Machine Learning Unveils Proteotypic Mimicry in Genetically Defined SCN Variants

Background Novel computational algorithms for multi-omics analysis bear great potential to highlight pathomechanisms of monogenic diseases. We recently defined the in-depth proteome of primary human neutrophil granulocytes (PMID 30630937). Here, we ask the question whether proteotypic patterns differ between defined genetic subtypes associated with severe congenital neutropenia (SCN). We focus on two novel genetic variants in constituents of the signal recognition particle (SRPRA and SRP19) and previously reported SCN genotypes SRP54, HAX1, and ELANE. Methods We analyzed proteomes of highly purified neutrophil granulocytes from a total of 26 SCN patients, including 5 with homozygous splice …