Elevated Galectin-3 Is Associated with Aging, Multiple Sclerosis, and Oxidized Phosphatidylcholine-Induced Neurodegeneration
Bibliographic record
Abstract
Aging is a significant risk factor associated with the progression of CNS neurodegenerative diseases including multiple sclerosis (MS). Microglia, the resident macrophages of the CNS parenchyma, are a major population of immune cells that accumulate in MS lesions. While they normally regulate tissue homeostasis and facilitate the clearance of neurotoxic molecules including oxidized phosphatidylcholines (OxPCs), their transcriptome and neuroprotective functions are reprogrammed by aging. Thus, determining the factors that instigate aging associated microglia dysfunction can lead to new insights for promoting CNS repair and for halting MS disease progression. Through single-cell RNA sequencing (scRNAseq), we identified Lgals3 , which encodes for galectin-3 (Gal3), as an age upregulated gene by microglia responding to OxPC. Consistently, excess Gal3 accumulated in OxPC and lysolecithin-induced focal spinal cord white matter (SCWM) lesions of middle-aged mice compared with young mice. Gal3 was also elevated in mouse experimental autoimmune encephalomyelitis (EAE) lesions and more importantly in MS brain lesions from two male and one female individuals. While Gal3 delivery alone into the mouse spinal cord did not induce damage, its co-delivery with OxPC increased cleaved caspase 3 and IL-1β within white matter lesions and exacerbated OxPC-induced injury. Conversely, OxPC-mediated neurodegeneration was reduced in Gal3 −/− mice compared with Gal3 +/+ mice. Thus, Gal3 is associated with increased neuroinflammation and neurodegeneration and its overexpression by microglia/macrophages may be detrimental for lesions within the aging CNS. SIGNIFICANCE STATEMENT Aging accelerates the progression of neurodegenerative diseases such as multiple sclerosis (MS). Understanding the molecular mechanisms of aging that increases the susceptibility of the CNS to damage could lead to new strategies to manage MS progression. Here, we highlight that microglia/macrophage-associated galectin-3 (Gal3) was upregulated with age exacerbated neurodegeneration in the mouse spinal cord white matter (SCWM) and in MS lesions. More importantly, co-injection of Gal3 with oxidized phosphatidylcholines (OxPCs), which are neurotoxic lipids found in MS lesions, caused greater neurodegeneration compared with injection of OxPC alone, whereas genetic loss of Gal3 reduced OxPC damage. These results demonstrate that Gal3 overexpression is detrimental to CNS lesions and suggest its deposition in MS lesions may contribute to neurodegeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".