Unraveling Single-Cell Regulatory Networks in iPSC-Derived Neurons from Veterans with Gulf War Illness
Gulf War Illness (GWI) is a complex condition affecting Veterans, and its underlying neuropathological mechanisms remain unclear. Patient-derived induced pluripotent stem cells (iPSCs) offer a platform to model the disease in vitro.Objective: To map transcriptomic landscapes and infer single-cell gene regulatory networks (scGRNs) in iPSC-derived neurons from symptomatic and non-symptomatic Gulf War Veterans to identify genes and pathways implicated in GWI pathophysiology and predisposition.Design, Setting, and Participants: This study utilized iPSCs generated from symptomatic GWI Veterans and non-symptomatic GWI Veteran controls. Neurons were differentiated from these iPSCs for analysis. MainOutcomes and Measures: Single-cell RNA sequencing (scRNAseq) was used to generate transcriptomic data. Machine learning algorithms were applied to infer and compare scGRNs between the symptomatic and non-symptomatic groups, identifying key regulatory differences.Results: Analysis of scRNAseq data revealed significant differences in gene expression profiles between neurons derived from symptomatic and non-symptomatic Veterans. scGRN inference identified distinct regulatory modules associated with GWI symptom status. Key transcription factors driving these differences were identified, along with target genes involved in neuroinflammatory responses, synaptic signaling, and stress response pathways. These findings point towards specific molecular dysregulations contributing to GWI neuropathology.Conclusions and Relevance: This study demonstrates the utility of iPSC-derived neurons coupled with single-cell transcriptomics and computational network inference for investigating GWI. The identified differences in scGRNs provide novel insights into the molecular underpinnings of the illness and highlight potential targets for future diagnostic and therapeutic strategies.