In our new publication out in the journal of Genetic Epidemiology titled “Correcting for Genomic Inflation Leads to Loss of Power in Large‐Scale Genome‐Wide Association Study Meta‐Analysis“, we investigate the impact of commonly used correction methods on the power of GWAS meta-analyses. Using type 2 diabetes (T2D) as a model trait, we show that genomic control (GC) and linkage disequilibrium score regression (LDSR)—while designed to reduce false positives—can significantly reduce the number of detected genetic associations in large, well-powered studies.

Notably, GC correction led to a 39.7% loss of independent loci, while LDSR correction resulted in a 25.2% reduction, highlighting a trade-off between statistical rigor and discovery potential. These findings underscore the need for improved methods to address genomic inflation without compromising the ability to detect true associations, especially in polygenic traits like T2D. You can read the full article here: https://doi.org/10.1002/gepi.70016