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Tissue Specificity of Human Disease Module.

ABSTRACT: Genes carrying mutations associated with genetic diseases are present in all human cells; yet, clinical manifestations of genetic diseases are usually highly tissue-specific. Although some disease genes are expressed only in selected tissues, the expression patterns of disease genes alone cannot explain the observed tissue specificity of human diseases. Here we hypothesize that for a disease to manifest itself in a particular tissue, a whole functional subnetwork of genes (disease module) needs to be expressed in that tissue. Driven by this hypothesis, we conducted a systematic study of the expression patterns of disease genes within the human interactome. We find that genes expressed in a specific tissue tend to be localized in the same neighborhood of the interactome. By contrast, genes expressed in different tissues are segregated in distinct network neighborhoods. Most important, we show that it is the integrity and the completeness of the expression of the disease module that determines disease manifestation in selected tissues. This approach allows us to construct a disease-tissue network that confirms known and predicts unexpected disease-tissue associations.

SUBMITTER: Kitsak M

PROVIDER: S-EPMC5066219 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Tissue Specificity of Human Disease Module.

Kitsak Maksim M Sharma Amitabh A Menche Jörg J Guney Emre E Ghiassian Susan Dina SD Loscalzo Joseph J Barabási Albert-László AL

Scientific reports 20161017

Genes carrying mutations associated with genetic diseases are present in all human cells; yet, clinical manifestations of genetic diseases are usually highly tissue-specific. Although some disease genes are expressed only in selected tissues, the expression patterns of disease genes alone cannot explain the observed tissue specificity of human diseases. Here we hypothesize that for a disease to manifest itself in a particular tissue, a whole functional subnetwork of genes (disease module) needs ...[more]

PMID: 27748412

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Project description:BackgroundN6-methyladenosine (m6A) is one of the most abundant post-transcriptional modifications on mRNA influencing mRNA metabolism. There is emerging evidence for its implication in metabolic disease. No comprehensive analyses on gene expression of m6A regulators in human adipose tissue, especially in paired adipose tissue depots, and its correlation with clinical variables were reported so far. We hypothesized that inter-depot specific gene expression of m6A regulators may differentially correlate with clinical variables related to obesity and fat distribution.MethodsWe extracted intra-individually paired gene expression data (omental visceral adipose tissue (OVAT) N=48; subcutaneous adipose tissue (SAT) N=56) of m6A regulators from an existing microarray dataset. We also measured gene expression in another sample set of paired OVAT and SAT (N=46) using RT-qPCR. Finally, we extracted existing gene expression data from peripheral mononuclear blood cells (PBMCs) and single nucleotide polymorphisms (SNPs) in METTL3 and YTHDF3 from genome wide data from the Sorbs population (N=1049). The data were analysed for differential gene expression between OVAT and SAT; and for association with obesity and clinical variables. We further tested for association of SNP markers with gene expression and clinical traits.ResultsIn adipose tissue we observed that several m6A regulators (WTAP, VIRMA, YTHDC1 and ALKBH5) correlate with obesity and clinical variables. Moreover, we found adipose tissue depot specific gene expression for METTL3, WTAP, VIRMA, FTO and YTHDC1. In PBMCs, we identified ALKBH5 and YTHDF3 correlated with obesity. Genetic markers in METTL3 associate with BMI whilst SNPs in YTHDF3 are associated with its gene expression.ConclusionsOur data show that expression of m6A regulators correlates with obesity, is adipose tissue depot-specific and related to clinical traits. Genetic variation in m6A regulators adds an additional layer of variability to the functional consequences.

Dataset Information

Tissue Specificity of Human Disease Module.

Publications

Tissue Specificity of Human Disease Module.

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