A new genome-wide polygenic score has been used to determine the risk of chronic kidney disease (CKD) in patients with scores in the top 2%.
A study published in natural medicine found that genetic testing through a genome-wide polygenic score (GPS) can detect people with an increased risk of chronic kidney disease (CKD) and also determined that the APOL1 genotype was an increased risk factor for CKD in people of African descent.
There were 19 candidate scores generated using the 1000-genome linkage disequilibrium benchmark and genome-wide association studies (GWAS) summary statistics for eGFR. The study used the UK Biobank, eMERGE, the University of Alabama and BioMe databases to collect data for this study. There were 6,573 patients of European ancestry and 170,635 controls for the GPS population. There were 967 patients of African descent and 6191 controls to determine the derivation of the effects of APOL1.
There were significant differences in mean polygenic risk across all populations, with a trend towards higher risk in people of African descent compared to other populations. The change was more pronounced when including APOL1 genotype at risk. The polygenic risk score for CKD was higher in people of African descent than in other populations, regardless of APOL1 as these data suggest.
The study also found that the mean difference in risk allele frequencies between African and European populations was greater than an expected mean of 0, indicating a higher frequency of risk alleles in African genomes. The GPS had highly reproducible performances (odds ratio [OR], 1.46; 95% CI, 1.43-1.48).
GPS was also tested in 6 cohorts of African descent, where GPS had a pooled OR of 1.32 (95% CI, 1.26-1.38) in the pooled meta-analysis. The risk of CRF for individuals in the top 2% of the GPS score was 80% higher in the model without APOL1 and 170% higher in the model with APOL1 compared to the remaining 98% of individuals.
GPS was used for 2 Latinx cohorts, which found a combined OR of 1.42 (95% CI, 1.29-1.57) in the combined meta-analysis. The inclusion of APOL1 genotypes improved risk prediction in Latinx cohorts. In 4 Asian cohorts, GPS had a pooled OR of 1.68 (95% CI, 1.45-2.06) although APOL1 genotypes were absent from these cohorts.
The top 2% of the risk score distribution was associated with a 166% to 393% higher risk of CKD than other individuals in Europe (OR, 3.60; 95% CI, 3.11-4 .17), in Africa (OR, 2.66; 95% CI, 2.01-3.51), Latinx (OR, 4.93; 95% CI, 2.46-9.89) and Asians ( OR, 3.81; 95% CI, 1.91-7.59).
There were some limitations to this study. There was a lack of large-scale GWA for renal function in non-European populations and existing cohorts were small. Performance comparisons between ancestral groups may have been biased by differences in genotyping platforms used by various biobanks. Ancestry definitions varied across the cohorts used in this study, with 2 using genetic approaches and the remainder using self-report. This prevented the study from assessing risk within African American populations by country of origin.
The study score models the polygenic effects of GWAS rather than CKD. There were also differences in the mean and variance of the GPS ancestry distributions. Finally, the CKD-EPI 2009 was used in this study for lack of an alternative at the time of the analyses.
The researchers concluded that their new GPS for IRC demonstrated that the polygenic component and APOL1 at-risk genotypes had effects on CKD risk. People with the highest risk score distribution had an increased risk of getting CKD roughly equivalent to a positive family history.
Khan A, Turchin MC, Patki A, et al. Genome-wide polygenic score to predict chronic kidney disease across ancestry. NatMed. Published online June 16, 2022. doi:10.1038/s41591-022-01869-1