Gene Set Enrichment Analysis (GSEA).

Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether the expression of a set of genes is significantly different between two phenotypes³⁰. GSEA was performed using GSEA 4.3.2 software^31,32. The GSEA calculates the signal-to-noise ratio for all proteins and orders gene sets by normalized enrichment scores (NES). We performed the GSEA with the default settings of the software, which included 1000 permutations, phenotype permutation type, exclusion of gene sets larger than 500 and smaller than 15 and using weighted enrichment statistics. FDR cut-off of 0.25 was adopted in this analysis as recommended by GSEA developers to avoid overlooking potentially significant pathways in the context of relatively small number of gene sets being analyzed^31,32.

In addition to ORA, we also performed GSEA in our proteomics study of CSF from iNPH and MCI patients. We chose to use both methods because they provide complementary information and can help to validate each other’s results³⁰.

ORA allowed us to identify pathways that are overrepresented in our list of differentially expressed proteins, whereas GSEA enabled us to assess the enrichment of pre-defined gene sets in the list of differentially expressed proteins ranked by normalized enrichment scores, which can provide a more comprehensive understanding of the biological processes affected by the disease³⁰.

Using both methods also helped to overcome the limitations of each method, such as the dependence on pre-defined gene sets in ORA and the need for a large reference gene set in GSEA. Overall, by using both ORA and GSEA, we were able to identify novel and previously known pathways that are dysregulated in iNPH and gain a better understanding of the underlying mechanisms contributing to the pathogenesis of this disease.