Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity.

Journal: Cell genomics

Volume: 2

Issue: 12

Year of Publication: 

Affiliated Institutions:  Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Minatu-ku, Tokyo, Japan.

Abstract summary 

Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.

Authors & Co-authors:  Tsuo Kristin K Zhou Wei W Wang Ying Y Kanai Masahiro M Namba Shinichi S Gupta Rahul R Majara Lerato L Nkambule Lethukuthula L LL Morisaki Takayuki T Okada Yukinori Y Neale Benjamin M BM Daly Mark J MJ Martin Alicia R AR

Study Outcome 

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Statistics
Citations :  Thomsen S.F., van der Sluis S., Kyvik K.O., Skytthe A., Backer V. Estimates of asthma heritability in a large twin sample. Clin. Exp. Allergy. 2010;40:1054–1061. doi: 10.1111/j.1365-2222.2010.03525.x.
Authors :  14
Identifiers
Doi : 100212
SSN : 2666-979X
Study Population
Male,Female
Mesh Terms
Other Terms
GWAS;asthma;cross-trait;heterogeneity;meta-analysis;multi-ancestry;polygenic risk prediction;subtypes
Study Design
Cross Sectional Study
Study Approach
Country of Study
Publication Country
United States