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Transcriptomic and genetic studies identify IL-33 as a candidate gene for Alzheimer's disease.

ABSTRACT: The only recognized genetic determinant of the common forms of Alzheimer's disease (AD) is the epsilon 4 allele of the apolipoprotein E gene (APOE). To identify new candidate genes, we recently performed transcriptomic analysis of 2741 genes in chromosomal regions of interest using brain tissue of AD cases and controls. From 82 differentially expressed genes, 1156 polymorphisms were genotyped in two independent discovery subsamples (n=945). Seventeen genes exhibited at least one polymorphism associated with AD risk, and following correction for multiple testing, we retained the interleukin (IL)-33 gene. We first confirmed that the IL-33 expression was decreased in the brain of AD cases compared with that of controls. Further genetic analysis led us to select three polymorphisms within this gene, which we analyzed in three independent case-control studies. These polymorphisms and a resulting protective haplotype were systematically associated with AD risk in non-APOE epsilon 4 carriers. Using a large prospective study, these associations were also detected when analyzing the prevalent and incident AD cases together or the incident AD cases alone. These polymorphisms were also associated with less cerebral amyloid angiopathy (CAA) in the brain of non-APOE epsilon 4 AD cases. Immunohistochemistry experiments finally indicated that the IL-33 expression was consistently restricted to vascular capillaries in the brain. Moreover, IL-33 overexpression in cellular models led to a specific decrease in secretion of the A beta(40) peptides, the main CAA component. In conclusion, our data suggest that genetic variants in IL-33 gene may be associated with a decrease in AD risk potentially in modulating CAA formation.

SUBMITTER: Chapuis J

PROVIDER: S-EPMC2860783 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

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Transcriptomic and genetic studies identify IL-33 as a candidate gene for Alzheimer's disease.

Chapuis J J Hot D D Hansmannel F F Kerdraon O O Ferreira S S Hubans C C Maurage C A CA Huot L L Bensemain F F Laumet G G Ayral A M AM Fievet N N Hauw J J JJ DeKosky S T ST Lemoine Y Y Iwatsubo T T Wavrant-Devrièze F F Dartigues J F JF Tzourio C C Buée L L Pasquier F F Berr C C Mann D D Lendon C C Alpérovitch A A Kamboh M I MI Amouyel P P Lambert J C JC

Molecular psychiatry 20090210 11

The only recognized genetic determinant of the common forms of Alzheimer's disease (AD) is the epsilon 4 allele of the apolipoprotein E gene (APOE). To identify new candidate genes, we recently performed transcriptomic analysis of 2741 genes in chromosomal regions of interest using brain tissue of AD cases and controls. From 82 differentially expressed genes, 1156 polymorphisms were genotyped in two independent discovery subsamples (n=945). Seventeen genes exhibited at least one polymorphism ass ...[more]

PMID: 19204726

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Project description:Alzheimer's (AD) and Parkinson's diseases (PD) are the two most prevalent neurodegenerative disorders in human populations. Epidemiological studies have shown that patients suffering from either condition present a reduced overall risk of cancer than controls (i.e., inverse comorbidity), suggesting that neurodegeneration provides a protective effect against cancer. Reduced risks of several site-specific tumors, including colorectal, lung, and prostate cancers, have also been observed in AD and PD. By contrast, an increased risk of melanoma has been described in PD patients (i.e., direct comorbidity). Therefore, a fundamental question to address is whether these associations are due to shared genetic and molecular factors or are explained by other phenomena, such as flaws in epidemiological studies, exposure to shared risk factors, or the effect of medications. To this end, we first evaluated the transcriptomes of AD and PD post-mortem brain tissues derived from the hippocampus and the substantia nigra and analyzed their similarities to those of a large panel of 22 site-specific cancers, which were obtained through differential gene expression meta-analyses of array-based studies available in public repositories. Genes and pathways that were deregulated in both disorders in each analyzed pair were examined. Second, we assessed potential genetic links between AD, PD, and the selected cancers by establishing interactome-based overlaps of genes previously linked to each disorder. Then, their genetic correlations were computed using cross-trait LD score regression and GWAS summary statistics data. Finally, the potential role of medications in the reported comorbidities was assessed by comparing disease-specific differential gene expression profiles to an extensive collection of differential gene expression signatures generated by exposing cell lines to drugs indicated for AD, PD, and cancer treatment (LINCS L1000). We identified significant inverse associations of transcriptomic deregulation between AD hippocampal tissues and breast, lung, liver, and prostate cancers, and between PD substantia nigra tissues and breast, lung, and prostate cancers. Moreover, significant direct (same direction) associations of deregulation were observed between AD and PD and brain and thyroid cancers, as well as between PD and kidney cancer. Several biological processes, including the immune system, oxidative phosphorylation, PI3K/AKT/mTOR signaling, and the cell cycle, were found to be deregulated in both cancer and neurodegenerative disorders. Significant genetic correlations were found between PD and melanoma and prostate cancers. Several drugs indicated for the treatment of neurodegenerative disorders and cancer, such as galantamine, selegiline, exemestane, and estradiol, were identified as potential modulators of the comorbidities observed between neurodegeneration and cancer.

Project description:BackgroundAlzheimer's disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling.ResultsOur approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (SR) based method followed by prioritization using clusters derived from PPI network. SR for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes.ConclusionsWith the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.

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Transcriptomic and genetic studies identify IL-33 as a candidate gene for Alzheimer's disease.

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Transcriptomic and genetic studies identify IL-33 as a candidate gene for Alzheimer's disease.

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