Additional file 4 of Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
Creators: name: Jain, Pritesh R.
name: Burch, Myson
name: Martinez, Melanie
name: Mir, Pablo
name: Fichna, Jakub P.
name: Zekanowski, Cezary
name: Rizzo, Renata
name: Tümer, Zeynep
name: Barta, Csaba
name: Yannaki, Evangelia
name: Stamatoyannopoulos, John
name: Drineas, Petros
name: Paschou, Peristera
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 4: Supplementary Table 1. Data sources and number of samples analyzed per population. Supplementary Table 2. Number of SNPs used for PRS calculation. The first column indicates the disorder, and each following column indicates number of SNPs used in the estimation at different p-value thresholds. Supplementary Table 3. Pearson’s correlation coefficients between average genetic risk between 14 complex disorders and the average location of 9 European populations in a PCA plot (PC1 and PC2 only). The value in each cell represents the correlation coefficient and the respective p-value estimate. Supplementary Table 4. Pearson’s correlation coefficients between average genetic risk between 14 complex disorders and the average location of 24 world populations in a PCA plot (PC1 and PC2 only). The value in each cell represents the correlation coefficient and the respective p-value estimate. Supplementary Table 5. Pearson's correlation coefficients of r2 estimates of SNP pairs in regions used for PRS estimation between 4 pairs of populations. Statistically significant results (empirical p-value &lt;0.05) are indicated as bold. Supplementary Table 6. Mean FST estimates of PRS SNPs between European and other populations for the six disorders that demonstrated significant correlation between average PRS and population prevalence. Statistically significant results (empirical p-value &lt; 0.05) are indicated as bold. Supplementary Table 7. Pearson’s correlation coefficients for average genetic risk between 18 complex disorders and their prevalence in European populations. The column headers indicate the p-value threshold for PRS calculation and the value in each cell shows the correlation coefficient (R2) and respective p-value (in parentheses). (*) indicates empirical p-value&lt;0.05. Supplementary Table 8. Pearson’s correlation coefficient for average genetic risk between 18 complex disorders and their prevalence in 24 countries. The column headers indicate the p-value threshold for PRS calculations. The value in each cell represents the correlation coefficients and p-values based on 1,000 permutations (shown in parentheses). (*) indicates empirical p-value&lt;0.05. Supplementary Figure 1. Bar plot showing the mean FST between four pairs of populations. The x-axis indicates the disorders, and the y-axis shows the mean FST for each pair of populations. The dotted line shows the mean FST value of a distribution formed using 100 random SNP sets. (*) indicates an empirical p-value below 0.05. Supplementary Figure 2. Heatmap of average PRS (r2 = 0.1; p-value&lt;1) of 14 Disorders across European Populations. Populations are arranged based on geographical proximity; shades of cells indicate the standardized genetic risk of each disorder for each population. A higher risk is shown by red, and a lower risk is indicated by blue [SEU – South Europeans, CEU – Central Europeans, NEU – North Europeans]. Supplementary Figure 3. Heatmap of average PRS (r2 = 0.1; p-value&lt;1) of 14 Disorders across Worldwide Populations. Populations are arranged based on geographical proximity; shades of cells indicate the standardized genetic risk of each disorder for each population. A higher risk is shown by red, and a lower risk is indicated by blue. [AFR – Africans, EUR – Europeans, SAS – South Asians, EAS– East Asians, AMR – Admixed Americans].