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Table 1 Overview of protein-protein interaction network studies

From: Relationships between the amyloid precursor protein and its various proteolytic fragments and neuronal systems

Reference Selection criteria Exclusion criteria Main focus
[25] Evidence of direct interaction between molecules from literature searches Metals, non-protein molecules, poorly characterised proteins, specific peptides are included as parent genes Direct PPI involving APP and associated fragments by domain with reference to APP770 isoform but with application to all isoforms; molecular networks with reference to biological processes
[33] Twelve causative or susceptibility 'seed' genes previously associated with AD; candidate genes were selected due to close proximity to GWAS-identified gene loci associated with AD Proteins lacking open reading frames; transcription factors, highly glycosylated proteins, extracellular proteins, proteins containing several transmembrane regions; co-expression data were used as a filter Identification of genes in AD with reference to direct PPI and biological processes
[31] Co-expressed genes that differ between controls and AD Probe-sets not mapping to any gene or mapping to hypothetical proteins were removed Variations in transcriptomes of AD suggest similarities with molecular networks associated with CVD and diabetes. Cis-regulatory elements identified in several diseases known to co-occur with AD
[30] Genes with variable expression between an AD and an aging microarray study Arrays that significantly varied between subjects in each study group; outlier removal, unreliable probe sets defined as being present in three or fewer arrays; control probe sets and probes not associated with known genes Transcriptional changes between AD and aging highlight possible contributors to disease pathways. Many biological processes are shared between AD and aging. Many novel associations found, including MAPK pathways and unknown proteins. New functional and disease related association for PSEN1 with glial/neuronal interactions; confirms and highlights gamma14.3.3 signalling in AD
[32] Genes with variable expression between human and mouse from brain sample microarray gene expression data sets Outlier removal, filtered (method not specified) to remove datasets with low interspecies expression or low connectivity correlations; only top 5,000 Human and 3,000 Mouse connected genes included, rest removed to reduce 'noise' Mouse and human networks are highly similar with expression levels more preserved than connectivity. Significant species difference in: i) co-expression arrays from astroglia and microglia but not neurons; ii) the role of PSEN1 in oligodendrocytes and myelination; and iii) further evidence of species difference in glial cells linked to neuroinflammation in human AD. Neuronal death is a small part of the biological changes associated with AD in this dataset; new transcription factors associated with AD
[27] All AD and related pathways in KEGG database with co-expression data Genes without corresponding data in the assembled PPI network and proteins with no corresponding genes in the co-expression data Crosstalk between pathways involved in AD; close relationships between APP and apoptosis, Notch, Wnt pathways and cytokine-cytokine interactions in this dataset, brain areas vary in specific pathway relationships and order of significance
  1. AD, Alzheimer's disease; APP, amyloid precursor protein; CVD, cardiovascular disease; GWAS, genome-wide association study; KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPK, mitogen-activated protein kinase; PPI, protein-protein interaction; PSEN, presenilin.