MUSSEL: Enhanced Bayesian Polygenic Risk Prediction Leveraging Information across Multiple Ancestry Groups

Polygenic risk scores (PRS) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across different populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in the summary statistics from genome-wide association studies (GWAS) across multiple ancestry groups. MUSSEL conducts Bayesian hierarchical modeling under a MUltivariate Spike-and-Slab model for effect-size distribution and incorporates an Ensemble Learning step using super learner to combine information across different tuning parameter settings and ancestry groups. In our simulation studies and data analyses of 16 traits across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. The method, for example, has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African Ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, underlying trait architecture, and the choice of reference samples for LD estimation, and thus ultimately, a combination of methods may be needed to generate the most robust PRS across diverse populations.

Genome-Wide Association Study of Age-Related Macular Degeneration Reveals 2 New Loci Implying Shared Genetic Components with Central Serous Chorioretinopathy

PURPOSE

To investigate the genetic architecture of age-related macular degeneration (AMD) in a Japanese population.

DESIGN

Genome-wide association study (GWAS).

PARTICIPANTS

Three thousand seven hundred seventy-two patients with AMD and 16 770 control participants from the Japanese population were enrolled in the association analyses.

METHODS

We conducted a meta-analysis of 2 independent GWASs that included a total of 2663 patients with AMD and 9471 control participants using the imputation reference panel for genotype imputation specified for the Japanese population (n = 3541). A replication study was performed using an independent set of 1109 patients with AMD and 7299 control participants.

MAIN OUTCOME MEASURES

Associations of genetic variants with AMD.

RESULTS

A meta-analysis of the 2 GWASs identified 6 loci significantly associated with AMD (P < 5.0 × 10^-8). Of these loci, 4 were known to be associated with AMD (CFH, C2/FB, TNFRSF10A, and ARMS2), and 2 were novel (rs4147157 near WBP1L and rs76228488 near GATA5). The newly identified associations were confirmed in a replication study (P < 0.01). After the meta-analysis of all datasets, we observed strong associations in these loci (P = 1.88 × 10^-12 and P = 1.35 × 10^-9 for meta-analysis for rs4147157 and rs76228488, respectively). When we looked up the associations in the reported central serous chorioretinopathy (CSC) GWAS conducted in the Japanese population, both loci were associated significantly with CSC (P = 4.86 × 10^-3 and P = 4.28 × 10^-3 for rs4147157 and rs76228488, respectively). We performed a genetic colocalization analysis for these loci and estimated that the posterior probabilities of shared causal variants between AMD and CSC were 0.39 and 0.60 for WBP1L and GATA5, respectively. Genetic correlation analysis focusing on the epidemiologically suggested clinical risk factors implicated shared polygenic architecture between AMD and smoking cessation (r_g [the measure of genetic correlation] = -0.33; P = 0.01; false discovery rate, 0.099).

CONCLUSIONS

Our findings imply shared genetic components conferring the risk of both AMD and CSC.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.