Analysis of renal transcriptome responses identifies LX-regulated transcriptional networks. Analysis of renal transcriptome responses identifies LX-regulated transcriptional networks. (A and B) Upstream regulator analysis of transcriptome data identifies regulators predicted to be changed between diabetic ApoE−/− mice administered ethanol versus (A) LXA4 or (B) Benzo-LXA4 treatment from weeks 1 to 10. Regulators were identified using the IPA regulation Z-score algorithm according to gene expression changes. A positive or negative Z-score value indicates that a function is predicted to be increased (red color) or decreased (blue color), respectively. Corresponding −Log2P values indicate whether there is a statistically significant overlap between the dataset genes and genes that are known to be regulated by the upstream regulator. All regulators represented on the graph are significantly enriched (Z-score ≥2 or ≤−2; P<0.05). (C and D) Heatmaps of normalized gene expression indicating transcripts displaying significant differential expression (FDR P value <0.05) between diabetic mice administered ethanol (0.1%) versus LXA4 or Benzo-LXA4 from weeks 1 to 10. Expression levels range from blue (low expression) to red (high expression). (E) Box plots indicating expression of genes regulated by both LXA4 and Benzo-LXA4 (egr1, adamtsl3, ngef, lamb3, grem1, and nr4a1). Transcript abundance across all treatment group is shown (*FDR P value <0.05). ID, identifier. Eoin P. Brennan et al. JASN 2018;29:1437-1448 ©2018 by American Society of Nephrology