| Literature DB >> 30465785 |
Zuo-Teng Wang1, Chen-Chen Tan1, Lan Tan1, Jin-Tai Yu2.
Abstract
Gene mining has been a fruitful approach in the study of Alzheimer's disease (AD). As a new starting point for studying AD, genetic and genomic investigations consistently strive to discover causative variants that are related to disease pathophysiology. Currently, genetic and genomic approaches have identified numerous loci. However, the elaboration of AD mechanism lagged behind gene discovery. The extensive use of parallel, high-throughput, next-generation sequencing techniques has improved our understanding of the roles of genetic variants in the brain at the highest level of functional hierarchy. We highlight three molecular systems (the transcriptome, proteome and epigenome) in this review to ascertain whether the methods used in systems biology studies of AD are useful. Here, we present many advantages of the high-throughput molecular, integrative and network methods, which may provide a good reference for future studies employing network biology approaches and large datasets.Entities:
Keywords: Alzheimer's disease; Epigenome; Network; Protein-protein interaction; Transcriptome
Mesh:
Year: 2018 PMID: 30465785 DOI: 10.1016/j.neubiorev.2018.11.007
Source DB: PubMed Journal: Neurosci Biobehav Rev ISSN: 0149-7634 Impact factor: 8.989