Ontology highlight
ABSTRACT:
PROVIDER: PRJEB55391 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| AD01.vcf.csi | Other | |||
| AD01.vcf.gz | Vcf | |||
| AD02.vcf.csi | Other | |||
| AD02.vcf.gz | Vcf | |||
| AD03.vcf.csi | Other |
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Project description:Genome-wide association studies (GWAS) have identified genes in lipid metabolism,inflammation and vesicular trafficking pathways as risk factors for late onset Alzheimer disease (LOAD). The mechanism by which they cause AD and their relationship to the amyloid cascade affected by genes causing early onset familial AD is unknown. Unproven hypotheses are that these LOAD genes modulate the amyloid cascade itself or downstream targets affected by this cascade.If so, it is likely that these genes and/or other genes in the same pathways may show alterations in their expression as an early consequence of misprocessing of amyloid precursor protein (APP) and accumulation of amyloid β-peptides (Aβ). We report that in three independent APP transgenic mouse models of AD, multiple genes in lipid and inflammation pathways show very early changes in mRNA and protein expression. Many of these changes are reversed by treatment with LXR agonists, which regulate transcription of genes in lipid/inflammation pathways, and which we have previously shown can reverse the cognitive deficits and neuropathology in Tg2756 mice. These results suggest that changes in lipid and inflammation pathways are likely to be very early consequences of APP misprocessing and Aβ accumulation in AD. Moreover, genetic variants within these pathways might affect risk for AD by modulating this early response. These pathways are likely to contain biomarkers of early disease and targets for therapies. TgCRND8 mice and wild-type littermate controls at ages 70, 80, and 150 days (n = 4 mice per cohort) were used in the study.
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Project description:Background: Asthma is common chronic inflammatory disease of the airways with a heterogenous clinical presentation. Individual differences in asthma susceptibility remain poorly understood, although genetics is thought to play a major role. Aim: To build a polygenic risk score (PRS) for asthma and determine whether predictive genetic variants can be epigenomically linked to specific pathophysiological mechanisms. Methods: PRSs were constructed using data from genome-wide association studies and performance was validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14,926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and exacerbations. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) data from 14 primary cell types, including lung epithelial cells and T lymphocytes was used for epigenomic PRS partitioning. Results: All PRSs successfully predicted risk to develop asthma and related outcomes, with the strongest predictive power (2.42 odds ratios per PRS standard deviation, area under the curve of 0.736) achieved for childhood-onset asthma. PRSs allowed for stratification of the Rotterdam Study cohort into groups at low or high risk to develop asthma. PRS partitioning using genome-wide epigenomic profiles identified 5 clusters of variants within gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways. Conclusions: PRSs can predict whether individuals in a Dutch cohort developed asthma and asthma-related phenotypes, which is most effective for childhood-onset asthma. Importantly, we show that PRS partitioning based on epigenomics data dissects a genetic risk score into blocks of regulatory variants with differential predictive power, which likely represent distinct genetically driven disease pathways. These findings have potential implications for personalized risk mitigation and treatment strategies.
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