{"title":"Causal associations between neuroinflammation and Alzheimer's disease risk","authors":"K-M Lin, Yizhou Yu","doi":"10.1145/3571532.3571536","DOIUrl":null,"url":null,"abstract":"Alzheimer's disease (AD) is an age-related disorder characterised by the degeneration of neurons, which leads to cognitive function. Recent research on the genetic basis of AD found some evidence of the potential implication of several risk genes in AD. Specifically, aberrant immune regulation in the brain could cause an increased risk of developing AD via damaging neurons and synapses. However, establishing a potential causal relationship between a gene and the risk of developing AD is hard to achieve in humans because this would require clinical trials. Here, we leverage intrinsic genetic variabilities in AD patients compared to non-diseased patients to propose genes that can cause AD. We used Mendelian randomisation to screen for genes causally associated with AD risk, starting with 36 potential genes identified in the most recent GWAS. We found a cluster of genes, CR1, PLCG2 and HLA-DQA1, associated with immune activation. Using single-cell sequencing data from AD patients, we found that they are significantly increased in microglia. Our results suggest that these higher levels of CR1, PLCG2 and HLA-DQA1 are associated with an increased risk of developing AD. We identified that 7-nitro-N-phenethyl-1H-indole-2-carboxamide is an inhibitor of PLCG2 and could act as a potential drug candidate for patients with genetic predispositions to significantly higher levels of PLCG2. We conclude that inhibitors of inflammation in patients who are genetically more susceptible to aberrant microglial activation could constitute as a strategy for personalised treatment. This study also establishes a workflow for further investigations of personalised treatment solutions using MR and causal inference.","PeriodicalId":355088,"journal":{"name":"Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3571532.3571536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Alzheimer's disease (AD) is an age-related disorder characterised by the degeneration of neurons, which leads to cognitive function. Recent research on the genetic basis of AD found some evidence of the potential implication of several risk genes in AD. Specifically, aberrant immune regulation in the brain could cause an increased risk of developing AD via damaging neurons and synapses. However, establishing a potential causal relationship between a gene and the risk of developing AD is hard to achieve in humans because this would require clinical trials. Here, we leverage intrinsic genetic variabilities in AD patients compared to non-diseased patients to propose genes that can cause AD. We used Mendelian randomisation to screen for genes causally associated with AD risk, starting with 36 potential genes identified in the most recent GWAS. We found a cluster of genes, CR1, PLCG2 and HLA-DQA1, associated with immune activation. Using single-cell sequencing data from AD patients, we found that they are significantly increased in microglia. Our results suggest that these higher levels of CR1, PLCG2 and HLA-DQA1 are associated with an increased risk of developing AD. We identified that 7-nitro-N-phenethyl-1H-indole-2-carboxamide is an inhibitor of PLCG2 and could act as a potential drug candidate for patients with genetic predispositions to significantly higher levels of PLCG2. We conclude that inhibitors of inflammation in patients who are genetically more susceptible to aberrant microglial activation could constitute as a strategy for personalised treatment. This study also establishes a workflow for further investigations of personalised treatment solutions using MR and causal inference.