Development and validation of a multiancestry and multitrait polygenic risk score for lung cancer

Polygenic risk scores (PRSs) quantify genetic susceptibilities, yet ancestry imbalance in genome-wide association studies (GWASs) limits the accuracy of monoracial PRSs in non-European populations. Here, we perform a multiancestry GWAS meta-analysis for lung cancer (76,953 cases and 1,886,372 controls), identifying 87 conditionally independent genome-wide significant loci, including two unreported cytobands. We use a PRS construction method, PRS-CSx, to develop a multiancestry PRS ( ${\mathrm{PRS}}_{\mathrm{MA}}$ ) which outperforms 32 published PRSs. To enhance predictive power, we construct a multitrait PRS ( ${\mathrm{PRS}}_{\mathrm{MT}}$ ) using CatBoost, integrating 32 cross-trait PRSs across three ancestries. Combining ${\mathrm{PRS}}_{\mathrm{MA}}$ and ${\mathrm{PRS}}_{\mathrm{MT}}$ , we generate ${\mathrm{PRS}}_{\mathrm{MAMT}}$ and validate it in independent cohorts (OncoArray, TRICL and All of Us). ${\mathrm{PRS}}_{\mathrm{MAMT}}$ demonstrates superior discriminability in European, Asian, and African populations, improves risk stratification, and identifies approximately 10% additional lung cancer cases in the UK Biobank. Individuals with elevated PLCO_m2012 scores and high genetic risk exhibit a 12.64-fold higher cumulative risk than those with low scores and low genetic risk, supporting precision prevention strategies.