Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

General information

Full name: a One-Stop Shop for Brain-related Traits
Description: Brain Catalog is a comprehensive resource for genetic landscape of brain disorders and related phenotypes. Currently, Brain Catalog includes the following components: 1. Variant annotation by three software VEP, snpEff and ANNOVAR. 2. Gene-based and gene set analysis by MAGMA. 3. Heritability, heritability enrichment and heritability correlation analysis by two software LDSC and LDAK. 4. Enrichment analysis of associated-trait loci in regulatory and functional annotations by GARFIELD and S-LDSC. 5. Finemapping analysis by four fine-mapping methods ABF, FINEMAP, SuSiE and PolyFun + SuSiE. 6. Gene-based TWAS association by three software S-PrediXcan, UTMOST and JTI. 7. Causal inference and colocalization between six kinds of molecule-QTLs and brain traits, and also the causal effect of exposure traits on outcome traits.
Year founded: 2022
Last update: 2022-10-18
Version: 1.0
Real time : Checking...
Country/Region: China

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Contact information

University/Institution: Beijing Institute of Genomics, Chinese Academy of Sciences
Address: No.1 Beichen West Road, Chaoyang District, Beijing
City: Beijing
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Peilin Jia
Contact email (PI/Helpdesk):


Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits. [PMID: 36243988]
Pan S, Kang H, Liu X, Lin S, Yuan N, Zhang Z, Bao Y, Jia P.

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 (, 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.

Nucleic Acids Res. 2022:() | 0 Citations (from Europe PMC, 2022-12-03)



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Created on: 2022-10-18
Curated by:
Lina Ma [2022-10-18]
Hongen Kang [2022-10-18]