How network-based approaches can complement gene identification studies in frontotemporal dementia.

Frontotemporal dementia (FTD) is a primary cause of dementia encompassing a broad range of clinical phenotypes and cellular pathologies. Genetic discoveries in FTD have largely been driven by linkage studies in well-documented extended families, explaining most of the patients with a known pathogenic mutation. In the context of complex diseases, it is hypothesized that mutations with reduced penetrance or a combination of low-effect size variants with environmental factors drive disease. Furthermore, these genes are likely to be part of the interaction networks of known FTD genes, contributing to converging cellular processes. In this review, we examine gene discovery approaches in FTD and introduce network biology concepts as tools to assist gene identification studies in genetically complex disease. Most genetic findings in frontotemporal dementia (FTD) result from family-based linkage studies, while the discovery and replication rate of cohort-based gene identification studies are relatively low. Protein products of genes causing the same or related diseases are organized in modules, with more frequent interactions with each other than expected by random chance and contribute to converging cellular pathways. Several algorithms have been developed to identify disease modules to prioritize genetic findings in the context of complex diseases. In this review we discuss classical gene identification strategies and introduce network biology concepts through protein interaction networks as tools to assist gene identification studies in frontotemporal dementia. [ABSTRACT FROM AUTHOR]