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Singh, A. ; Southam, L. ; Hatzikotoulas, K. ; Rayner, N.W. ; Suzuki, K.* ; Taylor, H.J.* ; Yin, X.* ; Mandla, R.* ; Huerta-Chagoya, A.* ; Morris, A.P. ; Zeggini, E. ; Bocher, O.

Correcting for genomic inflation leads to loss of power in large-scale Genome-wide association study meta-analysis.

Genet. Epidemiol. 49:e70016 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Inflation in genome-wide association studies (GWAS) summary statistics represents a major challenge, for which correction methods have been developed. These include the genomic control (GC) method, which uses the λ-value to correct summary statistics, and the linkage disequilibrium score regression (LDSR) method, which uses the LDSR intercept. By using type 2 diabetes (T2D) as an exemplar, we explore factors influencing λ-values and the impact of these corrections on association signals. We find that larger sample sizes increase λ-values due to increased captured polygenicity, while including lower frequency variants decreases λ-values due to reduced power. Comparing T2D genetic associations described in overlapping GWAS meta-analyses of increasing sample size, we find that GC correction reduces the false positive rate and leads to the loss of robust associations. In one of the largest meta-analysis, GC correction results in 39.7% loss of independent loci, substantially reducing the number of detected associations. In comparison, the LDSR intercept correction leads to a loss of up to 25.2% of the independent loci, being therefore less conservative than the GC correction. We conclude that in large, well-powered GWAS meta-analysis of polygenic traits, both GC and LDSR intercept correction leads to power loss, highlighting the need for improved genomic inflation correction methods.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Gwas Meta‐analysis ; Ld‐score Regression ; Genetic Associations ; Genomic Control ; Genomic Inflation; Complex Traits; Rare Variants; Polygenicity; Regression; Discovery; Efficient
ISSN (print) / ISBN 0741-0395
e-ISSN 1098-2272
Zeitschrift Genetic Epidemiology
Quellenangaben Band: 49, Heft: 6, Seiten: , Artikelnummer: e70016 Supplement: ,
Verlag Wiley
Verlagsort 111 River St, Hoboken 07030-5774, Nj Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)
Förderungen Archit Singh and Dr Ozvan Bocher have received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement No 101017802 (OPTOMICS).