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"

Abstract: 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.

This record contains two separate mass-spectrometry lipidomics data sets associated with this study:

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).

Data sets in other repositories associated with the same study:

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.