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Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease.

ABSTRACT: Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer's disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the association of genetic variants from three identified critical genes, APOE, EGFR, and ACTB, with AD. A total of 103 patients with AD and 146 healthy controls were recruited. A total of 46 single-nucleotide polymorphisms (SNPs) spanning the three genes were genotyped, of which only 19 SNPs were included in the final analyses after excluding non-polymorphic and Hardy-Weinberg equilibrium-violating SNPs. Apart from our previously reported APOE ε4, four other SNPs in APOE (rs405509, rs7259620, -rs769449, and rs7256173), one in EGFR (rs6970262), and one in ACTB (rs852423) showed a significant association with AD (p < 0.05). Our results validate the reliability of genomic convergence and network analysis approach in identifying the AD-associated candidate genes.

SUBMITTER: Talwar P

PROVIDER: S-EPMC8696000 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease.

Talwar Puneet P Kushwaha Suman S Rawat Chitra C Kaur Harpreet H Srivastava Ankit A Agarwal Rachna R Chandna Puneet P Tucci Paolo P Saso Luciano L Kukreti Ritushree R

Frontiers in genetics 20211209

Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer's disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the association of genetic variants from three identified critical genes, APOE, EGFR, and ACTB, with AD. A total of 103 patients with AD and 146 healthy controls were recruited. A total ...[more]

PMID: 34956307

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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.

Project description:Hepatosplenic T-cell lymphoma (HSTL) is an aggressive lymphoma cytogenetically characterized by isochromosome 7q [i(7)(q10)], of which the molecular consequences remain unknown. We report here results of an integrative genomic and transcriptomic (expression microarray and RNA-sequencing) study of six i(7)(q10)-positive HSTL cases, including HSTL-derived cell line (DERL-2), and three cases with ring 7 [r(7)], the recently identified rare variant aberration. Using high resolution array CGH, we profiled all cases and mapped the common deleted region (CDR) at 7p22.1p14.1 (34.88 Mb; 3506316-38406226 bp) and the common gained region (CGR) at 7q22.11q31.1 (38.77 Mb; 86259620-124892276 bp). Interestingly, CDR spans a smaller region of 13 Mb (86259620-99271246 bp) constantly amplified in cases with r(7). In addition, we found that TCRG (7p14.1) and TCRB (7q32) are involved in formation of r(7), which seems to be a byproduct of illegitimate somatic rearrangement of both loci. Further transcriptomic analysis has not identified any CDR-related candidate tumor suppressor gene. Instead, loss of 7p22.1p14.1 correlated with an enhanced expression of CHN2 (7p14.1) and the encoded β2-chimerin. Gain and amplification of 7q22.11q31.1 are associated with an increased expression of several genes postulated to be implicated in cancer, including RUNDC3B, PPP1R9A and ABCB1, a known multidrug resistance gene. RNA-sequencing did not identify any disease-defining mutation or gene fusion. Thus, chromosome 7 imbalances remain the only driver events detected in this tumor. We hypothesize that the Δ7p22.1p14.1-associated enhanced expression of CHN2/β2-chimerin leads to downmodulation of the NFAT pathway and a proliferative response, while upregulation of the CGR-related genes provides growth advantage for neoplastic δγT-cells and underlies their intrinsic chemoresistance. Finally, our study confirms the previously described gene expression profile of HSTL and identifies a set of 24 genes, including three located on chromosome 7 (CHN2, ABCB1 and PPP1R9A), distinguishing HSTL from other malignancies.

Project description:Background: Antipsychotics modulate expression of inflammatory cytokines and inducible inflammatory enzymes. Elopiprazole (a phenylpiperazine antipsychotic drug in phase 1) has been characterized as a therapeutic drug to treat SARS-CoV-2 infection in a repurposing study. We aim to investigate the potential effects of aripiprazole (an FDA approved phenylpiperazine) on COVID-19-related immunological parameters. Methods: Differential gene expression profiles of non-COVID-19 vs. COVID-19 RNA-Seq samples (CRA002390 project in GSA database) and drug-naïve patients with non-affective psychosis at baseline and after three months of aripiprazole treatment were identified. An integrative transcriptomic analyses of aripiprazole effects on differentially expressed genes in COVID-19 patients was performed. Findings: 82 out the 377 genes (21.7%) with expression significantly altered by aripiprazole have also their expression altered in COVID-19 patients and in 93.9% of these genes their expression is reverted by aripiprazole. The number of common genes with expression altered in both analyses is significantly higher than expected (Fisher's Exact Test, two tail; p value = 3.2e-11). 11 KEGG pathways were significantly enriched with genes with altered expression both in COVID-19 patients and aripiprazole medicated non-affective psychosis patients (p adj<0.05). The most significant pathways were associated to immune responses and mechanisms of hyperinflammation-driven pathology (i.e.,"inflammatory bowel disease (IBD)" (the most significant pathway with a p adj of 0.00021), "Th1 and Th2 cell differentiation" and "B cell receptor signaling pathway") that have been also associated with COVID19 clinical outcome. Interpretation: This exploratory investigation may provide further support to the notion that a protective effect is exerted by aripiprazole (phenylpiperazine) by modulating the expression of genes that have shown to be altered in COVID-19 patients. Along with many ongoing studies and clinical trials, repurposing available medications could be of use in countering SARS-CoV-2 infection, but require further studies and trials.

Dataset Information

Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease.

Publications

Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease.

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