We demonstrated that DeepGAMI improves phenotype prediction and prioritizes phenotypic features and networks in multiple multimodal datasets in complex brains and brain diseases.
Our results describe the complex regulation of cell composition at critical stages in lineage determination and shed light on the impact of spatiotemporal alterations in gene expression on neuropsychiatric disease.
We present a new atlas of bulk proteomics and DNA methylation, as well as cell-type-specific RNA-seq and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data for deeply characterized AD samples.
DNA methylation was found to have a profound impact on not only the AD-associated gene modules but also key regulators of the gene and protein networks. Key findings were validated in an independent multi-omics cohort in AD. The impact of DNA methylation on chromatin accessibility was also investigated by integrating the matched methylomic, epigenomic, transcriptomic, and proteomic data.
Genome-wide analyses identify 27 loci associated with attention-deficit hyperactivity disorder and provide insights into its genetic architecture in relation to other psychiatric disorders and cognitive traits.
Genome-wide analyses identify 27 loci associated with attention-deficit hyperactivity disorder and provide insights into its genetic architecture in relation to other psychiatric disorders and cognitive traits.