Identifying Alzheimer's genes via brain transcriptome mapping.
Jae Young BaikMansu KimJingxuan BaoQi LongLi Shennull nullPublished in: BMC medical genomics (2022)
We have proposed a novel disease-related brain transcriptomic mapping method to identify genes whose expression profiles spatially correlated with regional diagnostic effects on a studied brain trait. Our empirical study on the AHBA and ADNI data shows the promise of the approach, and the resulting AD gene discoveries provide valuable information for better understanding biological pathways from transcriptomic signatures to intermediate brain traits and to phenotypic disease outcomes.
Keyphrases
- genome wide
- resting state
- white matter
- dna methylation
- single cell
- functional connectivity
- high resolution
- genome wide identification
- copy number
- gene expression
- big data
- type diabetes
- healthcare
- skeletal muscle
- metabolic syndrome
- deep learning
- subarachnoid hemorrhage
- genome wide analysis
- data analysis
- glycemic control