Browsing by Subject "Pathway enrichment"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    An exploratory genome-wide analysis of genetic risk for alcoholic hepatitis
    (Taylor & Francis, 2017-11) Beaudoin, James J.; Long, Nanye; Liangpunsakul, Suthat; Puri, Puneet; Kamath, Patrick S.; Shah, Vijay; Sanyal, Arun J.; Crabb, David W.; Chalasani, Naga P.; Urban, Thomas J.; TREAT Consortium; Medicine, School of Medicine
    OBJECTIVES: To elucidate the genetic variability between heavy drinkers with and without alcoholic hepatitis (AH). MATERIALS AND METHODS: An exploratory genome-wide association study (GWAS; NCT02172898) was conducted comparing 90 AH cases with 93 heavy drinking matched controls without liver disease in order to identify variants or genes associated with risk for AH. Individuals were genotyped using the multi-ethnic genotyping array, after which the data underwent conventional quality control. Using bioinformatics tools, pathways associated with AH were explored on the basis of individual variants, and based on genes with a higher 'burden' of functional variation. RESULTS: Although no single variant reached genome-wide significance, an association signal was observed for PNPLA3 rs738409 (p = .01, OR 1.9, 95% CI 1.1-3.1), a common single nucleotide polymorphism that has been associated with a variety of liver-related pathologies including alcoholic cirrhosis. Using the improved gene set enrichment analysis for GWAS tool, it was shown that, based on the single variants' trait-association p-values, multiple pathways were associated with risk for AH with high confidence (false discovery rate [FDR] < 0.05), including several pathways involved in lymphocyte activation and chemokine signaling, which coincides with findings from other research groups. Several Tox Functions and Canonical Pathways were highlighted using Ingenuity Pathway Analysis, with an especially conspicuous role for pathways related to ethanol degradation, which is not surprising considering the phenotype of the genotyped individuals. CONCLUSION: This preliminary analysis suggests a role for PNPLA3 variation and several gene sets/pathways that may influence risk for AH among heavy drinkers.
  • Thumbnail Image
    Item
    Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease
    (Bentham Science, 2019) Li, Jin; Chen, Feng; Zhang, Qiushi; Meng, Xianglian; Yao, Xiaohui; Risacher, Shannon L.; Yan, Jingwen; Saykin, Andrew J.; Liang, Hong; Shen, Li; Radiology and Imaging Sciences, School of Medicine
    Background: The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms. Objective: The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy. Methods: First, we took advantage of a dense module search algorithm to identify modules enriched by genetic association signals in a protein-protein interaction network. Next, we performed statistical evaluation to the modules identified by dense module search, including a normalization process to adjust the topological bias in the network, a replication test to ensure the modules were not found randomly , and a permutation test to evaluate unbiased associations between the modules and amyloid imaging phenotype. Finally, topological analysis, module similarity tests and functional enrichment analysis were performed for the identified modules. Results: We identified 24 consensus modules enriched by robust genetic signals in a genome-wide association analysis. The results not only validated several previously reported AD genes (APOE, APP, TOMM40, DDAH1, PARK2, ATP5C1, PVRL2, ELAVL1, ACTN1 and NRF1), but also nominated a few novel genes (ABL1, ABLIM2) that have not been studied in Alzheimer's disease but have shown associations with other neurodegenerative diseases. Conclusion: The identified genes, consensus modules and enriched pathways may provide important clues to future research on the neurobiology of Alzheimer's disease and suggest potential therapeutic targets.