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Fig. 1 | Genome Medicine

Fig. 1

From: Development of genome-wide polygenic risk scores for lipid traits and clinical applications for dyslipidemia, subclinical atherosclerosis, and diabetes cardiovascular complications among East Asians

Fig. 1

Study design and workflow. A polygenic risk score (PRS) for each lipid trait was derived by (1) association statistics from the Biobank Japanese Project and (2) linkage disequilibrium (LD) between genetic variants from a reference panel of 504 East Asians in 1000 Genomes Project. A total of 34 candidate PRSs were developed using two strategies: (1) the “pruning and thresholding” approach, which involves pruning the genetic variants based on the pairwise threshold of LD r2 (0.2, 0.4, and 0.6), and subsequently applying a p value threshold (1, 0.5, 0.1, 0.05, 0.01, 1 × 10−3, 1 × 10−4, 1 × 10−5, and 5 × 10−8) to the association statistics. And (2) the LDPred computational algorithm, a Bayesian method that estimates the posterior mean causal effect for each variant by assuming a prior effect size from summary statistics and LD information from an external reference panel. Multiple LDpred scores were calculated by varying the tuning parameter ρ (1, 0.3, 0.1, 0.03, 0.01, 3 × 10− 3, and 1 × 10− 3) which are the fractions of markers with non-zero effects. The optimal PRS for each lipid trait was chosen based on maximal correlation with the corresponding lipid trait in a total of 4271 individuals in the validation datasets, and then tested for the associations with lipid metabolism, changes in lipid levels, and cardiovascular risk in multiple independent cohorts

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