Understanding multicellular function and disease with human tissue-specific networks

Abstract

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, reveal genes’ changing functional roles across tissues, and illuminate disease-disease relationships. We introduce NetWAS, which combines genes with nominally significant GWAS p-values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS, and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than one hundred human tissues and cell types.

An Epigenome-Wide Association Study of Inflammatory Response to Fenofibrate in the Genetics of Lipid Lowering Drugs and Diet Network

“…Human KIAA1324L, or EIG121L, is markedly downregulated by a constitutively active mutant of Ras [35]. At least seven of the top ten genes shown to interact with KIAA1324L were related to inflammation: DLC1, ERBB4, PDCD4, TSPAN3, RPS23, ESR1, TCEAL4 and PDE5A [36]. DLC1 is a tumor suppressor gene, absence of which results in inflammation in gastric cancer [37].…”

“…Pseudo response regulator 3 (PRR3) transcript levels vary in a circadian pattern with peak expression at dusk under long and short day conditions [46]. Of the ten top genes interacting with PRR3, five (GCN20, ABCF1, TRIM27, BLMH and LIG3) were associated with inflammation [36]. GNL1, a putative nucleolar GTPase, belongs to the MMR1-HSR1 family of large GTPases that are emerging as crucial coordinators of signaling cascades in different cellular compartments [47].…”

Pathway and network-based strategies to translate genetic discoveries into effective therapies

“…Researchers are now developing approaches that analyze genetic associations in the context of networks and pathways to prioritize potential drugs (16)(17)(18)(19)(20)(21). There is not yet a standard approach or set of techniques that are widely applied, so we highlight examples of the types of techniques being employed.…”

“…In contrast with approaches that overlay curated knowledge to calculate a score based on summed sources of evidence, Greene et al (17) used machine learning methods to identify regions of networks that were informative of genetic associations through a technique termed NetWAS. The NetWAS method uses the results of a genomewide association study to find these regions of the networks.…”

Is the neutrophil extracellular trap-driven microvascular inflammation essential for diabetes vasculopathy?

“…Because of the overexpression of PAD4 might be appeared beyond infection under several conditions (i.e. diabetes) (Greene et al, 2015), NETosis could be differentiated into respectively spontaneous or inducible (Leavy, 2015), while similar breaking out is not fulfill acceptable.…”