Introduction

Apolipoprotein L1 (APOL1) is a human innate immune factor that is active against African trypanosomes responsible for African trypanosomiasis (sleeping sickness)1. Two common APOL1 coding alleles, termed G1 and G2, are strongly associated with chronic kidney disease in African-ancestry populations. African Americans carrying two copies of APOL1 G1 or G2 kidney risk alleles (referred to herein as APOL1 variant alleles) have a sevenfold increased risk for nondiabetic end-stage kidney disease and a 17-fold increased risk for focal segmental glomerulosclerosis, respectively2,3,4. The strongest associations have been reported for HIV-associated nephropathy, with odds ratio (OR) 29 in African Americans and OR 89 in South Africans3,5, suggesting a strong interaction between APOL1 and HIV.

APOL1 is a trypanolytic protein that confers innate resistance to African Trypanosoma brucei1. Individuals with the G2 allele are resistant to acute T.b. rhodesiense Human African trypanosomiasis (HAT) but experience faster progression of chronic T.b. Gambiense HAT6. G1 is associated with asymptomatic carriage and undetectable parasitemia in individuals with chronic T.b. gambiense infection6. Both forms of HAT may have led to the selection of the APOL1 renal risk alleles in Africa2. APOL1 also provides resistance against Leishmania7. It has recently been reported that APOL1 restricts HIV infection in macrophages and differentiated monocytes in vitro8. The proposed mechanisms include degradation of HIV Gag protein and depletion of HIV Vif, but the in vivo consequences are largely unknown8.

In addition to its role in innate immunity against trypanosomes, overexpression of the APOL1 variant in monocytes induces differentiation into macrophages, an important component of innate immunity9. We thus hypothesized that APOL1 could potentially confer resistance to a broad spectrum of pathogens. APOL1 risk variants are found only on African chromosomes and are not present in European or Asian populations, except by African admixture (e.g., African Americans and Afro-Caribbeans). G1- and G2-combined allele frequencies are ~34% in African Americans and 10–50% in Sub-Saharan African populations4, where HIV infection is highly prevalent. Opportunistic infection (OI), caused by a variety of pathogens (bacteria, viruses, fungi, or protozoa), frequently occurs in patients with HIV infection due to a weakened immune system.

In this study, we explored a possible influence of APOL1 variants on opportunistic infections in African Americans from four HIV/AIDS cohorts. We observed that carriage of two APOL1 variant alleles was associated with a reduced risk of OI occurrence. Subgroup analysis of OI etiological categories (viral, parasitic, fungal, and mycobacterial) revealed a tendency of specific protection against fungal infection. Our results suggest that APOL1 variant alleles may confer host protection against OI in HIV-positive individuals.

Results

Baseline characteristics in the MACS, WIHS, and LSOCA cohorts

The genotype distribution of APOL1 genotypes was in concordance with Hardy–Weinberg equilibrium expectations in each of four cohorts (P > 0.05). The HIV-related characteristics of HIV-seroprevalent African Americans at study entry in a part of the ALIVE cohort, the LSOCA, MACS, and WIHS cohorts, stratified by APOL1 genotype status, are presented in Table 1. APOL1 variant alleles were present in 8.4, 8.3, 14.4, and 10.5% of HIV-positive participants in these cohorts, respectively.

Table 1 Baseline characteristics of seroprevalent participants with HIV infection at study entry by APOL1 variant allele counts in the ALIVE, WIHS, MACS, and LSOCA cohorts.
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Baseline HIV viral loads were not statistically different between the APOL1 high-risk and low-risk groups in the ALIVE, LSOCA, MACS, and WIHS cohorts (P = 0.18, 0.49, 0.97, and 0.82, respectively, Table 1). Baseline CD4+ T-cell counts were also not statistically different between the APOL1 high-risk and low-risk groups in the seroprevalent subgroup of the ALIVE cohort, and the seroprevalent LSOCA, MACS, and WIHS cohorts (P = 0.15, 0.98, 0.68, and 0.24, respectively, Table 1).

Impact of APOL1 variant alleles on opportunistic infections (OIs)

We evaluated whether APOL1 variant alleles might be protective against opportunistic infections. In ALIVE (n = 440), carriage of two APOL1 variant alleles (3.9% in OI+ vs. 12.1% in OI−) was recessively associated with a decreased risk of OIs (OR = 0.29, P = 0.040; ORadj = 0.32, Padj = 0.044, Table 2).

Table 2 Association of APOL1 G1 and G2 variant alleles with opportunistic infections in HIV-positive individuals in the ALIVE cohort.
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We next validated this finding in three other independent HIV-seroprevalent cohorts (LSOCA, MACS, and WIHS) by conducting a meta-analysis of the APOL1 variant allele’s effect on opportunistic infections. In the validation cohorts, carriage of two APOL1 variant alleles (8.7% in OI+ vs. 14.2% in OI−) was recessively associated with 36% lower odds of OI (combined OR 0.64, 95% CI 0.45–0.91, P = 0.006, Table 3). We also performed a meta-analysis of APOL1 variant alleles’ effect on OI combining all four HIV cohorts (Table 3). The global test combining the four independent cohorts revealed a significant association of carriage of two APOL1 variant alleles with protection against OI in both unadjusted analysis (OR 0.56, 95% CI 0.39–0.81, P = 0.002) and in an adjusted meta-analysis using covariates (including age, sex, ART usage, and HIV viral load at baseline) (OR 0.50, 95% CI 0.33–0.76, P = 0.001, Table 3, Fig. 1). The heterogeneity test revealed no apparent heterogeneity among cohorts (Pq-statistic ≥ 0.49). The leave-one-out meta-analysis removing any one cohort out did not abolish significance (Table 3 and Supplementary Table 1).

Table 3 Association of carriage of 2 versus 1 or 0 APOL1 variant alleles with opportunistic infection in four HIV cohorts, recessive model.
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Fig. 1: Forest plot showing the odds ratios (OR) of opportunistic infection (OI) for the carriage of 2 versus 1 or 0 APOL1 variant alleles in the meta-analysis of four HIV/AIDS cohorts.
figure 1

Data were pooled from the four studies using inverse variance (IV) (Table 3). The red block indicates the point estimate of OR, while the horizontal line depicts 95% CI of OR in each study. The area of the block indicates the weight assigned to that study in the meta-analysis.

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Among covariates tested (age, sex, ART treatment history, Pneumocystis pneumonia prophylaxis usage, HIV viral load, and African ancestry), HIV viral load was a consistent significant risk predictor of OI in all cohorts (OR 1.45, 95% CI 1.12–1.89), while ART usage was a protective predictor of OI in two cohorts though short of significance in the meta-analysis of four cohorts (OR 0.50, 95% CI 0.14–1.72, Table 3). These results are largely consistent with the expectation, attesting to the validity of our model testing.

Impact of APOL1 variant alleles on fungal infections

To determine if the APOL1 association was due to a specific OI etiology, we used the LSOCA cohort, which enrolled only participants with an AIDS diagnosis. Dichotomizing specific OI etiologies from the LSOCA cohort revealed that APOL1 variant alleles were associated with a lower risk of fungal OI (OR = 0.54, P = 0.02), and not with viral, parasitic, or bacterial OIs (Table 4). With a Bonferroni correction of four categories of OIs tested, a trend of fungal protection remained (PBonferroni corrected = 0.08) for this exploratory analysis.

Table 4 Association of APOL1 variant alleles with baseline AIDS-defining opportunistic infections among LSOCA participants under additive and recessive genetic models.
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Next, to know which individual pathogens are influenced by the APOL1 variants, we performed an explanatory analysis of the top seven most common OIs (N ≥ 40) in the LSOCA cohort. We saw consistent APOL1 variant protective effect trends on fungal OIs, no effect on viral OIs, and possibly increased risk for bacterial pneumonia (OR = 2.54, P = 0.03) (Supplementary Table 2). There is some evidence that variant APOL1 confers partial protection against multiple fungal pathogens, with nonsignificant protective trends for Pneumocystis carinii pneumonia and esophageal candidiasis and a significant protective association with Cryptococcal meningitis (P = 0.03). None of the 47 patients with two APOL1 variant alleles had Cryptococcal meningitis infections. However, we note that these associations did not reach the Bonferroni-corrected significance threshold (0.05/7 = 0.007).

Last, we assessed the association of APOL1 on multiple OI infections (or co-infections). Patients had an average of 2.16 OI diagnoses, most frequently among Pneumocystis carinii pneumonia, esophageal candidiasis, herpes simplex, mycobacterial, and cryptococcal infections (Supplementary Table 3). Using a multivariate regression model, we found that carriage of two copies of APOL1 G1–G2 alleles significantly reduced the number of multiple infections (1.59 vs. 2.17 multiple infections, beta = −0.58, P = 0.03, adjusted for HAART, age, sex, HIV transmission route, and HIV load, Supplementary Table 3).

In the MACS cohort, there was a nonsignificant trend of protection from fungal OI (OR 0.37, 95% CI 0.12–1.14, P = 0.084) and PCP (OR 0.28, 95% CI 0.06–1.28, P = 0.10). The other cohorts, which were smaller, did not have enough subgroup outcomes for meaningful analyses.

Discussion

APOL1 variants have a profound impact on African-ancestry populations in predisposing to a spectrum of progressive kidney diseases, most markedly in those with untreated or undertreated HIV infection3,10. In this study, we assessed the influence of APOL1 variants on susceptibility to opportunistic infections in African Americans from four HIV/AIDS cohorts. Our population genetic epidemiological data revealed a potential role of APOL1 variant alleles in protection against AIDS-related opportunistic infections.

A subgroup analysis of the LSOCA cohort revealed that APOL1 variant alleles are specifically associated with protection against fungal OIs, but not with viral, parasitic, or bacterial OIs. From studying the longitudinal seroconverter ALIVE cohort, we recently reported that APOL1 variants confer no obvious effect on HIV viral load11. This is further confirmed by the results from the seroprevalent patients in the four cohorts included in this study. This suggests that the APOL1 association with OI is unlikely to be mediated by affecting HIV replication but rather, more likely, by inhibiting OI-inducing pathogens directly or via the immune response. The direct inhibition of fungi by overexpression of APOL1 and its variants has recently been demonstrated in vitro12. Expression of human APOL1 reduces yeast S. cerevisiae growth, through impairment of endosomal trafficking and acidification processes12. APOL1 G1 and G2 variant proteins conferred significantly greater toxicity to yeast compared with the wild-type APOL1 G0, likely due to differential impairment of vacuole acidification12. The APOL1 G1 and G2 variant proteins kill T.b. rhodesiense by evading virulence factor serum resistance-associated protein (SRA) encoded by the T.b. rhodensiense1,10,13,14. Perhaps, fungi contain a similar counteractive mechanism that differentially interacts with variant APOL1 and APOL1 proteins.

Variant APOL1 may also affect susceptibility to OI through immune activation and enhancement. Host susceptibility to pathogen invasion is strongly determined by the robustness of the innate immune response, as adaptive immune response takes days to develop. APOL1 is upregulated by pro-inflammatory cytokines such as IFN-γ, IFN-β, IFN-α, and TNF, which are induced by invading viruses and other pathogens, including HIV and fungi15,16,17. APOL1 and APOL1 variant protein may differentially induce macrophage polarization and modify immune responses9. APOL1, under stimulation of pro-inflammatory cytokines IFNγ and lipopolysaccharide, a major component of the outer membrane of Gram-negative bacteria, induced differentiation of THP-1 monocyte cells into the polarization of atypical M1 macrophage state. APOL1 G1 and G2 variants induced more IL6 and TNF mRNA (M1 marker), a presumably stronger M1 state, compared with APOL1-G0 protein that carried no variant alleles9. Macrophages are among the first-line effectors of the innate immune defense against invading pathogens15,18,19. Activated M1 macrophages perform microbicidal function through phagocytosis of internalized pathogens and producing cytokines and chemokines to recruit other immune cells to control the infection18,19,20. Together, these data support differential roles of APOL1 protein isoforms in the immune defense of OI, although the mechanisms remain unresolved.

APOL1 expression is increased by elevated circulating levels of interferon in several clinical settings, leading to glomerular injury. These settings include (1) chronic viral infection, e.g., with HIV infection (as discussed above) and with parvovirus B19 infection21, (2) administration of therapeutic interferon, given for other indications16, and (3) a genetic disorder, e.g., the stimulator of interferon-gene (STING)-associated vasculopathy with onset in infancy (SAVI). It is likely that this list will grow longer.

The study adds to evidence that APOL1 or its variant isoforms may confer protection to a broader range of pathogens than only African trypanosomes. APOL1 has been shown to confer resistance against Trypanosoma brucei1, amelioration of Leishmania infection, and inhibition of HIV-1 replication in certain cell types8. APOL1 G1 and G2 variants exhibit recent positive selection signals in the form of extended haplotypes in some West Africa populations2,4, possibly due to selective pressure from pathogens during recent evolution14. The broader role of APOL1 as an innate immune factor against fungal pathogens, if validated, may explain in part why APOL1 G1 and G2 variants have been selected in African-ancestry populations, despite the increased risk for kidney disease and preeclampsia22. A protective impact of APOL1 variant alleles against OIs could therefore influence HIV disease outcomes among African-ancestry populations and have implications for targeted management. It is possible that APOL1 G1 and G2 variants could be under positive selective pressure from OIs, in addition to T.b. rhodesiense and T.b. gambiense. In addition to pleiotropic associations of APOL1 risk alleles with human African trypanosomiasis, kidney disease, cardiovascular disease, and preeclampsia, carriage of APOL1 risk alleles was unexpectedly found to be associated with an elevated risk of sepsis in a study of older, community-dwelling black participants enrolled in the REGARDS (reasons for geographic and racial differences in stoke)23. This is consistent with our observation of APOL1 risk alleles increasing the risk of bacterial pneumonia, as most sepsis is caused by bacterial infections. APOL1 variants may have pleiotropic-modifying effects on innate immune response or inflammatory responses to different classes of human pathogens.

There are limitations to our study. The strength of statistical association for OI is modest or nonsignificant in individual cohorts, likely due to the relatively low frequency of APOL1 variant alleles and the modest sample size. With the sample size in the combined cohorts, assuming a 30% OI prevalence rate, we had 80% power to detect a protective effect of OR of ≥0.43, but only 30% power to detect the observed effect size on OI (OR of 0.60). Nevertheless, APOL1 variant- protective effect on OI was largely consistent in the direction across the cohorts with diverse demographical features and at various disease stages, supporting the observed association. Although we only observed a protective effect with two copies of APOL1 variant alleles, we cannot exclude the possibility that an additive effect would be revealed with larger sample size. Similarly, APOL1 variants increase renal disease risk in the recessive model, possibly because a critical threshold of APOL1 protein level is required for cell toxicity24,25. Another concern is that APOL1 carriers of two risk alleles who developed HIV-associated nephropathy (HIVAN) may not have been enrolled in the seroprevalent cohorts. We also had the potential for incomplete data for prevalent OI diagnoses. A limitation of our study is that we only have data on the presence/absence of OI, but not OI disease severity. The association of the G1 and G2 alleles with trypanosome susceptibility and trypanosomiasis disease severity differs by trypanosome strain and by APOL1 G1 or G26; therefore, it is possible that the effect of APOL1 variants on infection susceptibility and disease severity may differ by OI and APOL1 genotype.

This study should be considered as exploratory and hypothesis-generating. More studies with a larger sample size are required to reach a definitive conclusion and to elucidate specific mechanisms leading to protection against OI. It also remains to be determined if the APOL1 association with OI in the settings of HIV infection extends to other settings of immune suppression (e.g., individuals with nephrotic syndrome or chronic and end-stage kidney disease experiencing uremia, or transplant recipients and cancer patients taking immunosuppressive drugs).

In summary, this population genetic study suggested that APOL1 might confer carriers of two variant alleles’ protection from HIV-related opportunistic infections, especially fungal infections. These findings warrant further replication and experimental validation and extension to infectious disease incidence and prevalence in populations of recent African ancestry, particularly those with chronic kidney disease and end-stage kidney disease and those immunocompromised due to many other diseases.

Methods

Ethics statement

Ethical approval for the study was obtained from the National Institute of Health Office of Human Subjects Research Protections (OHSRP #3314). Institutional Review Boards of all participating institutions approved the study protocols and written informed consent was obtained from all study participants.

Study participants

We studied African American subjects enrolled in four US-based HIV cohorts since APOL1 G1–G2 alleles are only present in individuals with recent African ancestry. The four HIV cohorts include the ALIVE, consisting of half seroconverters and half of the seroprevalence, and the seroprevalent cohorts LSOCA, MACS, and WIHS.

The ALIVE cohort

The epidemiological and clinical characteristics of the ALIVE (AIDS link to the intravenous experience) cohort have been previously described26. ALIVE is a prospective longitudinal cohort originally designed to characterize the incidence and natural history of HIV infection among injection drug users (IDU) in Baltimore, MD, initiated in 198826. The participants were followed at six-month intervals with blood draws for viral load and CD4+ T-cell measurements and physical exam at each visit. The censoring date used was the date of the last recorded visit, if prior to July 21, 1997, otherwise a date of July 31, 1997, was used, in order to minimize the confounding effect of antiretroviral therapy (ART)27. The study group includes 227 African American incident HIV seroconverters and 213 HIV-seroprevalent individuals (acquired HIV prior to study entry).

The LSOCA cohort

The LSOCA (longitudinal study or the ocular complications of AIDS) was a multicenter prospective observational study of patients diagnosed with AIDS28. The study was originally designed for the the occurrence and consequences of ocular opportunistic infections, particularly cytomegalovirus (CMV) retinitis, among patients with AIDS. Participants were enrolled at 19 clinical centers throughout the United States in 1998–2011. Each patient gave a detailed medical and HIV-related disease history and relevant findings were confirmed from the medical records. At least every 6 months, patients were examined and the standardized data were collected on AIDS history and treatment, eye examinations, and hematologic, virologic, and immunologic laboratory data29,30,31. Only baseline data at study entry were used in this study, as all these seroprevalent participants (n = 784) already had AIDS at the study entry.

The MACS cohort

Multicenter AIDS Cohort Study (MACS) is a longitudinal prospective cohort of men who have sex with men from four US cities: Chicago, Baltimore, Pittsburgh, and Los Angeles, with enrollment starting in 198432. Participants were followed at 6-month intervals. The data-censoring date was the earliest of the date of the last recorded visit, or December 31, 1995. In this study, 651 HIV-positive African Americans (90% seroprevalents) with complete APOL1 genotype, phenotype, and covariate information were included; their enrollment date ranged from 1984 to 2003 with an average follow-up of 10 years.

The WIHS cohort

The Women’s Interagency HIV Study (WIHS) is the largest multicenter longitudinal cohort of HIV-positive women in the United States, starting in 1994–199533,34. Participants were seen at 6-month intervals for laboratory and physical examinations. The current analysis included 91 seroprevalent HIV-positive non-Hispanic black women with APOL1 genotype and OI diagnostic information at study entry.

Diagnosis of opportunistic infections

AIDS-defining OI was classified based on CDC-revised 1993 AIDS case definition and the MMWR Recommendations28,35. The classification of opportunistic infections was made according to the AIDS Clinical Trials Group guidelines. Different etiologies for OIs were available for the LSOCA cohort, allowing us to test for APOL1 associations for the following subcategories: viral OI (including CMV, Kaposi sarcoma-related herpes virus, and herpes simplex virus), parasitic OIs (including extrapulmonary pneumocystosis, toxoplasma infections, cryptosporidiosis, and isosporiasis), fungal OI (including Pneumocystis carinii pneumonia (PCP), candidiasis, cryptococcal, histoplasmosis, and coccidioidomycal infections), and bacterial OI (including Mycobacterium tuberculosis, Mycobacterium avium complex (MAC), Mycobacterium kansasii, Mycobacterium genovensii, and other mycobacterial infections).

Genotyping of APOL1 G1–G2 variant alleles

APOL1 coding variants G1 (rs73885319, p.S342G) and G2 (rs71785313, p.N388_Y389del) were genotyped using ABI TaqMan genotyping assays on an ABI 7900HT sequencer detector system (Applied Biosystems, Foster City, CA), as previously described3. For quality control, water controls were included on each plate and 10% of samples were duplicated. No water contamination or genotype mismatches between duplicates were observed. G1 and G2 allele calls were also validated in the ALIVE cohort by the Sanger sequencing, following a previously described protocol36.

The APOL1 variants were genotyped in the Winkler lab for the ALIVE11 and LSOCA cohorts. The MACS and WIHS participants were genotyped by the cohort studies using Taqman protocols, as previously published37,38.

Defining APOL1 variant alleles

The APOL1 G1 variant allele is defined by the presence of rs73885319 G1 (342G), which is in almost complete positive linkage disequilibrium with rs60910145 (384M), and the G2 variant allele by rs71785313, an in-frame 6-base deletion (TTATAA), leading to the loss of two amino acids (p.N388_Y389del); the G0 haplotype contains neither the G1 nor the G2 variant allele2,3. The G1 and G2 variants are in absolute negative disequilibrium and always occur on different chromosomes2,3. Individuals carrying any two variant alleles in the homozygous or compound heterozygous state (G1/G1, G2/G2, or G1/G2) are considered APOL1 high-risk (HR) carriers and are at increased risk for kidney disease; individuals carrying 0 or 1 risk allele are defined as APOL1 low-risk carriers (LR) for kidney disease37.

Statistical analysis

We evaluated the effects of APOL1 variant alleles using an additive model (2 vs. 1 vs. 0 copies), a dominant model (2 or 1 copies vs. 0 copies), and a recessive model (2 vs. 1 or 0 copies). Analyses were performed using SAS version 9.12 (SAS Institute, Cary, NC). We tested Hardy–Weinberg equilibrium (HWE) of APOL1 variant genotypes by using a goodness-of-fit χ2 test39 and an exact test40.

We compared the mean baseline CD4 T-cell counts between the group carrying two APOL1 variant alleles and the group carrying 1 or 0 variant alleles using ANOVA. We adjusted the regression model analyses by sex and by age at seroconversion, or age at study entry for those who were seroprevalent, using the following age categories: 0–19, 20–40, and >40 years.

To account for potential population stratification among participants, we adjusted the regression model association tests in the ALIVE and WIHS cohort using the first five eigenvalues generated with principal component analysis (PCA) implemented in Eigenstrat41, using African-ancestry informative markers42 or GWAS data43; the PCA data were not available for the particular LSOCA and MACS datasets used in this study.

Analysis of opportunistic infections (OIs)

We evaluated the impact of APOL1 variant alleles on OI acquisition by comparing the frequencies of APOL1 genotypes between those with OI and those without OI among all HIV-positive subjects in the ALIVE (including seroconverters and seroprevalent subjects) using OI outcomes at the cohort- censoring date. For the WIHS and LSOCA cohorts, OI status at study enrollment was used to minimize the influence of ART and prophylaxis on OI outcomes. Odds ratios (OR) and two-tailed P values were obtained by chi-square tests or using a conditional logistic regression model. The regression model was adjusted for age, sex, HIV-1 viral load, ART use, and OI prevention medications, and proportions of African ancestry using the first five principal components (PC), based on the data available from each cohort. We obtained the Bonferroni multiple testing-corrected P value with p.adjust function from the stats package in R.

Meta-analysis

Meta-analysis was performed by calculating the inverse variance of OR and 95% CI in a random-effects model as implemented in the RevMan V.5.3 software (Cochrane Community, Copenhagen)44,45,46,47. Statistical heterogeneity between studies was assessed by calculating tau-squared (τ2), chi-squared (χ2) test, P values, and I2. Under a random-effects model in the meta-analysis, the variance of the distribution of true effect sizes was estimated by τ2. A low P value provides evidence of variation in effect estimates beyond chance. The I² statistic describes the fraction of variance across studies that is due to heterogeneity44,45.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.