five

Genetic modifiers of Huntington’s disease differentially influence motor and cognitive domains

收藏
DataONE2024-06-29 更新2024-07-06 收录
下载链接:
https://search.dataone.org/view/sha256:5b91f9b3f9167a8b4af4ce29a936816d745e43895354293ac95364b48ac11264
下载链接
链接失效反馈
官方服务:
资源简介:
Genome-wide association studies (GWAS) of Huntington’s disease (HD) have identified six DNA maintenance gene loci (among others) as modifiers and implicated a two step-mechanism of pathogenesis: somatic instability of the causative HTT CAG repeat with subsequent triggering of neuronal damage. The largest studies have been limited to HD individuals with a rater-estimated age at motor onset. To capitalize on the wealth of phenotypic data in several large HD natural history studies, we have performed algorithmic prediction using common motor and cognitive measures to predict age at other disease landmarks as additional phenotypes for GWAS.  Combined with imputation using the Trans-Omics for Precision Medicine reference panel, predictions using integrated measures provided objective landmark phenotypes with greater power to detect most modifier loci.  Importantly, substantial differences in the relative modifier signal across loci, highlighted by comparing common modifiers at MSH3 and FAN1,..., Five batches of GWA data sets were produced and subsequently imputed using the HRC reference panel.  as described previously (Cell 2019, 178, 887). Genotype imputation using the TOPMed reference panel was performed similarly. Briefly, the individual genotype data set (i.e., GWA1, 2, 3, 4, and 5) comprising subjects with genotype call rate greater than 90% and single nucleotide variants (SNVs) with call rate > 95% and MAF > 1% was subjected to quality control by the “HRC or 1000G Imputation preparation and checking” program. Additional QC was performed using the TOPMed Imputation Server, revealing genomic regions of 10 MB with at least one sample with call rate < 50%. Those low call rate samples at certain genomic regions were further excluded from genotype imputation. The final QC-passed typed data set was used for imputation by the TOPMed Imputation Server. Genomic coordinates of TOPMed imputation data were converted to GRCh37/hg19 to make this data set directly comparable to ..., ,
创建时间:
2024-06-30
二维码
社区交流群
二维码
科研交流群
商业服务