Protein-truncating variant in APOL3 increases chronic kidney disease risk in epistasis with APOL1 risk alleles

BACKGROUND. Two coding alleles within the APOL1 gene, G1 and G2, found almost exclusively in individuals genetically similar to West African populations, contribute substantially to the pathogenesis of chronic kidney disease (CKD). The APOL gene cluster on chromosome 22 contains a total of six APOL genes that have arisen as a result of gene duplication. METHODS. Using a genome-first approach in the Penn Medicine Biobank, we identified 62 protein-altering variants in the six APOL genes with a minor allele frequency > 0.1% in a population of participants genetically similar to African reference populations and performed population-specific phenome-wide association studies. RESULTS. We identified rs1108978, a stop-gain variant in APOL3 (p.Q58*), to be significantly associated with increased CKD risk, even after conditioning on APOL1 G1/G2 carrier status. These findings were replicated in the Veterans Affairs Million Veteran Program and the All of Us Research Program. APOL3 p.Q58* was also significantly associated with a number of quantitative traits linked to CKD including decreased kidney volume. This truncating variant contributed the most risk for CKD in patients monoallelic for APOL1 G1/G2, suggesting an epistatic interaction and a potential protective effect of wild-type APOL3 against […]


Introduction
Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are significantly more common in individuals genetically similar to African reference populations (AFR) compared with those genetically similar to European reference populations (EUR) (1,2).While there are multiple attributable factors, one of most impactful is common genetic variation in the APOL1 gene (3)(4)(5).Two coding alleles within the APOL1 gene, G1 and G2, are found almost exclusively in individuals genetically similar to West African populations and contribute substantially to the pathogenesis of nondiabetic kidney disease, focal segmental glomerulosclerosis (FSGS), and HIV-associated nephropathy (HIVAN) (6,7).The G1 allele (minor allele frequency -MAF ~23% in individuals genetically similar to African reference populations used by gnomAD) is comprised of 2 missense variants in near perfect linkage disequilibrium (LD), G1 G (p.S342G) and G1 M (p.I384M).The G2 allele (MAF ~14% in individuals genetically similar to African reference populations used by gnomAD) is a 6-base pair in-frame deletion (p.NYK388-389K).The high allele frequency of these variants particularly in West African populations is caused by a recent positive selective sweep due to the protective effects they confer against Trypanosoma brucei infections, the cause of African sleeping sickness (8).In fact, evidence suggests that G1/G2 are toxic gain-of-function variants in APOL1, a gene shown to play roles in programmed cell death and pathogen immunity (9).
The G1 and G2 alleles arose independently on separate chromosomes and are too close in proximity to have undergone a recombination event that would allow a single haplotype to carry both G1 and G2.
Hence, risk of CKD is modeled on a scale of zero to two by the total number of G1/G2 alleles an individual carries.Individuals with two G1/G2 risk alleles are considered to be 'high-risk' for CKD.
Recently, a missense variant p.N264K in APOL1 was shown to exert protective effects in 'high-risk' APOL1 individuals by inhibiting APOL1 pore-forming function and ion channel conduction (10).
The APOL gene cluster on chromosome 22 contains a total of six APOL genes that have arisen as a result of gene duplication (11).The physiological functions of the APOL proteins are poorly understood.
We hypothesized that there may be other protein-altering variants in the APOL genes that are associated with health and disease in the AFR population.Adopting a genome-first approach, we leveraged the Penn Medicine Biobank (PMBB), a large medical biobank with whole exome sequence data linked to electronic health records (EHR) (12), to study the phenotypes associated with proteinaltering variants in the six APOL genes with a focus on the AFR population.We identified an AFRspecific protein-truncating variant in APOL3 (MAF ~22% in individuals genetically similar to African reference populations used by gnomAD) that is significantly associated with increased risk of CKD and primarily increases CKD risk in monoallelic carriers of the APOL1 G1/G2 alleles.

Results
Phenome-wide association studies for protein-altering variants in APOL genes Of the 43,731 consented individuals in the PMBB with whole-exome sequencing (WES), we extracted 841 protein-altering variants across all six APOL genes, of which 100 were predicted loss-of-function (pLOF), 4 were in-frame insertions/deletions, and 737 were missense.With a specific focus on variants in individuals genetically similar to African reference populations, we filtered our variant set down to 62 variants with a minor allele frequency (MAF) > 0.1% in the PMBB AFR population (n = 11,198), for which we show that statistical power to detect an association is sufficient (Supplemental Figure 1).This set of variants included 6 pLOFs, 1 in-frame deletion, and 55 missense mutations including both APOL1 G1 and G2 AFR-specific risk alleles for kidney disease (Supplemental Table 1).For each of these 62 variants, we performed a phenome-wide association study (PheWAS) in the AFR population in PMBB against 1,222 binary phenotypes defined as PheCodes derived from EHR data (Figure 1), followed by additional downstream variant-specific analyses (Supplemental Figure 2).Using a strict Bonferroni p-value correction adjusting for every single variant-phenotype association performed, 58 significant associations (p-value < 6.63E-07) were observed across 5 variants (Table 1) and 23 unique phenotypes, all of which were related to renal disease (Supplemental Table 2).Three of the five significant variants were in APOL1, including the G1 risk allele [rs73885319 (p.S342G) and rs60910145 (p.I384M)] as well as a third missense variant rs2239785 (p.E150K).All three variants had strong associations with end-stage renal disease (ESRD) with odds ratios (OR) of 1.70 (95% CI = 1.52-1.90,p = 6.92E-21), 1.68 (95% CI = 1.50-1.88,p = 5.83E-20), and 1.50 (95% CI = 1.34-1.68,p = 1.06E-12) respectively.A missense variant in APOL2, rs7285167 (p.R182C), was significantly associated with ESRD with an OR of 1.43 (95% CI = 1.29-1.59,p = 1.29E-11).Finally, a stop-gain variant in APOL3, rs11089781 (p.Q58*), was significantly associated with ESRD, with an OR of 1.39 (95% CI = 1.24-1.56,p = 5.18E-09).Of note, the APOL1 G2 allele alone did not meet our strict significance threshold but was also found to be strongly associated with ESRD with an OR of 1.33 (95% CI = 1.16-1.53,p = 2.45E-05).Similarly, the APOL1 p.N264K protective variant also did not meet our significance threshold but was found to be nominally associated with decreased risk of nephritis; nephrosis; renal sclerosis with an OR of 0.43 (95% CI = 0.23-0.81,p = 4.63E-03) and decreased risk of ESRD with an OR of 0.64 (95% CI = 0.41-0.99,p = 2.18E-02).We repeated the analyses in the EUR population and meta-analyzed under a fixed-effects model and observed similar significant findings (Supplemental Figure 3, Supplemental Table 3).ESRD had a prevalence of 8.4% in the PMBB AFR population.The average age of ESRD cases was 55.8 years old compared to 51.2 years old in controls (t-test p = 1.86E-22).58.3% of cases were male compared to 34.8% of controls (chi-sq p = 3.31E-45).
All five significant variants were substantially more common in the AFR population compared to the EUR population in PMBB, and the MAFs in PMBB were similar to the MAFs in the gnomAD v.4.0.0 database (Table 1).We examined the LD structure between these five variants (as well as the APOL1 G2 allele and APOL1 p.N264K variant) in the PMBB AFR population (Figure 2).As expected, the two missense variants that comprise the G1 allele were in virtually complete LD, and neither were in any LD with the G2 allele.The APOL1 rs2239785 (p.E150K) allele had an r 2 value of 0.16 with the G1 allele.
To isolate the independent effects of the three significant non-APOL1 G1/G2 variants on renal disease, we performed conditional associations for the three variants in the PMBB AFR population for all phenotypes originally found to be significantly associated while conditioning on APOL1 G1/G2 risk modelled under its well-known recessive inheritance pattern (Table 2).The APOL1 rs2239785 (p.E150K) allele and the APOL2 rs7285167 (p.R182C) allele were no longer significantly associated with renal phenotypes.However, the APOL3 stop-gain variant rs11089781 (p.Q58*) remained nominally significantly associated with increased risk for renal disease.Conditioning APOL3 p.Q58* on APOL1 p.N264K made minimal difference compared to the unconditional analysis, and conditioning on both APOL1 G1/G2 and p.N264K resulted in minimal change compared to only conditioning on APOL1 G1/G2 (Supplemental Table 4).This persistence of the association signal indicates that this stop-gain variant in APOL3 has some independent effect on CKD risk.

Interrogation of APOL3 p.Q58* association with ESRD
To investigate potential gene dosage effects of APOL3 p.Q58* on ESRD risk, we compared the prevalence of ESRD cases among different carrier statuses of rs11089781 in the AFR population in our biobank.7.3% of non-carriers of APOL3 rs11089781 were diagnosed with ESRD (cases n = 501, controls n = 6,386) compared to 9.4% of heterozygote carriers (cases n = 332, controls n = 3,206) and 15.5% of homozygote carriers (cases n = 84, controls n = 459).Using Fisher's exact tests, the prevalence of ESRD was significantly different across all three carrier groups (p < 1E-03), suggesting a gene dosage effect on renal disease.Furthermore, we compared the age of onset for ESRD in our cohort among patients with different carrier statuses of p.Q58*.The average age of onset was 55.0 years old in patients who do not carry the variant, 53.1 years old in patients who carry one copy of the variant, and 49.6 years old in patients who carry two copies.Using Student's t-tests, the difference between non-carriers and monoallelic carriers was near significant (p = 0.056), the difference between monoallelic and biallelic carriers was nominally significant (p = 0.042), and the difference between noncarriers and biallelic carriers was most significant (p = 0.002).
Building upon our PheWAS results, we analyzed relevant EHR-derived laboratory measurements and kidney imaging traits to perform quantitative associations with this APOL3 stop-gain variant.Focusing on renal and kidney-related hematological lab values, we computed the maximum, median, and minimum values for each trait for each individual, performed inverse-normal transformation, and again ran all associations in the PMBB AFR population.The same analysis was carried out for relevant kidney imaging traits, where we curated clinically available CT scans from patients in PMBB, segmented the left and right kidneys, extracted quantitative imaging traits, and computed the maximum, median, and minimum values for each trait for each individual followed by normalization.We found that the APOL3 variant was strongly associated with decreased minimum estimated glomerular filtration rate eGFR (p = 2.17E-07, n = 10,435) and increased maximum creatinine (p = 3.85E-06, n = 10,435), consistent with increased risk for renal disease (Supplemental Table 5).We also identified nominally significant associations with decreased minimum red blood cell (RBC) counts (p = 3.49E-03, n = 10,020), consistent with decreased erythropoietin production, as well as decreased minimum lymphocyte percentage (p = 5.57E-03, n = 10,118).We replicated quantitative associations for eGFR and Creatinine in MVP and identified concordant significant associations for decreased mean eGFR (p = 2.42E-13, n = 110,674) and increased mean creatinine (p = 1.63E-08, n = 116,531).We observed similar associations in All of Us for decreased minimum eGFR (p = 7.97E-03, n = 25,572) and increased maximum creatinine (p = 8.13E-03, n = 25,572).Finally, using our analysis of quantitative kidneyderived CT imaging traits, carriers of the APOL3 p.Q58* were found to have significantly decreased minimum kidney volume (p = 2.49E-03, n = 1,767) as well as decreased minimum kidney surface area (p = 5.14E-03, n = 1,768) (Supplemental Table 5).Similar association results were observed when the AFR population results were meta-analyzed under a fixed-effects model with results from the EUR population (Supplemental Table 6).Thus, in addition to its association with diagnosis codes reflecting CKD, APOL3 p.Q58* is associated with a number of quantitative traits concordant with CKD across three different cohorts enriched in participants genetically similar to African reference populations.
We then analyzed the association of APOL3 p.Q58* with CKD after stratifying by APOL1 G1/G2 carrier status.Given the possible recessive effects of our APOL3 variant suggested by our gene dosage results, we performed the stratification analyses under both an additive and recessive model.Interestingly, we found that APOL3 p.Q58* increases risk for ESRD most significantly under a recessive inheritance pattern in monoallelic APOL1 G1/G2 risk allele carriers (Table 3).We found the same result upon stratified analyses of this variant with eGFR and creatinine.This result suggested that this APOL3 stopgain variant may have an epistatic interaction with APOL1 G1/G2 and increases risk of CKD most prominently in monoallelic carriers for either the APOL1 G1 or G2 allele.Carrier counts for both APOL1 G1/G2 and APOL3 p.Q58* are specified in Supplemental Table 7.In these APOL1 G1/G2 monoallelic individuals, we found that 7.0% of individuals who are low-risk (Q/Q or Q/*) for p.Q58* under its recessive inheritance pattern were diagnosed with ESRD (cases n = 330, controls n = 4,379) compared to 11.6% of individuals who are high-risk (*/*) for p.Q58* (cases n = 29, controls n = 221) with a significant Fischer's exact test (p = 0.011).In addition, the average age of onset for ESRD in the p.Q58* low-risk group was 56.9 years old compared to 50.6 years old in the p.Q58* high-risk group (t-test p = 0.036).Furthermore, we performed an interaction analysis between APOL1 G1/G2, modelled under its well-known recessive inheritance pattern, and APOL3 p.Q58*, also under a recessive model given the results of the stratified analyses.We found that the interaction between the variants was nominally significant (p = 0.02) with a negative association coefficient ( = -0.15),suggesting that although there is evidence of variant interaction, any risk conferred by APOL3 p.Q58* is likely overwhelmed by biallelic APOL1 G1/G2 risk.

Discussion
The growing scale of genetic association studies has powered the discovery of novel disease variants, increased our understanding of disease pathogenesis, and spurred the development of precision medicine therapeutics (13)(14)(15).Yet, of all the genome-wide association studies (GWAS) currently compiled in the GWAS catalog, ~95% of all GWAS participants are genetically similar to European reference populations (16).The lack of population diversity not only limits the study and discovery of non-EUR variants to those with high penetrance and large effect sizes (17)(18)(19)(20), but also hinders the generalizability of any GWAS discoveries at risk of further compounding existing health disparities (21)(22)(23).Even though using increasingly diverse population cohorts will begin to mitigate these concerns, further enriching a genetic association study specifically for variants common in non-EUR populations may also enhance our ability to uncover new genetic variant associations.It is well-known that two coding alleles within the APOL1 gene, G1 and G2, found almost exclusively in individuals genetically similar to West African populations, contribute substantially to risk for chronic kidney disease (CKD).
Taking a genome-first approach, we used a medical biobank enriched in participants genetically similar to African reference populations with whole exome genomic data linked to rich phenotypic data to perform PheWAS of protein-coding variants in the six APOL genes.After correction for multiple testing, we identified several variants in the APOL gene family predominantly represented in the AFR population and significantly associated with CKD.Of particular interest, we identified a stop-gain variant p.Q58* in the APOL3 gene, with an AFR MAF of 0.211 and EUR MAF of < 0.001, that is significantly associated with CKD risk independent of APOL1 G1/G2.These results highlight the value of combining targeted genome-first approaches with PheWAS in diverse patient biobanks for better understanding genetic risk for kidney disease.
Our initial analysis identified 3 significant variants other than APOL1 G1/G2 with significant kidney disease associations.rs2239785 is a missense variant in APOL1 that has been previously reported to be linked with risk for nondiabetic nephropathy and FSGS (24,25).Another missense variant, rs7285167, in APOL2 has been shown to be weakly associated with all-cause ESRD (26) and also identified in a APOL2 protein-specific quantitative trait loci (QTL) study as strongly associated with protein levels (27).However, this variant is in moderate linkage with APOL1 G1/G2 (r 2 = 0.264).
Furthermore, in our present study, the significant association signals for both variants disappear when conditioning on APOL1 G1/G2 recessive risk, decreasing our confidence that they play an independent role in renal disease risk.A third variant we identified, rs11089781, is a stop-gain variant in APOL3 at amino acid position 58 out of 402 (p.Q58*), thereby truncating most of the peptide and likely inhibiting its wild-type function.This specific nonsense mutation is also documented as likely to trigger nonsensemediated decay (28).rs11089781 has previously been identified to be weakly associated with nondiabetic nephropathy in small African American and Hispanic American populations, but the finding did not always replicate successfully (29,30).This APOL3 p.Q58* variant is in minimal LD with the APOL1 G1/G2 alleles and upon conditioning on APOL1 G1/G2, remained nominally significantly associated with CKD.The average age of onset for ESRD in individuals who are homozygous for the APOL3 variant was significantly younger than in individuals who do not carry the p.Q58* variant.Furthermore, we replicated this significant association of APOL3 p.Q58* with CKD in both the Million Veteran Program and the All of Us Research Program.Finally, we found that APOL3 p.Q58* was significantly associated with a number of quantitative traits associated with CKD, including increased creatinine and decreased eGFR, kidney volume, and surface area.
The APOL3 protein is thought to play a role in pathogen immunity, similar to APOL1, but specifically targeting intracellular pathogens by dissolving their anionic membranes (31).Our genetic data indicate that wild-type APOL3 may play a protective role in CKD, given that the APOL3 p.Q58* risk variant is very likely to be loss-of-function and confers increased risk for renal disease.While association results solely in individuals with low-risk APOL1 G1/G2 genotypes showed that our APOL3 variant was still strongly associated with increased risk for CKD, our stratified analyses identified that APOL3 p.Q58* contributes the most risk for renal disease in patients who carry one copy of an APOL1 G1 or G2 risk allele, suggesting a complex epistatic interaction with APOL1 G1/G2.Of interest, there is an increasing body of evidence suggesting that APOL1 G1/G2 are toxic gain-of-function mutations, despite their observed recessive inheritance pattern (9,(32)(33)(34).A previous study on the interactions between APOL1 and APOL3 suggested that deletion of APOL3 triggers intracellular actomyosin reorganization, increasing susceptibility to kidney disease through APOL1-induced podocyte dysfunction and kidney damage (35).The specific mechanisms by which APOL1 risk alleles induce podocyte dysfunction are still being studied, with evidence that suggests the APOL1 variant proteins increase endoplasmic reticulum stress, enhances inflammatory signaling within the cells, and interferes with endosomal trafficking (36)(37)(38).The fact that APOL3 p.Q58* contributes no additional significant risk in individuals who carry zero copies of APOL1 G1/G2 suggests that the truncated APOL3 protein is not likely to have a toxic gain of function and further supports the presence of some epistatic interaction with the APOL1 variants.The lack of additional significant risk in patients with two APOL1 G1/G2 risk alleles may indicate that in this high-risk situation, loss of APOL3 has little effect in further increasing CKD risk.Our interaction analysis also showed a nominally significant association between the interaction of APOL1 G1/G2 and APOL3 p.Q58* with CKD, further supporting the presence of some variant-variant interaction.
The negative association coefficient indicates that the overall effect of the interaction term is less than the cumulative effects of the two separate APOL1 and APOL3 risk alleles, supporting the conclusion from the stratified analyses that this truncating APOL3 variant confers little additional risk in the setting of the high-risk APOL1 G1/G2 genotype.The concept that loss of APOL3 promotes the toxic gain-offunction of a single copy of APOL1 G1/G2 might partially explain the observed positive selection of this APOL3 stop-gain variant in African populations, inferred from the regions of extended homozygosity around the truncating mutation (39).A potential explanation is that selection for the APOL3 loss-offunction variant may increase the pathogenicity of APOL1 G1/G2, increasing potential for efficacy against Trypanosoma infection even in the presence of only one G1 or G2 allele.We suggest that the protective effects of wild-type APOL3 on CKD, most markedly observed in monoallelic APOL1 G1/G2 carriers, contribute to the general lack of kidney injury induced by one copy of the APOL1 risk alleles, but not by two copies of the APOL1 risk alleles.This gives rise to the biological manifestation of a recessive inheritance pattern for the APOL1 G1/G2 alleles while reconciling with their gain-of-function toxicity.
The genome-first approach used in our study to filter for AFR-specific protein-altering variants allowed us to identify and focus on variants that likely would have been omitted in larger association studies in EUR-dominated populations.Many of the variants included in our study are extremely rare in the EUR population (Supplemental Table 1), including this APOL3 stop-gain variant, and are too rare to study in predominantly EUR cohorts, highlighting the necessity of study cohorts enriched for non-EUR populations.Furthermore, the threshold for significance used in our initial meta-analysis was calculated based on a strict Bonferroni correction of the total number of genotype-phenotype associations performed, often recommended for PheWAS (40).However, it is evident that not all the variants studied in the APOL gene family are in perfect linkage equilibrium and not all phenotypes analyzed are independent of each other.Using an overly strict significance threshold gives us increased confidence in our findings.
We note that there are certain limitations in the context of our work.Phenotyping data derived from electronic health records have intrinsic noise and imprecisions.We attempted to mitigate this using phecodes that group relevant ICD codes together and applying strict quality control steps on our quantitative clinical traits.We also recognize that there is some selection bias in that patients with disease are more likely to get laboratory markers measured and to undergo CT imaging.This means that the quantitative traits derived from lab values and imaging metrics we have available may be enriched for individuals with pathological trait values.However, this problem is reduced by the diversity in phenotypes in the PMBB, such that a large proportion of patients have non-renal conditions and may still have normal kidney-related lab values and imaging traits.In addition, our LD calculations were based on unphased whole-exome sequencing data estimated using maximum likelihoods on the haplotype frequency cubic equation instead of phased haplotype frequencies.Although the computed values may be inexact, we also obtained LD metrics calculated using phased haplotypes from the 1000 Genomes Project as validation.While the overall sample size of the AFR population in PMBB is limited, we replicated our observations in MVP and All of Us, both of which have substantial participation from individuals genetically similar to African reference populations.However, it is worthwhile to note that the reference populations used for defining population assignments differ between the biobanks, as noted in the Methods.
In conclusion, our study represents a targeted approach to studying population-specific genetic variation in a diverse medical biobank.Our approach identified multiple AFR-specific protein-altering variants in the APOL gene family implicated in kidney disease risk, including a stop-gain variant in APOL3 that increases the risk of CKD primarily in persons carrying one APOL1 G1/G2 risk allele.While it is imperative that population diversity is emphasized when recruiting patients for biobanks and building cohorts for association studies, our genome-first approach that filters for population-specific variants represents a step in that same direction in helping us understand disease risk in underrepresented populations.
50,080 AFR individuals and 125,860 EUR individuals with whole genome sequencing data.Population assignments were determined based on genetic similarity using a random forest classifier to respective reference populations from the Human Genome Diversity Project and 1000 Genomes.Documentation on data quality and curation are as described previously (49,50).

Variant annotations
Annotations for variants selected for the initial analyses in PMBB were obtained using ANNOVAR (51).
Variants of interest were annotated as pLOF, missense, or in-frame insertion/deletion variants according to the NCBI Reference Sequencing database.pLOF variants were defined as frameshift substitution, stop-gain, or splicing variants.MAFs for each variant were calculated in the relevant PMBB population using their respective allele counts.Only variants with a MAF > 0.1% in the PMBB AFR population were considered in our study.MAFs for all studied variants were also compiled from the Genome Aggregation Database gnomAD (v4.0.0) (52).
Phenotype data collection ICD-9 and ICD-10 disease diagnosis codes and laboratory measurements were extracted from patient EHRs for the PMBB.Binary phenotypes for each individual were determined by mapping ICD-9 and ICD-10 codes to phecodes as previously described (53).A rule of two was then applied where participants were determined as having a certain disease phenotype if they had the corresponding phecode diagnosis on two or more dates, while phenotypic controls consisted of individuals who never had the phecode.Individuals with a phecode diagnosis on only one date were not considered in statistical analyses.
Quantitative laboratory traits were also extracted from patient EHRs for the PMBB.All units were converted to their respective clinical traditional units.After removing outliers (greater than 4 standard deviations from the mean), we recorded the minimum, median, and maximum measurements for each laboratory measurement and each individual to use for subsequent association analyses.For our imaging-derived phenotypes, the kidney was segmented from abdominal and pelvic CT scans using TotalSegmentator (54).Of the 7,946 unique individuals with scans in which the entirety of the kidney was captured and labelled, subsequent quantitative kidney traits such as volume and surface area were derived using PyRadiomics (55).Outliers were then removed in a similar fashion and a minimum, median, and maximum value for each trait and individual was computed and used for downstream analysis.
Phecodes were classified in an identical fashion in the MVP cohort.Quantitative traits were extracted as previously described (48).Binary phecodes and quantitative traits were computed in the All of Us cohort using the same methods as the PMBB cohort.

Phenome-wide association study
Within the AFR and EUR population groups in PMBB, we performed a PheWAS for each of the 62 variants of interest against 1,222 binary phenotypes with at least 20 cases in both the PMBB AFR and EUR population.We used the generalized linear mixed model framework to account for participant relatedness and unbalanced case-control ratios with the SAIGE package (56).Directly genotyped variants were used for step 1 of SAIGE.Whole-exome sequenced variants were used for step 2 of SAIGE.Analyses were adjusted for sex, age, age^2, and 5 population-specific genetic principal components (PCs) in the AFR population and 10 PCs in the EUR population.A fixed-effects metaanalysis was then performed using the inverse variance method for pooling as implemented by the 'meta' R package (57).A Bonferroni-adjusted significance threshold was then computed using the total number of associations performed in both genetically inferred population groups.A suggestive significance threshold was also calculated by adjusting 1 by the total number of associations.
Replication for specific variants and phenotypes of interests were also performed using SAIGE in MVP, adjusting for age, sex, and 10 population-specific PCs (48).Identical methods were used for replication in the All of Us cohort as in PMBB including using SAIGE for association analyses.
The study was approved by the Institutional Review Board of the University of Pennsylvania and complied with the principles set out in the Declaration of Helsinki.Conditional associations for all significant variant-phenotype associations conditioned on APOL1 G1/G2 carrier status modelled under a recessive inheritance pattern.Significant phenotype associations for APOL1 G1/G2 not included to avoid conditioning on themselves.Associations for APOL3 variant rs11089781 against ESRD, maximum creatinine, and minimum eGFR stratified by APOL1 G1/G2 carrier status.Both an additive and a recessive model were used to represent the carrier status for rs11089781.

Figure 1 .
Figure 1.PheWAS for 62 protein-altering variants in APOL genes.Associations were performed in

Figure 2 .
Figure 2. LD heatmap between significant variants in APOL genes.Includes the 5 variants with

Table 2 .Table 1 . Significant variants from AFR PheWAS analysis.
Annotations for variants with at least one significant phenotype association in AFR analysis.All significant phenotype associations are detailed in Supplemental Table2.Includes MAFs calculated both in PMBB and from allele counts in gnomAD v.4.0.0.NFE represents the non-Finnish European population in gnomAD.A allele frequency > 0.5 for the minor allele as determined by gnomAD