DOI: 10.6084/m9.figshare.22825532
title: <b>Unravelling Adipose Tissue Proteomic Landscapes in Severe Obesity: Insights into Metabolic Complications and Potential Biomarkers</b> - Supplementary Files

description: <strong>Supplementary files</strong> <strong>S File 1 – LC-MS Analysis Methods</strong> A comprehensive description of the liquid chromatography-mass spectrometry (LC-MS) analysis methods employed in this study. <br> <strong>S File 2 – Normalized and Imputed Intensity Values for SAT and VAT Proteomics Dataset</strong> The MaxQuant search proteinGroups.txt dataset for SAT and VAT proteomics data, including the following modifications: (a) removal of decoy hits and contaminant protein groups; (b) exclusion of library data; (c) exclusion of protein groups without measured intensity in ≤ 8 samples in at least one of the sample groups (SAT Males/Females, VAT Males/Females); (d) log2 transformation of protein group intensities; (e) LoessF normalization; and (f) imputation of missing values using the sample minimum. <br> <strong>S File 3 – Normalized and Imputed Intensity Values for Serum Proteomics Dataset</strong> The DIA-NN output dataset for serum proteomics data, including only features with Lib.Q.Val &lt;0.01, Lib.PG.Val &lt;0.01, and Quantity quality &gt;0.5, has undergone the following modifications: (a) removal of contaminant protein groups; (b) exclusion of protein groups without measured intensity data in ≤ 8 samples in at least one of the sample groups (males/females); (c) log2 transformation of protein group intensities for DIA-NN normalized data; and (d) imputation of missing values using the sample minimum. <br> <strong>S File 4 – LIMMA Differential Expression Analysis of SAT and VAT Protein Expression</strong> This file contains the results of a linear model differential expression analysis using LIMMA, which compares protein group intensities between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in paired design while accounting for sex as a confounding variable. The outcomes were corrected for multiple hypothesis testing using the Benjamini-Hochberg procedure, as implemented in the LIMMA package. <br> <strong>S File 5 – LIMMA Analysis of Sex Differences in VAT and SAT Protein Expression</strong> This file presents the results of a linear model differential expression analysis using LIMMA, comparing protein group intensities between males' and females' visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). The outcomes were corrected for multiple hypothesis testing with the Benjamini-Hochberg procedure, as implemented in the LIMMA package. <br> <strong>S File 6 – LIMMA Analysis of Sex Differences in Serum Protein Expression</strong> This file contains the results of a linear model differential expression analysis using LIMMA, comparing protein group intensities between male and female serum samples. The outcomes were corrected for multiple hypothesis testing using the Benjamini-Hochberg procedure, as implemented in the LIMMA package. <br> <strong>S File 7 - SignalP 6.0 Prediction of Putative Secreted Proteins</strong> This file contains the output of the putative secreted proteins analysis using the SignalP 6.0 Server. The analysis was performed on the FASTA sequences of proteins overlapping between the adipose tissue and serum proteome. <br> <strong>S File 8 – Bioinformatics Data Analysis Methods</strong> A detailed description of the bioinformatics data analysis techniques employed in this study. <br> <strong>S File 9a – Gene Ontology Enrichment Analysis for Biological Processes in SAT and VAT</strong> Gene Ontology (GO) enrichment analysis of biological processes for differentially expressed proteins in SAT (n = 693) and VAT (n = 556), conducted using the Cytoscape GlueGO plug-in with a two-cluster approach. Only GO terms of levels 5-8 were considered, with a significance threshold of 0.05, and redundant groups with &gt; 50% overlap were merged. This file contains the most significantly enriched terms (adj. P-value &lt;0.05). <br> <strong>S File 9b – Gene Ontology Enrichment Analysis for Cellular Components in SAT and VAT</strong> Gene Ontology (GO) enrichment analysis of cellular components for differentially expressed proteins in SAT (n = 693) and VAT (n = 556), conducted using the Cytoscape GlueGO plug-in with a two-cluster approach. Only GO terms of levels 5-8 were considered, with a significance threshold of 0.05, and redundant groups with &gt; 50% overlap were merged. This file contains the most significantly enriched terms (adj. P-value &lt;0.05). <br> <strong>S File 9c – Gene Ontology Enrichment Analysis for Molecular Function in SAT and VAT</strong> Gene Ontology (GO) enrichment analysis of molecular function for differentially expressed proteins in SAT (n = 693) and VAT (n = 556), conducted using the Cytoscape GlueGO plug-in with a two-cluster approach. Only GO terms of levels 5-8 were considered, with a significance threshold of 0.05, and redundant groups with &gt; 50% overlap were merged. This file contains the most significantly enriched terms (adj. P-value &lt;0.05). <br> <strong>S File 10 – Pathway Enrichment Analysis of Differentially Expressed Proteins in SAT and VAT</strong> This file contains the results of Reactome pathways and reactions enrichment analysis for all upregulated SAT and VAT proteins, conducted using the Cytoscape ClueGO plugin with separate groups for SAT and VAT proteins. The analysis was performed using default settings, but only displaying results with a p-value &lt; 0.05. <br> <strong>S File 11a – SAT Reactome Over-Representation Pathway Analysis</strong> This file contains the results obtained by submitting the list of UniProt accessions for all significantly upregulated SAT proteins to the Reactome data analysis tool. <br> <strong>S File 11b – VAT Reactome Over-Representation Pathway Analysis</strong> This file contains the results obtained by submitting the list of UniProt accessions for all significantly upregulated VAT proteins to the Reactome data analysis tool. <br> <strong>S File 12 – Tissue-Serum Expression Correlations</strong> This file contains the biweight midcorrelation results between SAT, VAT, and serum protein expression levels. <br> <strong>S File 13 – WGCNA Module Enrichments for SAT, VAT, and Serum</strong> This ZIP file contains the results of all Cytoscape ClueGO combined enrichment analyses for biological processes (BP), cellular components (CC), molecular functions (MF), and Reactome pathways and processes for WGCNA module proteins in SAT, VAT, and serum. <br> <strong>S File 14 – Clinical Traits Correlation Matrix</strong> This file contains a cluster correlation matrix of clinical traits, illustrating the intercorrelation between similar clinical variables. <br> <strong>S File 15a - SAT WGCNA Module-Trait Relationships Results</strong> This table presents the module membership and gene significance, along with their respective p-values, from the WGCNA and module-trait relationship analysis for SAT protein expression. <br> <strong>S File 15b - VAT WGCNA Module-Trait Relationships Results</strong> This table presents the module membership and gene significance, along with their respective p-values, from the WGCNA and module-trait relationship analysis for VAT protein expression. <br> <strong>S File 15c - Serum WGCNA Module-Trait Relationships Results</strong> This table presents the module membership and gene significance, along with their respective p-values, from the WGCNA and module-trait relationship analysis for serum protein expression.