Genetic variants of APOL1, encoding apolipoprotein L1, are strongly associated with chronic kidney disease (CKD) in individuals with sub-Saharan African ancestry.1 Risk allele frequency is highest in West Africa, with lower prevalence elsewhere in sub-Saharan Africa.2 Risk alleles are absent from populations outside Africa, unless population admixture has occurred. African Americans have a ∼35% prevalence of APOL1 risk alleles, whereas 12%–14% of individuals have high-risk genotypes comprising 2 risk alleles, inherited in a homozygous or compound heterozygous state.3,4
Carriage of high-risk APOL1 genotypes increases CKD risk in adults.4–10 The strongest association is for HIV-associated nephropathy (HIVAN) with an odds ratio (OR) of 29 in the United States (US)4 and 89 in South Africa.10 A spectrum of CKD, described in children born with HIV infection, includes HIVAN, nephrotic syndrome, and various forms of immune-complex glomerulonephritis.11–16
The association between APOL1 variants and CKD in these children has not been investigated. We evaluated this relationship in a large US cohort of youth with perinatal HIV-1 infection (PHIV). As ancestry may confound the association between APOL1 risk variants and CKD, we determined continental ancestry with a genetic panel and adjusted for African ancestry in our analysis. We also evaluated the association between self-reported race and CKD, and African ancestry and CKD.
The Adolescent Master Protocol (AMP) of the Pediatric HIV/AIDS Cohort Study is an ongoing prospective cohort study of youth with PHIV designed to evaluate the impact of HIV and antiretroviral therapy on long-term outcomes.17 Between 2007 and 2009, 451 PHIV participants aged 7–16 years with comprehensive medical history since birth were enrolled at 15 sites within the US and Puerto Rico. Participating sites and the Harvard T.H. Chan School of Public Health obtained Institutional Review Board approvals, and consent/assent was obtained from parents/legal guardians and participants. This study analyzed data as of January 1, 2014.
DNA was extracted from saliva and buccal cells from participants who consented for genetic testing. Continental ancestry across 5 superpopulations (Africa, Eurasia, East Asia, Americas, and Oceania) was determined using a panel of ancestry informative markers.18–20APOL1 genotyping was performed for 2 renal risk alleles: G1 [coding variants rs73885319A>G (p.S342G) and rs60910145 G>T (p.I384M)] and G2 (6 base pair deletion, rs71785313), by Taqman assays (Applied Biosystems, Foster City, CA).4 Carriage of 2 APOL1 risk alleles (G1/G1, G1/G2, or G2/G2) was defined as high risk for renal disease; possession of zero or one risk allele (+/+, G1/+, or G2/+) was considered low risk for renal disease.
We performed a nested case–control study. Cases of CKD were defined as a clinical diagnosis established by chart documentation of nephropathy, nephrotic syndrome, chronic renal failure, and/or focal segmental glomerulosclerosis, or by clinical tests, either of the following: (1) persistent proteinuria for >6 months established by ≥2 sequential urine protein/creatinine ratios (UPC) ≥0.2 g/g not followed by a UPC <0.2 g/g, or alternatively 2 or more sequential urine dipstick proteins ≥1+ not followed by a urine dipstick protein <1+, or (2) persistent low glomerular filtration rate, for >6 months established by ≥2 sequential estimated glomerular filtration rates (eGFRs) <60 mL·min−1·1.73 m−2 not followed by an eGFR above this value. Clinical diagnoses were accepted even without laboratory abnormalities as effective combination antiretroviral therapy can result in subsequent normalization.21 For children, the bedside Schwartz equation was used to calculate eGFR.22 For those ≥18 years of age, the CKD-EPI 2009 eGFR was used.23 A control group consisted of AMP participants with no clinical history or chart documentation of kidney disease, all measured UPCs <0.2 g/g, all protein dipstick tests <1+, and all eGFRs ≥80 mL·min−1·1.73 m−2.
Kruskal–Wallis and Fisher exact tests were used to compare distributions of covariates by case–control status. Area under the curve (AUC) HIV viral load was calculated using the trapezoidal rule and mean case–control difference calculated (see Supplemental Digital Content 1, https://links.lww.com/QAI/A811).24 Logistic regression models were used to determine associations between APOL1 risk status, self-reported race, and African ancestry with CKD.
Of 451 AMP participants, 419 had APOL1 genotype data available. The combined frequency of G1 and G2 risk alleles was 27%. Self-reported blacks (302 participants) had an allele frequency of 35%, with 13% (40 participants) having 2 risk alleles, 43% having 1 risk allele, and 44% having none. This genotype distribution did not deviate from Hardy–Weinberg equilibrium expectations (P = 0.66). No self-reported white (91 participants) or other race (2 Asians, 3 Native Americans) had 2 risk alleles. However, 11% of white participants carried 1 risk allele. Race was not self-reported in 21 participants, none of whom had 2 risk alleles and 3 had one risk allele. As expected, there was a strong positive correlation between APOL1 risk allele frequency and proportion of African ancestry (r = 0.93, P < 0.001). Risk allele frequency ranged from ∼3% in participants with 0%–10% African ancestry to 60% with 90%–100% African ancestry.
Among 428 participants with ancestry data, median proportions of African ancestry correlated with self-reported race. Among non-Hispanics, blacks showed much higher proportions of African ancestry [76%, interquartile range (IQR): 69%–84%] compared with whites (1%, IQR: 1%–3%). Similarly, among Hispanics, the median African ancestry proportion was higher in blacks (36%, IQR: 21%–57%, minimum 1%) than in whites (6%, IQR: 2%–24%, maximum 85%) (see Supplemental Digital Content 2, https://links.lww.com/QAI/A811).
There were 27 cases of CKD, all with ancestry data and self-reported race/ethnicity and 207 subjects in the comparison group (196 had genetically determined ancestry, 193 self-reported race, and 194 APOL1 genotype data). Among CKD cases, 24/27 (89%) were black, of whom 7 (29%) had high-risk APOL1 genotypes. Of 26 CKD cases with genotype data, 7 (27%) had high-risk genotypes. Among control participants, 140/193 (73%) were black, of whom 16 (11%) had high-risk genotypes. Of all control participants with genotype data, 8% had high-risk genotypes. Breakdown by diagnosis for the 27 CKD cases is shown in Supplemental Digital Content 1 (https://links.lww.com/QAI/A811).
CKD was identified at a median age of 14.3 years (IQR: 8–16.3 years). No statistically significant differences between cases and controls were noted in socio-demographic or clinical characteristics (Table 1) including mean AUC HIV viral load [mean difference: 3.55 log10 copy-years/mL, 95% confidence interval (CI): −3.01 to 10.11 log10 copy-years/mL]. Seven of 40 subjects with 2 APOL1 risk alleles had CKD (17.5%). Over 580.2 person-years of follow-up, we estimated a crude incidence rate of 1.2 cases per 100 person-years (95% CI: 0.5 to 2.5) for this high-risk group. The median age of these 7 was 8.8 (IQR: 1.1–18.0) years, whereas the median age of the 19 CKD cases with 0 or 1 risk allele was 14.3 (IQR: 10.5–16.3) years, P = 0.54.
Subjects with high-risk genotypes had a 4.1-fold increased odds of CKD compared with those with low-risk genotypes (95% CI: 1.5 to 11.2) in unadjusted analysis (Table 2). When adjusted for African ancestry, this finding was slightly attenuated, but still significant (adjusted OR 3.5; 95% CI: 1.2 to 10.0). When analysis was limited to self-reported blacks, the increased risk for CKD associated with high-risk genotype persisted (adjusted OR 3.3; 95% CI: 1.1 to 9.6).
There was a 3-fold increased odds of CKD in self-reported blacks compared with white/other race (95% CI: 0.9 to 10.5). We found an 8.8-fold (95% CI: 1.9 to 41.4) and a 2.8-fold (95% CI: 0.5 to 14.9) increased odds of CKD among participants with 71%–80% and >80% genetically determined African ancestry, respectively, compared with those with ≤25% African ancestry (see Supplemental Digital Content 2, https://links.lww.com/QAI/A811).
We show for the first time that high-risk APOL1 genotype is associated with increased susceptibility to CKD in youth with PHIV, with a 3.5-fold increased OR compared with low-risk genotypes. We found that 27% of CKD cases in the AMP cohort carried 2 risk alleles.
Although most individuals carrying a high-risk genotype will not develop kidney disease, a recent report estimates the lifetime risk of kidney disease in these individuals to be at least 15%.25 In our cohort, 18% of children with PHIV who carried the high-risk genotype developed CKD, which supports the observation in adult studies that HIV infection is a potent environmental factor that interacts with APOL1 genetic risk. With a median age of 15.3 years for children included in the analysis, there is potential for even higher rates of CKD over their lifetimes. Because our participants were HIV infected at birth, we were able to estimate the crude incidence of CKD and report a rate of 1.2 cases per 100 person-years in PHIV children with the APOL1 high-risk genotype. Unfortunately, lack of data on the incidence of CKD in a similar population of PHIV children with this genotype from other countries, including sub-Saharan Africa, precludes us from making any direct comparisons.
There was no difference between our comparison group and CKD cases in proportions with an undetectable viral load and CD4 counts. Persistent viremia over a sustained period of time, and not viral load at the time of diagnosis, may be more relevant in causing HIV-related renal injury.24,26,27 We therefore investigated cumulative HIV burden, and although a mean viral load difference of 3.55 log10 copy-years per milliliter between cases and controls was observed, it was not statistically significant. Although it is possible the small number of cases of CKD may have resulted in a type II error, other as-yet-unidentified environmental triggers may also play a role in the development of CKD in PHIV children with 2 risk alleles.
The observed combined allele frequency for APOL1 G1 and G2 was 35% in participants who self-identified as black, and 13% had 2 risk alleles, similar to that described in adult African Americans,4 and strongly supporting sub-Saharan origins of youth in the AMP cohort.28 Determining African ancestry further allowed us to examine the relationship between Hispanic ethnicity, race, and proportion of African ancestry. Participants who self-identified as black had a wide range in their proportion of African ancestry, as did those identifying as white. Compared with whites and blacks who do not self-report Hispanic ethnicity, self-reported Hispanic ethnicity was associated with higher mean African ancestry proportion in white-Hispanics and lower African ancestry proportion in black-Hispanics, likely the consequence of migration into the US from the Caribbean region, where these populations underwent admixture.29 African admixture also accounts for the presence of a single risk allele in 11% of our white participants. Because children in our cohort had varying proportions of African ancestry, we adjusted for genetic ancestry, rather than self-reported race, when evaluating the association between CKD and the APOL1 risk alleles. The marginal difference in effect size after adjustment suggests that the increased risk for CKD was associated specifically with high-risk APOL1 haplotypes, rather than African ancestry per se.
Major strengths of this study include use of ancestry informative markers, allowing us to estimate and adjust for proportion of African ancestry, and availability of APOL1 genotypes on a large number of children with perinatally acquired HIV infection drawn from 15 sites across the United States and Puerto Rico. There are limitations worth noting. The strongest association of APOL1 risk alleles was with HIVAN and focal segmental glomerulosclerosis, which can only be definitively diagnosed by biopsy. Some cases of CKD identified may represent other types of kidney disease, such as HIV immune-complex glomerulonephritis16 or antiretroviral drug–associated renal disease30 that may not be associated or less strongly associated with APOL1 risk alleles. HIV viral load measurements were not performed at regular intervals in our participants' lifetime, affecting an accurate assessment of the impact of viral burden on renal disease expression.
Our findings may have important implications for youth with PHIV living in sub-Saharan Africa, where HIV prevalence is the highest in the world. Of 3.2 million children living with HIV globally in 2013, 91% are in sub-Saharan Africa.31 Even with the recent 43% reduction in the number of new pediatric HIV infections in this region, the prevalence of PHIV among children will increase as antiretroviral therapy allows them to survive into adolescence and beyond.32 Therefore, the burden of HIV-related kidney disease among youth in those regions of sub-Saharan Africa, where APOL1 high-risk genotypes are prevalent, is likely to be substantial.
In summary, APOL1 risk alleles are prevalent in black children and youth with PHIV living in the US. This study provides robust evidence that carriage of high-risk APOL1 genotypes increases risk for CKD in this population.
We thank the children and families for their participation in PHACS and the individuals and institutions involved in the conduct of PHACS.
The following institutions, clinical site investigators, and staff participated in conducting PHACS AMP in 2014, in alphabetical order: Ann & Robert H. Lurie Children's Hospital of Chicago: Ram Yogev, Margaret Ann Sanders, Kathleen Malee, and Scott Hunter; Baylor College of Medicine: William Shearer, Mary Paul, Norma Cooper, and Lynnette Harris; Bronx Lebanon Hospital Center: M.U.P., Mahboobullah Baig, and Anna Cintron; Children's Diagnostic & Treatment Center: Ana Puga, Sandra Navarro, Patricia Garvie, and James Blood; Children's Hospital, Boston: Sandra Burchett, Nancy Karthas, and Betsy Kammerer; Jacobi Medical Center: Andrew Wiznia, Marlene Burey, and Molly Nozyce; Rutgers—New Jersey Medical School: Arry Dieudonne, Linda Bettica, and Susan Adubato; St. Christopher's Hospital for Children: Janet Chen, Maria Garcia Bulkley, Latreaca Ivey, and Mitzie Grant; St. Jude Children's Research Hospital: Katherine Knapp, Kim Allison, and Megan Wilkins; San Juan Hospital/Department of Pediatrics: Midnela Acevedo-Flores, Heida Rios, and Vivian Olivera; Tulane University Health Sciences Center: Margarita Silio, Medea Jones, and Patricia Sirois; University of California, San Diego: S.A.S., Kim Norris, and Sharon Nichols; University of Colorado Denver Health Sciences Center: Elizabeth McFarland, Alisa Katai, Jennifer Dunn, and Suzanne Paul; University of Miami: Gwendolyn Scott, Patricia Bryan, and Elizabeth Willen. We would also like to thank Sean Brummel, Harvard T.H. Chan School of Public Health, for his statistical expertise.
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