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. 2026 Jul 13;17:1880997. doi: 10.3389/fphar.2026.1880997

FIGURE 1.

Flowchart illustrating a bioinformatics workflow starting with data extraction from four gene databases, identifying 1,288 genes, followed by analyses including Open-XGr, functional annotation, and enrichment analysis. The workflow leads to bioinformatics and genetics analysis revealing abnormal macrophage activation, focusing on ApoE, bone marrow, and cerebrospinal fluid, supported by icons, charts, and network diagrams.

Comprehensive workflow of the bioinformatics and genetic analysis for inborn errors of metabolism (IEM). Genes associated with IEM were extracted from multiple databases resulting in a total of 1,288 genes. Disease ontology enrichment analysis using the Open-XGR platform confirmed that these genes were highly enriched in IEM-related pathways. Functional annotation and enrichment analyses were then performed using cell-related databases such as the Human Cell Landscape, Cellular Component, and Tabula Sapiens. Integration of bioinformatics findings and descriptive clinical observations prioritized APOE as a candidate gene associated with lipid metabolism and macrophage-related signatures in IEM.