FAO Sub-Signature Decomposition

Related to Figure 3.

The composite FAO UCell score is elevated in captopril-treated mice (Cohen's d = 0.46, small), yet direct measurement of FAO activity in kidney tissue shows significantly reduced mitochondrial fatty acid oxidation (p = 0.032). This apparent discrepancy is addressed by decomposing the 27-gene FAO signature into three mechanistically distinct sub-groups and computing effect sizes for each.

Gene sub-groups

# Transport / CPT1 (rate-limiting step; CPT1 is inhibited by malonyl-CoA)
fao_transport_genes <- c(
  "Slc27a1", "Slc27a2", "Slc27a3", "Slc27a4", "Slc27a5",
  "Cd36",
  "Cpt1a", "Cpt1b", "Cpt1c",
  "Cpt2",
  "Slc25a20"
)

# Mitochondrial beta-oxidation enzymes
fao_mitochondrial_genes <- c(
  "Acadl", "Acadm", "Acads", "Acadvl",
  "Echs1",
  "Hadha", "Hadhb",
  "Acaa1", "Acaa2",
  "Eci1", "Eci2",
  "Decr1"
)

# Peroxisomal acyl-CoA oxidases (PPAR-alpha targets)
fao_peroxisomal_genes <- c(
  "Acox1", "Acox2", "Acox3"
)

Step 1 — Score FAO sub-signatures with UCell

captopril_obj <- AddModuleScore_UCell(
  captopril_obj,
  features = list(
    FAO_transport     = fao_transport_genes,
    FAO_mitochondrial = fao_mitochondrial_genes,
    FAO_peroxisomal   = fao_peroxisomal_genes
  ),
  assay = "RNA",
  storeRanks = TRUE
)
# Output columns: FAO_transport_UCell, FAO_mitochondrial_UCell, FAO_peroxisomal_UCell

ren1c_obj <- AddModuleScore_UCell(
  ren1c_obj,
  features = list(
    FAO_transport     = fao_transport_genes,
    FAO_mitochondrial = fao_mitochondrial_genes,
    FAO_peroxisomal   = fao_peroxisomal_genes
  ),
  assay = "RNA",
  storeRanks = TRUE
)

Step 2 — Wilcoxon statistics per sub-signature

for (metric in c("FAO_transport_UCell", "FAO_mitochondrial_UCell", "FAO_peroxisomal_UCell")) {
  capt_sub_stats[[metric]] <- calcStatistics(
    captopril_obj,
    group_var = "condition",
    group1    = "ctrl",
    group2    = "trt",
    metric    = metric
  )
  fwrite(
    capt_sub_stats[[metric]]$celltype_results,
    paste0(parent_dir, "captopril_", gsub("_UCell", "", metric), "_celltype_stats.csv"),
    row.names = FALSE, sep = ","
  )
}

Step 3 — Cohen's d effect sizes per sub-group

cohensD is defined in 5B. Effect sizes compare CKD+ACEi vs Healthy (captopril model) and KO vs WT (Ren1c model):

calcSubsigEffectSizes <- function(seurat_obj, group_var, group1, group2, model_label) {
  meta <- seurat_obj@meta.data
  g1 <- meta[meta[[group_var]] == group1, ]
  g2 <- meta[meta[[group_var]] == group2, ]
  scores <- c("FAO_transport_UCell", "FAO_mitochondrial_UCell", "FAO_peroxisomal_UCell")
  results <- lapply(scores, function(s) {
    d <- cohensD(g1[[s]], g2[[s]])
    data.frame(
      model = model_label, sub_score = gsub("_UCell", "", s),
      group1 = group1, group2 = group2,
      mean_group1 = mean(g1[[s]]), mean_group2 = mean(g2[[s]]),
      cohens_d = d,
      magnitude = case_when(
        abs(d) >= 0.8 ~ "large",
        abs(d) >= 0.5 ~ "medium",
        abs(d) >= 0.2 ~ "small",
        TRUE          ~ "negligible"
      )
    )
  })
  do.call(rbind, results)
}

effect_capt  <- calcSubsigEffectSizes(captopril_obj, "condition", "ctrl", "trt",  "captopril")
effect_ren1c <- calcSubsigEffectSizes(ren1c_obj,     "genotype",  "WT",   "KO",   "ren1c")
effect_all   <- rbind(effect_capt, effect_ren1c)

fwrite(effect_all, paste0(parent_dir, "FAO_subsignature_cohens_d.csv"), row.names = FALSE, sep = ",")

Results (captopril model, ctrl → trt):

In the Ren1^c KO model all three sub-groups are negligible (|d| < 0.11), consistent with the FAO signature elevation being specific to the pharmacologic ACE-inhibitor model.

Step 4 — Individual gene dot plots

The dot plots show percent expressed and average expression for all 27 FAO genes, ordered by sub-group with dashed vertical lines at sub-group boundaries.

all_fao_ordered <- c(fao_transport_genes, fao_mitochondrial_genes, fao_peroxisomal_genes)

makeFaoDotplot <- function(seurat_obj, group_by, group_colors, title_str) {
  genes_present   <- all_fao_ordered[all_fao_ordered %in% rownames(seurat_obj)]
  n_transport     <- sum(fao_transport_genes %in% genes_present)
  n_mitochondrial <- sum(fao_mitochondrial_genes %in% genes_present)
  n_peroxisomal   <- sum(fao_peroxisomal_genes %in% genes_present)
  vlines <- c(n_transport + 0.5, n_transport + n_mitochondrial + 0.5)
  n_groups <- length(unique(seurat_obj@meta.data[[group_by]]))
  label_y  <- n_groups + 0.6

  DotPlot(seurat_obj, features = genes_present, group.by = group_by,
          cols = group_colors, dot.scale = 6) +
    RotatedAxis() +
    ggtitle(title_str) +
    geom_vline(xintercept = vlines, linetype = "dashed", color = "grey50", linewidth = 0.4) +
    coord_cartesian(clip = "off") +
    annotate("text",
      x = c(n_transport / 2,
             n_transport + n_mitochondrial / 2,
             n_transport + n_mitochondrial + n_peroxisomal / 2),
      y = label_y,
      label = c("Transport / CPT1", "Mitochondrial \u03b2-ox", "Peroxisomal"),
      size = 2.8, color = "grey30", hjust = 0.5)
}

p_capt_dot <- makeFaoDotplot(
  captopril_obj, group_by = "condition",
  group_colors = c("lightgrey", "#d73027"),
  title_str    = "Captopril model \u2014 FAO gene expression (ctrl vs trt)"
)
ggsave(paste0(parent_dir, "captopril_FAO_gene_dotplot_", Sys.Date(), ".svg"),
       p_capt_dot, width = 300, height = 100, units = "mm", dpi = 300)

p_ren1c_dot <- makeFaoDotplot(
  ren1c_obj, group_by = "genotype",
  group_colors = c("lightgrey", "#4575b4"),
  title_str    = "Ren1cKO model \u2014 FAO gene expression (WT vs KO)"
)
ggsave(paste0(parent_dir, "ren1c_FAO_gene_dotplot_", Sys.Date(), ".svg"),
       p_ren1c_dot, width = 300, height = 100, units = "mm", dpi = 300)

Export the dot plot data as a table too:

dp_capt  <- DotPlot(captopril_obj, features = all_fao_ordered[all_fao_ordered %in% rownames(captopril_obj)],
                    group.by = "condition")
dp_ren1c <- DotPlot(ren1c_obj,    features = all_fao_ordered[all_fao_ordered %in% rownames(ren1c_obj)],
                    group.by = "genotype")
fwrite(dp_capt$data,  paste0(parent_dir, "captopril_FAO_dotplot_data.csv"), row.names = FALSE, sep = ",")
fwrite(dp_ren1c$data, paste0(parent_dir, "ren1c_FAO_dotplot_data.csv"),     row.names = FALSE, sep = ",")