Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants

Guanghao Qi, Surya B. Chhetri, Debashree Ray, Diptavo Dutta, Alexis Battle, Samsiddhi Bhattacharjee () and Nilanjan Chatterjee ()
Additional contact information
Guanghao Qi: University of Washington
Surya B. Chhetri: Johns Hopkins University
Debashree Ray: Johns Hopkins University
Diptavo Dutta: National Cancer Institute
Alexis Battle: Johns Hopkins University
Samsiddhi Bhattacharjee: Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG)
Nilanjan Chatterjee: Johns Hopkins University

Nature Communications, 2024, vol. 15, issue 1, 1-18

Abstract: Abstract Genome-wide association studies (GWAS) have found widespread evidence of pleiotropy, but characterization of global patterns of pleiotropy remain highly incomplete due to insufficient power of current approaches. We develop fastASSET, a method that allows efficient detection of variant-level pleiotropic association across many traits. We analyze GWAS summary statistics of 116 complex traits of diverse types collected from the GRASP repository and large GWAS Consortia. We identify 2293 independent loci and find that the lead variants in nearly all these loci (~99%) to be associated with $$\ge 2$$ ≥ 2 traits (median = 6). We observe that degree of pleiotropy estimated from our study predicts that observed in the UK Biobank for a much larger number of traits (K = 4114) (correlation = 0.43, p-value $$

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-51075-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51075-5

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-51075-5

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().