Therapeutic targets for diabetic nephropathy identified by druggable genome mendelian randomization: the role of the gut microbiota-metabolite axis.

Differential expression analysis identified 8,913 differentially expressed genes (DEGs) in diabetic nephropathy datasets.

• DEGs were identified from publicly available gene expression datasets related to diabetic nephropathy.
• These DEGs served as the starting pool for downstream Mendelian randomization and machine learning analyses.
• The large number of DEGs reflects the broad transcriptional dysregulation associated with DN pathogenesis.

Mendelian randomization analysis identified 1,263 druggable genes potentially causally involved in diabetic nephropathy pathogenesis.

• MR analysis was applied to establish causal associations between druggable genome genes (DGGs) and DN.
• 1,263 genes were identified as both potentially involved in DN pathogenesis and as candidate drug targets.
• This approach leverages genetic variants as instrumental variables to infer causality, reducing confounding compared to observational studies.

FOS and IL12A were selected as key candidate therapeutic target genes for diabetic nephropathy using machine learning algorithms.

• Machine learning algorithms were applied to the MR-prioritized gene list to further narrow down key genes.
• Both FOS and IL12A were significantly downregulated in DN samples.
• RT-qPCR validation in blood samples confirmed the downregulation of both genes (p < 0.05).
• These two genes were selected from the broader pool of 1,263 MR-identified candidate genes.

A predictive nomogram model incorporating FOS and IL12A achieved an area under the curve (AUC) greater than 0.7 for diabetic nephropathy.

• The nomogram was constructed to assess the predictive utility of the two key genes.
• AUC > 0.7 indicates acceptable discriminative ability for DN diagnosis or risk stratification.
• This model provides a preliminary framework for clinical translation of these biomarkers.

Functional enrichment analysis highlighted the mTOR complex 1 (mTORC1) signaling pathway as a key biological mechanism associated with FOS and IL12A in diabetic nephropathy.

• Gene Set Enrichment Analysis (GSEA) was used to identify enriched pathways.
• mTORC1 signaling was the most prominently highlighted pathway.
• mTORC1 is a known regulator of cellular metabolism and has prior implications in kidney disease progression.

FOS expression showed a strong positive correlation with neutrophil infiltration in diabetic nephropathy tissue.

• The correlation coefficient between FOS expression and neutrophil infiltration was r = 0.856 (p < 0.05).
• Immune infiltration analysis was performed to assess the relationship between gene expression and immune cell composition.
• This strong positive correlation suggests FOS may play a role in neutrophil-mediated inflammatory processes in DN.

IL12A expression showed an inverse correlation with M2 macrophage infiltration in diabetic nephropathy.

• The correlation coefficient between IL12A expression and M2 macrophage infiltration was r = -0.377 (p < 0.05).
• M2 macrophages are generally considered anti-inflammatory and tissue-remodeling immune cells.
• The inverse correlation suggests that reduced IL12A in DN may be associated with altered macrophage polarization states.

Molecular docking revealed that both FOS and IL12A may stably bind to the gut microbiota-derived metabolite butyrate.

• Binding energy for FOS with butyrate was -7.3 kcal/mol.
• Binding energy for IL12A with butyrate was -7.0 kcal/mol.
• IL12A also demonstrated binding to trimethylamine (TMA), another gut microbiota metabolite, with a binding energy of -6.4 kcal/mol.
• Lower (more negative) binding energies indicate more stable molecular interactions.

Specific gut microbiota species, including Faecalibacterium prausnitzii and Lactobacillus acidophilus, showed preliminary associations with the identified therapeutic targets.

• These microbiota associations were identified as preliminary correlations supporting the gut microbiota-metabolite axis hypothesis.
• Faecalibacterium prausnitzii is a known butyrate-producing bacterium, consistent with the butyrate docking findings.
• Lactobacillus acidophilus is associated with various metabolic and immune regulatory functions.
• The authors describe these as 'preliminary associations' requiring further validation.

Single-cell RNA sequencing analysis identified proximal convoluted tubule cell 1 (PCT1) as a central cell type in diabetic nephropathy, with altered cell communication and differentiation trajectories.

• scRNA-seq analysis included pseudotime trajectory and cell communication analysis.
• PCT1 cells showed altered differentiation trajectories in the DN context.
• FOS expression showed dynamic changes across pseudotime in PCT1 cells.
• IL12A remained persistently downregulated across cell states in PCT1 cells.
• The authors describe these scRNA-seq findings as 'preliminary analysis.'