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Zhuoting Zhu

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Open access Aug 2026

Spatial multi‐omics unveils sphingolipid metabolic reprogramming within the retinal pathological niche

Abstract Retinal ischemia‐reperfusion (RIR) injury is a central mechanism underlying irreversible vision loss in glaucoma and other retinal diseases, yet the spatial organization of the pathogenic microenvironment remains poorly understood. Here, we constructed a high‐resolution, whole‐eye spatial multi‐omics atlas integrating Stereo‐seq transcriptomics and MALDI‐MSI‐based metabolomics to capture the early molecular events in the RIR mouse model. Spatially, retinal ganglion cell (RGC) interactions with surrounding cells were markedly reduced after injury, whereas immune–glial interactions were enhanced, revealing a shift from a neuron‐centered to an immunometabolic state. Within the ganglion cell layer (GCL), the primary pathological locus, we identified Trem2 + microglia that expand in situ, establish close proximity to degenerating RGCs, and exhibit strong spatial association with dysregulated sphingolipid metabolism. Mechanistically, using Trem2 knockout mice and microglia‐specific Trem2 siRNA knockdown, we demonstrate that TREM2 directly binds to SPTLC2, the rate‐limiting enzyme of de novo sphingolipid biosynthesis, driving ceramide‐centric metabolic reprogramming that modulates the AKT‐mTOR signaling axis and amplifies inflammatory activation. Pharmacological inhibition of serine palmitoyl transferase (SPT) with myriocin reverses this cascade, protecting RGCs. Multi‐omics integration of human glaucoma aqueous humor datasets further reveals conserved upregulation of sphingolipid biosynthetic enzymes, sphingolipid metabolites, and lipid‐sensing immune effectors, offering preliminary translational clues. Collectively, our findings reveal that spatially defined immunometabolic remodeling—in which Trem2 + microglia are central—converges on sphingolipid metabolism as a druggable regulatory axis, with the TREM2‐SPTLC2 interface thus emerging as a new therapeutic opportunity for retinal neurodegenerative diseases.

Yun-Hong Shi, Jinpei Lin, Yi Wu et al. · 0 citations