Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits. Issue Volume 51:Issue D1(2023) (16th October 2022)

• Record Type: Journal Article
• Authors: Pan, Siyu; Kang, Hongen; Liu, Xinxuan; Lin, Shiqi; Yuan, Na; Zhang, Zhang; Bao, Yiming; Jia, Peilin
• Is Part Of: Nucleic acids research. Volume 51:Issue D1(2023)
• Page Start: D835
• Page End: D844
• Publication Date: 2022-10-16
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkac895
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog ), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.