Multiomics reveal unique signatures of human epiploic adipose tissue related to systemic insulin resistance

Figures

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  Figure 1. Collection sites and study design. AT, adipose tissue; BMI, body mass index; FACS, fluorescence activated cell Sorting; SVF, stromal vascular fraction.

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  Figure 2. General characterisation of epiAT and mesAT adipose tissue (AT) in comparison to omAT and scAT. (A) Depot differences in adipocyte size and (B) differences between patient groups (nT2D and T2D) for individual depots, showing mean percentage of adipocytes over all patients in increments of 10 µm (large images, Student’s t-test) and overall mean diameter per individual (small image, Wilcoxon signed-rank test); colour of significance levels indicate differences compared with epiAT of the respective depot. (C) AT macrophages indicated as count per 100 adipocytes; significance levels above plot indicate tissue differences (Wilcoxon signed-rank test) and below differences between patient groups (Mann-Whitney U test). (D) FACS analysis of AT SVF (n=7) for immune cell populations and adipocyte progenitors (paired t-test). (E) Expression of central AT metabolic genes, indicated as mean±SEM; asterisks indicate significance levels between patient groups (Mann-Whitney U test); p values for comparisons between tissues are given below plot (Wilcoxon signed-rank test). (F) Fat-depot-specific mass of epiAT and omAT in g (Wilcoxon signed-rank test). (G) Correlation of fat depot mass with BMI…

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  Figure 3. Multiomics characterisation of epiAT in IS subjects I. (A–C) PCA depicting performed omics in the analysed tissue for transcriptome (A), methylome (B) and proteome (C). (D–E) DEGs (D) and proteins (E) between epiAT and scAT or omAT; red colour indicates upregulation and blue colour indicates downregulation in epiAT; numbers indicate total identified analytes as well as significantly altered analytes. (F) Cell-type specificity of DEGs according to array data of FACS-sorted cell-type populations from human scAT. (G) Transcriptome-based gene set enrichment analysis using KEGG pathways comparing epiAT to omAT. (H) Validation of selected, DEGs compared with all other analysed tissue shown as mean±SEM (Wilcoxon signed-rank test). DEGs, differentially expressed genes; epiAT, epiploic adipose tissue; FACS, fluorescence activated cell sorting; FDR, false discovery rate; IS, insulin sensitive; mesAT, mesenteric AT; omAT, omental AT; scAT, subcutaneous AT; IS, PCA, principal component analysis; SEM, standard error of the mean.

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  Figure 4. Characterisation of developmental genes, browning capacity of epiAT in IS subjects and multiomics integration. (A) Heatmap showing expression of selected HOX genes and (B) heatmap showing gene-specific methylation for selected HOX genes. (C) IPA for transcriptome, proteome and combined data comparing epiAT to omAT (z-score >0 pathway is upregulated in epiAT, z-score <0 pathway is downregulated in epiAT and n.d. is marked in grey) and (D) browning capacity of analysed depots using the ProFAT tool; significance levels are indicated as *p<0.05; **p<0.01; ***:p<0.001. AT, adipose tissue; epiAT, epiploic AT; IPA, ingenuity pathway analysis; IR, insulin resistance; IS, insulin sensitive; JAK, janus kinase; n.d., not detected; mes, mesenteric; om, omental; PPAR, peroxisome proliferator-activated receptor; sc, subcutaneous; STAT, signal transducer and activator of transcription proteins.

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  Figure 5. Multiomics profile of IR vs IS obesity in epiAT. (A) Top 25 DEGs (based on adjusted p value) for all analysed tissues, and (B) top 25 differentially abundant proteins, both shown as z-scores. (C) Overlap between significantly regulated transcripts/proteins in epiAT. (D) IPA integrating transcriptome and proteome data (z-score >0 pathway is upregulated in IR, z-score <0 pathway is down-regulated in IR and n.d. is marked in grey). (E) Cell-type specificity of DEGs according to array data of FACS-sorted cell-type populations from human scAT. AT, adipose tissue; DEGs, differentially expressed genes; epiAT, epiploic AT; FACS, fluorescence activated cell sorting; IPA, ingenuity pathway analysis; IR, insulin resistant; IS, insulin sensitive; n.d., not detected; scAT, subcutaneous AT; TCA, tricarboxylic acid.

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  Figure 6. Analyte-based data integration characteristic for IR epiAT. (A) Visualisation of integrative sparse discriminant analysis to maximise variance between IS and IR state in epiAT (upper panel) and corresponding abundance heatmap and clustering of the identified features (lower panel). (B) Circos plot showing the same identified feature by highlighting correlation between methylation state in promoter region and gene body with transcripts and proteins, n=12, circos plot outer layers show average analyte abundance, followed by names and the inner circles show correlation relationship (r>0.9), where red indicates positive correlation. (C) Analyte-focused visualisation of IR enriched KEGG pathways: chemokine signalling pathway (hsa:04062) and leucocyte transendothelial migration (hsa:04670). The gene nodes are separated into four slots, each representing the different abundances between IR and IS in epiAT, measured in the variant omics layers. From left to right, the slots show the fold changes of transcription intensity, protein abundance and the difference of the methylation rate in the CpGs of the gene promoter, and the gene body. Values exceeding the limits of the colour key are…

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  Figure 7. Effects of IR on epiAT. (A) qPCR replication of candidate genes (based on adjusted p value and fold change) in the age-matched, sex-matched and BMI-matched cohort comparing patients with or without IR. (B) Adipocyte-specific expression of candidate genes in an independent cohort of 14 subjects (NnT2D=7 and NT2D=7). (C) Correlation of expression values with clinical data in the complete study cohort. (D) Selected key drivers of the IR epiAT based on WGCNA, filtered for absolute gene significance ≥0.4, absolute module membership ≥0.4, connectivity >0.1 and indicating observed changes for each key driver in the different ATs. Their connectivity was visualised as cytoscape network with colouring based on log2(FC) for IR vs IS in epiAT. (E) Correlation of key drivers with selected clinical parameters and (F) correlation of key drivers in epiAT with circulating adipokines and apolipoproteins. Heatmaps are coloured by Pearson; *p<0.05; **p<0.01; ***p<0.001. ATs, adipose tissues; BMI, body mass index; EpiAT, epiploic AT; FC, fold change; IR, insulin resistence; IS, insulin sensitive; nT2D, type 2 diabetes; qPCR, quantitative real-time PCR; T2D, type 2 diabetes; WGCNA, weighted gene…