Anyi Yang, Xingzhong Zhao, Yucheng T. Yang, Xing-Ming Zhao
{"title":"破译细胞类型特异性遗传因子与脑成像衍生表型和疾病之间的因果关系","authors":"Anyi Yang, Xingzhong Zhao, Yucheng T. Yang, Xing-Ming Zhao","doi":"10.1101/2024.08.30.24312836","DOIUrl":null,"url":null,"abstract":"The integration of expression quantitative trait loci (eQTLs) and genome-wide association study (GWAS) findings to identify causal genes aids in elucidating the biological mechanisms and the discovery of potential drug targets underlying complex traits. This can be achieved by Mendelian randomization (MR), but to date, most MR studies investigating the contribution of genes to brain phenotypes have been conducted on heterogeneous brain tissues and not on specific cell types, thus limiting our knowledge at the cellular level. In this study, we employ a MR framework to infer cell type-specific causal relationships between gene expression and brain-associated complex traits, using eQTL data from eight cell types and large-scale GWASs of 123 imaging-derived phenotypes (IDPs) and 26 brain disorders and behaviors (DBs). Our analysis constructs a cell type-specific causal gene atlas for IDPs and DBs, which include 254 and 217 potential causal cell type-specific eQTL target genes (eGenes) for IDPs and DBs, respectively. The identified results exhibit high cell type specificity, with over 90% of gene-IDP and 80% of gene-DB associations being unique to a single cell type. We highlight shared cell type-specific patterns between IDPs and DBs, characterize the putative causal pathways among cell type-specific causal eGenes, DBs and IDPs, and reveal the spatiotemporal expression patterns of these cell type-specific causal eGenes. We also demonstrate that cell type-specific causal eGenes can characterize the associations between IDPs and DBs. In summary, our study provides novel insights into the genetic foundations at the cellular level that influence brain structures, disorders and behaviors, which reveals important implications for therapeutic targets and brain health management.","PeriodicalId":501375,"journal":{"name":"medRxiv - Genetic and Genomic Medicine","volume":"62 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deciphering causal relationships between cell type-specific genetic factors and brain imaging-derived phenotypes and disorders\",\"authors\":\"Anyi Yang, Xingzhong Zhao, Yucheng T. Yang, Xing-Ming Zhao\",\"doi\":\"10.1101/2024.08.30.24312836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integration of expression quantitative trait loci (eQTLs) and genome-wide association study (GWAS) findings to identify causal genes aids in elucidating the biological mechanisms and the discovery of potential drug targets underlying complex traits. This can be achieved by Mendelian randomization (MR), but to date, most MR studies investigating the contribution of genes to brain phenotypes have been conducted on heterogeneous brain tissues and not on specific cell types, thus limiting our knowledge at the cellular level. In this study, we employ a MR framework to infer cell type-specific causal relationships between gene expression and brain-associated complex traits, using eQTL data from eight cell types and large-scale GWASs of 123 imaging-derived phenotypes (IDPs) and 26 brain disorders and behaviors (DBs). Our analysis constructs a cell type-specific causal gene atlas for IDPs and DBs, which include 254 and 217 potential causal cell type-specific eQTL target genes (eGenes) for IDPs and DBs, respectively. The identified results exhibit high cell type specificity, with over 90% of gene-IDP and 80% of gene-DB associations being unique to a single cell type. We highlight shared cell type-specific patterns between IDPs and DBs, characterize the putative causal pathways among cell type-specific causal eGenes, DBs and IDPs, and reveal the spatiotemporal expression patterns of these cell type-specific causal eGenes. We also demonstrate that cell type-specific causal eGenes can characterize the associations between IDPs and DBs. In summary, our study provides novel insights into the genetic foundations at the cellular level that influence brain structures, disorders and behaviors, which reveals important implications for therapeutic targets and brain health management.\",\"PeriodicalId\":501375,\"journal\":{\"name\":\"medRxiv - Genetic and Genomic Medicine\",\"volume\":\"62 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Genetic and Genomic Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.08.30.24312836\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Genetic and Genomic Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.30.24312836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deciphering causal relationships between cell type-specific genetic factors and brain imaging-derived phenotypes and disorders
The integration of expression quantitative trait loci (eQTLs) and genome-wide association study (GWAS) findings to identify causal genes aids in elucidating the biological mechanisms and the discovery of potential drug targets underlying complex traits. This can be achieved by Mendelian randomization (MR), but to date, most MR studies investigating the contribution of genes to brain phenotypes have been conducted on heterogeneous brain tissues and not on specific cell types, thus limiting our knowledge at the cellular level. In this study, we employ a MR framework to infer cell type-specific causal relationships between gene expression and brain-associated complex traits, using eQTL data from eight cell types and large-scale GWASs of 123 imaging-derived phenotypes (IDPs) and 26 brain disorders and behaviors (DBs). Our analysis constructs a cell type-specific causal gene atlas for IDPs and DBs, which include 254 and 217 potential causal cell type-specific eQTL target genes (eGenes) for IDPs and DBs, respectively. The identified results exhibit high cell type specificity, with over 90% of gene-IDP and 80% of gene-DB associations being unique to a single cell type. We highlight shared cell type-specific patterns between IDPs and DBs, characterize the putative causal pathways among cell type-specific causal eGenes, DBs and IDPs, and reveal the spatiotemporal expression patterns of these cell type-specific causal eGenes. We also demonstrate that cell type-specific causal eGenes can characterize the associations between IDPs and DBs. In summary, our study provides novel insights into the genetic foundations at the cellular level that influence brain structures, disorders and behaviors, which reveals important implications for therapeutic targets and brain health management.