Fig. 4: Transcriptional regulation of ACSL1 influences BCF, glucose metabolism and diabetes.
a, Regional signal plot at the ACSL1 locus, showing P values on a −log10 scale (y axis) in hg19 locations (x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation (r2) with the lead variant (rs10022124). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU, or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b, Forest plot of the strongest functionally prioritized signal at the ACSL1 locus (rs4862423, DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications49,50 and FinnGen (release v.8). OR, odds ratio. c,d, Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose (c) and KCl stimuli (d). e–g, Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose (e), KCl (f) and pyruvate (g). Bar plots show the means of three (in c and d) and four (in e–g) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).
