Human Disease Phenotypes Associated With Mutations in TREX1

2015 ◽  
Vol 35 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Gillian I. Rice ◽  
Mathieu P. Rodero ◽  
Yanick J. Crow
Keyword(s):  
Human Disease ◽  
Disease Phenotypes

scholarly journals Erratum: CRISPR-engineered mosaicism rapidly reveals that loss of Kcnj13 function in mice mimics human disease phenotypes

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Hua Zhong ◽  
Yiyun Chen ◽  
Yumei Li ◽  
Rui Chen ◽  
Graeme Mardon
Keyword(s):  
Human Disease ◽  
Disease Phenotypes

scholarly journals The signaling lipid PI(3,5)P2 stabilizes V1–Vo sector interactions and activates the V-ATPase

2014 ◽  
Vol 25 (8) ◽  
pp. 1251-1262 ◽  
Author(s):  
Sheena Claire Li ◽  
Theodore T. Diakov ◽  
Tao Xu ◽  
Maureen Tarsio ◽  
Wandi Zhu ◽  
...  
Keyword(s):  
Salt Stress ◽  
Atpase Activity ◽  
Human Disease ◽  
Proton Pumps ◽  
Disease Phenotypes ◽  
Reversible Dissociation ◽  
Signaling Mechanisms ◽  
Vacuolar Acidification ◽  
Direct Binding

Vacuolar proton-translocating ATPases (V-ATPases) are highly conserved, ATP-driven proton pumps regulated by reversible dissociation of its cytosolic, peripheral V1 domain from the integral membrane Vo domain. Multiple stresses induce changes in V1-Vo assembly, but the signaling mechanisms behind these changes are not understood. Here we show that certain stress-responsive changes in V-ATPase activity and assembly require the signaling lipid phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2). V-ATPase activation through V1-Vo assembly in response to salt stress is strongly dependent on PI(3,5)P2 synthesis. Purified Vo complexes preferentially bind to PI(3,5)P2 on lipid arrays, suggesting direct binding between the lipid and the membrane sector of the V-ATPase. Increasing PI(3,5)P2 levels in vivo recruits the N-terminal domain of Vo-sector subunit Vph1p from cytosol to membranes, independent of other subunits. This Vph1p domain is critical for V1-Vo interaction, suggesting that interaction of Vph1p with PI(3,5)P2-containing membranes stabilizes V1-Vo assembly and thus increases V-ATPase activity. These results help explain the previously described vacuolar acidification defect in yeast fab1∆ and vac14∆ mutants and suggest that human disease phenotypes associated with PI(3,5)P2 loss may arise from compromised V-ATPase stability and regulation.

scholarly journals The population-specific impact of Neandertal introgression on human disease

2020 ◽  
Author(s):  
Michael Dannemann
Keyword(s):  
Prostate Cancer ◽  
Human Disease ◽  
European Ancestry ◽  
Summary Statistics ◽  
Behavioral Traits ◽  
Disease Phenotypes ◽  
Disease Associations ◽  
Specific Impact ◽  
People Today

Abstract Since the discovery of admixture between modern humans and Neandertals, multiple studies investigated the effect of Neandertal-derived DNA on human disease and non-disease phenotypes. These studies have linked Neandertal ancestry to skin and hair related phenotypes, immunity, neurological and behavioral traits. However, these inferences have so far been limited to cohorts with participants of European ancestry. Here, I analyze summary statistics from 40 disease GWAS cohorts of ∼212,000 individuals provided by the Biobank Japan Project for phenotypic effects of Neandertal DNA. I show that Neandertal DNA is associated with autoimmune diseases, prostate cancer and type 2 diabetes. Many of these disease associations are linked to population-specific Neandertal DNA, highlighting the importance of studying a wider range of ancestries to characterize the phenotypic legacy of Neandertals in people today.

scholarly journals MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes

2020 ◽  
Author(s):  
Guocai Yao ◽  
Wenliang Zhang ◽  
Minglei Yang ◽  
Huan Yang ◽  
Jianbo Wang ◽  
...  
Keyword(s):  
Human Disease ◽  
Rapid Identification ◽  
Reciprocal Relationship ◽  
Metagenomic Data ◽  
Web Interfaces ◽  
Disease Phenotypes ◽  
Link Type ◽  
Pathogenic Microbes ◽  
Service Application ◽  
Core Genes

AbstractMicrobes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, microbial core genes, and disease phenotypes. We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data. MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites. MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes. Disease phenotypes are classified and described using the Experimental Factor Ontology (EFO). A refined score model was developed to prioritize the associations based on evidential metrics. The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly. MicroPhenoDB offers data browsing, searching and visualization through user-friendly web interfaces and web service application programming interfaces. MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes, core genes, and disease phenotypes. It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases. MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb.

scholarly journals Characterization of human disease phenotypes associated with mutations inTREX1,RNASEH2A,RNASEH2B,RNASEH2C,SAMHD1,ADAR, andIFIH1

2015 ◽  
Vol 167 (2) ◽  
pp. 296-312 ◽  
Author(s):  
Yanick J. Crow ◽  
Diana S. Chase ◽  
Johanna Lowenstein Schmidt ◽  
Marcin Szynkiewicz ◽  
Gabriella M.A. Forte ◽  
...  
Keyword(s):  
Human Disease ◽  
Disease Phenotypes

scholarly journals Disease and phenotype gene set analysis of disease-based gene expression in mouse and human

2010 ◽  
Vol 42A (2) ◽  
pp. 162-167 ◽  
Author(s):  
Supriyo De ◽  
Yongqing Zhang ◽  
John R. Garner ◽  
S. Alex Wang ◽  
Kevin G. Becker
Keyword(s):  
Gene Expression ◽  
Human Disease ◽  
Complex Disease ◽  
Population Based ◽  
Gene Set Analysis ◽  
Common Disease ◽  
Analysis Tool ◽  
Gene Set ◽  
Disease Phenotypes ◽  
Gene Sets

The genetic contributions to common disease and complex disease phenotypes are pleiotropic, multifactorial, and combinatorial. Gene set analysis is a computational approach used in the analysis of microarray data to rapidly query gene combinations and multifactorial processes. Here we use novel gene sets based on population-based human genetic associations in common human disease or experimental genetic mouse models to analyze disease-related microarray studies. We developed a web-based analysis tool that uses these novel disease- and phenotype-related gene sets to analyze microarray-based gene expression data. These gene sets show disease and phenotype specificity in a species-specific and cross-species fashion. In this way, we integrate population-based common human disease genetics, mouse genetically determined phenotypes, and disease or phenotype structured ontologies, with gene expression studies relevant to human disease. This may aid in the translation of large-scale high-throughput datasets into the context of clinically relevant disease phenotypes.

scholarly journals Gain-of-function mutations in IFIH1 cause a spectrum of human disease phenotypes associated with upregulated type I interferon signaling

2014 ◽  
Vol 46 (5) ◽  
pp. 503-509 ◽  
Author(s):  
Gillian I Rice ◽  
Yoandris del Toro Duany ◽  
Emma M Jenkinson ◽  
Gabriella M A Forte ◽  
Beverley H Anderson ◽  
...  
Keyword(s):  
Human Disease ◽  
Type I Interferon ◽  
Type I ◽  
Interferon Signaling ◽  
Gain Of Function ◽  
Disease Phenotypes
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