Association between craniosynostosis and phospholipid metabolism: Insights from single-cell and transcriptomic analysis

颅缝早闭与磷脂代谢的关联:来自单细胞和转录组分析的启示

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Abstract

Craniosynostosis is a common defect in the craniofacial structure of children, yet its pathogenesis remains unclear. Current research focuses mainly on bone-related genetic mutations, with less emphasis on lipid metabolism disorders. Hence, it is imperative to investigate the underlying mechanisms from various perspectives. We investigated the association between craniosynostosis and phospholipid metabolism through a multi-omics approach. This included Mendelian randomization (MR) to assess causal relationships of lipid traits, transcriptomic differential analysis of clinical samples, and single-cell RNA sequencing of murine cranial sutures to identify key cell subtypes. Furthermore, drug-target MR and network pharmacology were conducted to explore the potential therapeutic repurposing of statins. MR analysis revealed a significant protective effect of phospholipids in very low-density lipoprotein remnants against craniosynostosis. Drug-target MR targeting HMGCR indicated a protective trend (OR = 0.79) for statins, consistent with the lipid-metabolic link, although statistical significance was limited by sample size. Transcriptomic analysis identified MORN5 as a key upregulated gene enriched in glycerophospholipid metabolism. Single-cell RNA sequencing identified a specific osteogenic subtype (C4) and lipid-metabolic subtypes (C5/C6) driving the disease. Pharmacological prediction and molecular docking further suggested that Rosuvastatin could target MORN5 and epidermal growth factor receptor, showing high binding affinity (<-5 kcal/mol). Our findings provide robust evidence that phospholipid metabolism plays a critical role in craniosynostosis. While the genetic evidence for statins is exploratory, the consistent protective trend and molecular docking results suggest a potential therapeutic avenue that warrants further investigation in larger cohorts and experimental models.

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