were thaw–mounted onto Superfrost Plus slides (Thermo Scientific, J1800AMNZ) and stored at -80°C for immunofluorescence and histochemical staining. Frozen frontal lobe white matter blocks (400–500 mg) from the same lesion and patient were stored at -80°C in preparation for western blot and metabolomic studies. In addition to the frontal white matter sections, tissue samples from the subventricular zone, ventral and dorsolateral spinal cord, cerebral cortex, periventricular white matter and cerebellum of individuals with SPMS (n = 8) were provided by VBBN for histochemical and immunofluorescence staining. Full protocols for histochemical and immunofluorescence staining are provided in the Supplementary Information. Human tissue: Fourier transform infrared imaging (FTIR) and photothermal optical infrared (OPTIR) spectroscopy To preserve tissue morphology, 20 µm cryosections of frontal white matter from MS cases (n = 10) were freeze–dried on glass slides for infrared spectroscopic analysis. FTIR chemical imaging was performed at the SISSI-Bio beamline (Elettra Sincrotrone Trieste, Italy) 45 using a Bruker Hyperion II microscope coupled to an INVENIO-II interferometer with a 128×128-pixel focal plane array (FPA) detector. Spectra were acquired using 8 scans per pixel, a spectral resolution of 8 cm⁻¹, and 4×4 binning with a 15× Cassegrain objective and condenser. Mosaics of multiple tiles were recorded to capture the entire tissue section. Optical photothermal infrared (O-PTIR) measurements were obtained using a mid-IR quantum cascade laser (QCL) operating at 100 kHz repetition rate as the pump beam, and a continuous-wave 532 nm laser as the visible probe. Spectra were collected from selected tissue arrays previously characterized by FTIR imaging to directly compare demyelinating and non-lesioned regions. The infrared power was maintained at 5%, using a 40× reflective Cassegrain objective (0·78 NA, Pike Technologies) in co-propagation mode. The probe laser power was set at 1% for the avalanche photodiode detector. The spectral range covered 3027–2795 cm⁻¹ and 1800–791 cm⁻¹ with a resolution of 2 cm⁻¹. The system was enclosed and purged with nitrogen to minimize atmospheric water vapor interference. Spectra were acquired over 100 × 100 µm fields, with a section thickness of 4 µm for each region. Spectral data were processed and analysed using Quasar ( https://quasar.codes).2 ,3 For FTIR imaging, the following integration bands were used: CH₂ (2900–2950 cm⁻¹), CH₃ (2948–2980 cm⁻¹), lipid (2800–3000 cm⁻¹), olefin (3000–3027 cm⁻¹), aromatic (3030–3100 cm⁻¹), and OH (3030–3365 cm⁻¹). Principal component analysis (PCA) was performed on second-derivative spectra (Savitzky–Golay 9-point smoothing, 3rd-order polynomial). K–means clustering with six clusters and random initialization was applied to identify spatially distinct biochemical domains within tissue sections. Metabolomics Untargeted metabolomic profiling was performed on ~ 30 mg cryo–pulverised human frontal white matter, as previously described with minor modifications. 46 , 47 Frozen human frontal white matter (from NNDC, AD, FTD, and MS) were cryo-pulverized (approximately 30 mg powder). The samples cryo-pulverised using a pre-chilled mortar and pestle on a bed of dry ice. Approximately 40 mg of pulverised tissue (range 30–56 mg) shipped on dry ice to the Monash Proteomics and Metabolomics Platform (MPMP), where samples were stored at − 80°C until preparation and liquid chromatography–mass spectrometry (LC–MS) analysis. Upon inspection, tissue was further ground in Eppendorf tubes using a liquid nitrogen–cooled mini mortar (Sigma, Australia; PN Z756377-1EA) to improve homogenisation. Extraction was performed using 20 µL of ice–cold extraction solvent (2:6:1 chloroform/methanol/water with 2 µM CCPT [CHAPS, CAPS, PIPES and TRIS] as internal standards) per mg of tissue. The mixture was vortexed (3 × 10 sec), sonicated (10 min, ice–water bath), and centrifuged (10 min, 4°C) to remove debris. Supernatants were stored at -80°C. For pooled biological quality control (pbQC), 10 µL of reconstituted lysates from each sample were combined. LC–MS was performed using a Dionex RSLC3000 UHPLC system coupled to a Q–Exactive Plus Orbitrap mass spectrometer (Thermo Scientific, Australia). Samples were analysed by hydrophilic interaction liquid chromatography (HILIC) following a previously described protocol. 48 Chromatographic separation was achieved using a ZIC–p (HILIC) column (5 µm, 150 × 4·6 mm, 25°C; Merck Millipore, Australia) with a gradient elution of 20 mM ammonium carbonate (solvent A) and acetonitrile (solvent B) under the following conditions (time–%B): 0 min, 80%; 15 min, 50%; 18 min, 5%; 21 min, 5%; 24 min, 80%; 32 min, 80%. The flow rate was maintained at 300 µL/min. Samples were maintained at 6°C in the autosampler, and 10 µL was injected per run. Mass spectrometry was conducted at 70 000 resolutions in positive (+ 4 kV) and negative (− 3·5 kV) electrospray ionisation modes (capillary temperature 300°C; sheath gas flow rate 50; auxiliary gas flow rate 20; probe temperature 120°C To support accurate metabolite identification, a library of approximately 400 authentic standards was analysed before sample acquisition, and retention times were recorded for each compound. This library also informed a retention time prediction model used to assign putative identities to metabolites not represented in the reference set. 49 Raw LC–MS spectra were processed using IDEOM, with msConvert (ProteoWizard) for mzXML conversion 50 and XCMS for peak detection and generation of. peakML files 51 , and MzMatch for alignment and filtering, 52 followed by further pre–processing, organisation, and quality assessment in IDEOM 51 . Metabolite intensity peaks were analyzed in R (v4·2·1). Missing values were imputed using the k–nearest neighbours (kNN) algorithm (neighbours = 5, sample_max = 50, feature_max = 50, by = “features”). Data were normalised using probabilistic quotient normalisation, log₁₀ transformation, and Pareto scaling within the structToolbox package. PCA visualised sample variance, and two–tailed Student’s t–tests ( p < 0·05, FDR–adjusted) were applied for pairwise comparisons. Significant metabolite changes were visualised using volcano plots (–log₁₀[FDR–adjusted p ] vs log₂[fold change], fold change threshold 1·5) and heatmaps and violin plot generated in R ( struct , structToolbox , heatmap , and ggplot2 packages). Pathway enrichment and topology analyses were conducted in MetaboAnalyst 6·0 using KEGG identifiers and the Homo sapiens pathway library. The Global Test algorithm was applied for enrichment analysis with relative betweenness centrality used as the primary metric for topology analysis. Proteomics Protein lysates from mouse lumbo–sacral spinal cord and human frontal white matter were prepared in RIPA buffer with protease and phosphatase inhibitors. Protein concentrations were determined by bicinchoninic acid (BCA) assay. For immunoblotting, 10 µg protein (30 µg for mTOR) was separated on NuPAGE gels, transferred to PVDF membranes, and probed with primary and HRP–conjugated secondary antibodies (supplementary. table2). Detection used enhanced chemiluminescence with a ChemiDoc™ Touch System (Bio–Rad) and densitometry (Image Lab v6.1). Co–immunoprecipitation (mouse) and immunoprecipitation (human) were performed on 100 µg protein. Full protocols are provided in the Supplementary Information. Animal models C57BL/6 naïve mice were analyzed postnatally to assess MCT8 expression during brain development. Experimental autoimmune encephalomyelitis (EAE) was induced in this strain to enable proteomic, immunofluorescence, histochemical, and flow cytometry analyses. A subset of mice received intraocular injections of rAAV2–GFP to transduce and label optic nerve axons, followed by EAE induction. Plp–CreERT2::ROSA26–stop–EYFP transgenic mice were used to evaluate MCT8 expression in mature OLs within naïve spinal cord. These mice were subsequently subjected to EAE to assess OL loss and alterations in MCT8 and TH signaling around inflammatory lesions. Cuprizone–induced demyelination was employed for immunofluorescence and transmission electron microscopy (TEM) analyses of the corpus callosum (CC). All experimental protocols are described in detail in the Supplementary Information. Statistical analysis Statistical analyses were performed using GraphPad Prism (v9·2·0) and R (v4·2·1) in RStudio. Data distribution was assessed with Shapiro–Wilk and Kolmogorov–Smirnov tests. Two–group comparisons were conducted using unpaired two–tailed Student’s t–tests or Mann–Whitney U tests, as appropriate. For comparisons of more than two groups, one–way ANOVA with Tukey’s post hoc or non–parametric ANOVA with Dunn’s multiple comparisons was used. P ≤ 0·05 was considered significant. Sample sizes and specific tests are indicated in figure legends. Declarations Data availability. Data available in a public (institutional, general or subject specific) repository that issues datasets with DOIs (non-mandated deposition). Data available on request from the authors. Authors can confirm that all relevant data are included in the paper and/or its supplementary information files. Acknowledgements The authors would like to thank the contributions of Mary Dass, Michael F Azari, Simon Lee, James Portelli, Salome Bazkurt and Aaron Lewis for the experimental support with animal tissue analysis. Georg Ramm from the Monash Ramaciotti Centre for Cryo Electron Microscopy (Cryo–EM), Samantha from the Alfred Research Alliance–Monash Micro Imaging (ARA–MMI), Robert Brkljaca from the Alfred Research Alliance–Monash Biomedical Imaging (ARA–MBI), for their work and assistance in experiments that have provided data in preparation of this study. The authors acknowledge the facilities and scientific and technical assistance of the National Imaging Facility (NIF), a National Collaborative Research Infrastructure Strategy (NCRIS) capability at ARA–MBI and ARA–MMI and a Technology Research Platform at Monash University. We acknowledge the assistance of Animal Services and the veterinary team at the University of Tasmania, and Drs Thomas Lewis, Phuong Tram Nguyen, and Alastair Fortune of Prof Kaylene Young’s Glial Research Team. Katarina Vogel–Mikus from the Biotechnical Faculty, Department of Biology, University of Ljubljana, Jamnikarjeva 101, 1000, Ljubljana, Slovenia. We acknowledge support from a Monash University postgraduate scholarship awarded to RE; from Multiple Sclerosis Research Australia and Trish Multiple Sclerosis Research Foundation Postgraduate Scholarship awarded to JYL; from a Multiple Sclerosis Research Australia Postgraduate Scholarship awarded to DN; from MS Australia for a Senior Research Fellowship (21-3-023) awarded to K.M.Y.; and from an EU Horizon Europe Marie Sklodowska–Curie Global Fellowship (101106307) awarded to DEB. We also acknowledge grant support from Multiple Sclerosis Australia (17-0206; 18-0521); the Trish Multiple Sclerosis Research Foundation (19-0673); the Bethlehem Griffiths Research Foundation (BGRF1902); the Medical Research Future Fund (EPCD08), and NeuOrphan Pty Ltd through a Research Services agreement with Monash University (L/341646038.16). Author contribution R.E. performed experiments and analysed data directly related to the following data sets: immunofluorescence, metabolomics, proteomics and EAE clinical scoring, contributed to data interpretation and manuscript writing. R.E. generated all figures using various software packages as defined within the methods sections and figure legends with appropriate illustrations generated using Biorender. P.T. performed EAE experiments, edited figures and manuscript. J.Y.L. performed EAE and clinical scoring, conducted electrophysiology, conducted proteomics, completed ontogeny immunofluorescence histology staining and conducted all optic nerve transduction experiments. M.P. conducted cuprizone studies and tissue immunofluorescence experiments. D.N., O.E. and S.Y. performed tissue immunofluorescence counting via ImageJ (Fiji). M.J.K. performed fate-mapping analysis on PLP-YFP+ transgenic mice, EAE induction and clinical scoring. E.O. performed counting via ImageJ (Fiji) and edited the manuscript. M.M. performed tissue immunofluorescence counting via ImageJ (Fiji) and interpreted data. I.S., Z.R., N.T.L., D.K.W., S.M. and W.O. validated and interpreted data along with edited manuscript. C.M. conducted neuropathological reporting of human biobanked tissue. D.E.B., G.B. B.W., P.H. conducted FTIR and OPTIR experiments and interpreted data from the spectral images. K.Y.M generated PLP-YFP+ transgenic mouse line, completed animal ethics submissions, edited the manuscript. K.J.J. and C.K.B performed metabolomic analysis and interpretation of data along with edited manuscript. I.C. performed tissue analysis through software packages outlined in the methods section. N.G. contributed unpublished reagents/analytic tools, assessed human clinical data prepared in Supplementary Table 1. S.P. conceptualized and designed all experiments, performed data analysis, wrote the first draft of the manuscript and provided edited feedback through the review process. Additional information Supplementary Information is provided as a PDF file. Competing financial interests SP is a co–founder, holds equity and is the Chief Scientific Officer for NeuOrphan Pty Ltd which seeks to develop DITPA for the treatment of neurological conditions. Patent All data presented in this manuscript are defined within the Australian Provisional Patent Application ( 2025901533 ), in the name of NeuOrphan Pty Ltd. Entitled: NOVEL TREATMENTS FOR DEMYELINATING DISORDERS . NeuOrphan Pty Ltd. has commercial interests in the current technology for research and clinical development purposes. References Lee, Y., et al.: Oligodendroglia metabolically support axons and contribute to neurodegeneration. 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Supplementary Files SupplementaryFigure2Ocopy.jpg Suppl Fig2o SupplementaryFigure2FIcopy.jpg Suppl Fig2f-i SupplementaryFigure3ACcopy.jpg Suppl Fig3a-c SupplementaryFigure1Tcopy.jpg Suppl Fig1t SupplementaryFigure2Jcopy.jpg Suppl Fig2j SupplementaryFigure5copy.jpg Suppl Fig5 SupplementaryFigure1Scopy.jpg Suppl Fig1s SupplementaryFigure7copy.jpg Suppl Fig7 SpplementaryFigure4AJcopy.jpg Suppl Fig4a-j SupplementaryFigure8GHcopy.jpg Suppl Fig8g-h SupplementaryFigure1INcopy.jpg Suppl Fig1i-n SupplementaryFigure1MRcopy.jpg Suppl Fig1m-r SupplementaryFigure3DPcopy.jpg Suppl Fig3d-p SupplementaryFigure8ABcopy.jpg Suppl Fig8a-b SupplementaryFigure2KNcopy.jpg Suppl Fig2k-n SupplementaryFigure1AHcopy.jpg Suppl Fig1a-h SupplementaryFigure8CFcopy.jpg Suppl Fig8c-f SupplementaryFigure2AEcopy.jpg Suppl Fig2a-e SupplementaryFigure6copy.jpg Suppl Fig6 Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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University","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"O'Brien","suffix":""},{"id":571949879,"identity":"edfe4cff-815a-4cbc-8830-482c1be88dcd","order_by":17,"name":"Catriona McLean","email":"","orcid":"https://orcid.org/0000-0002-0302-5727","institution":"Department of Anatomical Pathology, Alfred Hospital","correspondingAuthor":false,"prefix":"","firstName":"Catriona","middleName":"","lastName":"McLean","suffix":""},{"id":571949880,"identity":"77bcc47b-3567-47d2-9834-4caae9d77322","order_by":18,"name":"Diana Bedolla","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"","lastName":"Bedolla","suffix":""},{"id":571949881,"identity":"c3fe162b-e694-41b7-b57b-2d06c022895d","order_by":19,"name":"Giovanni Birarda","email":"","orcid":"https://orcid.org/0000-0003-2418-058X","institution":"Elettra - Sincrotrone Trieste","correspondingAuthor":false,"prefix":"","firstName":"Giovanni","middleName":"","lastName":"Birarda","suffix":""},{"id":571949882,"identity":"cfe62428-2e04-48c5-b584-374c5e56c8d9","order_by":20,"name":"Bayden Wood","email":"","orcid":"https://orcid.org/0000-0003-3581-447X","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Bayden","middleName":"","lastName":"Wood","suffix":""},{"id":571949883,"identity":"3fadde02-7f45-42b4-a4e0-a71e1ef8c979","order_by":21,"name":"Philip Heraud","email":"","orcid":"","institution":"School of Chemistry, Monash university","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"","lastName":"Heraud","suffix":""},{"id":571949884,"identity":"514000d7-f063-4935-97bd-5992e53ce037","order_by":22,"name":"Kaylene Young","email":"","orcid":"https://orcid.org/0000-0002-1686-3463","institution":"University of Tasmania","correspondingAuthor":false,"prefix":"","firstName":"Kaylene","middleName":"","lastName":"Young","suffix":""},{"id":571949885,"identity":"66559dd6-57fe-44fd-93b1-7a3d7a9faaff","order_by":23,"name":"Katherine Jeppe","email":"","orcid":"https://orcid.org/0000-0003-2284-5090","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Katherine","middleName":"","lastName":"Jeppe","suffix":""},{"id":571949886,"identity":"dfb18333-cc39-4911-b78b-78a09530f080","order_by":24,"name":"Christopher Barlow","email":"","orcid":"https://orcid.org/0000-0001-9309-2829","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Barlow","suffix":""},{"id":571949887,"identity":"d7ab92ba-3983-411a-a166-ad9cc4b1bd71","order_by":25,"name":"Irena Carmichael","email":"","orcid":"","institution":"Monash University,","correspondingAuthor":false,"prefix":"","firstName":"Irena","middleName":"","lastName":"Carmichael","suffix":""},{"id":571949888,"identity":"8f7fcba8-c98e-450d-ae7d-a63d0b0b75e9","order_by":26,"name":"Nikolaos Grigoriadis","email":"","orcid":"https://orcid.org/0000-0002-4278-3301","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Nikolaos","middleName":"","lastName":"Grigoriadis","suffix":""}],"badges":[],"createdAt":"2025-12-23 02:51:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8429369/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8429369/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101202999,"identity":"30e5f5f9-65f7-4b73-a949-621812461e80","added_by":"auto","created_at":"2026-01-27 09:38:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6385133,"visible":true,"origin":"","legend":"","description":"","filename":"Emamnejadetal.2025NaturecommunicationPaper1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/642b2d830fb30d9203e35ea8.docx"},{"id":100982250,"identity":"2cdaf4a7-fd64-4a11-9669-5518a7ce3ad6","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1472859,"visible":true,"origin":"","legend":"","description":"","filename":"Figure7copy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/180a358d876a03c4bc26bb29.jpg"},{"id":101203235,"identity":"08eb0538-aedf-459a-946f-b21b0b42b1e8","added_by":"auto","created_at":"2026-01-27 09:39:08","extension":"json","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23874,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS25103860.json","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/a484ea46c5b7c390156f3b2f.json"},{"id":100982246,"identity":"4b4dc678-4635-4c17-a535-8e4eeaa89492","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26929866,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbrogated MCT8 expression in oligodendrocytes within chronic\u003c/strong\u003e–\u003cstrong\u003eactive demyelinating lesions of SPMS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A–D)\u003c/strong\u003e20– µm OCT–embedded frontal white matter sections were qualitatively analysed by immunofluorescence. White arrowheads in high magnification images indicate MCT8 expression in CC1⁺ and Olig2⁺ oligodendrocytes within chronic active demyelinating lesions of SPMS (n=23), including the PPWM (\u003cstrong\u003eC\u003c/strong\u003e) compared with NAWM in MS \u003cstrong\u003e(B)\u003c/strong\u003e, NNDC (n=6), and primary neurodegenerative diseases, including AD (n =6), FTD (n=9), and HD (n=3) (\u003cstrong\u003eA\u003c/strong\u003e). \u003cstrong\u003e(D)\u003c/strong\u003e depicts MCT8 (green) in GFAP⁺ astrocytes (magenta). Images were acquired as single–plane scans using a 20× oil–immersion objective on a Nikon A1 Eclipse confocal microscope and analysed in FIJI (ImageJ distribution). Scale bar = 50 µm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReduced MCT10 expression in oligodendrocytes within chronic\u003c/strong\u003e–\u003cstrong\u003eactive demyelinating lesions of SPMS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(E–G)\u003c/strong\u003e 20–µm OCT–embedded frontal white matter sections were qualitatively analysed by immunofluorescence. White arrowheads in high magnification images indicate MCT10 expression (red) in CC1⁺ oligodendrocytes (green), including the PPWM (\u003cstrong\u003eG\u003c/strong\u003e) compared with NAWM in MS \u003cstrong\u003e(\u003c/strong\u003en=23; \u003cstrong\u003eF)\u003c/strong\u003e, NNDC (n=6), and primary neurodegenerative diseases, including AD (n =6), FTD (n=9), and HD (n=3) (\u003cstrong\u003eE\u003c/strong\u003e). Images were acquired as single–plane scans using a 20× oil–immersion objective on a Nikon A1 Eclipse confocal microscope and analysed in FIJI (ImageJ distribution). Scale bar = 50 µm.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/a846ebf127d4829b306ca83b.png"},{"id":101942729,"identity":"e9429fa0-f5fe-493b-b526-430bbdf20e7f","added_by":"auto","created_at":"2026-02-05 09:35:53","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4747438,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAltered lipid architecture in chronic\u003c/strong\u003e–\u003cstrong\u003eactive lesions of SPMS frontal white matter revealed by Fourier Transform Infrared (FTIR) and Photothermal Optical Infrared (OPTIR) spectroscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHaematoxylin and Eosin (H\u0026amp;E) staining was performed to verify anatomical structures in SPMS sections.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFTIR analysis:\u003c/strong\u003e FTIR imaging was conducted on frontal white matter from SPMS cases (n=10). Infrared chemical maps display the spatial distribution of lipid–related vibrational signatures, including total lipid content (3000–2800 cm⁻¹), CH₂/CH₃ ratio, CH₂/lipid ratio, and OH:lipid ratio. Individual absorbance peaks were measured at 2950–2900 cm⁻¹ (asymmetric stretching of methylene [–CH₂–] groups), 2980–2948 cm⁻¹ (asymmetric stretching of terminal methyl [–CH₃] groups), and 3365–3030 cm⁻¹ (OH stretching). Additional ratio maps depict the olefin/lipid ratio—corresponding to unsaturated fatty acids (~3027–3000 cm⁻¹)—and the aromatic/lipid ratio, reflecting aromatic C–H stretching (~3100–3030 cm⁻¹). Principal Component Analysis (PCA) of second–derivative FTIR spectra indicated that PC1 accounted for 78.7% of the total spectral variance. K–means clustering (6 clusters) identified distinct biochemical signatures (C1–C6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOPTIR analysis:\u003c/strong\u003e Regions of interest (ROIs) were defined as lesional (green box) or non–lesional (red box) based on FTIR lipid maps and subjected to high–resolution OPTIR spectroscopy. OPTIR spectra (3000–2800 cm⁻¹) revealed marked differences in lipid chain organization between lesional and non–lesional areas, whereas protein content, assessed by the Amide I and II bands (1710–1500 cm⁻¹), remained similar.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/eb67d7985f55623b2681ac31.jpg"},{"id":100982243,"identity":"28327bf5-86b7-448f-b2b3-ceb87afb2db3","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":11284527,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A-C). Overview of pantothenate and CoA biosynthesis, regulation, metabolite dysregulation, and functional roles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Schematic illustration of pantothenate and CoA biosynthesis, its regulatory signaling, and functional outcomes. The central panel depicts the stepwise enzymatic conversion of pantothenic acid to CoA, with intermediates and enzymes arranged in sequential order. Metabolic connections were derived from the KEGG pathway database, with Homo sapiens (hsa) pathway identifiers indicated. The right panels highlight related metabolic routes influencing pantothenate–CoA biosynthesis, while the left panel shows the PI3K–AKT signaling cascade. Under physiological conditions, ligand binding (e.g., growth factors or hormones) to transmembrane receptors activates PI3K, inducing AKT phosphorylation. Activated AKT subsequently phosphorylates pantothenate kinases PANK2 and PANK4, key regulators of CoA synthesis. PANK2 catalyses the first committed step of the pathway, whereas PANK4, a conserved enzyme with phosphatase activity toward mitochondrially derived metabolites, suppresses CoA production. Through this PI3K–AKT–PANK axis, CoA availability modulates mitochondrial function, lipid metabolism, and cell proliferation. Dotted lines indicate sequential substrate–product conversions.\u003cstrong\u003e (B)\u003c/strong\u003e Violin plots show the distribution and density of abundance values for significantly altered metabolites associated with dysregulation of pantothenic acid and CoA biosynthesis in MS (n = 23) compared with controls (CTR, n = 7). Significantly dysregulated metabolites were identified by volcano plot analysis (adjusted \u003cem\u003ep\u003c/em\u003e \u0026lt; 0·05; fold change \u0026gt; 1·5). Violin outlines represent kernel density estimates, and embedded boxplots display the interquartile range and median. Plots were generated in R (version 4·2·1) using the \u003cem\u003eggplot2\u003c/em\u003e package. \u003cstrong\u003e(C)\u003c/strong\u003e CoA is an essential cofactor in all living cells, acting as a central mediator in diverse biochemical processes including energy metabolism; lipid and carbohydrate catabolism and anabolism; signal transduction; epigenetic and transcriptional regulation; and cellular antioxidant defence. The schematic illustrates the interplay between CoA production and cytoplasmic and mitochondrial metabolic pathways that maintain cellular homeostasis. Solid arrows denote direct interactions, and dotted lines indicate indirect relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(D-F)Pathway\u003c/strong\u003e–\u003cstrong\u003elinked distribution and enrichment of significantly altered metabolites in MS compared with CTR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(D–F)\u003c/strong\u003e Violin plots show the distribution and density of abundance values for metabolites significantly altered between MS (n = 23) and CTR (n = 7) samples, mapped to their respective metabolic pathways. All relevant pathways are displayed, including those not significantly dysregulated, when constituent metabolites demonstrated meaningful involvement. Significantly dysregulated metabolites were identified through volcano plot analysis (adjusted \u003cem\u003ep\u003c/em\u003e \u0026lt; 0·05; fold change \u0026gt; 1·5). Each violin outline represents the kernel density estimate, with the embedded boxplot indicating the interquartile range and median. Plots were generated in R (version 4·2·1) using the \u003cem\u003eggplot2\u003c/em\u003epackage.\u003c/p\u003e\n\u003cp\u003eThe pathway enrichment network (\u003cstrong\u003eD\u003c/strong\u003e, E) illustrates enriched metabolic pathways, with circle size reflecting pathway impact and colour intensity (yellow to red) indicating statistical significance, where deeper red denotes higher significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(G): Metabolite level alterations associated with metabolic pathways in MS compared with CTR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(G)\u003c/strong\u003e Violin plots show the distribution and density of abundance values for metabolites significantly altered between MS (n = 23) and CTR (n = 7) samples, demonstrating associations with multiple metabolic pathways that were not themselves significantly dysregulated. Significantly altered metabolites were identified through volcano plot analysis (adjusted \u003cem\u003ep\u003c/em\u003e \u0026lt; 0·05; fold change \u0026gt; 1·5). Each violin outline represents the kernel density estimate, and the embedded boxplot indicates the interquartile range and median. Plots were generated in R (version 4·2·1) using the \u003cem\u003eggplot2\u003c/em\u003e package.\u003c/p\u003e\n\u003cp\u003eThe pathway enrichment network in each panel depicts enriched metabolic pathways, with circle size proportional to pathway impact and colour intensity (yellow to red) indicating statistical significance, where deeper red represents higher significance.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/60d0242be6d6ae7fa6960316.png"},{"id":100982238,"identity":"5419ddef-4862-4778-8cd5-731aa9e18e70","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1680927,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePathway linked distribution of significantly altered metabolites in MS compared with AD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eViolin plots show the distribution and density of abundance values for metabolites significantly altered between MS (n = 23) and AD (n = 6) samples, demonstrating notable involvement across multiple metabolic pathways. All relevant pathways are displayed, including those not significantly dysregulated, when constituent metabolites showed meaningful participation. Significantly dysregulated metabolites were identified through volcano plot analysis (adjusted \u003cem\u003ep\u003c/em\u003e\u0026lt; 0·05; fold change \u0026gt; 1·5). Each violin outline represents the kernel density estimate, and the embedded boxplot indicates the interquartile range and median. Plots were generated in \u003cem\u003eR\u003c/em\u003e (version 4·2·1) using the \u003cem\u003eggplot2\u003c/em\u003epackage.\u003c/p\u003e\n\u003cp\u003eThe pathway enrichment network in each panel depicts enriched metabolic pathways, with circle size proportional to pathway impact and colour intensity (yellow to red) indicating statistical significance, where deeper red denotes higher significance.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/820f593ce0a51af7afbcea40.jpg"},{"id":101203281,"identity":"a76f8ece-1ad4-4c5b-b3f8-348137d0a5a4","added_by":"auto","created_at":"2026-01-27 09:39:15","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":9317199,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDysregulated thyroid hormone signaling and related pathways in chronic degenerative demyelinating lesions of SPMS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Western blot (10% input) showing thyroid hormone transporters OATP1C1 (~79 kDa), MCT8 (~59 kDa), MCT10 (~55 kDa), and deiodinases DIO2 (~31 kDa) and DIO3 (~31 kDa), with β–actin (~42 kDa) as a loading control, in frontal lobe white matter lysates NNDC, AD, FTD, HD, and MS.\u003cstrong\u003e (B)\u003c/strong\u003eDensitometric quantification of protein expression levels (arbitrary units, AU%) for OATP1C1, MCT8, MCT10, DIO2, and DIO3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(C)\u003c/strong\u003e Immunoprecipitation of total protein lysates with anti–AKT or anti–mTOR antibodies, followed by probing with the corresponding phosphorylated forms. Phosphorylated AKT (p–AKT) includes both T308 and S473 sites. Validation was performed by Western blot (10% input) for mTOR (~288 kDa), AKT (~56 kDa), p–AKT (T308), precursor PANK2 (pPANK2, ~63 kDa), mature PANK2 (mPANK2, ~48 kDa), and β–Actin (~42 kDa, loading control). \u003cstrong\u003e(D)\u003c/strong\u003eDensitometric quantification of protein expression levels (AU%) for mTOR, AKT, p–AKT, pPANK2, and mPANK2.\u003c/p\u003e\n\u003cp\u003eData are presented as mean ± SEM (n = 4–11). Statistical significance was determined using one–way ANOVA with Tukey’s post–hoc test (*\u003cem\u003ep\u003c/em\u003e≤ 0·05, **\u003cem\u003ep\u003c/em\u003e≤ 0·01, ***\u003cem\u003ep\u003c/em\u003e≤ 0·001, ****\u003cem\u003ep\u003c/em\u003e≤ 0·0001).\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/9111f2a26b26af0bce7627bc.jpg"},{"id":101203182,"identity":"bfaea6de-51e4-49bd-8c6c-a9c1f48ac115","added_by":"auto","created_at":"2026-01-27 09:39:00","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4573209,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A-D). Electrophysiological, western blot, and immunofluorescence characterization of EAE\u003c/strong\u003e–\u003cstrong\u003einduced spinal cord lesions reveal altered neural activity, reduced MCT8 expression, and OL loss during EAE.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003eRepresentative traces of compound action potentials (CAPs) recorded from the spinal cords of control and EAE–induced mice at the peak disease stage, with quantitative analysis of conduction velocity (m/s), CAP duration at 50% amplitude (ms), and CAP amplitude (mV). Statistical comparisons were made between peak–stage EAE mice and age–matched non–EAE controls. Data are presented as mean ± SEM (n = 3), and statistical significance was determined using an unpaired Student’s \u003cem\u003et\u003c/em\u003e–test. \u003cstrong\u003e(B)\u003c/strong\u003e Representative histochemical staining of frontal white matter from the spinal cords of EAE mice at peak stage revealed pronounced neuropathology: Bielschowsky silver staining demonstrated marked axonal loss, while Sudan Black and semithin Toluidine Blue staining indicated extensive demyelination, consistent with severe neurodegeneration. \u003cstrong\u003e(C)\u003c/strong\u003e Western blot analysis of spinal cord lysates from EAE–induced mice with clinical scores ranging from 1 to 3 (severe EAE), alongside naïve controls (no–EAE), assessing expression of MCT8 (~59 kDa), MCT10 (~55 kDa), DIO2, and DIO3 (~31 kDa). Beta–actin was used as a loading control. Densitometric quantification of protein expression is shown in arbitrary units (AU) as mean ± SEM (n=3–4). Statistical analysis was performed using one–way ANOVA followed by Tukey’s post–hoc test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(D-E)\u003c/strong\u003e Immunofluorescence analysis of spinal cord sections (10–µm) from EAE–induced transgenic mice (Plp–CreERT2::ROSA26–stop–EYFP) compared with naïve controls (no–EAE) showed a marked reduction in the co–localization of MCT8 (red) with PLP⁺ mature OLs (green) within PPWM, relative to NAWM at the severe disease stage (clinical score 3). Imaging performed using a Nikon A1 confocal microscope with a 20× oil–immersion objective and analysed in FIJI (ImageJ distribution). The cell density (cells/mm²) are presented as median ± SEM (n = 3–8). Statistical significance was determined using Student’s t–test for two–group comparisons or one–way ANOVA with Tukey’s post–hoc test for multiple groups. Scale bar = 50 µm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(F)\u003c/strong\u003e Immunofluorescence staining for GFP (green) and DIO3 (magenta) in the lumbo–sacral spinal cord sections (10–µm) of Plp–CreERT2::ROSA–stop–eYFP mice. Scale bar, 10 µm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(G)\u003c/strong\u003eRepresentative images showing DIO3 expression in wild–type and EAE mice (clinical score 3) within NAWM and PPWM regions. Scale bar, 25 µm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(H)\u003c/strong\u003e Quantification of DIO3⁺ PLP⁺ oligodendrocytes per mm² in naïve tissue and NAWM, and PPWM regions of the lumbo–sacral spinal cord. Data are presented as mean ± SEM (n=3). Statistical analysis was performed using one–way ANOVA with Tukey’s post–hoc test\u003c/p\u003e\n\u003cp\u003eSignificance thresholds: \u003cem\u003ep\u003c/em\u003e≤ 0·05; *\u003cem\u003ep≤ \u003c/em\u003e0·01; **\u003cem\u003ep\u003c/em\u003e≤ 0·001; ***\u003cem\u003ep\u003c/em\u003e≤ 0·0001.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/b6a877cbefeba313c908dbfd.jpg"},{"id":100982240,"identity":"d3f87349-eec8-4027-a1c8-734a17982863","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1472859,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA-D. Altered thyroid hormone signaling and downstream pathway activity in the spinal cord of EAE\u003c/strong\u003e–\u003cstrong\u003einduced mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Co-immunoprecipitation analysis of AKT–mTOR signaling using spinal cord lysates from EAE–induced mice and naïve controls. Lane numbers indicate EAE clinical scores (0 = no EAE; 3 = severe EAE). Lysates (100 µg) were immunoprecipitated with anti–total AKT (1:100) and probed for p–AKT and mTOR, or immunoprecipitated with anti–mTOR (1:100) and probed for total AKT.\u003cstrong\u003e (B)\u003c/strong\u003e Western blots (10% input) of spinal cord lysates were probed for total mTOR (~288 kDa), total AKT (~56 kDa), PANK2 (~57 kDa), and beta–Actin (~42 kDa; loading control). Densitometric quantification of protein expression is showed in arbitrary units (AU%) as mean ± SEM (n = 3–8). Statistical analysis: one–way ANOVA with Tukey’s post hoc test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(C)\u003c/strong\u003eDiagrammatic representation of AKT–mTOR signaling interactions in the spinal cord under physiological (naïve) and pathological (EAE) conditions, illustrating disease–associated alterations in pathway activity. \u003cstrong\u003e(D–E)\u003c/strong\u003eImmunofluorescence staining of spinal cord sections (10–µm) from EAE–induced transgenic mice (Plp–CreERT2::ROSA26–stop–EYFP) was performed. PLP⁺ mature oligodendrocytes (green), MCT8 (red), and phosphorylated AKT (p–AKT, magenta) in (D) NAWM and (E) PPWM of spinal cords from EAE–induced mice at peak disease (clinical score = 3). Imaging performed using a Nikon A1 confocal microscope with a 20× oil–immersion objective and analyzed in FIJI (ImageJ distribution). The cell density (cells/mm²) are presented as median ± SEM (n = 3–8). Statistical significance was assessed by one–way ANOVA with Tukey’s post–hoc test. Scale bar = 50 µm.\u003c/p\u003e\n\u003cp\u003eSignificance thresholds: \u003cem\u003ep\u003c/em\u003e≤ 0·05; *\u003cem\u003ep≤ \u003c/em\u003e0·01; **\u003cem\u003ep\u003c/em\u003e≤ 0·001; ***\u003cem\u003ep\u003c/em\u003e≤ 0·0001.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/bc400e77e4fa766c1b31e47c.jpg"},{"id":101943996,"identity":"150d90b3-5abb-4a9d-a5aa-0a62ba45856a","added_by":"auto","created_at":"2026-02-05 09:47:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":64936556,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/a123659e-1aa1-4736-a8fb-9d1e63ac2551.pdf"},{"id":100982237,"identity":"124f0a5f-9b88-4386-ae0c-e8664ca91089","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1489097,"visible":true,"origin":"","legend":"Suppl Fig2o","description":"","filename":"SupplementaryFigure2Ocopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/f68d170af9fe31312ddfdbf9.jpg"},{"id":101203790,"identity":"782d5f05-439c-4299-a3b7-19349293914b","added_by":"auto","created_at":"2026-01-27 09:40:40","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2899255,"visible":true,"origin":"","legend":"Suppl Fig2f-i","description":"","filename":"SupplementaryFigure2FIcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/00562b8be7269da1f00b1baa.jpg"},{"id":101203645,"identity":"9071670f-3ab6-47ee-b293-47d16fa4eaf4","added_by":"auto","created_at":"2026-01-27 09:40:19","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":589262,"visible":true,"origin":"","legend":"Suppl Fig3a-c","description":"","filename":"SupplementaryFigure3ACcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/a911caf8d2aecb9b8829f413.jpg"},{"id":101203153,"identity":"47f75d23-648a-4a46-a31b-b5c164c08d44","added_by":"auto","created_at":"2026-01-27 09:38:53","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5360597,"visible":true,"origin":"","legend":"Suppl Fig1t","description":"","filename":"SupplementaryFigure1Tcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/a9ca5a1646b573e9c18aaffc.jpg"},{"id":100982245,"identity":"2b7fb819-90dc-4e54-baea-deedbd14cdc8","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1608614,"visible":true,"origin":"","legend":"Suppl Fig2j","description":"","filename":"SupplementaryFigure2Jcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/b56b0bb54493020c17da9bc3.jpg"},{"id":100982256,"identity":"06d9e837-f5be-48c9-80d6-615f2a0bd368","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":4920696,"visible":true,"origin":"","legend":"Suppl Fig5","description":"","filename":"SupplementaryFigure5copy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/06df7b470b94a1236932b81a.jpg"},{"id":101203326,"identity":"72e7fd5f-f6fe-4a92-a2cc-81ca8d69b0d2","added_by":"auto","created_at":"2026-01-27 09:39:23","extension":"jpg","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":5894308,"visible":true,"origin":"","legend":"Suppl Fig1s","description":"","filename":"SupplementaryFigure1Scopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/b6ca453b0174d83caee74c8d.jpg"},{"id":100982255,"identity":"d4dc8b05-5228-47c9-add2-5a392a1f944c","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":697555,"visible":true,"origin":"","legend":"Suppl Fig7","description":"","filename":"SupplementaryFigure7copy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/6a3559827d51d428615abde9.jpg"},{"id":101203334,"identity":"ceb7ad9f-9fac-4c48-bbe8-c47ecf5ba60f","added_by":"auto","created_at":"2026-01-27 09:39:24","extension":"jpg","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":15559236,"visible":true,"origin":"","legend":"Suppl Fig4a-j","description":"","filename":"SpplementaryFigure4AJcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/aa1b545d2df7146318f5da34.jpg"},{"id":101203342,"identity":"225d99dd-858c-400e-b55a-6a5e0b938d50","added_by":"auto","created_at":"2026-01-27 09:39:25","extension":"jpg","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":3750248,"visible":true,"origin":"","legend":"Suppl Fig8g-h","description":"","filename":"SupplementaryFigure8GHcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/1d93276a5e346407440999d3.jpg"},{"id":101203942,"identity":"3d70238a-1ed4-46a0-805a-cbea082bbc17","added_by":"auto","created_at":"2026-01-27 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12:30:05","extension":"jpg","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":30504639,"visible":true,"origin":"","legend":"Suppl Fig8c-f","description":"","filename":"SupplementaryFigure8CFcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/67e4d0732ead61e68f462ed7.jpg"},{"id":100982253,"identity":"109c4856-2d74-4567-8bf9-de136134bd0c","added_by":"auto","created_at":"2026-01-23 12:30:05","extension":"jpg","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":30654312,"visible":true,"origin":"","legend":"Suppl Fig2a-e","description":"","filename":"SupplementaryFigure2AEcopy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/c0a2fb6e169c635418c5aee5.jpg"},{"id":100982263,"identity":"58b61f09-5d50-4e2b-b6f4-9b36fc2e6b90","added_by":"auto","created_at":"2026-01-23 12:30:06","extension":"jpg","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":56347165,"visible":true,"origin":"","legend":"Suppl Fig6","description":"","filename":"SupplementaryFigure6copy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8429369/v1/71f2d49dd3702ee3220e7819.jpg"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nSP is a co–founder, holds equity and is the Chief Scientific Officer for NeuOrphan Pty Ltd which seeks to develop DITPA for the treatment of neurological conditions.","formattedTitle":"Delineating the role of monocarboxylate transporter 8 (MCT8) in the context of neuroinflammation–mediated oligodendrocytopathy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe loss of oligodendrocytes (OLs) or specific developmental defects in oligodendrogenesis results in denudement of axons, potentiating the brain\u0026rsquo;s vulnerability to further neurodegeneration.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Central nervous system (CNS) neurons and their axons receive the structural and metabolic support of OLs,\u003csup\u003e1\u003c/sup\u003e and failure of this support results in severe neurological disorders, as manifest in multiple sclerosis (MS) or during inherited forms of leukoencephalopathy.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e In adult CNS disorders, oligodendrogenesis and repair can be limited by the availability and stalled maturation of oligodendroglial progenitor cells (OPCs).\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e In MS, this is partially due to a lack of trophic support, including thyroid hormone (TH) within demyelinated lesions.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Furthermore, the accumulation of \u0026ldquo;disease\u0026ndash;associated\u0026rdquo; oligodendroglia (DOLs) is associated with cognitive decline in tauopathy, neurodegeneration and autoimmune\u0026ndash;mediated neuroinflammation.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Providing trophic support to OLs may limit inflammatory damage, including the transition to DOLs, to combat neurodegeneration.\u003c/p\u003e \u003cp\u003eThe neuroactive TH, tri-iodothyronine (T\u003csub\u003e3\u003c/sub\u003e), supports OL differentiation \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. It plays a central role in OL development and myelination \u003cem\u003ein vivo\u003c/em\u003e by regulating OPC replication, and the expression of genes required for myelin production and OL survival.\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Although THs stimulate OL differentiation,\u003csup\u003e9\u0026ndash;11\u003c/sup\u003e the mechanism of TH transport into OLs is not well known.\u003c/p\u003e \u003cp\u003eTHs are shuttled across the plasma membrane by transporters including the monocarboxylate transporter (MCT)8,\u003csup\u003e12\u003c/sup\u003e MCT10,\u003csup\u003e13\u003c/sup\u003e organic anion transporting polypeptide 1C1 (OATP1C1),\u003csup\u003e14\u003c/sup\u003e and SLC17A4.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e MCT8 encoded by the \u003cem\u003eSLC16A2\u003c/em\u003e gene, facilitates the uptake of T3 across the blood brain barrier (BBB).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Mutations in the \u003cem\u003eSLC16A2\u003c/em\u003e gene locus cause a severe congenital X\u0026ndash;linked psychomotor dysfunction, known as Allan\u0026ndash;Herndon\u0026ndash;Dudley syndrome (AHDS).\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e This disease is associated with increased serum levels of free\u0026ndash;T\u003csub\u003e3\u003c/sub\u003e, developmentally delayed/incomplete myelination, and persistent neurological deficits, which suggests that MCT8 is required for normal OL development and myelination.\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe MCT10, encoded by the gene \u003cem\u003eslc16a10\u003c/em\u003e, transports TH in addition to performing its common T\u0026ndash;type amino acid transporter function.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e MCT10 shows overlapping expression with MCT8 particularly in mature white matter tracts, suggesting a functional role in differentiated OLs.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe recently demonstrated that TH transporters are expressed by human oligodendroglia and support their differentiation and myelination \u003cem\u003ein vitro.\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e When MCT8 expression was downregulated in human OPCs (hOPCs), OPC survival and OL maturation was impaired.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e However, the TH analog, 3,5-diiodothyropropionic acid (DITPA), preserved hOPCs, promoted oligodendroglial maturation, and increased their myelination of co-cultured retinal ganglion neurons.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study we report that MCT8 expression is essential for normal mouse brain and spinal cord development but is reduced during inflammatory demyelination, coinciding with OL loss and impaired TH\u0026ndash;dependent non-genomic signaling. Using archival human brain white matter samples, we identified that impaired TH transport into the CNS and its altered metabolism, alongside dysfunctional aspects of the AKT\u0026ndash;mTOR\u0026ndash;PANK2 signaling pathway, may represent common features of neurodegeneration. Metabolomic profiling further revealed disruption of the pantothenic acid and coenzyme A (CoA) biosynthesis pathway. This dysregulated pathway stems from disruptions in the AKT\u0026ndash;mTOR\u0026ndash;PANK2 pathway. In parallel, Fourier transform infrared imaging (FTIR) and photothermal optical infrared spectroscopy (OPTIR) imaging demonstrated pronounced lipid degradation, reflecting the downstream effects of these molecular and metabolic disturbances. Together, these findings reveal that metabolic disruptions in the pantothenic acid and CoA biosynthesis pathway in progressive MS can be therapeutically targeted by overcoming the dysregulated TH\u0026ndash;dependent signalling within white matter of progressive MS lesions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTo characterize the MS tissue utilized in this study, post\u0026ndash;mortem CNS specimens from SPMS were evaluated by histopathology and immunofluorescence to confirm the presence of chronic active demyelinating plaques exhibiting ongoing OL dystrophy (supplementary Fig.\u0026nbsp;1). Detailed histopathological classification of lesions is provided in the Supplementary Information. Chronic active plaques demonstrating pronounced axonopathy were subsequently selected for analysis of OL\u0026ndash;specific MCT8 and MCT10 expression, as well as for metabolic and proteomic profiling.\u003c/p\u003e \u003cp\u003eAbrogated MCT8 and MCT10 expression levels are evident in OLs throughout neurodegenerative lesions.\u003c/p\u003e \u003cp\u003eTo initially assess if there exists TH resistance in neuropathological lesions with active degeneration, we performed a qualitative immunofluorescence analysis of MCT8 and MCT10 expression comparing acquired neuroinflammation\u0026ndash;mediated demyelination, as seen in MS, control (NNDC), and other primary neurodegenerative diseases, including Alzheimer\u0026rsquo;s disease (AD), Fronto\u0026ndash;temporal dementia (FTD), Huntington\u0026rsquo;s disease (HD) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;G; supplementary Fig.\u0026nbsp;1S). MCT8 and MCT10 were detected in mature OLs (CC1⁺ or Olig2⁺ cells), but their expression was markedly reduced within degenerative lesions, particularly in chronic active demyelinating white matter of SPMS. This reduction indicates impaired TH transporter function consistent with TH resistance in mature OLs resident in chronic active MS lesions.\u003c/p\u003e \u003cp\u003eFurther immunofluorescence analysis assessing downstream OLs survival signaling revealed decreased co\u0026ndash;localization of phosphorylated AKT (p\u0026ndash;AKT) with MCT8 in glial cells including astrocytes and OLs within SPMS white matter chronic active lesions compared with AD and non\u0026ndash;neurological disease controls (supplementary Fig.\u0026nbsp;1T).\u003c/p\u003e \u003cp\u003eFTIR and OPTIR imaging identified pronounced lipid degradation within chronic active lesion in SPMS.\u003c/p\u003e \u003cp\u003eFTIR imaging revealed disrupted lipid spectral profiles within chronic active demyelinating lesions of SPMS tissue, characterized by decreased CH₂:CH₃, CH\u003csub\u003e2\u003c/sub\u003e: lipid, Olefin: lipid ratios and increased OH: lipid ratios (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The decrease in CH\u003csub\u003e2\u003c/sub\u003e:CH\u003csub\u003e3\u003c/sub\u003e and CH\u003csub\u003e2\u003c/sub\u003e: lipid ratios reflects acyl chain shortening and structural lipid degradation, consistent with lipid peroxidation and oxidative stress\u0026ndash;induced myelin damage.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e In contrast, the increase of OH: lipid ratio suggests accumulation of lipid peroxidation end products,\u003csup\u003e26\u003c/sup\u003e while the decreased olefin: lipid ratio further indicates oxidative damage to double bonds, leading to loss of unsaturation.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Together, these findings are consistent with ongoing myelin degeneration linked to impaired mitochondrial acetyl\u0026ndash;CoA metabolism [for review, see \u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e]. The Aromatic: lipid ratio may suggest that the neurotransmitter tryptophan is a significant contributor to the changes observed in the lesion (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eComplementary OPTIR measurements confirmed these lipid alterations, showing reduced CH stretching related to lipids (3000\u0026ndash;2800 cm⁻\u0026sup1;) in lesion regions compared with adjacent non\u0026ndash;lesioned white matter, while protein\u0026ndash;associated Amide I and II bands (1710\u0026ndash;1500 cm⁻\u0026sup1;) remained comparable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The complementary capabilities of FTIR and OPTIR imaging\u0026mdash;restricted spectral range in FTIR (4000\u0026ndash;2600 cm⁻\u0026sup1;, due to the use of glass slides as the sample substrate) versus extended coverage by OPTIR (3000\u0026ndash;800 cm⁻\u0026sup1;)\u0026mdash;together support the presence of lesion\u0026ndash;specific lipid degradation within SPMS white matter.\u003c/p\u003e \u003cp\u003eHuman post\u0026ndash;mortem tissue demonstrates dysregulated metabolic pathways in chronic active and degenerative demyelinating lesions.\u003c/p\u003e \u003cp\u003eWe first conducted an untargeted metabolomic analysis to profile metabolites in archival chronic active white matter lesions from people with MS (pwMS), and compared these with frontal white matter tissue from individuals with AD, FTD, or NNDC as the control (CTR) tissue group. After performing multiple student's t\u0026ndash;tests on the metabolite databases we identified a compilation of 89 significant changes occurring in SPMS, 67 in AD, and 62 in FTD, when compared to CTR frontal white matter. We generated volcano plots based on significant t\u0026ndash;test results, using a threshold of 1\u0026middot;5\u0026ndash;fold change (FC), which revealed that 30 metabolites were increased, while 28 showed decreased levels in MS relative to CTR white matter (supplementary Fig.\u0026nbsp;2A, supplementary table 3).\u003c/p\u003e \u003cp\u003eFollowing metabolic pathway analysis of dysregulated metabolites (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05; FC\u0026thinsp;\u0026gt;\u0026thinsp;1\u0026middot;5) identified between MS and CTR, we tabulated the alterations that affect 20 metabolic pathways (supplementary table 4). Among these, four pathways were significantly enriched, including Pantothenate and Coenzyme A (CoA) biosynthesis (KEGG pathway ID: hsa00770; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;001), Histidine metabolism (hsa00340, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;01), beta\u0026ndash;Alanine metabolism (hsa00410, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;02), Pentose and glucuronate interconversions (hsa00040, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;02), as detailed in supplementary Fig.\u0026nbsp;2F and supplementary table 4. Within the Pantothenate and CoA biosynthesis, the major dysregulated pathway, three key metabolites were altered: pantothenic acid, pantetheine 4'\u0026ndash;phosphate, and dephospho\u0026ndash;CoA were significantly downregulated (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;004, 0\u0026middot;03, 0\u0026middot;003; FC\u0026thinsp;=\u0026thinsp;0\u0026middot;56, 0\u0026middot;47, 0\u0026middot;51, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Similarly, beta\u0026ndash;Alanine metabolism exhibited notable perturbations, characterized by decreased levels of beta\u0026ndash;alanyl\u0026ndash;L\u0026ndash;lysine and carnosine (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;002, 0\u0026middot;03 and FC\u0026thinsp;=\u0026thinsp;0\u0026middot;48, 0\u0026middot;61, respectively), this pathway is also involved in the biosynthesis of pantothenate and CoA biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). In histidine metabolism, an increase in 1\u0026ndash;methylhistidine (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;004, FC\u0026thinsp;=\u0026thinsp;2\u0026middot;6) and decrease in carnosine levels contributed to pathway dysregulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). In addition, the upregulated levels of glucuronate and ribulose (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;02 and 0\u0026middot;02, FC\u0026thinsp;=\u0026thinsp;1\u0026middot;89 and 1\u0026middot;98, respectively) were involved in dysregulation of pentose and glucuronate interconversions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eAlthough some pathways did not reach statistical significance, the dysregulated metabolites involved are biologically meaningful and suggest functionally relevant metabolic alterations. Several of these metabolites were associated with antioxidant defence mechanisms. Specifically, gamma\u0026ndash;glutamylcysteine, alpha\u0026ndash;aminobutyric acid, and glucuronate (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;03, 0\u0026middot;004, 0\u0026middot;02, and FC\u0026thinsp;=\u0026thinsp;0\u0026middot;57, 1\u0026middot;76, and 1\u0026middot;89 respectively) are implicated in glutathione metabolism (hsa00480), cysteine and methionine metabolism (hsa00270), and ascorbate and aldarate metabolism (hsa00053), respectively \u0026mdash; pathways that play central roles in maintaining redox homeostasis and neutralizing ROS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-F). These metabolites are aligned with a downregulation in carnosine levels in MS,\u003csup\u003e31\u003c/sup\u003e consistent with its consumption during oxidative or carbonyl stress and a decreased availability of this non\u0026ndash;enzymatic antioxidant dipeptide.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Similarly, β\u0026ndash;alanyl\u0026ndash;L\u0026ndash;lysine was decreased, suggesting increased utilization of β\u0026ndash;alanine\u0026ndash;containing dipeptides (carnosine) with potential antioxidant and buffering roles. These reductions indicate a loss of small\u0026ndash;molecule dipeptide defences, which may shift the burden of redox protection toward the glutathione system and other enzymatic antioxidant pathways.\u003c/p\u003e \u003cp\u003eElevated levels of kynurenine (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;004, FC\u0026thinsp;=\u0026thinsp;2\u0026middot;7) indicate potential activation of tryptophan metabolism, which has been linked to neurotoxicity and immunomodulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). Uric acid and UMP were altered (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;04, 0\u0026middot;01; FC\u0026thinsp;=\u0026thinsp;2\u0026middot;43, 0\u0026middot;58), with participation in nucleotide metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). Moreover, 2\u0026ndash;hydroxybutyric acid\u0026mdash;a metabolite associated with the propanoate metabolism pathway \u0026mdash; was markedly elevated (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;004; FC\u0026thinsp;=\u0026thinsp;3\u0026middot;37; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), underscoring links between altered CoA biosynthesis and energy metabolism. Finally, altered levels of glyceric acid and ethanolamine phosphate (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;002, and 0\u0026middot;01, FC\u0026thinsp;=\u0026thinsp;1\u0026middot;61, and 0\u0026middot;64 respectively) mapped to lipid\u0026ndash;related pathways, including glycerolipid metabolism, glycerophospholipid metabolism, sphingolipid metabolism, and GPI\u0026ndash;anchored lipid biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). Broader analysis revealed additional dysregulated metabolites across various amino acid metabolic routes.\u003c/p\u003e \u003cp\u003eSubsequent comparisons between MS and AD revealed a total of 50 significantly altered metabolites, with 33 upregulated and 10 downregulated (volcano plot analysis, adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05, FC\u0026thinsp;\u0026gt;\u0026thinsp;1\u0026middot;5; supplementary Fig.\u0026nbsp;2D, supplementary table 5). These dysregulated metabolites were mapped to ten metabolic pathways, with statistically significance observed in three: D\u0026ndash;amino acid metabolism (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;05), nicotinate and nicotinamide metabolism (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;05), and histidine metabolism (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;05) (supplementary Fig.\u0026nbsp;2I, supplementary table 6). The primary metabolites contributing to these pathway perturbations were serine (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;01, FC\u0026thinsp;=\u0026thinsp;1\u0026middot;6), nicotinic acid (p\u0026thinsp;=\u0026thinsp;0\u0026middot;01, FC\u0026thinsp;=\u0026thinsp;1\u0026middot;6), and 1\u0026ndash;methylhistidine (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;03, FC\u0026thinsp;=\u0026thinsp;0\u0026middot;57), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Additionally, several metabolites exhibited biologically meaningful roles within key metabolic pathways, although they did not reach statistical significance for pathway\u0026ndash;level disruption. These included (6R)-6-(L-Erythro-1,2-Dihydroxypropyl)-5,6,7,8-tetrahydro-4a-hydroxypterin (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;02, FC\u0026thinsp;=\u0026thinsp;2\u0026middot;5) involved in folate biosynthesis, and guanosine diphosphate (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0\u0026middot;02, FC\u0026thinsp;=\u0026thinsp;0\u0026middot;53) within purine metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, comparison of frontal white matter tissues between MS and FTD revealed only seven significantly altered metabolites, of which two were upregulated and two downregulated based on volcano plot analysis (supplementary Fig.\u0026nbsp;2E, supplementary table 7).\u003c/p\u003e \u003cp\u003eThe metabolomic analysis for comparison between AD and CTR, or FTD and CTR are provided in Supplementary Information.\u003c/p\u003e \u003cp\u003eThese data suggest that SPMS chronic active MS lesions display dysregulated metabolic pathways that are depicted in the white matter of brain tissue from primary neurodegenerative disorders.\u003c/p\u003e \u003cp\u003eHuman post\u0026ndash;mortem tissue demonstrates dysregulated TH\u0026ndash;dependent signaling in chronic active demyelinating lesions.\u003c/p\u003e \u003cp\u003eTo investigate whether dysregulated metabolites seen in MS are related to changes in TH\u0026ndash;dependent signaling, post\u0026ndash;mortem human white matter lysates from four different neurological diseases (AD, FTD, HD, and SPMS with chronic active lesions) and NNDC as control, were assessed for the expression of TH transporters, TH\u0026ndash;converting enzymes, and components of the non\u0026ndash;genomic TH signalling pathway (AKT\u0026ndash;mTOR\u0026ndash;PANK2) using western blotting and immunoprecipitation (IP) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-D). Analysis of 10% input human tissue lysates revealed a marked downregulation of the TH transporters MCT8, MCT10, and OATP1C1 in SPMS frontal white matter tissue compared with NNDC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;B; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;0001, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;001, respectively), indicating profoundly altered TH transport during progressive demyelination. Although MCT8 expression in FTD exceeded that seen in AD and HD, MCT10 expression was significantly reduced relative to NNDC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;B; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;001), demonstrating TH\u0026ndash;resistance, since ~\u0026thinsp;25% of circulating thyroxine (T4) binds to this plasma membrane transporter for its intracellular uptake.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurthermore, we demonstrated that both deiodinase\u0026ndash;2 (DIO2) and deiodinase\u0026ndash;3 (DIO3) expression significantly reduced in SPMS white matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B, p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01 and 0\u0026middot;0001, respectively), while remaining unchanged in AD compared with NNDC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). Collectively, these data may suggest that the deficiencies identified in the plasma membrane TH transporters along with both T4 to T3 and T3 to rT3/T2 converting enzymes clearly contribute to a chronic impairment of TH signalling in SPMS demyelinating and neurodegenerative lesions.\u003c/p\u003e \u003cp\u003eFurther analysis of non\u0026ndash;genomic TH signalling in frontal white matter lesions from SPMS tissue revealed a significant reduction in phosphorylated AKT (p\u0026ndash;AKT at T308 and S473) levels and in the p\u0026ndash;AKT/AKT ratio compared with NNDC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u0026ndash;D, p\u0026thinsp;=\u0026thinsp;0\u0026middot;05), as shown by pulling down with an anti\u0026ndash;total AKT antibody. IP pulling down with anti\u0026ndash;total mTOR also demonstrated decreased level of phosphorylated mTOR in SPMS samples. Western blot analysis of 10% input confirmed decreased levels of both total and phosphorylated\u0026ndash;forms of AKT along with total mTOR, in MS tissue compared with NNDC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-D, p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01, 0\u0026middot;01 and 0\u0026middot;05, respectively). However, these non\u0026ndash;genomic mechanisms downstream of TH\u0026ndash;dependent signaling required further investigation in cell culture and animal models.\u003c/p\u003e \u003cp\u003eFrom human frontal lobe white matter lysates, the levels of key mitochondrial enzymes downstream of AKT\u0026ndash;mTOR signalling, fundamental for the conversion of pantothenic acid to acetyl CoA for lipid synthesis were assessed. Consistent with metabolomic analysis that showed a significant dysregulated pantothenate metabolism in SPMS (supplementary Fig.\u0026nbsp;2A and F). PANK2 was markedly reduced in SPMS compared to NNDC, with substantive reductions in both mature (mPANK2) and precursor (pPANK2) forms (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u0026ndash;D; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05 for both). These data may identify the mechanisms by which the phosphorylated\u0026ndash;proteins are dysregulated downstream of TH\u0026ndash;dependent nongenomic signalling during SPMS that may lead to profound deficits in myelin lipid synthesis pathways during mature OL dystrophy.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe expression of MCT8 in OLs during CNS development in na\u0026iuml;ve C57BL/6 mice\u003c/h2\u003e \u003cp\u003eAs \u003cem\u003ein vitro\u003c/em\u003e MCT8 expression was identified in oligodendroglial lineage cells derived from hESCs,\u003csup\u003e24\u003c/sup\u003e we investigated the \u003cem\u003ein vivo\u003c/em\u003e expression of MCT8 during postnatal C57BL/6 mouse brain development. MCT8 expression was prominently localized to developing OLs defined on PDGFRα\u003csup\u003e+\u003c/sup\u003e OPCs during brain and white matter development were clearly identified within the SVZ and CC tracts (supplementary Fig.\u0026nbsp;3A-C). Expression peaked at P21 in the developing CC, highlighting a critical role for MCT8 in OPC-mediated myelinogenesis, as previously reported.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Hence re\u0026ndash;establishing this signalling role would be of great importance in limiting myelin degeneration. For details, see the Supplementary Information.\u003c/p\u003e \u003cp\u003eExpression of the TH\u0026ndash;transporters, MCT8 and MCT10, in mature OLs present in white matter tracts of the na\u0026iuml;ve \u003cem\u003ePLP\u003c/em\u003e\u0026ndash;\u003cem\u003eYFP transgenic\u003c/em\u003e adult mouse spinal cord.\u003c/p\u003e \u003cp\u003eTo understand the TH\u0026ndash;dependent mechanisms operative in mature OLs across CNS white matter prior to neuroinflammatory challenge, we initially utilized the Plp\u0026ndash;CreER\u003csup\u003eT2\u003c/sup\u003e::ROSA26\u0026ndash;stop\u0026ndash;EYFP transgenic mouse model for fate mapping of mature OLs. The quantitative analysis of MCT8 or MCT10 expression in mature OLs (PLP\u003csup\u003e+\u003c/sup\u003e/CC1\u003csup\u003e+\u003c/sup\u003e) (supplementary Fig.\u0026nbsp;3D-P), demonstrated the presence of both transporters within the white matter of the spinal cord. Comparable numbers of MCT8⁺ and MCT10⁺ OLs were detected in white matter regions, whereas MCT10⁺ OLs were markedly reduced in the grey matter (supplementary Fig.\u0026nbsp;3L and P), where myelinated fibers are sparse. These findings suggest potential differential T₃ versus T₄ transport dynamics between spinal white and grey matter, warranting further investigation. For details, see the Supplementary Information.\u003c/p\u003e \u003cp\u003eThe optic nerve and lumbo\u0026ndash;sacral spinal cord of EAE\u0026ndash;induced C57BL/6 mice and the corpus callosum of cuprizone\u0026ndash;induced mice demonstrate significantly reduced TH\u0026ndash;transporter expression with profound OL dystrophy.\u003c/p\u003e \u003cp\u003eTo assess the MCT8\u0026ndash;dependent signalling mechanisms during neuroinflammatory processes within the CNS, we analysed lumbo\u0026ndash;sacral spinal cord and optic nerve tissues from EAE\u0026ndash;induced adult C57BL/6 female mice at pre\u0026ndash;onset, onset and peak disease (up to 30 days post\u0026ndash;induction). At peak disease, pronounced white matter inflammation coincided with reduced amplitude and conduction velocity of dorsal column compound action potentials (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Expression of full-length MCT8 declined approximately five-fold compared with na\u0026iuml;ve controls (\u003cem\u003ep\u0026thinsp;\u0026le;\u003c/em\u003e\u0026thinsp;0\u0026middot;001; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). This may demonstrate the persistent MCT8 degradation throughout EAE progression, leading to reduced transporter expression and impaired TH dependent signalling. MCT10 expression was similarly reduced, by about two-fold (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eOL loss and dystrophic morphology were evident at the peak of neuroinflammation of EAE, predominantly within inflammatory regions of the lumbo\u0026ndash;sacral spinal cord and optic nerve white matter, coinciding with reduced MCT8 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eD-E; supplementary Fig.\u0026nbsp;4C-D). A comparable loss of MCT8\u0026ndash;deficient SOX10⁺ mature OLs was also identified in the cuprizone model of demyelination (supplementary Fig.\u0026nbsp;5). Downregulation of MCT8 in mature CC1⁺ OLs was associated with cleaved caspase\u0026ndash;3 expression, indicating apoptosis as a key contributor to OL loss (supplementary Fig.\u0026nbsp;4H-J) possibly resulting from deprivation of trophic support by T3 due to impaired MCT8 function.\u003c/p\u003e \u003cp\u003eIn the optic nerve, axonal integrity was evaluated by rAAV2\u0026ndash;GFP transduction of retinal ganglion cells (~\u0026thinsp;40% of temporal retina) before EAE induction in C57Bl/6 mice. At disease peak, dystrophic GFP⁺ axons were frequently located near apoptotic (caspase\u0026ndash;3⁺) mature OLs (CC1⁺), representing 27\u0026middot;7% of CC1⁺ OLs near inflammatory lesions (supplementary Fig.\u0026nbsp;4F-I). The optic nerve showed greater susceptibility to neuroinflammatory damage than the spinal cord, likely reflecting its compact architecture and dense myelination. Refer to Supplementary Information for more detail.\u003c/p\u003e \u003cp\u003eConcomitant with MCT8 loss, deiodinase expression declined at all disease stages. DIO2 levels decreased three-fold from na\u0026iuml;ve to clinical scores 1\u0026ndash;2 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05) and score 3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01), while DIO3 expression decreased two\u0026ndash;fold at scores 1\u0026ndash;2 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01) and ten\u0026ndash;fold at score 3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;0001), with an additional five\u0026ndash;fold reduction between clinical score of 1\u0026ndash;2 and 3 diseases (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). This highlights a progressive decline in DIO2 and DIO3 expression correlating with the severity of EAE. DIO3 expression was particularly diminished in dystrophic PLP⁺ mature OLs (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-H).\u003c/p\u003e \u003cp\u003eCollectively, these data support the hypothesis that neuroinflammatory demyelination is associated with a progressive decline in MCT8, DIO2, and DIO3 expression, leading to impaired TH transport and metabolism in mature OLs. This likely contributes to localized TH resistance, disrupting TH\u0026ndash;dependent metabolic and homeostatic processes critical for OL survival and axonal maintenance during active neuroinflammation.\u003c/p\u003e \u003cp\u003eModulation of MCT8 expression in spinal cord and peripheral immune cell populations following EAE induction in wildtype C57BL/6 mice.\u003c/p\u003e \u003cp\u003eTo determine MCT8 expression modulation during neuroinflammatory demyelination, we examined its distribution in peripheral blood cells from na\u0026iuml;ve and EAE\u0026ndash;induced wild\u0026ndash;type C57BL/6 mice at a clinical score of 3. Flow cytometric analysis revealed a marked upregulation of MCT8 in cells of the monocytic lineage, suggesting an enhanced metabolic demand associated with the inflammatory state (supplementary Fig.\u0026nbsp;6B).\u003c/p\u003e \u003cp\u003eWithin the spinal cord white matter of EAE mice at peak disease, MCT8 expression was broadly increased in inflammatory regions but showed minimal overlap with immune cells, including CD3e\u003csup\u003e+\u003c/sup\u003e T cells, B220\u003csup\u003e+\u003c/sup\u003e B cells and CD206\u003csup\u003e+\u003c/sup\u003e macrophages. These findings suggest that MCT8 upregulation during neuroinflammation occurs mainly in non-lymphoid, non-macrophage populations within the CNS (supplementary Fig.\u0026nbsp;6C-F).\u003c/p\u003e \u003cp\u003eDetailed information is provided in the Supplementary Information.\u003c/p\u003e \u003cp\u003eTH signaling is altered in the spinal cord of EAE\u0026ndash;induced C57BL/6 mice.\u003c/p\u003e \u003cp\u003eGiven the decreased MCT8 expression in OLs at peak neuroinflammation, suggesting impaired T3 transport and trophic deprivation contributing to OL loss, we next examined non\u0026ndash;genomic TH signaling in spinal cord lysates across disease stages [figure \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B]. Lumbo\u0026ndash;sacral spinal cords from EAE\u0026ndash;induced adult female C57BL/6 mice were analysed at pre\u0026ndash;onset, onset, and peak disease (day 30 post\u0026ndash;induction; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B).\u003c/p\u003e \u003cp\u003eWestern blot analysis revealed progressive decreases in AKT, mTOR and PANK2 protein levels at peak disease (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;001, 0\u0026middot;01, and 0\u0026middot;0001 respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Co-immunoprecipitation (co\u0026ndash;IP) using total AKT demonstrated dynamic AKT\u0026ndash;mTOR interactions, with binding at clinical scores 0\u0026ndash;1, with dissociation evident from score 2 onwards. Notably, bound mTOR levels transiently increased at score 1, coinciding with reduced p\u0026ndash;AKT relative to score 0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Reciprocal co\u0026ndash;IP using mTOR confirmed these findings, showing maximal AKT\u0026ndash;mTOR interaction at onset of neurological deficits (clinical score 1; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eA), highlighting a stage\u0026ndash;specific dysregulation of TH\u0026ndash;dependent non\u0026ndash;genomic signalling, potentially mediated via αvβ3 integrin complexes, during neuroinflammation (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eCollectively, these findings indicate that neuroinflammation disrupts the AKT\u0026ndash;mTOR\u0026ndash;PANK2 signalling axis and its multimeric complex, correlating with disease severity and myelin damage.\u003c/p\u003e \u003cp\u003eWe next evaluated whether MCT8⁺ OLs at peak EAE were protected from apoptosis through p-AKT signalling, as suggested by our previous \u003cem\u003ein vitro\u003c/em\u003e findings.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e In the spinal cord, 50\u0026middot;4% of PLP⁺/MCT8⁺ OLs co-expressed p\u0026ndash;AKT in normal appearing white matter (NAWM), compared with 45\u0026middot;1% in periplaque white matter (PPWM), showing a 32\u0026middot;8% PLP\u0026thinsp;+\u0026thinsp;OL reduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eD-E). These data suggest that OLs adjacent to inflammatory lesions are particularly vulnerable to reduced MCT8 expression and diminished p\u0026ndash;AKT, implicating p\u0026ndash;AKT signalling as a compensatory pro\u0026ndash;survival mechanism in mature OLs under neuroinflammatory stress.\u003c/p\u003e \u003cp\u003eReduced MCT8 expression and AKT signaling drive oligodendrocyte loss during peak\u0026ndash;stage EAE in PLP\u0026ndash;YFP transgenic mice despite MCT8\u0026ndash;positive OPC mobilization.\u003c/p\u003e \u003cp\u003eTo investigate how reduced MCT8 expression in mature OLs contributes to cell death, as previously observed in human OL cultures,\u003csup\u003e24\u003c/sup\u003e cleaved caspase\u0026ndash;3 was quantified in PLP\u0026ndash;YFP\u003csup\u003e+\u003c/sup\u003e mice at peak EAE (supplementary Fig.\u0026nbsp;7A\u0026ndash;C). Among MCT8⁺ cells within and around inflammatory lesions, only\u0026thinsp;~\u0026thinsp;18.3% co\u0026ndash;expressed cleaved caspase\u0026ndash;3 (supplementary Fig.\u0026nbsp;7B). In PPWM, ~\u0026thinsp;17% of mature PLP\u0026ndash;YFP\u003csup\u003e+\u003c/sup\u003e OLs exhibited cleaved caspase\u0026ndash;3\u0026ndash;dependent apoptosis (supplementary Fig.\u0026nbsp;7C), suggesting partial resistance to apoptosis in MCT8\u003csup\u003e+\u003c/sup\u003e OLs. However, OL loss remained significant (~\u0026thinsp;23%; Fig.\u0026nbsp;8D\u0026ndash;E), indicating additional death pathways, possibly ferroptosis but need appropriate validation.\u003c/p\u003e \u003cp\u003eWe next investigated whether MCT8\u0026ndash;deficient OL apoptosis near inflammatory lesions promotes expansion of MCT8⁺ OPCs, a lineage previously shown to activate in the optic nerve. MCT8⁺/PDGFRα⁺ OPCs were increased in inflamed optic nerves compared with non\u0026ndash;lesion and showed elevated p\u0026ndash;AKT expression (supplementary Fig.\u0026nbsp;8A-B). Similar findings were observed in the spinal cord, where PDGFRα⁺/P-AKT⁺ cells were sparse in the PPWM (~\u0026thinsp;95 cells/mm\u0026sup2;), but 66.9% expressed MCT8 (supplementary Fig.\u0026nbsp;8C).\u003c/p\u003e \u003cp\u003eTo further characterize remyelinating populations, BCAS1⁺ pro-myelinating OPCs, enriched near MS lesions and mice that lack this gene display hypomyelination, were examined. These cells were more abundant (~\u0026thinsp;638 cells/mm\u0026sup2;) in PPWM, with 34.4% co\u0026ndash;expressing MCT8 (supplementary Fig.\u0026nbsp;8D-F). Among BCAS1⁺/p\u0026ndash;AKT⁺ cells, 58.4% were MCT8⁺, suggesting a link between MCT8 expression and p\u0026ndash;AKT signalling in viable OPCs near lesions.\u003c/p\u003e \u003cp\u003eAs mTOR signalling upstream of AKT is known to regulate OPC-mediated remyelination, we examined p-mTOR in BCAS1⁺ OPCs. Approximately 52.1% were p-mTOR⁺ (supplementary Fig.\u0026nbsp;8G-H), suggesting additional upstream regulators of AKT activation in BCAS1⁺/p-AKT⁺ OPCs (41.3%) within PPWM (supplementary Fig.\u0026nbsp;8F). Whether these p-mTOR⁺ OPCs are directly regulated by MCT8-dependent signalling during neuroinflammation remains to be clarified.\u003c/p\u003e \u003cp\u003eA detailed quantitative analysis of OL apoptosis, OPC activation, and associated MCT8\u0026ndash;AKT\u0026ndash;mTOR signalling is provided in the Supplementary Information.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMS is a debilitating neurological disorder of the CNS that involves axonal demyelination and neurodegeneration. Over the past two decades, several disease modifying therapies (DMTs) have been developed for the treatment of the multiphasic representations of MS.\u003csup\u003e34\u003c/sup\u003e Despite the major advancements, most drugs are only suitable for the treatment of the relapsing\u0026ndash;remitting multiple sclerosis phase but not its progressive form.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Therefore, there is an immediate unmet medical need for patients transitioning to the progressive form of disease.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Prior to addressing this, we need to establish the pathogenic mechanisms that are driving CNS injury during active neuroinflammation, both in its acute and chronic active (or indeed inactive) phases of the disease. Therefore, this study addresses key mechanistic aspects of OL damage and demyelination during active neuroinflammation.\u003c/p\u003e \u003cp\u003eIn this study, we identified \u003cem\u003ein vivo\u003c/em\u003e MCT8 expression in OLs during normal mouse brain development, co\u0026ndash;expressed with oligodendroglial markers. Persistent MCT8 expression in precursor cells within and around the SVZ throughout development suggests a key role in regulating metabolism, as intracellular T3 is essential for OPC proliferation, myelin synthesis, and mature OL survival.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e This is consistent with the proposed function for transportation of TH across the BBB but we report for the first time, utilizing the PLP\u0026ndash;YFP\u003csup\u003e+\u003c/sup\u003e transgenic model the importance of TH metabolism in spinal cord of OLs.\u003c/p\u003e \u003cp\u003eWe demonstrated oligodendroglial expression of MCT8 and MCT10 is reduced during neuroinflammatory\u0026ndash;driven demyelination. Both transporters were downregulated during peak\u0026ndash;chronic stages of EAE which may be related to oligodendrogliopathy, as tissue destruction occurs leading to progressive neurologic symptoms and myelin degeneration. This aligns with previous reports of cellular hypothyroidism during EAE, which disrupts TH\u0026ndash;dependent processes essential for OPC maturation into myelinating OLs.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Moreover, our recent \u003cem\u003ein vitro\u003c/em\u003e study has demonstrated the specific MCT8\u0026ndash;deficiency in human OPCs promoted their cell death.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e This may indicate that OL apoptosis results from downregulated MCT8 expression causing an acute deprivation in TH\u0026ndash;dependent metabolic support for these cells. However, co\u0026ndash;expression of these cells with cleaved caspase\u0026ndash;3 indicated that only a subset of mature MCT8\u003csup\u003e+\u003c/sup\u003e OLs undergo apoptosis. Whether this reflects secondary pro\u0026ndash;inflammatory mechanisms causing MCT8 deprivation through OLs loss in the white matter requires further elucidation. This also calls into question if the remaining subset of detectable OLs which do not show the expression of MCT8 may be undergoing alternative cell death pathways, such as necrosis (uncontrolled cell death) and ferroptosis (oxidative stress\u0026ndash;induced cell death).\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Further work is required to resolve some of these fundamental scientific questions and understand how TH support can indeed protect the CNS OLs from cell death in the context of neuroinflammation.\u003c/p\u003e \u003cp\u003eTo abrogate oligodendroglial cell death, we need to be able to regulate downstream p\u0026ndash;AKT and mTOR signaling.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Indeed, these pathways are activated during OPC differentiation and thereby support OL survival and CNS repair in demyelinating conditions.\u003c/p\u003e \u003cp\u003eMany extracellular signals that regulate OL survival converge on AKT phosphorylation.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Experimental inhibition of AKT induces OL apoptosis even in the presence of mitogens such as neuregulin, whereas constitutively active AKT enhances CNS myelination in transgenic models.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Our data suggest that MCT8\u003csup\u003e+\u003c/sup\u003e mature OLs may be protected from apoptotic cell death during neuroinflammation through the downstream activation of p\u0026ndash;AKT.\u003c/p\u003e \u003cp\u003eThese data suggest that MCT8\u0026ndash;mediated TH transport is critical for OL survival, likely through non\u0026ndash;genomic p\u0026ndash;AKT activation. Beyond maintaining mature OL viability and myelin integrity, p-AKT signaling may drive remyelination by promoting OPC differentiation from anatomical areas in the CNS where they can be expanded from. We demonstrated here that the 58% of p\u0026ndash;AKT\u003csup\u003e+\u003c/sup\u003e OPCs co\u0026ndash;expressed MCT8 in the PPWM spinal cord. This may suggest that in the presence of MCT8, TH is able to enter OPCs (PDGFRα\u003csup\u003e+\u003c/sup\u003e and BCAS1\u003csup\u003e+\u003c/sup\u003e) and stimulate the downstream signalling of p\u0026ndash;AKT via genomic and non\u0026ndash;genomic signalling pathways for cell growth and survival.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eImportantly, the upregulation mTOR signalling upstream of the PI3K\u0026ndash;AKT pathway is critical for OPC survival and proliferation, as its loss reduces myelin protein synthesis and causes hypomyelination.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e The AKT and mTOR pathway has also been shown to promote the differentiation of OPCs \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Our findings further suggest that mTOR may act in concert with p-AKT, but further experiments may allow us to establish direct mechanistic evidence that identify MCT8 as a key driver of remyelination.\u003c/p\u003e \u003cp\u003eHuman chronic active demyelinating lesions of frontal lobe white matter from pwMS, demonstrated metabolic and proteomic alterations. The key TH transporters and metabolic enzymes\u0026mdash;MCT8, MCT10, OATP1C1, DIO2, and DIO3\u0026mdash;as well as components of the AKT\u0026ndash;mTOR\u0026ndash;PANK2 signalling pathway, were dysregulated in MS frontal white matter lysates. These proteomic alterations were supported by untargeted metabolomic analysis, which revealed disruption of the pantothenic acid and CoA biosynthesis pathway in progressive MS\u0026mdash;a mitochondrial pathway previously shown to be downstream of AKT\u0026ndash;mTOR\u0026ndash;PANK2.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eComplementary FTIR and OPTIR imaging confirmed pronounced lipid degradation within lesions, evidenced by reduced CH stretching associated with lipids, while protein-related Amide I and II bands remained largely unchanged. These FTIR and OPTIR features are consistent with lipid peroxidation and oxidative stress\u0026ndash;induced myelin damage, supporting ongoing myelin degeneration linked to impaired mitochondrial acetyl-CoA metabolism.\u003c/p\u003e \u003cp\u003eBy understanding the potential molecular mechanisms of MCT8 deficiency during different neuroinflammatory challenges within the CNS, we were able to incorporate these findings in a large\u0026ndash;scale preclinical study that has utilized MCT8\u0026ndash;independent TH analogues to rescue OL dystrophy during progressive neuroinflammation and to limit neurological decline. Such interventions may hold promise to limit further degeneration and enhance remyelination in conditions such as progressive MS.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHuman post-mortem tissue\u003c/h2\u003e \u003cp\u003eHuman research was approved by the Monash University Human Research Ethics Committee (HREC) (#34474 and #CF13/1646-2013000831) and met the requirements of the National Statement on Ethical Conduct in Human Research (NHMRC). Post\u0026ndash;mortem CNS tissue (frontal lobe white matter), provided by the Victorian Brain Bank Network (VBBN), included tissue from: NNDC donors (n\u0026thinsp;=\u0026thinsp;10); other neurological disease control donors, including AD (n\u0026thinsp;=\u0026thinsp;6), FTD (n\u0026thinsp;=\u0026thinsp;16), HD (n\u0026thinsp;=\u0026thinsp;4), and MS donors with chronic\u0026ndash;active lesions (n\u0026thinsp;=\u0026thinsp;40). Participant de\u0026ndash;identified details of sex, age, weight, post\u0026ndash;mortem interval (PMI) and disease type were provided with the archival donor tissue (See supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Post\u0026ndash;mortem interval did not exceed 73 hours h. All samples were fixed with 10% formalin and blocked using optical cutting temperature (OCT) \u0026ndash;mounting medium and transferred to a Leica cryo\u0026ndash;microtome at \u0026minus;\u0026thinsp;18\u0026deg;C, to generate 20 \u0026micro;m cryosections that were thaw\u0026ndash;mounted onto Superfrost Plus slides (Thermo Scientific, J1800AMNZ) and stored at -80\u0026deg;C for immunofluorescence and histochemical staining. Frozen frontal lobe white matter blocks (400\u0026ndash;500 mg) from the same lesion and patient were stored at -80\u0026deg;C in preparation for western blot and metabolomic studies.\u003c/p\u003e \u003cp\u003eIn addition to the frontal white matter sections, tissue samples from the subventricular zone, ventral and dorsolateral spinal cord, cerebral cortex, periventricular white matter and cerebellum of individuals with SPMS (n\u0026thinsp;=\u0026thinsp;8) were provided by VBBN for histochemical and immunofluorescence staining.\u003c/p\u003e \u003cp\u003eFull protocols for histochemical and immunofluorescence staining are provided in the Supplementary Information.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHuman tissue: Fourier transform infrared imaging (FTIR) and photothermal optical infrared (OPTIR) spectroscopy\u003c/h3\u003e\n\u003cp\u003eTo preserve tissue morphology, 20 \u0026micro;m cryosections of frontal white matter from MS cases (n\u0026thinsp;=\u0026thinsp;10) were freeze\u0026ndash;dried on glass slides for infrared spectroscopic analysis. FTIR chemical imaging was performed at the SISSI-Bio beamline (Elettra Sincrotrone Trieste, Italy)\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e using a Bruker Hyperion II microscope coupled to an INVENIO-II interferometer with a 128\u0026times;128-pixel focal plane array (FPA) detector. Spectra were acquired using 8 scans per pixel, a spectral resolution of 8 cm⁻\u0026sup1;, and 4\u0026times;4 binning with a 15\u0026times; Cassegrain objective and condenser. Mosaics of multiple tiles were recorded to capture the entire tissue section.\u003c/p\u003e \u003cp\u003eOptical photothermal infrared (O-PTIR) measurements were obtained using a mid-IR quantum cascade laser (QCL) operating at 100 kHz repetition rate as the pump beam, and a continuous-wave 532 nm laser as the visible probe. Spectra were collected from selected tissue arrays previously characterized by FTIR imaging to directly compare demyelinating and non-lesioned regions. The infrared power was maintained at 5%, using a 40\u0026times; reflective Cassegrain objective (0\u0026middot;78 NA, Pike Technologies) in co-propagation mode. The probe laser power was set at 1% for the avalanche photodiode detector. The spectral range covered 3027\u0026ndash;2795 cm⁻\u0026sup1; and 1800\u0026ndash;791 cm⁻\u0026sup1; with a resolution of 2 cm⁻\u0026sup1;. The system was enclosed and purged with nitrogen to minimize atmospheric water vapor interference. Spectra were acquired over 100 \u0026times; 100 \u0026micro;m fields, with a section thickness of 4 \u0026micro;m for each region.\u003c/p\u003e \u003cp\u003eSpectral data were processed and analysed using Quasar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://quasar.codes).2\u003c/span\u003e\u003cspan address=\"https://quasar.codes).2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e,3 For FTIR imaging, the following integration bands were used: CH₂ (2900\u0026ndash;2950 cm⁻\u0026sup1;), CH₃ (2948\u0026ndash;2980 cm⁻\u0026sup1;), lipid (2800\u0026ndash;3000 cm⁻\u0026sup1;), olefin (3000\u0026ndash;3027 cm⁻\u0026sup1;), aromatic (3030\u0026ndash;3100 cm⁻\u0026sup1;), and OH (3030\u0026ndash;3365 cm⁻\u0026sup1;). Principal component analysis (PCA) was performed on second-derivative spectra (Savitzky\u0026ndash;Golay 9-point smoothing, 3rd-order polynomial). K\u0026ndash;means clustering with six clusters and random initialization was applied to identify spatially distinct biochemical domains within tissue sections.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMetabolomics\u003c/h2\u003e \u003cp\u003eUntargeted metabolomic profiling was performed on ~\u0026thinsp;30 mg cryo\u0026ndash;pulverised human frontal white matter, as previously described with minor modifications.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e Frozen human frontal white matter (from NNDC, AD, FTD, and MS) were cryo-pulverized (approximately 30 mg powder). The samples cryo-pulverised using a pre-chilled mortar and pestle on a bed of dry ice. Approximately 40 mg of pulverised tissue (range 30\u0026ndash;56 mg) shipped on dry ice to the Monash Proteomics and Metabolomics Platform (MPMP), where samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until preparation and liquid chromatography\u0026ndash;mass spectrometry (LC\u0026ndash;MS) analysis. Upon inspection, tissue was further ground in Eppendorf tubes using a liquid nitrogen\u0026ndash;cooled mini mortar (Sigma, Australia; PN Z756377-1EA) to improve homogenisation. Extraction was performed using 20 \u0026micro;L of ice\u0026ndash;cold extraction solvent (2:6:1 chloroform/methanol/water with 2 \u0026micro;M CCPT [CHAPS, CAPS, PIPES and TRIS] as internal standards) per mg of tissue. The mixture was vortexed (3 \u0026times; 10 sec), sonicated (10 min, ice\u0026ndash;water bath), and centrifuged (10 min, 4\u0026deg;C) to remove debris. Supernatants were stored at -80\u0026deg;C. For pooled biological quality control (pbQC), 10 \u0026micro;L of reconstituted lysates from each sample were combined.\u003c/p\u003e \u003cp\u003eLC\u0026ndash;MS was performed using a Dionex RSLC3000 UHPLC system coupled to a Q\u0026ndash;Exactive Plus Orbitrap mass spectrometer (Thermo Scientific, Australia). Samples were analysed by hydrophilic interaction liquid chromatography (HILIC) following a previously described protocol.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Chromatographic separation was achieved using a ZIC\u0026ndash;p (HILIC) column (5 \u0026micro;m, 150 \u0026times; 4\u0026middot;6 mm, 25\u0026deg;C; Merck Millipore, Australia) with a gradient elution of 20 mM ammonium carbonate (solvent A) and acetonitrile (solvent B) under the following conditions (time\u0026ndash;%B): 0 min, 80%; 15 min, 50%; 18 min, 5%; 21 min, 5%; 24 min, 80%; 32 min, 80%. The flow rate was maintained at 300 \u0026micro;L/min. Samples were maintained at 6\u0026deg;C in the autosampler, and 10 \u0026micro;L was injected per run. Mass spectrometry was conducted at 70 000 resolutions in positive (+\u0026thinsp;4 kV) and negative (\u0026minus;\u0026thinsp;3\u0026middot;5 kV) electrospray ionisation modes (capillary temperature 300\u0026deg;C; sheath gas flow rate 50; auxiliary gas flow rate 20; probe temperature 120\u0026deg;C To support accurate metabolite identification, a library of approximately 400 authentic standards was analysed before sample acquisition, and retention times were recorded for each compound. This library also informed a retention time prediction model used to assign putative identities to metabolites not represented in the reference set.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRaw LC\u0026ndash;MS spectra were processed using IDEOM, with msConvert (ProteoWizard) for mzXML conversion\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and XCMS for peak detection and generation of. peakML files \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, and MzMatch for alignment and filtering,\u003csup\u003e52\u003c/sup\u003e followed by further pre\u0026ndash;processing, organisation, and quality assessment in IDEOM \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMetabolite intensity peaks were analyzed in \u003cem\u003eR\u003c/em\u003e (v4\u0026middot;2\u0026middot;1). Missing values were imputed using the k\u0026ndash;nearest neighbours (kNN) algorithm (neighbours\u0026thinsp;=\u0026thinsp;5, sample_max\u0026thinsp;=\u0026thinsp;50, feature_max\u0026thinsp;=\u0026thinsp;50, by = \u0026ldquo;features\u0026rdquo;). Data were normalised using probabilistic quotient normalisation, log₁₀ transformation, and Pareto scaling within the \u003cem\u003estructToolbox\u003c/em\u003e package.\u003c/p\u003e \u003cp\u003ePCA visualised sample variance, and two\u0026ndash;tailed Student\u0026rsquo;s t\u0026ndash;tests (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05, FDR\u0026ndash;adjusted) were applied for pairwise comparisons. Significant metabolite changes were visualised using volcano plots (\u0026ndash;log₁₀[FDR\u0026ndash;adjusted \u003cem\u003ep\u003c/em\u003e] vs log₂[fold change], fold change threshold 1\u0026middot;5) and heatmaps and violin plot generated in \u003cem\u003eR\u003c/em\u003e (\u003cem\u003estruct\u003c/em\u003e, \u003cem\u003estructToolbox\u003c/em\u003e, \u003cem\u003eheatmap\u003c/em\u003e, and \u003cem\u003eggplot2\u003c/em\u003e packages).\u003c/p\u003e \u003cp\u003ePathway enrichment and topology analyses were conducted in MetaboAnalyst 6\u0026middot;0 using KEGG identifiers and the \u003cem\u003eHomo sapiens\u003c/em\u003e pathway library. The Global Test algorithm was applied for enrichment analysis with relative betweenness centrality used as the primary metric for topology analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProteomics\u003c/h3\u003e\n\u003cp\u003eProtein lysates from mouse lumbo\u0026ndash;sacral spinal cord and human frontal white matter were prepared in RIPA buffer with protease and phosphatase inhibitors. Protein concentrations were determined by bicinchoninic acid (BCA) assay. For immunoblotting, 10 \u0026micro;g protein (30 \u0026micro;g for mTOR) was separated on NuPAGE gels, transferred to PVDF membranes, and probed with primary and HRP\u0026ndash;conjugated secondary antibodies (supplementary. table2). Detection used enhanced chemiluminescence with a ChemiDoc\u0026trade; Touch System (Bio\u0026ndash;Rad) and densitometry (Image Lab v6.1). Co\u0026ndash;immunoprecipitation (mouse) and immunoprecipitation (human) were performed on 100 \u0026micro;g protein. Full protocols are provided in the Supplementary Information.\u003c/p\u003e\n\u003ch3\u003eAnimal models\u003c/h3\u003e\n\u003cp\u003eC57BL/6 na\u0026iuml;ve mice were analyzed postnatally to assess MCT8 expression during brain development. Experimental autoimmune encephalomyelitis (EAE) was induced in this strain to enable proteomic, immunofluorescence, histochemical, and flow cytometry analyses.\u003c/p\u003e \u003cp\u003eA subset of mice received intraocular injections of rAAV2\u0026ndash;GFP to transduce and label optic nerve axons, followed by EAE induction.\u003c/p\u003e \u003cp\u003ePlp\u0026ndash;CreERT2::ROSA26\u0026ndash;stop\u0026ndash;EYFP transgenic mice were used to evaluate MCT8 expression in mature OLs within na\u0026iuml;ve spinal cord. These mice were subsequently subjected to EAE to assess OL loss and alterations in MCT8 and TH signaling around inflammatory lesions.\u003c/p\u003e \u003cp\u003eCuprizone\u0026ndash;induced demyelination was employed for immunofluorescence and transmission electron microscopy (TEM) analyses of the corpus callosum (CC).\u003c/p\u003e \u003cp\u003eAll experimental protocols are described in detail in the Supplementary Information.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using GraphPad Prism (v9\u0026middot;2\u0026middot;0) and R (v4\u0026middot;2\u0026middot;1) in RStudio. Data distribution was assessed with Shapiro\u0026ndash;Wilk and Kolmogorov\u0026ndash;Smirnov tests. Two\u0026ndash;group comparisons were conducted using unpaired two\u0026ndash;tailed Student\u0026rsquo;s t\u0026ndash;tests or Mann\u0026ndash;Whitney U tests, as appropriate. For comparisons of more than two groups, one\u0026ndash;way ANOVA with Tukey\u0026rsquo;s post hoc or non\u0026ndash;parametric ANOVA with Dunn\u0026rsquo;s multiple comparisons was used. \u003cem\u003eP\u0026thinsp;\u0026le;\u003c/em\u003e\u0026thinsp;0\u0026middot;05 was considered significant. Sample sizes and specific tests are indicated in figure legends.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability.\u003c/p\u003e\n\u003cp\u003eData available in a public (institutional, general or subject specific) repository that issues datasets with DOIs (non-mandated deposition).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData available on request from the authors.\u003c/p\u003e\n\u003cp\u003eAuthors can confirm that all relevant data are included in the paper and/or its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the contributions of Mary Dass, Michael F Azari, Simon Lee, James Portelli, Salome Bazkurt and Aaron Lewis for the experimental support with animal tissue analysis. Georg Ramm from the Monash Ramaciotti Centre for Cryo Electron Microscopy (Cryo–EM), Samantha from the Alfred Research Alliance–Monash Micro Imaging (ARA–MMI), Robert Brkljaca from the Alfred Research Alliance–Monash Biomedical Imaging (ARA–MBI), for their work and assistance in experiments that have provided data in preparation of this study. The authors acknowledge the facilities and scientific and technical assistance of the National Imaging Facility (NIF), a National Collaborative Research Infrastructure Strategy (NCRIS) capability at ARA–MBI and ARA–MMI and a Technology Research Platform at Monash University. We acknowledge the assistance of Animal Services and the veterinary team at the University of Tasmania, and Drs Thomas Lewis, Phuong Tram Nguyen, and Alastair Fortune of Prof Kaylene Young’s Glial Research Team. Katarina Vogel–Mikus from the Biotechnical Faculty, Department of Biology, University of Ljubljana, Jamnikarjeva 101, 1000, Ljubljana, Slovenia.\u003c/p\u003e\n\u003cp\u003eWe acknowledge support from a Monash University postgraduate scholarship awarded to RE; from Multiple Sclerosis Research Australia and Trish Multiple Sclerosis Research Foundation Postgraduate Scholarship awarded to JYL; from a Multiple Sclerosis Research Australia Postgraduate Scholarship awarded to DN; from MS Australia for a Senior Research Fellowship (21-3-023) awarded to K.M.Y.; and from an EU Horizon Europe Marie Sklodowska–Curie Global Fellowship (101106307) awarded to DEB. We also acknowledge grant support from Multiple Sclerosis Australia (17-0206; 18-0521); the Trish Multiple Sclerosis Research Foundation (19-0673); the Bethlehem Griffiths Research Foundation (BGRF1902); the Medical Research Future Fund (EPCD08), and NeuOrphan Pty Ltd through a Research Services agreement with Monash University (L/341646038.16).\u003c/p\u003e\n\u003cp\u003eAuthor contribution\u003c/p\u003e\n\u003cp\u003eR.E. performed experiments and analysed data directly related to the following data sets: immunofluorescence, metabolomics, proteomics and EAE clinical scoring, contributed to data interpretation and manuscript writing. R.E. generated all figures using various software packages as defined within the methods sections and figure legends with appropriate illustrations generated using Biorender. P.T. performed EAE experiments, edited figures and manuscript. J.Y.L. performed EAE and clinical scoring, conducted electrophysiology, conducted proteomics, completed ontogeny immunofluorescence histology staining and conducted all optic nerve transduction experiments. M.P. conducted cuprizone studies and tissue immunofluorescence experiments. D.N., O.E. and S.Y. performed tissue immunofluorescence counting via ImageJ (Fiji). \u0026nbsp;M.J.K. performed fate-mapping analysis on PLP-YFP+ transgenic mice, EAE induction and clinical scoring. E.O. performed counting via ImageJ (Fiji) and edited the manuscript. M.M. performed tissue immunofluorescence counting via ImageJ (Fiji) and interpreted data. I.S., Z.R., N.T.L., D.K.W., S.M. and W.O. validated and interpreted data along with edited manuscript. C.M. conducted neuropathological reporting of human biobanked tissue. D.E.B., G.B. B.W., P.H. conducted FTIR and OPTIR experiments and interpreted data from the spectral images. K.Y.M generated PLP-YFP+ transgenic mouse line, completed animal ethics submissions, edited the manuscript. K.J.J. and C.K.B performed metabolomic analysis and interpretation of data along with edited manuscript. I.C. performed tissue analysis through software packages outlined in the methods section. N.G. contributed unpublished reagents/analytic tools, assessed human clinical data prepared in Supplementary Table 1. S.P. conceptualized and designed all experiments, performed data analysis, wrote the first draft of the manuscript and provided edited feedback through the review process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditional information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information\u0026nbsp;\u003c/strong\u003eis provided as a PDF file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting financial interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SP is a co–founder, holds equity and is the Chief Scientific Officer for NeuOrphan Pty Ltd which seeks to develop DITPA for the treatment of neurological conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data presented in this manuscript are defined within the Australian Provisional Patent Application (\u003cstrong\u003e2025901533\u003c/strong\u003e), in the name of NeuOrphan Pty Ltd. Entitled: \u003cstrong\u003eNOVEL TREATMENTS FOR DEMYELINATING DISORDERS\u003c/strong\u003e. NeuOrphan Pty Ltd. has commercial interests in the current technology for research and clinical development purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLee, Y., et al.: Oligodendroglia metabolically support axons and contribute to neurodegeneration. 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Chem. \u003cb\u003e83\u003c/b\u003e, 2786\u0026ndash;2793 (2011). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1021/ac2000994\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1021/ac2000994\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8429369/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8429369/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOligodendrocytes (OLs) myelinate central nervous system (CNS) axons and provide metabolic support to maintain axonal integrity. Thyroid hormone (TH) is a mitogen for oligodendroglial precursor cells (OPCs) maturation into myelinating OLs. Cellular uptake of TH is mediated by monocarboxylate transporter 8 (MCT8; encoded by \u003cem\u003eslc16a2\u003c/em\u003e), and its dysfunction results in intracellular triiodothyronine (T3) deprivation, leading to hypomyelination and myelin degeneration during neuroinflammation. We showed that MCT8 expression is maintained in OPCs residing within the sub\u0026ndash;ventricular zone (SVZ) throughout CNS development, suggesting a role during OL development. We identified MCT8 deficiency during neuroinflammatory and cuprizone demyelination models, as well as in secondary progressive multiple sclerosis (SPMS). These conditions were associated with dysregulated AKT\u0026ndash;mTOR\u0026ndash;PANK2 signaling and abrogated Co Enzyme A and lipid synthesis pathways in the CNS during myelin degeneration. Hence, neuroprotection during SPMS maybe achieved by overcoming MCT8 deficiencies in OLs.\u003c/p\u003e","manuscriptTitle":"Delineating the role of monocarboxylate transporter 8 (MCT8) in the context of neuroinflammation–mediated oligodendrocytopathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-23 12:29:59","doi":"10.21203/rs.3.rs-8429369/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2f2e7696-0d7e-4d49-b808-ea8e259ae6f9","owner":[],"postedDate":"January 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":60866474,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Multiple sclerosis"},{"id":60866475,"name":"Health sciences/Neurology/Neurological disorders/Multiple sclerosis"}],"tags":[],"updatedAt":"2026-01-23T12:30:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-23 12:29:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8429369","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8429369","identity":"rs-8429369","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}