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. Author manuscript; available in PMC: 2019 Aug 15.
Published in final edited form as: J Acquir Immune Defic Syndr. 2018 Aug 15;78(5):549–556. doi: 10.1097/QAI.0000000000001714

Biomarkers of aging in HIV-infected children on suppressive antiretroviral therapy

Stephanie Shiau 1,2,3, Renate Strehlau 3, Jing Shen 1, Avy Violari 4, Faeezah Patel 3, Afaaf Liberty 4, Marc Foca 5, Shuang Wang 6, Mary Beth Terry 2, Michael T Yin 7, Ashraf Coovadia 3, Elaine J Abrams 2,3,4,5, Stephen M Arpadi 1,2,3,4,5, Louise Kuhn 1,2,3
PMCID: PMC6037570  NIHMSID: NIHMS962063  PMID: 29771780

Abstract

Background

Data on accelerated aging in HIV-infected children are limited. In this study we assess two biomarkers of aging – telomere length and DNA methylation (DNAm) age – in a cohort of early-treated HIV-infected children and compare these aging biomarkers to HIV-exposed uninfected (HEU) and HIV-unexposed uninfected (HUU) children.

Setting

Cross-sectional study of 120 HIV-infected, 33 HEU, and 25 HUU children enrolled in a cohort study in Johannesburg, South Africa. Children were a mean of 6.4 years at the time of measurement. HIV-infected children initiated LPV/r-based ART before 2 years of age and had been on continuous ART until biomarker measurement.

Methods

Telomere length was determined using multiplex quantitative PCR. DNAm was measured using the Illumina 450K array and DNAm age was calculated as the acceleration residual from regressing DNAm age on chronological age.

Results

Telomere length (ln[Kb/genome]) was shorter in HIV-infected children compared to HUU children (4.14±0.85 vs. 4.53±0.79, p=0.038) and in HEU children compared to HUU children (4.05±0.74 vs. 4.53±0.79, p=0.023). Age acceleration residual based on DNAm levels was not different between HIV-infected (−0.003±2.95), HEU (0.038±2.39), and HUU (0.18 ±2.49) children in unadjusted analysis and after adjustment for cell type proportions.

Conclusions

Unlike reports of accelerated DNAm age in HIV-infected adults, there was no evidence of accelerated biological aging by DNAm levels in this cohort of early-treated HIV-infected children. In contrast, absolute telomere length was shorter in HIV-infected and HEU children compared to HUU children, but did not differ between HIV-infected and HEU children.

Introduction

Accumulating evidence in adults indicates HIV-infected individuals have a shorter life expectancy and are at greater risk for HIV-associated non-AIDS (HANA) conditions, such as cardiovascular disease and osteoporosis, despite suppressive antiretroviral therapy (ART), possibly due to accelerated aging.[1, 2] Various biomarkers, including telomere length and DNA methylation (DNAm) age, have been used to measure accelerated biological aging in HIV-infected adults. Shorter telomere length consistent with accelerated aging has been observed in HIV-infected adults compared to HIV-uninfected adults, with telomere length inversely associated with immunological recovery with ART as well as HANA outcomes.[3–9] Similarly, increased DNAm age in different tissues, including blood and brain tissue, has been reported in several studies of HIV-infected adults compared to HIV-uninfected adults, including those on suppressive ART.[10–13]

However, there has been very limited application of these biomarkers in studies of HIV-infected children. To our knowledge, there have been only two studies of telomere length[14, 15] and no studies of DNAm age in children with HIV. One study found telomere length to be significantly shorter in HIV-infected children (58% on ART) than HIV-exposed uninfected (HEU) and HIV-unexposed uninfected children (HUU) ages 0–5 years (median 3.1 years).[14] The other study of older children (ages 0–19 years, median 13.3 years) did not find any difference in telomere length between HIV-infected children (78% on ART) and HEU or HUU children, although they did find an association between detectable HIV viral load and shorter telomere length in HIV-infected children.[15]

It is important to assess accelerated biological aging in pediatric populations. Precursors to HANA conditions, such as metabolic abnormalities and low bone mineral content, are observed in HIV-infected children on ART.[16, 17] Elevated levels of inflammation by cytokines and high-sensitivity C-reactive protein and monocyte activation by soluble CD14 are also reported in children with HIV compared to HIV-uninfected children.[18–20] Understanding potential mechanisms for HANA conditions may have important implications for the estimated 2.1 million children currently living with HIV who will experience lifelong exposure to both HIV and its treatments in the absence of a cure.[21] In addition, there are few studies that examine the impact on aging biomarkers of in utero and perinatal exposure to HIV and ART among HEU children.

Here we assess two aging biomarkers – telomere length and DNA methylation (DNAm) age – and the factors associated with these biomarkers in a cohort of early-treated HIV-infected children in South Africa. We compare these aging biomarkers to HEU and HUU children. We also investigate whether these biomarkers are associated with markers of inflammation.

Methods

Study population

Children were selected from an observational cohort study of 553 perinatally HIV-infected children and 300 HIV-uninfected controls conducted at two sites in Johannesburg, South Africa: Empilweni Services and Research Unit (ESRU) at Rahima Moosa Mother and Child Hospital and the Perinatal HIV Research Unit (PHRU) at Chris Hani Baragwanath Hospital. All HIV-infected children initiated ART before 3 years of age and were former participants in clinical trials at these sites. HIV-uninfected controls were recruited from among eligible siblings or household members of HIV-infected study patients or those attending the study site for routine outpatient health services. Any HIV-uninfected children with known chronic medical conditions were excluded from enrollment.[22–27] The Institutional Review Boards of Columbia University in New York, NY, USA, and the University of the Witwatersrand in Johannesburg, South Africa approved the study. Children’s guardians provided informed consent and children provided assent if they displayed appropriate understanding.

For this analysis, we randomly selected 120 HIV-infected children at the enrollment visit in the cohort study who were initiated on a ritonavir-boosted lopinavir (LPV/r) ART regimen before 24 months of age, had never interrupted treatment, and were suppressed with a viral load <400 copies/ml at the time of blood draw. We also selected 58 HIV-uninfected controls, including 33 HEU children and 25 HUU children, frequency matched by age at enrollment to the selected HIV-infected children. All selected children had stored blood samples available for analysis. In keeping with standard practice for prevention of mother-to-child transmission (PMTCT) at the time, HIV-positive mothers and/or their infants were provided with antiretrovirals; therefore most HIV-infected and HEU children were exposed to antiretrovirals in utero or in the immediate neonatal period.

Sample preparation

Venous blood samples were collected and stored at ambient temperature. Within 6 hours of collection, buffy coat and plasma were separated and stored at −80°C by BARC Global Central Laboratory in Johannesburg, South Africa and shipped on dry ice to Columbia University Medical Center in New York, NY, USA and stored at −80°C. Buffy coat samples for the measurement of biomarkers of aging were available for both HIV-infected and HIV-uninfected children. Plasma samples for measurement of inflammatory markers were only available for HIV-infected children. Genomic DNA (50ng/μl) was isolated and quantified with PicoGreen (Life Technologies, Carlsbad, CA) from buffy coat at the Biomarkers Shared Resource at Columbia University Medical Center.

Measurements

At the enrollment visit, demographic information and medical history were obtained by interview with the caregiver. For HIV-infected children, plasma HIV-RNA levels (lower limit of detection 40 copies/ml) were measured by the Abbott RealTime HIV-1 Assay (Abbott Park, Illinois, USA). CD4 counts and percentage were measured by the TruCount Method (BD Biosciences, Germany).

Biological aging was measured by the biomarkers telomere length and DNAm age in all children. Absolute telomere length in Kb/genome was determined by combination of methods developed by O’Callaghan et al. and Cawthon et al. using known quantities of synthesized oligonucleotides containing TTAGGG repeats and a single copy gene (albumin) to generate standard curves in a multiplex quantitative polymerase chain reaction (PCR) method.[28–30] The assay was optimized by measuring both telomere and single copy gene amplifications on the same 384-well plate in a Bio-Rad iQ5 real-time PCR detection system (Biorad, Richmond, CA, USA). Measurements were performed in triplicate and the average was considered the result. This assay was performed at the Biomarkers Shared Resource at Columbia University Medical Center (New York, NY).

DNAm levels were measured using the Infinium HumanMethylation450 BeadChips array (Illumina, San Diego, CA) at the Genomics Shared Resource at Roswell Park Cancer Institute (Buffalo, NY). Samples were randomly distributed across the chips taking into account group, sex, and age to minimize potential batch effects.[31] Pre-processing pipeline procedures, including filtering, background correction, and beta-mixture quantile normalization, were performed with the R/Bioconductor minfi package.[32] Quality control steps were applied to the laboratory pipeline to identify outlying samples and remove non-CpG probes, control probes, SNP-enriched probes, probes previously demonstrated to potentially cross-hybridize non-specifically in the genome,[33] unreliable probes with detection p-value ≥0.05, and sex chromosome probes. DNAm age was measured using the method developed by Horvath et al., which uses 353 CpG dinucleotides to estimate age.[34]

In HIV-infected children, plasma markers of systemic inflammation were measured, including cytokines IL-6 (ELISA; R&D Systems, Minneapolis, MN) and TNF-alpha (ELISA; R&D Systems, Minneapolis, MN), and high-sensitivity C-reactive protein (Cobas Integra 400 Plus; Roche Diagnostics, Indianapolis, IN), an acute phase reactant and marker of general inflammation. In addition, we measured soluble CD14 (ELISA; R&D Systems, Minneapolis, MN), a marker of monocyte activation.

Statistical analyses

In all analyses, telomere length was natural log-transformed (ln[Kb/genome]) before analysis. The relationship between chronological age and the aging biomarkers was first evaluated to determine the validity of our assay and determine if it was necessary to adjust for chronological age in subsequent analyses. To adjust for chronological age in our analyses of DNAm age, we used an “age acceleration residual” (residual from regressing DNAm age on chronological age), where positive values greater than 0 indicate accelerated aging and negative values less than 0 indicate decelerated aging. Next, the biomarkers of aging were compared in the three groups (HIV-infected, HEU, and HUU). To account for potential confounding by differential cell type distributions in whole blood, analyses of DNAm age comparing HIV-infected and HIV-uninfected groups were adjusted for cell type composition estimated using the method described by Houseman et al.[35]

In the HIV-infected children, the following predictors were evaluated for associations with the biomarkers of aging: sex, household smoke exposure (someone in household smokes cigarettes), age at ART initiation, duration on ART, pre-treatment CD4 percentage, pre-treatment viral load, and current CD4 percentage. Finally, we evaluated if the biomarkers of aging were related to markers of inflammation in the HIV-infected children, independent of potential confounders.

Continuous variables were descriptively summarized into mean±SD and categorical variables into percentages. Unadjusted comparisons of continuous variables were assessed by ANOVA and t-tests, and comparisons of categorical variables were assessed by chi-squared or Fisher’s exact tests. Linear regression was used for adjusted comparisons. Spearman’s p coefficient was used for correlations. All p-values are 2-tailed and p-values <0.05 were considered statistically significant. Statistical calculations were performed using SAS version 9.4 (Cary, North Carolina, USA).

Results

Study participants

Demographic characteristics of the 120 HIV-infected children as well as the 33 HEU and 25 HUU children are shown in Table 1. There were no significant differences in characteristics between the three groups. Approximately a third of children in all groups reported exposure to smoke in the household. At the time of measurement, age was 6.4±1.4 years and ranged from 4.1 years to 9.9 years. The 120 HIV-infected children were all suppressed (viral load <400 copies/mL) with a concurrent CD4 percentage of 33.5±6.4 and CD4 count of 1182±474 cells/mm3. Two children were on an efavirenz-based ART regimen and the remainder on a LPV/r-based ART regimen at the time of measurement. All but one child was on lamivudine and either abacavir (N=73), zidovudine (N=20), or stavudine (N=26). One child was on abacavir and zidovudine. All were previously initiated on a LPV/r-based ART regimen before 24 months of age at an average of 7.8±6.1 months.

Table 1.

Characteristics of 120 HIV-infected, 33 HIV-exposed uninfected (HEU), and 25 HIV-unexposed uninfected (HUU) children in Johannesburg, South Africa at the time of measurement of biomarkers of aging

Characteristic HIV-infected
(N=120)		 HEU
(N=33)		 HUU
(N=25)		 P1
Male, N (%) 56 (46.7) 18 (54.6) 11 (44.0) 0.67
Age at the time of measurement, Mean±SD 6.4±1.4 6.1±1.5 6.9±1.1 0.07
Mother is primary caregiver, N (%) 109 (90.8) 32 (97.0) 25 (100.0) 0.81
Lives in house, N (%) 75 (62.5) 20 (60.6) 17 (68.0) 0.94
Caregiver finished high school, N (%) 54 (45.0) 10 (30.3) 13 (52.0) 0.20
Caregiver has paid job, N (%) 52 (43.3) 11 (33.3) 11 (44.0) 0.58
Household member smokes cigarettes, N (%) 41 (34.2) 11 (33.3) 9 (36.0) 0.98
Age at treatment start in months, Mean±SD 7.8±6.1
Duration on ART in years, Mean±SD 5.8±1.4
Telomere length measurement obtained 119 (99.2) 32 (97.0) 25 (100.0) 0.55
DNAm age measurement obtained 119 (99.2) 33 (100.0) 25 (100.0) 1.0
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1

Continuous variables are compared using ANOVA; categorical variables are compared using Chi-squared test

A telomere length measurement was obtained for 176 (98.9%) of all participants. Average telomere length (ln[Kb/genome]) was 4.18±0.83 with values ranging from 1.80 to 5.87 (median [IQR]: 4.05 [3.72, 4.74]). DNAm age was calculated for 177/178 (99.4%) of participants. Average DNAm age was 11.6±3.4 years and ranged from 5.3 to 24.0 (median [IQR]: 11.3 [9.2, 13.6]).

HIV infection and aging biomarkers

Telomere length and DNAm age were compared to chronological age in the full group of children. Although DNAm age was positively correlated with chronological age (r=0.57, p<0.001), telomere length was not (r=0.007, p=0.92) (Figure 1A and B). There was no significant correlation between chronological age and telomere length even when stratified into HIV-infected (r=−0.09, p=0.33), HEU (r=0.02, p=0.91), or HUU children (r=0.35, p=0.09) separately (Figure 1C). The correlation between chronological age and DNAm age was positive for HIV-infected (r=0.58, p<0.01), HEU (r=0.56, p<0.01), and HUU (r=0.39, p=0.055) children (Figure 1D). Given this, we used an age acceleration residual for our comparisons of DNAm age between groups going forward.

Figure 1.

Figure 1

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Scatter plots of A) chronological age and telomere length, B) chronological age and DNAm age, C) chronological age and telomere length by HIV status, D) chronological age and DNAm age by HIV status

Box and whisker plots of telomere length and age acceleration residual by group are shown in Figure 2. Telomere length (ln[Kb/genome]) was shorter in HIV-infected children compared to HUU children (4.14±0.85 vs. 4.53±0.79, p=0.038) and in HEU children compared to HUU children (4.05±0.74 vs. 4.53±0.79, p=0.023). There was no significant difference in telomere length between HIV-infected and HEU children (p=0.58). Findings were similar after adjusting for age (data not shown). Age acceleration residual based on DNAm levels was not different between HIV-infected (−0.003±2.95), HEU (0.038±2.39), and HUU (0.18±2.49) children in unadjusted analysis and after adjustment for cell type proportions (data not shown).

Figure 2.

Figure 2

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Box and whisker plots of A) telomere length by HIV status and B) DNAm age acceleration residual by HIV status

Predictors of aging biomarkers in HIV-infected children

Among HIV-infected children, sex, time on ART, and pre-treatment viral load were not associated with telomere length or DNAm age acceleration residual (data not shown). As shown in Figure 3A, current CD4 percentage was significantly negatively correlated with age acceleration residual (r=−0.36, p<0.001) in the expected direction (higher CD4 percentage, less age acceleration). Current CD4 percentage was not correlated with telomere length (r=0.07, p=0.43). Unexpectedly, we found a weak negative correlation between pre-treatment CD4 percentage and telomere length (higher pre-treatment CD4 percentage, shorter telomere length) (r=−0.19, p=0.04) (data not shown). Given the variability in pre-treatment CD4 percentage by age, we adjusted the association between pre-treatment CD4 percentage and telomere length in a linear regression model for age at the time of the pre-treatment CD4 measurement and the association was no longer significant (unadjusted β = −0.015, p=0.046; adjusted β=−0.014, p=0.08). There was no correlation between pre-treatment CD4 percentage and DNAm age acceleration residual (r=−0.14, p=0.14) (data not shown).

Figure 3.

Figure 3

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In HIV-infected children, A) scatter plot of current CD4 percentage and DNAm age acceleration residual and B) box and whisker plots of DNAm age acceleration residual by smoke exposure status

As shown in Figure 3B, age acceleration residual was higher in the 41 HIV-infected children with reported household smoke exposure compared to the 78 who did not report household smoke exposure (0.712±3.63 vs. −0.379±2.48, p=0.05), indicative of more age acceleration in those with exposure to smoke in the household. Telomere length followed the same pattern, with shorter telomere length in children with reported household smoke exposure compared to those without, although not significant (4.01±0.86 vs. 4.22±0.83, p=0.21).

Relationship between biological aging and markers of inflammation in HIV-infected children

Finally, we evaluated the relationship between the aging biomarkers and markers of inflammation in the HIV-infected children (Figure 4). We did not observe any associations between the markers of inflammation and either telomere length or DNAm age acceleration residual. There was only a weak negative correlation between soluble CD14 and telomere length (r=−0.14, p=0.14).

Figure 4.

Figure 4

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Relationship between markers of inflammation (IL-6, TNF-alpha, high-sensitivity CRP, and soluble CD14) and A) telomere length and B) DNAm age acceleration residual for HIV-infected children

Discussion

We observed no evidence of accelerated biological aging using the biomarker based on DNAm patterns in perinatally HIV-infected children 4–9 years of age who were initiated early on ART and had a suppressed viral load <400 copies/ml at the time of measurement compared to HUU children. In contrast, we observed that absolute telomere length was shorter, generally considered a biomarker of accelerated aging, in both HIV-infected and HEU children compared to HUU children. However, telomere length did not differ between HIV-infected and HEU children.

Our finding of no accelerated aging by DNAm age was in contrast to studies documenting accelerated aging in antiretroviral-naïve HIV-infected adults as well as HIV-infected adults with 2 years of ART in comparison to HIV-uninfected adults.[10, 13, 36] It is possible that the negative impact of HIV on DNAm age in these children may occur after a longer duration of infection (i.e. greater than a mean of 6.4 years), later in life, or that it was prevented with initiation of ART in perinatally-infected children close to the time of primary infection. Given the finding of a strong correlation of DNAm age with chronological age and accelerated DNAm age among those with household smoke exposure, consistent with other reports,[37] the null HIV finding does not appear to be due to inadequacies of the markers we used to assess biological age. If accelerated aging by DNAm age occurs during adolescence and adulthood, long-term follow up will be necessary to detect this association.

We observed an association between current CD4 percentage and DNAm age, similar to findings from a study of 109 adult men which found a correlation between DNAm age and CD4+ T cells in PBMCs (r=−0.23, p=0.023).[10] That same study found a higher DNAm age in those with a detectable viral load (>35 copies/mL) compared to those with a non-detectable viral load, but we were unable to assess this association as we deliberately selected only children who were well-suppressed on ART. In the HIV-infected children, accelerated biological aging measured by DNAm age was associated with exposure to smoke in the household, but not with plasma markers of inflammation. The children in this study have been well-suppressed on ART for many years and the markers of inflammation that were measured were in the normal range for most children. These findings suggest that adverse environmental events in early life may play an important role in biological aging, as reported in other studies.[38, 39]

Our telomere length findings were consistent with a study by Gianesin et al. of slightly younger children aged 0–5 years (median 3.1 years) in Spain.[14, 40] Similar to our findings, Gianesin et al. reported significantly lower telomere length in HIV-infected children on ART than HUU infants (T/S ratio 2.46 vs. 2.88, p=0.0017, personal communication) and a trend of lower telomere length in HEU children than HUU infants (T/S ratio 2.63 vs. 2.88, p=0.057, personal communication), but no significant difference between HIV-infected children on ART and HEU children (p=0.098).

In contrast, a Canadian study did not find differences in telomere length between HIV-infected, HEU, and HUU children.[15] This may be due to the wider age range in the Canadian study (ages 0–19 years) or a slightly longer duration of ART exposure than children in our study (median 7 years vs. 5.7 years in our study). It is possible that longer ART duration may restore telomere length differences, but further follow-up is needed.[14, 15] Two other studies reporting on HEU and HUU children but not HIV-infected children at birth did not find evidence of shorter telomere length in HEU children compared to HUU children;[41, 42] our study reports on children at a mean age of 6.4 years and in a different setting.

Our findings suggest that telomere length shortening may occur early on in the natural history of the disease (in utero in the case of perinatal HIV infection) and potentially prior to ART initiation. Supporting this hypothesis are adult studies that show telomere shortening occurring shortly after HIV seroconversion.[7, 43, 44] However, whether this finding is due to in utero HIV infection, in utero HIV exposure, in utero antiretroviral exposure, or other factors, is unclear. We were unable to separate HIV infection or exposure from antiretroviral exposure, as all children were exposed to antiretrovirals as prevention prior to initiating treatment. Although we observed an association between pre-treatment CD4 percentage and telomere length in unadjusted analyses, this finding did not remain significant after adjustment for age at measurement of pre-treatment CD4.

Our study has several limitations. First, we did not measure DNAm levels in specific cell sub-sets and it is possible findings may be different; a study in HIV-infected children showed accelerated immune senescence in the CD8+ T-cell sub-set.[14] Second, quantitative PCR is a practical, but indirect, marker of telomere length. Third, we did not find telomere length to be associated with chronological age in our study, as observed in adults. This null correlation likely reflects the plateau in telomere shortening generally seen in healthy children between age 4 and young adulthood.[45, 46] Fourth, since all HIV-infected children were on ART and virally suppressed, we were unable to assess the impact of no ART or viremia on DNAm age or telomere length. Similarly, we were unable to separate effects of HIV infection or exposure from ART exposure. In addition, we were unable to account for certain unmeasured variables, such as biological father’s age, which has been shown to be associated with offspring telomere length or cytomegalovirus infection which is known to be associated with shorter telomeres.[47, 48] Finally, the cross-sectional nature of this study limits our ability to interpret these findings.

In conclusion, a cross-sectional measure of DNAm age was not accelerated in HIV-infected children initiated on ART early compared to HEU and HUU children. Telomere length was shorter in HIV-infected and HEU children compared to HUU children. As the HIV-infected children were initiated and maintained on ART since an early age, the lack of differences between the HIV-infected children and HEU children may be due to viral suppression. Further studies in children are needed to understand if these findings are sustained longitudinally, and to determine if the telomere shortening is due to in utero HIV infection, in utero HIV exposure, in utero antiretroviral exposure, or other factors.

Acknowledgments

Source of Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD 073977, HD 073952)

Footnotes

Conflicts of Interest: The authors have no conflicts of interest to declare.

Conference Presentations: Portions of this work were presented at the 8th International Workshop on HIV & Aging on October 2–3, 2017 in New York, NY, USA.

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