Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

Raffaele Ferrari,Claudia Manzoni,John Hardy,Ruth C Lovering,Patrick A Lewis

doi:10.1021/acs.jproteome.6b00934

Raffaele Ferrari, Claudia Manzoni + Show 3 more

Open Access

https://doi.org/10.1021/acs.jproteome.6b00934

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Abstract

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein–protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

Highlights

IntroductionThe genetic analysis of complex diseases has led to the identification of a wealth of associations between Mendelian genes or susceptibility loci (i.e., regions of DNA incorporating coding and noncoding variants) and specific traits or endophenotypes.[1,2] While genetic association has greatly aided shedding light on disorders as diverse as heart disease and leprosy,[3,4] such knowledge is still insufficient to fully explain disease pathogenesis
The genetic analysis of complex diseases has led to the identification of a wealth of associations between Mendelian genes or susceptibility loci and specific traits or endophenotypes.[1,2] While genetic association has greatly aided shedding light on disorders as diverse as heart disease and leprosy,[3,4] such knowledge is still insufficient to fully explain disease pathogenesis
On the basis of this analysis, these functional blocks indicated susceptibility processes shared by at least 60% of the frontotemporal dementia (FTD)-PN, highlighting processes of critical relevance and clearly worthy of attention as well as further investigation and characterization at the molecular level. To put these data better into context, we evaluated the groups of genes contributing to the enrichment of similar functional blocks in our previous weighted gene coexpression network analysis (WGCNA) study[53] searching for overlaps with the list of proteins found in the current W-protein−protein interaction (PPI)-NA (Figure 7B)

Summary

Introduction

The genetic analysis of complex diseases has led to the identification of a wealth of associations between Mendelian genes or susceptibility loci (i.e., regions of DNA incorporating coding and noncoding variants) and specific traits or endophenotypes.[1,2] While genetic association has greatly aided shedding light on disorders as diverse as heart disease and leprosy,[3,4] such knowledge is still insufficient to fully explain disease pathogenesis This is a critical issue considering that the final goal of biomedical research is that of understanding disease mechanisms and their associated molecular underpinnings to identify biomarkers or targets for disease diagnosis, prevention, or treatment. In complex disorders many of the established mutations in Mendelian (familial) genes are rare and may present with incomplete penetrance.[5,6] the vast majority of cases are sporadic and are associated with the gradual and cumulative effect of susceptibility loci, that is, multiple variants with small effect size, the severity of which might be modulated, for example, by environmental factors.[7−11] The implication of this is that in complex disorders a broad underlying genetic susceptibility architecture contributing to disease risk may be or even more relevant than just Mendelian inheritance.[12,13] In addition the current absence of a straightforward translation of genetic knowledge into the functional landscape of biochemistry and cell biology[14] represents a challenge that contributes to a substantive gap in our understanding of the molecular underpinnings of disease

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