Two lipidomics data sources for the publication "Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories toward type 2 diabetes"

<strong>Abstract:</strong> Wigger, Barovic, Brunner et al present a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodeling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or trans-differentiation stages in T2D. Furthermore, through integration of islet transcriptomics with pre-operative blood plasma lipidomics, we define the relative importance of gene co-expression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers. <strong>This record contains two separate mass-spectrometry lipidomics data sets associated with this study:</strong> 1. Shotgun lipidomics (blood plasma of 61 individuals) 2. Targeted lipidomics of ceramides and other sphingolipid species (blood plasma of 102 individuals) We provide two data tables for each data set: original lipid quantifications as obtained from the lipidomics platforms and processed data as used for data analyses. Processed data was generated by a data filtering and an imputation step: Lipids were removed when they had more than 25% (shotgun experiment) or more than 10% (targeted experiment) of missing values. The remaining missing values were imputed by a missForest approach (using the R package missForest). <strong>Data sets in other repositories associated with the same study:</strong> Additional data sets (transcriptomics, proteomics) pertaining to the same study have been deposited in other public data bases: in the Gene Expression Omnibus (NCBI GEO) with the accession number GSE164416; in the PRIDE Archive (EMBL-EBI) with the identifier PXD022561.**摘要：** 威格（Wigger）、巴罗维奇（Barovic）、布伦纳（Brunner）等学者对经过代谢表型分型的活体胰腺切除供体的胰岛（pancreatic islets）开展了全面的多组学分析，这些供体按血糖连续谱分层，涵盖从正常血糖到2型糖尿病（T2D）的全部阶段。研究团队发现，经激光捕获显微切割（laser-capture microdissection）从手术样本中分离的胰岛群，在糖尿病患者中展现出较非糖尿病对照更为显著的转录组（transcriptomic）与蛋白质组（proteomic）异质性。胰岛基因表达的差异调控在糖耐量受损（impaired glucose tolerance）的前驱糖尿病（prediabetic）个体中已可观测到。本研究结果证实，成熟β细胞存在进行性但不协调的重塑，这对当前关于2型糖尿病中细胞向前体细胞或转分化阶段的线性轨迹假说提出了挑战。此外，通过将胰岛转录组与术前血浆脂质组学进行整合，研究团队明确了与糖化血红蛋白（HbA1c）水平呈正相关或负相关的基因共表达模块及脂质的相对重要性，为潜在预后标志物的筛选指明了方向。 **本数据集包含与本研究相关的两组独立质谱脂质组学（mass-spectrometry lipidomics）数据集：** 1. 鸟枪法脂质组学（Shotgun lipidomics）：来自61名个体的血浆样本 2. 神经酰胺及其他鞘脂类物质靶向脂质组学（Targeted lipidomics of ceramides and other sphingolipid species）：来自102名个体的血浆样本 针对每组数据集，我们提供两张数据表：分别为脂质组学平台直接获取的原始脂质定量结果，以及用于数据分析的处理后数据。处理后数据通过数据过滤与缺失值插补步骤生成：当脂质的缺失值占比超过25%（鸟枪法实验）或10%（靶向实验）时将被剔除；剩余缺失值通过missForest插补法（missForest）完成（使用R包`missForest`）。 **本研究关联的其他存储库数据集：** 本研究涉及的其他数据集（转录组学、蛋白质组学）已提交至其他公共数据库：提交至基因表达综合数据库（Gene Expression Omnibus, NCBI GEO），收录编号为GSE164416；提交至PRIDE数据库（PRIDE Archive, EMBL-EBI），收录标识符为PXD022561。