Monogenic diabetes is a Mendelian disorder following the autosomal-dominant pattern of inheritance. Despite the relative simplicity of the genetic architecture of Mendelian diseases, monogenic diabetes seems to be difficult for precision diagnosis due to its symptomatic similarity with the other diabetes types. In this regard the diagnostics quality may contribute from more personalised approach. The aim of our work is to move away from the standard diabetes classification towards precision diagnostics and treatment. The analysis of proteome, meaning the actual functioning part of the biological system, may contribute to the personalised profiling of patients as well as add to the fundamental understanding of the disease pathogenesis. There are two ways of adding the analysis of proteome to the profiling of patients with diabetes: study of pancreatic tissue directly affected by the disease and measuring the indirect effect of the disease on the blood protein concentrations. With the first approach the altered sequences of the protein products of gene variation are studied using mass spectrometry-based proteomics. This approach contributes to the fundamental knowledge of disease pathogenesis and brings results on protein consequences that, in turn, can be used for variant pathogenicity evaluation. In the second one, patients’ blood samples are analyzed with eather affinity-based high-throughput protein assays or shotgun mass spectrometry-based proteomics analysis and the abundances of proteins are estimated. We have collected all the available information on the rare genetic variants linked to monogenic diabetes and translated them into protein sequences mapped to all the isoforms from Ensemble. This is implemented in our developed and publicly available python-based pipeline. These variant sequences have been added to a human protein database containing common protein haplotypes, enabling the account of the common genetic variation to avoid search space inflation. This database is ready to be used for the sequence-level identification of the protein product of the monogenic diabetes-causing genetic variants. With the method of LC-MS/MS with the timsTOF type of instrument in the DIA mode in the samples of hiPSC at stage 0 and stage 4 we were able to detect the PSMs that map to 72 proteins linked to MD of which 13 are products of commonly-known MODY genes. In the DDA Orbitrap data obtained from the samples of children's serum by Bonal and Herrera, 2008...