Longitudinal changes in bone mineral density among children living with HIV over 96 weeks following switch to second-line antiretroviral therapy in Uganda

Eva Natukunda; Erisa Mwaka; Alexander J. Szubert; Alasdair Bamford; Katja Doerholt; Centurio Wandera; Spencer Byaruhanga; Esther Nambi; Diana M. Gibb; Victor Musiime; Philippa Musoke; Ann Sarah Walker

doi:10.1371/journal.pgph.0005979

Abstract

Long-term impact of antiretroviral therapy (ART) on bone health in children living with HIV (CLWH) remains uncertain. We aimed to determine associations of change in bone mineral density (BMD) among CLWH in Uganda in a 2-year prospective sub-study in the CHAPAS-4 randomized trial (ISRCTN22964075). CLWH aged 3–15 years switched to second-line ART including tenofovir alafenamide fumarate-emtricitabine (TAF/FTC) or standard-of-care (SOC) (abacavir (ABC) or zidovudine (ZDV) with dolutegravir (DTG), atazanavir/ritonavir (ATV/r), darunavir/ritonavir (DRV/r) or lopinavir/ritonavir (LPV/r). BMD was assessed by dual-energy X-ray absorptiometry (DXA) at baseline, weeks 48 and 96 and bone turnover markers measured at baseline, week 24, 48, and 96. Robust regression analysis determined associations of BMD and bone turnover markers through week 96. Of 196 participants,167 contributed BMD measurements. Median (IQR) age was 9.9(7.0,12.3) years, 47% male, median (IQR) CD4 T-cell count 797(537,1140) cells/µl and mean (SD) viral load (log₁₀ copies/ml) 4.3(0.8). Change in Procollagen type I N-terminal propeptide (PINP), C-terminal telopeptide of type I collagen (CTX) and height-adjusted (HA) BMD were similar between TAF/FTC and SOC. Greater declines in total-body-less-head (TBLH) BMD were associated with higher baseline TBLH (HA) BMD (Coef. -0.30,95% CI: -0.46, -0.15], p < 0.001) and first-line nevirapine (NVP) exposure (-0.25,95% CI: -0.43, -0.06, p = 0.009). Smaller TBLH HA BMD declines were associated with higher baseline fat-mass (0.06, 95% CI:0.01, 0.11, p = 0.021), higher lumbar spine (LS) HA BMD (0.17, 95% CI:0.03, 0.31, p = 0.015), DRV/r (0.46, p < 0.001,95% CI:0.21,0.71), DTG (0.26, p = 0.041,95% CI:0.01,0.51) or ATV/r (0.28, p = 0.026, 95% CI: 0.03, 0.52) use compared with LPV/r. Smaller declines in TBLH BMD were associated with higher baseline fat mass, higher LS HA BMD, and use of DRV/r, DTG, or ATV/r compared with LPV/r. These findings emphasize the importance of ART selection and body composition in supporting bone health among CLWH.

Citation: Natukunda E, Mwaka E, Szubert AJ, Bamford A, Doerholt K, Wandera C, et al. (2026) Longitudinal changes in bone mineral density among children living with HIV over 96 weeks following switch to second-line antiretroviral therapy in Uganda. PLOS Glob Public Health 6(2): e0005979. https://doi.org/10.1371/journal.pgph.0005979

Editor: Vishal Goyal, Ex DNDi, UNITED STATES OF AMERICA

Received: May 23, 2025; Accepted: January 28, 2026; Published: February 17, 2026

Copyright: © 2026 Natukunda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The dataset contains sensitive clinical information from children living with HIV who were enrolled in the CHAPAS-4 trial. According to the Joint Clinical Research Centre (JCRC) institutional policy, the CHAPAS-4 protocol, and the requirements of the Research Ethics Committees in Uganda, individual-level participant data cannot be placed in a public repository. Any access to the data must: 1. Be requested by a qualified researcher, 2. Be accompanied by formal ethical approval for secondary analysis from a recognized Institutional Review Board/Ethics Committee, and 3. Receive clearance from the corresponding author, the head of the Institution (JCRC), and the trial sponsor, due to the contractual data-sharing agreements in place for the CHAPAS-4 trial. However, we confirm that de-identified individual-level data can be shared with other researchers upon reasonable request, provided they submit the required ethical approvals and meet the conditions specified above. Requests for data access should be directed to the Joint Clinical Research Centre. Email: jcrc@jcrc.org.ug.

Funding: The CHAPAS-4 trial was funded by the European and Developing countries clinical trials partnership (EDCTP) as part of the EDCTP program, which is supported by European Union through grant (TRIA2015-1078). DMG received the award (www.ucl.uk). Gilead Sciences, CIPLA, ViiV healthcare and Janssen provided the trial drugs. AJS, DMG and ASW were supported by core support to the MRC Clinical Trials Unit at UCL (MC UU 00004/03). Gilead Sciences and Janssen also provided funding to support the study. DMG received the funds. The funders had no role in study design, data collection, analysis, or the decision to prepare the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Antiretroviral therapy (ART) has transformed the lives of people living with HIV(PLWH) and significantly improved their life expectancy and quality of life. [1] However, as children with HIV (CLWH) live longer on lifelong therapy, long-term safety concerns, including effects on bone development become increasingly important. Studies have shown lower bone mineral density (BMD) among PLWH compared with their negative counterparts [2]. The prevalence of low BMD among adults living with HIV is 20–80% [3,4], while in CLWH ranges from 4-32% with the lower prevalence in high-income countries [5] and higher in low and middle-income countries in sub-Saharan Africa and Asia, where stunting, undernutrition, and delayed puberty are common [6,7]. Achieving optimal peak bone mass during childhood and adolescence is crucial for reducing the risk of osteoporosis and fractures later in life. Yet, HIV infection and ART exposure may disrupt normal bone accrual during the developmental window [6].

Low BMD in HIV is influenced by a combination of traditional risk factors such as low body mass index (BMI), female sex, reduced physical activity, and HIV related mechanisms like immune activation and direct drug-induced toxicity. [8,9] In addition, body composition, such as fat mass and lean mass, have an impact on bone development among children, given the relationship between adiposity, lean tissue, and BMD [10]. Despite the existing literature on risk factors for low BMD in PLWH, the associations of change in BMD in CLWH switching to second-line ART remain underexplored in resource-limited settings (RLS).

Long-term use of older generation boosted protease inhibitors (bPIs), such as ritonavir-boosted lopinavir(LPV/r), have been associated with deterioration in bone health [11]. Previous studies have demonstrated that tenofovir disoproxil fumarate (TDF) may contribute to reduced BMD and alterations in bone turnover markers (BTMs) [6,12]. These findings have raised concerns about the long-term effects of TDF on bone health and signify the importance of identifying alternative treatment strategies that minimize bone loss and optimize peak bone mass in childhood.

Circulating BTMs, procollagen type 1 N-terminal propeptide (P1NP), and C-terminal telopeptide of type 1 collagen (CTX) released during bone remodeling can be a useful tool in predicting fracture risk among adults with low BMD but there is limited literature on their usefulness in predicting BMD change among CLWH [13]. Among South African CLWH with viral suppression, annual percentage change in P1NP was positively associated with BMD [14]. An adult study found elevated BTMs among PLWH with viral suppression who switched to TDF compared with ABC [15].

Tenofovir alafenamide fumarate (TAF), a novel prodrug of tenofovir, exhibits high intracellular conversion to its active form, resulting in potent antiviral efficacy at lower doses compared to TDF [16]. Although TAF has demonstrated improved renal and bone safety compared with TDF in adults and adolescents [17,18], its long-term effects in younger children remain unclear. Few studies have evaluated longitudinal changes in BMD and BTMs following ART switch in African pediatric populations, where limited access to dual-energy X-ray absorptiometry (DXA) and a lack of reference data complicates the assessment. Moreover, the influence of previous first-line non-nucleoside reverse transcriptase inhibitors NNRTIs) exposure as well as second-line anchor drugs on bone outcomes remain underexplored.

Although several studies have investigated the impact of TAF on bone health among the adult populations [19,20], there is a paucity of data regarding its effects on BMD and BTMs in CLWH switching to second-line ART, when co-administered with bPIs or dolutegravir (DTG) [17,18,21]. This sub-study aimed to determine the associations of BMD and BTM changes among CLWH switching to second-line TAF/FTC or standard- of- care (SOC) based backbone when co-administered with DTG or bPIs. We aimed to identify modifiable risk factors for bone loss in CLWH from low-income countries where diagnostic facilities are limited.

Materials and methods

Ethics statement

The main CHAPAS-4 trial was approved by the JCRC institutional review board (Reference -JC 1417), Uganda National Council of Science and Technology (UNCST)(HS:2369), and National Drug Authority (Ref CTC 066). Written informed consent was obtained from the caregivers or parents of all participants, and written assent was obtained from the children aged 8 years and above before enrolment into the sub-study.

Study design

We conducted a prospective longitudinal sub-study from January 2019 to March 2023 at the Joint Clinical Research Centre (JCRC), Uganda. We enrolled the first participant on 21^st Jan 2019 and the last on 23^rd Feb 2021.One hundred and ninety-six children aged 3–15 years were enrolled in this sub-study, which was nested within the main CHAPAS-4 trial, a randomized controlled trial (ISRCTN22964075) that enrolled children who were failing non-nucleoside reverse transcriptase inhibitor (NNRTI) based first-line ART in Uganda, Zambia and Zimbabwe. Participants were randomized to receive TAF/FTC or standard-of-care (SOC)-based backbone, which was ABC/3TC (lamivudine) or ZDV/3TC (whichever was not used first-line), and simultaneously randomized to DTG, ATV/r, LPV/r, or DRV/r as anchor drug. All children were followed up for 96 weeks. In the sub-study, we assessed associations of longitudinal change in BMD and BTMs among CLWH on TAF/FTC or SOC backbone (Fig 1–5).

Download:

Fig 1. Consort flow diagram.

https://doi.org/10.1371/journal.pgph.0005979.g001

Download:

Fig 2. Mean change in C-terminal telopeptide (ng/ml) over time in participants receiving TAF/FTC or SOC-based backbone.

ng/ml = nanograms per ml, TAF/FTC = Tenofovir alafenamide fumarate/Emtricitabine, SOC = Standard of care, CTX = C-Terminal Telopeptide of type I collagen.

https://doi.org/10.1371/journal.pgph.0005979.g002

Download:

Fig 3. Mean change in procollagen type I N-terminal propeptide (pg/ml) over time in participants receiving TAF/FTC or SOC-based backbone.

pg/ml = picograms per ml, TAF/FTC = Tenofovir alafenamide fumarate/Emtricitabine, SOC = Standard of care P1NP=Procollagen Type I N-terminal Propeptide.

https://doi.org/10.1371/journal.pgph.0005979.g003

Download:

Fig 4. Mean change in height-adjusted lumbar spine BMD Z-scores (LS HA BMD) over time in participants on TAF/FTC or SOC.

TAF = Tenofovir alafenamide fumarate, SOC = Standard of care.

https://doi.org/10.1371/journal.pgph.0005979.g004

Download:

Fig 5. Mean change in height-adjusted total body less head BMD Z-scores (TBLH HA BMD) over time in participants on TAF/FTC or SOC.

TAF = Tenofovir alafenamide fumarate, SOC = Standard of care.

https://doi.org/10.1371/journal.pgph.0005979.g005

Study population

Children aged 3–15 years, switching to second-line ART were eligible for inclusion in the sub-study. Participants were recruited from the JCRC pediatric outpatient clinic and nearby public health facilities. We excluded one participant with disabilities that compromised body positioning during scan acquisition.

Measurements

Areal BMD was assessed using DXA Hologic Discovery Wi apex software version 3.1 (Hologic Bedford Inc., Bedford, MA, USA) at baseline, weeks 48 and 96 at one facility with the same densitometer. The procedure for BMD acquisition has been previously described [22]. Areal BMD values underestimate true volumetric BMD in smaller bones [23,24]. We therefore determined height-adjusted BMD (HA BMD) Z-scores using reference data as per International Society of Clinical Densitometry (ISCD) recommendation [25,26]. Plasma samples were collected at baseline, weeks 24, 48, and 96, and stored at -80°C. Samples were obtained from fasting participants during morning hours (mean collection time ≈ 10:30 a.m., SD 1 hour) to minimize the effect of diurnal variation for C-terminal telopeptide of type I collagen (CTX). CTX (0.156-10ng/ml) was measured in nanograms per litre (ng/ml)and Procollagen type I N-terminal propeptide (P1NP)(78–5000pg/ml) in picograms per millilitre (pg/ml) using enzyme-linked immunosorbent assay (ELISA) following the manufacturer’s manual [27]. Each sample was run in duplicate and an average reading was obtained.

Collection of baseline demographic and clinical characteristics, including age, sex, time since HIV diagnosis, previous ART history, WHO stage, weight and height, have been previously described along with baseline viral load, CD4 count [22]. Data on BMD and BTMs were collected and recorded by trained personnel blinded to the treatment arms.

Statistical analysis

All analyses were performed using Stata 15 (Stata Corp LLC, College Station, Texas). Baseline characteristics were summarized as means and standard deviations (SD) for continuous, normally distributed data (assessed using the Shapiro-Wilk test) and as medians (interquartile ranges) for non-normally distributed data. Categorical data were presented as frequencies and percentages.

The primary outcomes were changes in HA BMD Z-scores—total body less head (TBLH) and lumbar spine (LS), and bone turnover markers (P1NP and CTX) from baseline (Week 0) to Week 96. Changes were calculated as the difference between values at Week 96 and baseline. Participants with missing baseline values were excluded from analysis as their change could not be calculated. Z-scores were approximately normally distributed so were modelled on the absolute scale whereas BTMs were approximately log-normally distributed so were modelled on the log scale.

Group comparisons were conducted to assess differences in changes in HA BMD Z-scores and BTMs between the TAF/FTC and SOC treatment groups. Independent t-tests were used for normally distributed changes, while Wilcoxon rank-sum tests were applied for non-normally distributed changes.

To identify baseline factors associated with the four outcomes above, robust regression was employed to reduce the influence of outliers and potential heteroscedasticity, providing more reliable estimates than a normal linear regression model under these conditions. Models assessed associations of 96-week changes in HA BMD Z-scores and BTMs, adjusting for baseline log₁₀ viral load, CD4 count, BMI Z-score, fat mass, fat-free mass, P1NP, CTX, first-line ART regimen, WHO stage, sex, treatment arm, and randomized anchor and backbone drugs. Log transformations were applied to viral load, CD4 count, P1NP, and CTX to reduce right-skewness and stabilize variance, and age at the measurement was excluded as it is numerically equal to age at ART initiation plus time on first-line ART; a priori because the Z-score calculation includes current age and current age is not modifiable we chose to estimate the effects of age at ART initiation and time on first-line ART. Model adequacy was evaluated by regressing the residuals from each robust regression model within a standard linear regression framework to assess whether any systematic variation remained.

The sub-study was nested within the CHAPAS-4 trial; therefore, the sample size was determined by the parent trial enrolment, and no formal a priori sample size calculation was conducted. Based on the observed sample sizes and standard deviations, the study had 80% power to detect the differences in the outcomes between TAF/FTC and SOC arms at 5% significance level.

To visualize trends, line graphs with 95% confidence intervals were generated for mean changes in HA BMD Z-scores, P1NP, and CTX over 96 weeks, stratified by treatment group (TAF/FTC vs. SOC). A box plot illustrated the impact of prior nevirapine (NVP)-based vs. efavirenz (EFV)-based first-line regimens on baseline HA BMD and also on changes at week 96.

Results

The baseline characteristics are shown in Table 1. One hundred ninety-six children aged 3–15 years were enrolled in the sub-study, of which 167 had BMD measurements. There was no significant difference between the baseline characteristics of participants receiving SOC or TAF-based backbone.

Download:

Table 1. Baseline characteristics study participants N = 196.

https://doi.org/10.1371/journal.pgph.0005979.t001

Table 2 summarizes the change in HA BMD Z-scores. Changes in HA BMD Z-scores over 96 weeks were comparable between TAF/FTC and SOC. The mean changes in TBLH HA BMD Z-scores were slightly greater in the TAF/FTC group compared to SOC; however, the difference was not statistically significant (p = 0.736). Similarly, LS HA BMD Z-scores declined in both groups with no significant difference observed (p = 0.849).

Download:

Table 2. Height adjusted BMD Z scores and bone turnover marker change at 96 weeks by treatment group (TAF vs. SOC).

https://doi.org/10.1371/journal.pgph.0005979.t002

Bone turnover markers (BTMs) also showed similar patterns of decline between groups. The median change in P1NP levels was slightly larger in the TAF/FTC group compared to SOC, but this difference was not significant (p = 0.775). Likewise, CTX levels decreased in both groups with no significant difference between TAF/FTC and SOC (p = 0.101).

Multivariate analysis results for BMD associations are presented in S1 Table. Every one-unit kg higher baseline fat mass was associated with a 0.06 SD higher in TBLH HA BMD Z-scores at week 96. Similarly, every unit higher baseline LS HA BMD Z-score was associated with a 0.17 unit increase in baseline HA BMD Z-score. Every unit higher TBLH HA BMD Z-score was associated with a 0.30-unit greater decline in TBLH HA BMD Z-score at week 96. First-line NVP use was associated with a 0.25-unit greater decrease in TBLH HA BMD Z-score decline compared with first-line EFV use. A similar trend was observed for LS HA BMD Z-scores, with a 0.30-unit greater decrease in LS HA BMD Z-score associated with first-line NVP use. ATV/r based second line regimen was associated with a 0.25 SD smaller TBLH HA BMD Z-score decline compared with LPV/r, as were DRV/r and DTG.

Multivariate analysis results for BTM associations are presented in S2 Table. A 1% higher baseline CTX was associated with a 0.32% decline in CTX level, while a 1% higher baseline P1NP was associated with a 0.31% decline in CTX level. Similarly, a 1% higher baseline P1NP was associated with a 1.07% decline in P1NP level. Prior exposure to first-line NVP was associated with a 25% higher CTX level compared to prior EFV-based regimens. Female sex was associated with 20% higher CTX levels compared to males.

Discussion

In this two-year sub-study of the CHAPAS-4 clinical trial among children randomized to TAF/FTC or SOC-based backbone after first-line NNRTI-based ART failure, the independent associations with BMD decline included prior first-line NVP exposure and higher baseline TBLH HA BMD. In addition, receiving DRV/r, ATV/r or DTG compared with LPV/r, higher baseline fat-mass, and higher baseline LS BMD were associated with a greater increase in BMD. BTM parameters showed no significant difference between TAF/FTC and SOC arms.

Previous adult and adolescent studies have reported a mixture of traditional and HIV associated risk factors for BMD decline [28]. In our study, prior use of NVP-based first-line ART was associated with greater BMD decline compared with EFV. One possible explanation for this observation, although hypothetical, is that NVP may have relatively bone-sparing effects compared to EFV and some second-line ART regimens. Previous studies have reported that NVP may have neutral or suppressive effects on cytokine interleukin (IL)-6 release, which promotes osteoclast activity, whereas EFV has been associated with increased cytokine release, which may enhance bone turnover [29,30]. Although NVP is no longer commonly used, children transitioning to currently recommended regimens from NVP may be at risk of reduced BMD accrual since the putative bone-sparing effects of NVP were not sustained when CLWH transitioned to second-line ART regimens. These explanations remain theoretical, and interventional studies are required to confirm these proposed pathways.

The anchor drugs (ATV/r, DRV/r, and DTG but not LPV/r) were significantly associated with an increase in TBLH HA BMD. Compared with LPV/r, mean increases in TBLH Z-scores were 0.28 SD higher with ATV/r, 0.46 SD higher with DRV/r, and 0.26 SD higher with DTG. This finding is consistent with results from previous adult studies. In the CASTLE sub-study, hip BMD declined by –2.4% with LPV/r versus –1.2% with ATV/r after 48 weeks [31], Similarly, Brown et al. reported comparable bone outcomes for ATV/r and DRV/r in adults initiating TDF-based ART, with mean total hip BMD declines of –2.7% and –2.4%, respectively, at week 48 [32]. The absence of a significant increase in TBLH BMD with LPV/r may be attributed to the greater bone loss associated with ritonavir (RTV) boosting [33], which is more pronounced with LPV/r than with ATV/r or DRV/r. In addition, Bonfanti et al. demonstrated significant bone recovery after switching from PI-based to DTG-based therapy, with LS BMD increasing by 1.7% and femoral neck by 1.3% over 48 weeks, accompanied by reductions in BTMs, hence demonstrating a positive impact on BMD in real-world adult cohorts, further supporting its bone-sparing properties [34].

In our cohort, fat mass was positively associated with total body less head (TBLH) BMD, with a mean increase of 0.06 SD per unit increase in fat mass, whereas the corresponding association with lumbar spine (LS) BMD was smaller and non-significant (0.04 SD per unit). This is similar to a previous report of fat mass correlation with bone site that was stronger with TBLH BMD than LS BMD (p = 0.001) [35]. Fat mass contributes to the overall body weight, which increases mechanical loading on weight-bearing bones. The relationship between fat mass and bone density may be stronger at weight-bearing sites compared to the spine, which has more trabecular bone and is less influenced by mechanical loading [36].

Higher baseline TBLH HA BMD Z-scores was associated with -0.3SD decline in TBLH HA BMD Z-scores over 96 weeks. Comparative literature is scarce; however, in a previous study among virally suppressed South African CLWH, there was a progressive annual decline of -0.05 SD in TBLH HA BMD Z-scores over time despite viral suppression [14]. The greater decline in our cohort likely reflects the negative impact of viral non-suppression and inflammation on bone formation, compounded by delayed growth recovery after ART switch.

LS predominantly consists of trabecular bone, which is more metabolically active and responds more rapidly to changes in interventions compared with TBLH, which is cortical [37]. The observed LS HA BMD Z-scores prediction may reflect improvement in BMD due to reduced HIV-related bone resorption or direct effects of effective second-line ART.

In our study, we observed that there was a decline in BTMs by week 96, suggesting a reduction in osteoblast and osteoclast activity. The decline could be attributed to multiple factors. This trend may be attributed to growth. Bone remodeling declines with age and increases up to mid-puberty, followed by another decline [38,39]. The median age of our study participants was approximately 10 years at baseline, meaning they were approaching their peak growth period, particularly the females. By week 96, growth velocity may have slowed, leading to reduced BTMs; we did not do a Tanner evaluation to confirm the pubertal status either at baseline or over follow-up. One limitation is therefore that we are not able to formally assess the impact of puberty on these changes; however, power would be very low to detect differences in the effect of backbone NRTIs across pubertal stages. Some children may have reached late puberty, where BTMs naturally declined.

The decline in BTMs may also be attributed to a reduction in systemic inflammation following viral suppression, although a reduction in bone turnover may also occur when there is viral suppression [40]. In the CHANGES longitudinal study among CLWH, there was a mean increase in BTMs over time, contrary to our findings. This discrepancy may be due to the study enrolling predominantly younger children with viral suppression [14]. Longer periods of viral suppression may lead to an increase in BTMs.

In our study, PINP changes between TAF and SOC were comparable (–496 pg/mL vs –379 pg/mL). Although direct comparative paediatric data on BTMs between TAF and ABC are limited, Winston et al. reported no significant differences in hip and spine BMD at week 48 (0.27% vs 0.16% at the hip, and 0.10% vs 0.03% at the spine) between adults maintained on ABC/3TC and those switched to TAF/FTC [41]. In addition, a study comparing bone outcomes in ART-naïve adults who started TAF, TDF, or ABC-based first-line ART found no significant difference in BTMs between participants on TAF or ABC by week 48 (18 pg/mL for TAF, and 21 pg/mL for ABC), which is consistent with our findings [42].

Higher BTMs at baseline were associated with a greater decline in BTMs after the switch to effective second-line ART. This may be explained by a possible significant reduction in systemic inflammation compared with those who had a lower level of baseline BTMs.

There are several limitations to this study. A relatively short follow-up period and hence long-term effects of ART on bone outcomes may not have been captured, given the fact that TBLH is primarily trabecular, hence less sensitive to changes following drug exposure. Secondly, the study did not collect data on pubertal development, which is a crucial contributor to bone health. The potential for confounding due to the low vitamin D status that is prevalent in Ugandan children: Vitamin D was not measured, and neither was dietary calcium intake nor sun exposure, which are all determinants for bone mineralization [43–45]. We did not collect data on physical activity, one of the strongest predictors of peak bone mass development, and therefore its impact was not assessed [46,47]. The study was conducted at a single site, which limits the generalizability of the findings.

The sample sizes and observed variability indicated that the study had sufficient power to detect moderate between-group differences in BMD and BTM-related outcomes, but limited power to detect smaller differences in the BMD and BTM-outcomes. In addition, we used HA BMD reference values from the black American population, which may be inappropriate given the lack of local reference values [25].

Despite the limitations, this is the first study to determine associations of bone changes among CLWH switching to second-line ART in Uganda. The longitudinal design allowed for detailed tracking of changes in BTMs over time, and the inclusion of multiple ART regimens provided a detailed understanding of the comparative bone changes.

In conclusion, we observed no difference in the BTMs or HA BMD between children and adolescents receiving TAF/FTC and SOC-based backbone. Fat mass, second-line DRV/r, ATV/r, or DTG use (but not LPV/r), and higher baseline LS BMD were associated with an increase in BMD among CLWH. Prior first-line NVP exposure was associated with BMD decline. Optimizing drug choices to minimize effects on body composition alongside nutritional programs is crucial for promoting bone health in this population.

Supporting information

S1 Fig. Box plot of lumbar spine (LS) and total-body-less-head (TBLH) height-adjusted BMD Z-scores stratified by first-line ART regimen (EFV vs. NVP) at baseline.

The baseline LS HA BMD Z scores for prior first-line EFV exposure were significantly lower than those on NVP, with a mean difference of -0.33 (95% CI: -0.64 to -0.03, p = 0.034). In contrast, no significant difference was observed in the TBLH BMD Z scores between the two groups (z = -1.86, p = 0.063). Participants who were previously on NVP showed a greater decline, as the majority experienced negative changes in LS HA BMD Z-scores compared to those on EFV-based regimens. EFV = Efavirenz, NVP = Nevirapine.

https://doi.org/10.1371/journal.pgph.0005979.s001

(TIF)

S2 Fig. The boxplot illustrates the change in LS HA BMD and TBLH HA BMD Z-score changes over 96 weeks among participants previously on EFVor NVP-based first-line ART regimens.

The mean HA LS HA BMD Z score change was -0.118 (SD = 0.567) in the EFV-based and -0.437 (SD = 0.675) in the NVP-based, with a statistically significant mean difference of 0.320 (95% CI: 0.110, 0.530), p = 0.003. For HA TB BMD Z-score change, the mean was -0.006 (SD = 0.583) in the EFV group and -0.199 (SD = 0.673) in the NVP group, with a non-significant mean difference of 0.193 (95% CI: -0.019, 0.405), p = 0.074. EFV = Efavirenz, NVP = Nevirapine.

https://doi.org/10.1371/journal.pgph.0005979.s002

(TIF)

S1 Table. Multivariable linear regression analysis identifying factors associated with a change in bone mineral density.

https://doi.org/10.1371/journal.pgph.0005979.s003

(DOCX)

S2 Table. Multivariable linear regression analysis identifying factors associated with change in bone turnover markers.

https://doi.org/10.1371/journal.pgph.0005979.s004

(DOCX)

Acknowledgments

This work was done as part of the CHAPAS 4 trial. The authors would like to thank the children and their caretakers who volunteered to participate in this study.

We thank the pediatric clinic and laboratory team at the Joint Clinical Research Centre, Kampala.

We thank Gilead Sciences, CIPLA, ViiV Healthcare, and Janssen for providing the trial drugs.

References

1. Wandeler G, Johnson LF, Egger M. Trends in life expectancy of HIV-positive adults on antiretroviral therapy across the globe: comparisons with general population. Curr Opin HIV AIDS. 2016;11(5):492–500. pmid:27254748
- View Article
- PubMed/NCBI
- Google Scholar
2. Arpadi SM, Thurman CB, Patel F, Kaufman JJ, Strehlau R, Burke M, et al. Bone quality measured using calcaneal quantitative ultrasonography is reduced among children with HIV in Johannesburg, South Africa. J Pediatr. 2019;215:267–271.e2. pmid:31474425
- View Article
- PubMed/NCBI
- Google Scholar
3. Mwaka ES, Munabi IG, Castelnuovo B, Kaimal A, Kasozi W, Kambugu A, et al. Low bone mass in people living with HIV on long-term anti-retroviral therapy: a single center study in Uganda. PLoS One. 2021;16(2):e0246389. pmid:33544754
- View Article
- PubMed/NCBI
- Google Scholar
4. Katzenstein TL, Wessman M, Moseholm E, Sandholdt H, Hansen ABE, Lebech AM. Prevalence of low bone mineral density among people living with HIV. Cogent Med. 2021;8(1):1920667.
- View Article
- Google Scholar
5. DiMeglio LA, Wang J, Siberry GK, Miller TL, Geffner ME, Hazra R, et al. Bone mineral density in children and adolescents with perinatal HIV infection. AIDS. 2013;27(2):211–20. pmid:23032412
- View Article
- PubMed/NCBI
- Google Scholar
6. Rukuni R, Rehman AM, Mukwasi-Kahari C, Madanhire T, Kowo-Nyakoko F, McHugh G, et al. Effect of HIV infection on growth and bone density in peripubertal children in the era of antiretroviral therapy: a cross-sectional study in Zimbabwe. Lancet Child Adolesc Health. 2021;5(8):569–81. pmid:34139202
- View Article
- PubMed/NCBI
- Google Scholar
7. Puthanakit T, Saksawad R, Bunupuradah T, Wittawatmongkol O, Chuanjaroen T, Ubolyam S, et al. Prevalence and risk factors of low bone mineral density among perinatally HIV-infected Thai adolescents receiving antiretroviral therapy. J Acquir Immune Defic Syndr. 2012;61(4):477–83. pmid:22918157
- View Article
- PubMed/NCBI
- Google Scholar
8. Alsaad LN, Akolaa EA, Muttappallymyalil J, Sreedharan J. Bone mineral density and its determinants: a systematic review of risk factors and prevention strategies. Biomed Pharmacol J. 2023;16(3):1791–6.
- View Article
- Google Scholar
9. Duvivier C, Kolta S, Assoumou L, Ghosn J, Rozenberg S, Murphy RL, et al. Greater decrease in bone mineral density with protease inhibitor regimens compared with nonnucleoside reverse transcriptase inhibitor regimens in HIV-1 infected naive patients. AIDS. 2009;23(7):817–24. pmid:19363330
- View Article
- PubMed/NCBI
- Google Scholar
10. Soininen S, Sidoroff V, Lindi V, Mahonen A, Kröger L, Kröger H, et al. Body fat mass, lean body mass and associated biomarkers as determinants of bone mineral density in children 6-8years of age - The Physical Activity and Nutrition in Children (PANIC) study. Bone. 2018;108:106–14. pmid:29307776
- View Article
- PubMed/NCBI
- Google Scholar
11. Madeddu G, Spanu A, Solinas P, Babudieri S, Calia GM, Lovigu C, et al. Different impact of NNRTI and PI-including HAART on bone mineral density loss in HIV-infected patients. Eur Rev Med Pharmacol Sci. 2015;19(23):4576–89. pmid:26698255
- View Article
- PubMed/NCBI
- Google Scholar
12. Komatsu A, Ikeda A, Kikuchi A, Minami C, Tan M, Matsushita S. Osteoporosis-related fractures in HIV-infected patients receiving long-term tenofovir disoproxil fumarate: an observational cohort study. Drug Saf. 2018;41(9):843–8. pmid:29623648
- View Article
- PubMed/NCBI
- Google Scholar
13. Yoon B-H, Yu W. Clinical utility of biochemical marker of bone turnover: fracture risk prediction and bone healing. J Bone Metab. 2018;25(2):73–8. pmid:29900156
- View Article
- PubMed/NCBI
- Google Scholar
14. Shen Y, Shiau S, Strehlau R, Burke M, Patel F, Johnson CT, et al. Persistently lower bone mass and bone turnover among South African children living with well controlled HIV. AIDS. 2021;35(13):2137–47. pmid:34127577
- View Article
- PubMed/NCBI
- Google Scholar
15. Haskelberg H, Hoy JF, Amin J, Ebeling PR, Emery S, Carr A, et al. Changes in bone turnover and bone loss in HIV-infected patients changing treatment to tenofovir-emtricitabine or abacavir-lamivudine. PLoS One. 2012;7(6):e38377. pmid:22719882
- View Article
- PubMed/NCBI
- Google Scholar
16. Podany AT, Bares SH, Havens J, Dyavar SR, O’Neill J, Lee S, et al. Plasma and intracellular pharmacokinetics of tenofovir in patients switched from tenofovir disoproxil fumarate to tenofovir alafenamide. AIDS. 2018;32(6):761–5. pmid:29334548
- View Article
- PubMed/NCBI
- Google Scholar
17. Natukunda E, Gaur AH, Kosalaraksa P, Batra J, Rakhmanina N, Porter D, et al. Safety, efficacy, and pharmacokinetics of single-tablet elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide in virologically suppressed, HIV-infected children: a single-arm, open-label trial. Lancet Child Adolesc Health. 2017;1(1):27–34. pmid:30169223
- View Article
- PubMed/NCBI
- Google Scholar
18. Gaur AH, Kizito H, Prasitsueubsai W, Rakhmanina N, Rassool M, Chakraborty R, et al. Safety, efficacy, and pharmacokinetics of a single-tablet regimen containing elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide in treatment-naive, HIV-infected adolescents: a single-arm, open-label trial. Lancet HIV. 2016;3(12):e561–8. pmid:27765666
- View Article
- PubMed/NCBI
- Google Scholar
19. Post FA, Yazdanpanah Y, Schembri G, Lazzarin A, Reynes J, Maggiolo F, et al. Efficacy and safety of emtricitabine/tenofovir alafenamide (FTC/TAF) vs. emtricitabine/tenofovir disoproxil fumarate (FTC/TDF) as a backbone for treatment of HIV-1 infection in virologically suppressed adults: subgroup analysis by third agent of a randomized, double-blind, active-controlled phase 3 trial. HIV Clin Trials. 2017;18(3):135–40. pmid:28303753
- View Article
- PubMed/NCBI
- Google Scholar
20. Liang X, Zhang H, Guo M, Zhao H, Yang D, Sun R, et al. Impact of different antiretroviral therapy regimens on bone mineral density in people living with HIV: a retrospective and longitudinal study in China. BMC Infect Dis. 2024;24(1):1400. pmid:39695982
- View Article
- PubMed/NCBI
- Google Scholar
21. O’Rourke J, Townsend CL, Milanzi E, Collins IJ, Castro H, Judd A, et al. Effectiveness and safety of tenofovir alafenamide in children and adolescents living with HIV: a systematic review. J Int AIDS Soc. 2023;26(2):e26037. pmid:36823283
- View Article
- PubMed/NCBI
- Google Scholar
22. Natukunda E, Szubert A, Otike C, Namyalo I, Nambi E, Bamford A, et al. Bone mineral density among children living with HIV failing first-line anti-retroviral therapy in Uganda: a sub-study of the CHAPAS-4 trial. PLoS One. 2023;18(7):e0288877. pmid:37471330
- View Article
- PubMed/NCBI
- Google Scholar
23. Faulkner RA, Davison KS, Bailey DA, Mirwald RL, Baxter-Jones ADG. Size-corrected BMD decreases during peak linear growth: implications for fracture incidence during adolescence. J Bone Miner Res. 2006;21(12):1864–70. pmid:17002589
- View Article
- PubMed/NCBI
- Google Scholar
24. Crabtree N, Ward K. Bone densitometry: current status and future perspective. Endocr Dev. 2015;28:72–83. pmid:26138836
- View Article
- PubMed/NCBI
- Google Scholar
25. Zemel BS, Kalkwarf HJ, Gilsanz V, Lappe JM, Oberfield S, Shepherd JA, et al. Revised reference curves for bone mineral content and areal bone mineral density according to age and sex for black and non-black children: results of the bone mineral density in childhood study. J Clin Endocrinol Metab. 2011;96(10):3160–9. pmid:21917867
- View Article
- PubMed/NCBI
- Google Scholar
26. ISCD. 2019 ISCD Official positions Pediatric. 2019. Available from: https://iscd.org/wp-content/uploads/2021/09/2019-Official-Positions-Pediatric-1.pdf
- View Article
- Google Scholar
27. Abbexa - Antibodies, Proteins, ELISA kits. Abbexa.
28. Ahmed M, Mital D, Abubaker NE, Panourgia M, Owles H, Papadaki I. Bone health in people living with HIV/AIDS: an update of where we are and potential future strategies. Microorganisms. 2023;11(3).
- View Article
- Google Scholar
29. Dave JA, Cohen K, Micklesfield LK, Maartens G, Levitt NS. Antiretroviral therapy, especially efavirenz, is associated with low bone mineral density in HIV-infected South Africans. PLoS One. 2015;10(12):e0144286. pmid:26633015
- View Article
- PubMed/NCBI
- Google Scholar
30. Biver E. Osteoporosis and HIV infection. Calcified Tissue Int. 2022;110(5):624–40.
- View Article
- Google Scholar
31. Moyle GJ, Hardy H, Farajallah A, McGrath SJ, Kaplita S, Ward D. Changes in bone mineral density after 96 weeks of treatment with atazanavir/ritonavir or lopinavir/ritonavir plus tenofovir DF/emtricitabine in treatment-naive patients with HIV-1 infection: the CASTLE body composition substudy. J Acquir Immune Defic Syndr. 2015;68(1):40–5. pmid:25296097
- View Article
- PubMed/NCBI
- Google Scholar
32. Brown TT, Moser C, Currier JS, Ribaudo HJ, Rothenberg J, Kelesidis T, et al. Changes in bone mineral density after initiation of antiretroviral treatment with tenofovir disoproxil fumarate/emtricitabine plus atazanavir/ritonavir, darunavir/ritonavir, or raltegravir. J Infect Dis. 2015;212(8):1241–9. pmid:25948863
- View Article
- PubMed/NCBI
- Google Scholar
33. Wang MW-H, Wei S, Faccio R, Takeshita S, Tebas P, Powderly WG, et al. The HIV protease inhibitor ritonavir blocks osteoclastogenesis and function by impairing RANKL-induced signaling. J Clin Invest. 2004;114(2):206–13. pmid:15254587
- View Article
- PubMed/NCBI
- Google Scholar
34. Bonfanti P, De Vito A, Ricci E, Menzaghi B, Orofino G, Squillace N, et al. Bone safety of dolutegravir-containing regimens in people living with HIV: results from a real-world cohort. Infect Drug Resist. 2020;13:2291–300. pmid:32765005
- View Article
- PubMed/NCBI
- Google Scholar
35. Jacobson DL, Lindsey JC, Coull BA, Mulligan K, Bhagwat P, Aldrovandi GM, et al. The association of fat and lean tissue with whole body and spine bone mineral density is modified by HIV status and sex in children and youth. Pediatr Infect Dis J. 2018;37(1):71–7. pmid:28817419
- View Article
- PubMed/NCBI
- Google Scholar
36. Wang Q, Alén M, Nicholson P, Suominen H, Koistinen A, Kröger H, et al. Weight-bearing, muscle loading and bone mineral accrual in pubertal girls--a 2-year longitudinal study. Bone. 2007;40(5):1196–202. pmid:17258519
- View Article
- PubMed/NCBI
- Google Scholar
37. Seeman E, Delmas PD. Bone quality--the material and structural basis of bone strength and fragility. N Engl J Med. 2006;354(21):2250–61. pmid:16723616
- View Article
- PubMed/NCBI
- Google Scholar
38. Chubb SAP, Vasikaran SD, Gillett MJ. Reference intervals for plasma β-CTX and P1NP in children: a systematic review and pooled estimates. Clin Biochem. 2023;118:110582. pmid:37187224
- View Article
- PubMed/NCBI
- Google Scholar
39. Geserick M, Vogel M, Eckelt F, Schlingmann M, Hiemisch A, Baber R, et al. Children and adolescents with obesity have reduced serum bone turnover markers and 25-hydroxyvitamin D but increased parathyroid hormone concentrations - Results derived from new pediatric reference ranges. Bone. 2020;132:115124. pmid:31830529
- View Article
- PubMed/NCBI
- Google Scholar
40. Shiau S, Yin MT, Strehlau R, Patel F, Mbete N, Kuhn L, et al. Decreased bone turnover in HIV-infected children on antiretroviral therapy. Arch Osteoporos. 2018;13(1):40. pmid:29623447
- View Article
- PubMed/NCBI
- Google Scholar
41. Winston A, Post FA, DeJesus E, Podzamczer D, Di Perri G, Estrada V, et al. Tenofovir alafenamide plus emtricitabine versus abacavir plus lamivudine for treatment of virologically suppressed HIV-1-infected adults: a randomised, double-blind, active-controlled, non-inferiority phase 3 trial. Lancet HIV. 2018;5(4):e162–71. pmid:29475804
- View Article
- PubMed/NCBI
- Google Scholar
42. Atencio P, Conesa-Buendía FM, Cabello-Ubeda A, Llamas-Granda P, Pérez-Tanoira R, Prieto-Pérez L, et al. Bone deleterious effects of different NRTIs in treatment-naïve HIV patients after 12 and 48 weeks of treatment. Curr HIV Res. 2021;19(5):434–47. pmid:34353266
- View Article
- PubMed/NCBI
- Google Scholar
43. Piloya TW, Bakeera-Kitaka S, Kisitu GP, Idro R, Cusick SE. Vitamin D status and associated factors among HIV-infected children and adolescents on antiretroviral therapy in Kampala, Uganda. PLoS One. 2021;16(6):e0253689. pmid:34166428
- View Article
- PubMed/NCBI
- Google Scholar
44. Bonjour JP, Carrie AL, Ferrari S, Clavien H, Slosman D, Theintz G, et al. Calcium-enriched foods and bone mass growth in prepubertal girls: a randomized, double-blind, placebo-controlled trial. J Clin Invest. 1997;99(6):1287–94. pmid:9077538
- View Article
- PubMed/NCBI
- Google Scholar
45. Nichols EK, Khatib IMD, Aburto NJ, Serdula MK, Scanlon KS, Wirth JP, et al. Vitamin D status and associated factors of deficiency among Jordanian children of preschool age. Eur J Clin Nutr. 2015;69(1):90–5. pmid:25117992
- View Article
- PubMed/NCBI
- Google Scholar
46. Rosengren BE, Bergman E, Karlsson J, Ahlborg H, Jehpsson L, Karlsson MK. Downturn in childhood bone mass: a cross-sectional study over four decades. JBMR Plus. 2021;6(1):e10564. pmid:35079676
- View Article
- PubMed/NCBI
- Google Scholar
47. Weaver CM, Gordon CM, Janz KF, Kalkwarf HJ, Lappe JM, Lewis R, et al. The National Osteoporosis Foundation’s position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations. Osteoporos Int. 2016;27(4):1281–386. pmid:26856587
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Wandeler G, Johnson LF, Egger M. Trends in life expectancy of HIV-positive adults on antiretroviral therapy across the globe: comparisons with general population. Curr Opin HIV AIDS. 2016;11(5):492–500. pmid:27254748
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Arpadi SM, Thurman CB, Patel F, Kaufman JJ, Strehlau R, Burke M, et al. Bone quality measured using calcaneal quantitative ultrasonography is reduced among children with HIV in Johannesburg, South Africa. J Pediatr. 2019;215:267–271.e2. pmid:31474425
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Mwaka ES, Munabi IG, Castelnuovo B, Kaimal A, Kasozi W, Kambugu A, et al. Low bone mass in people living with HIV on long-term anti-retroviral therapy: a single center study in Uganda. PLoS One. 2021;16(2):e0246389. pmid:33544754
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. Katzenstein TL, Wessman M, Moseholm E, Sandholdt H, Hansen ABE, Lebech AM. Prevalence of low bone mineral density among people living with HIV. Cogent Med. 2021;8(1):1920667.
View Article
Google Scholar

[14] View Article

[15] Google Scholar

[ref5] 5. DiMeglio LA, Wang J, Siberry GK, Miller TL, Geffner ME, Hazra R, et al. Bone mineral density in children and adolescents with perinatal HIV infection. AIDS. 2013;27(2):211–20. pmid:23032412
View Article
PubMed/NCBI
Google Scholar

[17] View Article

[18] PubMed/NCBI

[19] Google Scholar

[ref6] 6. Rukuni R, Rehman AM, Mukwasi-Kahari C, Madanhire T, Kowo-Nyakoko F, McHugh G, et al. Effect of HIV infection on growth and bone density in peripubertal children in the era of antiretroviral therapy: a cross-sectional study in Zimbabwe. Lancet Child Adolesc Health. 2021;5(8):569–81. pmid:34139202
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref7] 7. Puthanakit T, Saksawad R, Bunupuradah T, Wittawatmongkol O, Chuanjaroen T, Ubolyam S, et al. Prevalence and risk factors of low bone mineral density among perinatally HIV-infected Thai adolescents receiving antiretroviral therapy. J Acquir Immune Defic Syndr. 2012;61(4):477–83. pmid:22918157
View Article
PubMed/NCBI
Google Scholar

[25] View Article

[26] PubMed/NCBI

[27] Google Scholar

[ref8] 8. Alsaad LN, Akolaa EA, Muttappallymyalil J, Sreedharan J. Bone mineral density and its determinants: a systematic review of risk factors and prevention strategies. Biomed Pharmacol J. 2023;16(3):1791–6.
View Article
Google Scholar

[29] View Article

[30] Google Scholar

[ref9] 9. Duvivier C, Kolta S, Assoumou L, Ghosn J, Rozenberg S, Murphy RL, et al. Greater decrease in bone mineral density with protease inhibitor regimens compared with nonnucleoside reverse transcriptase inhibitor regimens in HIV-1 infected naive patients. AIDS. 2009;23(7):817–24. pmid:19363330
View Article
PubMed/NCBI
Google Scholar

[32] View Article

[33] PubMed/NCBI

[34] Google Scholar

[ref10] 10. Soininen S, Sidoroff V, Lindi V, Mahonen A, Kröger L, Kröger H, et al. Body fat mass, lean body mass and associated biomarkers as determinants of bone mineral density in children 6-8years of age - The Physical Activity and Nutrition in Children (PANIC) study. Bone. 2018;108:106–14. pmid:29307776
View Article
PubMed/NCBI
Google Scholar

[36] View Article

[37] PubMed/NCBI

[38] Google Scholar

[ref11] 11. Madeddu G, Spanu A, Solinas P, Babudieri S, Calia GM, Lovigu C, et al. Different impact of NNRTI and PI-including HAART on bone mineral density loss in HIV-infected patients. Eur Rev Med Pharmacol Sci. 2015;19(23):4576–89. pmid:26698255
View Article
PubMed/NCBI
Google Scholar

[40] View Article

[41] PubMed/NCBI

[42] Google Scholar

[ref12] 12. Komatsu A, Ikeda A, Kikuchi A, Minami C, Tan M, Matsushita S. Osteoporosis-related fractures in HIV-infected patients receiving long-term tenofovir disoproxil fumarate: an observational cohort study. Drug Saf. 2018;41(9):843–8. pmid:29623648
View Article
PubMed/NCBI
Google Scholar

[44] View Article

[45] PubMed/NCBI

[46] Google Scholar

[ref13] 13. Yoon B-H, Yu W. Clinical utility of biochemical marker of bone turnover: fracture risk prediction and bone healing. J Bone Metab. 2018;25(2):73–8. pmid:29900156
View Article
PubMed/NCBI
Google Scholar

[48] View Article

[49] PubMed/NCBI

[50] Google Scholar

[ref14] 14. Shen Y, Shiau S, Strehlau R, Burke M, Patel F, Johnson CT, et al. Persistently lower bone mass and bone turnover among South African children living with well controlled HIV. AIDS. 2021;35(13):2137–47. pmid:34127577
View Article
PubMed/NCBI
Google Scholar

[52] View Article

[53] PubMed/NCBI

[54] Google Scholar

[ref15] 15. Haskelberg H, Hoy JF, Amin J, Ebeling PR, Emery S, Carr A, et al. Changes in bone turnover and bone loss in HIV-infected patients changing treatment to tenofovir-emtricitabine or abacavir-lamivudine. PLoS One. 2012;7(6):e38377. pmid:22719882
View Article
PubMed/NCBI
Google Scholar

[56] View Article

[57] PubMed/NCBI

[58] Google Scholar

[ref16] 16. Podany AT, Bares SH, Havens J, Dyavar SR, O’Neill J, Lee S, et al. Plasma and intracellular pharmacokinetics of tenofovir in patients switched from tenofovir disoproxil fumarate to tenofovir alafenamide. AIDS. 2018;32(6):761–5. pmid:29334548
View Article
PubMed/NCBI
Google Scholar

[60] View Article

[61] PubMed/NCBI

[62] Google Scholar

[ref17] 17. Natukunda E, Gaur AH, Kosalaraksa P, Batra J, Rakhmanina N, Porter D, et al. Safety, efficacy, and pharmacokinetics of single-tablet elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide in virologically suppressed, HIV-infected children: a single-arm, open-label trial. Lancet Child Adolesc Health. 2017;1(1):27–34. pmid:30169223
View Article
PubMed/NCBI
Google Scholar

[64] View Article

[65] PubMed/NCBI

[66] Google Scholar

[ref18] 18. Gaur AH, Kizito H, Prasitsueubsai W, Rakhmanina N, Rassool M, Chakraborty R, et al. Safety, efficacy, and pharmacokinetics of a single-tablet regimen containing elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide in treatment-naive, HIV-infected adolescents: a single-arm, open-label trial. Lancet HIV. 2016;3(12):e561–8. pmid:27765666
View Article
PubMed/NCBI
Google Scholar

[68] View Article

[69] PubMed/NCBI

[70] Google Scholar

[ref19] 19. Post FA, Yazdanpanah Y, Schembri G, Lazzarin A, Reynes J, Maggiolo F, et al. Efficacy and safety of emtricitabine/tenofovir alafenamide (FTC/TAF) vs. emtricitabine/tenofovir disoproxil fumarate (FTC/TDF) as a backbone for treatment of HIV-1 infection in virologically suppressed adults: subgroup analysis by third agent of a randomized, double-blind, active-controlled phase 3 trial. HIV Clin Trials. 2017;18(3):135–40. pmid:28303753
View Article
PubMed/NCBI
Google Scholar

[72] View Article

[73] PubMed/NCBI

[74] Google Scholar

[ref20] 20. Liang X, Zhang H, Guo M, Zhao H, Yang D, Sun R, et al. Impact of different antiretroviral therapy regimens on bone mineral density in people living with HIV: a retrospective and longitudinal study in China. BMC Infect Dis. 2024;24(1):1400. pmid:39695982
View Article
PubMed/NCBI
Google Scholar

[76] View Article

[77] PubMed/NCBI

[78] Google Scholar

[ref21] 21. O’Rourke J, Townsend CL, Milanzi E, Collins IJ, Castro H, Judd A, et al. Effectiveness and safety of tenofovir alafenamide in children and adolescents living with HIV: a systematic review. J Int AIDS Soc. 2023;26(2):e26037. pmid:36823283
View Article
PubMed/NCBI
Google Scholar

[80] View Article

[81] PubMed/NCBI

[82] Google Scholar

[ref22] 22. Natukunda E, Szubert A, Otike C, Namyalo I, Nambi E, Bamford A, et al. Bone mineral density among children living with HIV failing first-line anti-retroviral therapy in Uganda: a sub-study of the CHAPAS-4 trial. PLoS One. 2023;18(7):e0288877. pmid:37471330
View Article
PubMed/NCBI
Google Scholar

[84] View Article

[85] PubMed/NCBI

[86] Google Scholar

[ref23] 23. Faulkner RA, Davison KS, Bailey DA, Mirwald RL, Baxter-Jones ADG. Size-corrected BMD decreases during peak linear growth: implications for fracture incidence during adolescence. J Bone Miner Res. 2006;21(12):1864–70. pmid:17002589
View Article
PubMed/NCBI
Google Scholar

[88] View Article

[89] PubMed/NCBI

[90] Google Scholar

[ref24] 24. Crabtree N, Ward K. Bone densitometry: current status and future perspective. Endocr Dev. 2015;28:72–83. pmid:26138836
View Article
PubMed/NCBI
Google Scholar

[92] View Article

[93] PubMed/NCBI

[94] Google Scholar

[ref25] 25. Zemel BS, Kalkwarf HJ, Gilsanz V, Lappe JM, Oberfield S, Shepherd JA, et al. Revised reference curves for bone mineral content and areal bone mineral density according to age and sex for black and non-black children: results of the bone mineral density in childhood study. J Clin Endocrinol Metab. 2011;96(10):3160–9. pmid:21917867
View Article
PubMed/NCBI
Google Scholar

[96] View Article

[97] PubMed/NCBI

[98] Google Scholar

[ref26] 26. ISCD. 2019 ISCD Official positions Pediatric. 2019. Available from: https://iscd.org/wp-content/uploads/2021/09/2019-Official-Positions-Pediatric-1.pdf
View Article
Google Scholar

[100] View Article

[101] Google Scholar

[ref27] 27. Abbexa - Antibodies, Proteins, ELISA kits. Abbexa.

[ref28] 28. Ahmed M, Mital D, Abubaker NE, Panourgia M, Owles H, Papadaki I. Bone health in people living with HIV/AIDS: an update of where we are and potential future strategies. Microorganisms. 2023;11(3).
View Article
Google Scholar

[104] View Article

[105] Google Scholar

[ref29] 29. Dave JA, Cohen K, Micklesfield LK, Maartens G, Levitt NS. Antiretroviral therapy, especially efavirenz, is associated with low bone mineral density in HIV-infected South Africans. PLoS One. 2015;10(12):e0144286. pmid:26633015
View Article
PubMed/NCBI
Google Scholar

[107] View Article

[108] PubMed/NCBI

[109] Google Scholar

[ref30] 30. Biver E. Osteoporosis and HIV infection. Calcified Tissue Int. 2022;110(5):624–40.
View Article
Google Scholar

[111] View Article

[112] Google Scholar

[ref31] 31. Moyle GJ, Hardy H, Farajallah A, McGrath SJ, Kaplita S, Ward D. Changes in bone mineral density after 96 weeks of treatment with atazanavir/ritonavir or lopinavir/ritonavir plus tenofovir DF/emtricitabine in treatment-naive patients with HIV-1 infection: the CASTLE body composition substudy. J Acquir Immune Defic Syndr. 2015;68(1):40–5. pmid:25296097
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref32] 32. Brown TT, Moser C, Currier JS, Ribaudo HJ, Rothenberg J, Kelesidis T, et al. Changes in bone mineral density after initiation of antiretroviral treatment with tenofovir disoproxil fumarate/emtricitabine plus atazanavir/ritonavir, darunavir/ritonavir, or raltegravir. J Infect Dis. 2015;212(8):1241–9. pmid:25948863
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref33] 33. Wang MW-H, Wei S, Faccio R, Takeshita S, Tebas P, Powderly WG, et al. The HIV protease inhibitor ritonavir blocks osteoclastogenesis and function by impairing RANKL-induced signaling. J Clin Invest. 2004;114(2):206–13. pmid:15254587
View Article
PubMed/NCBI
Google Scholar

[122] View Article

[123] PubMed/NCBI

[124] Google Scholar

[ref34] 34. Bonfanti P, De Vito A, Ricci E, Menzaghi B, Orofino G, Squillace N, et al. Bone safety of dolutegravir-containing regimens in people living with HIV: results from a real-world cohort. Infect Drug Resist. 2020;13:2291–300. pmid:32765005
View Article
PubMed/NCBI
Google Scholar

[126] View Article

[127] PubMed/NCBI

[128] Google Scholar

[ref35] 35. Jacobson DL, Lindsey JC, Coull BA, Mulligan K, Bhagwat P, Aldrovandi GM, et al. The association of fat and lean tissue with whole body and spine bone mineral density is modified by HIV status and sex in children and youth. Pediatr Infect Dis J. 2018;37(1):71–7. pmid:28817419
View Article
PubMed/NCBI
Google Scholar

[130] View Article

[131] PubMed/NCBI

[132] Google Scholar

[ref36] 36. Wang Q, Alén M, Nicholson P, Suominen H, Koistinen A, Kröger H, et al. Weight-bearing, muscle loading and bone mineral accrual in pubertal girls--a 2-year longitudinal study. Bone. 2007;40(5):1196–202. pmid:17258519
View Article
PubMed/NCBI
Google Scholar

[134] View Article

[135] PubMed/NCBI

[136] Google Scholar

[ref37] 37. Seeman E, Delmas PD. Bone quality--the material and structural basis of bone strength and fragility. N Engl J Med. 2006;354(21):2250–61. pmid:16723616
View Article
PubMed/NCBI
Google Scholar

[138] View Article

[139] PubMed/NCBI

[140] Google Scholar

[ref38] 38. Chubb SAP, Vasikaran SD, Gillett MJ. Reference intervals for plasma β-CTX and P1NP in children: a systematic review and pooled estimates. Clin Biochem. 2023;118:110582. pmid:37187224
View Article
PubMed/NCBI
Google Scholar

[142] View Article

[143] PubMed/NCBI

[144] Google Scholar

[ref39] 39. Geserick M, Vogel M, Eckelt F, Schlingmann M, Hiemisch A, Baber R, et al. Children and adolescents with obesity have reduced serum bone turnover markers and 25-hydroxyvitamin D but increased parathyroid hormone concentrations - Results derived from new pediatric reference ranges. Bone. 2020;132:115124. pmid:31830529
View Article
PubMed/NCBI
Google Scholar

[146] View Article

[147] PubMed/NCBI

[148] Google Scholar

[ref40] 40. Shiau S, Yin MT, Strehlau R, Patel F, Mbete N, Kuhn L, et al. Decreased bone turnover in HIV-infected children on antiretroviral therapy. Arch Osteoporos. 2018;13(1):40. pmid:29623447
View Article
PubMed/NCBI
Google Scholar

[150] View Article

[151] PubMed/NCBI

[152] Google Scholar

[ref41] 41. Winston A, Post FA, DeJesus E, Podzamczer D, Di Perri G, Estrada V, et al. Tenofovir alafenamide plus emtricitabine versus abacavir plus lamivudine for treatment of virologically suppressed HIV-1-infected adults: a randomised, double-blind, active-controlled, non-inferiority phase 3 trial. Lancet HIV. 2018;5(4):e162–71. pmid:29475804
View Article
PubMed/NCBI
Google Scholar

[154] View Article

[155] PubMed/NCBI

[156] Google Scholar

[ref42] 42. Atencio P, Conesa-Buendía FM, Cabello-Ubeda A, Llamas-Granda P, Pérez-Tanoira R, Prieto-Pérez L, et al. Bone deleterious effects of different NRTIs in treatment-naïve HIV patients after 12 and 48 weeks of treatment. Curr HIV Res. 2021;19(5):434–47. pmid:34353266
View Article
PubMed/NCBI
Google Scholar

[158] View Article

[159] PubMed/NCBI

[160] Google Scholar

[ref43] 43. Piloya TW, Bakeera-Kitaka S, Kisitu GP, Idro R, Cusick SE. Vitamin D status and associated factors among HIV-infected children and adolescents on antiretroviral therapy in Kampala, Uganda. PLoS One. 2021;16(6):e0253689. pmid:34166428
View Article
PubMed/NCBI
Google Scholar

[162] View Article

[163] PubMed/NCBI

[164] Google Scholar

[ref44] 44. Bonjour JP, Carrie AL, Ferrari S, Clavien H, Slosman D, Theintz G, et al. Calcium-enriched foods and bone mass growth in prepubertal girls: a randomized, double-blind, placebo-controlled trial. J Clin Invest. 1997;99(6):1287–94. pmid:9077538
View Article
PubMed/NCBI
Google Scholar

[166] View Article

[167] PubMed/NCBI

[168] Google Scholar

[ref45] 45. Nichols EK, Khatib IMD, Aburto NJ, Serdula MK, Scanlon KS, Wirth JP, et al. Vitamin D status and associated factors of deficiency among Jordanian children of preschool age. Eur J Clin Nutr. 2015;69(1):90–5. pmid:25117992
View Article
PubMed/NCBI
Google Scholar

[170] View Article

[171] PubMed/NCBI

[172] Google Scholar

[ref46] 46. Rosengren BE, Bergman E, Karlsson J, Ahlborg H, Jehpsson L, Karlsson MK. Downturn in childhood bone mass: a cross-sectional study over four decades. JBMR Plus. 2021;6(1):e10564. pmid:35079676
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref47] 47. Weaver CM, Gordon CM, Janz KF, Kalkwarf HJ, Lappe JM, Lewis R, et al. The National Osteoporosis Foundation’s position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations. Osteoporos Int. 2016;27(4):1281–386. pmid:26856587
View Article
PubMed/NCBI
Google Scholar

[178] View Article

[179] PubMed/NCBI

[180] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Ethics statement

Study design

Study population

Measurements

Statistical analysis

Results

Discussion

Supporting information

S1 Fig. Box plot of lumbar spine (LS) and total-body-less-head (TBLH) height-adjusted BMD Z-scores stratified by first-line ART regimen (EFV vs. NVP) at baseline.

S2 Fig. The boxplot illustrates the change in LS HA BMD and TBLH HA BMD Z-score changes over 96 weeks among participants previously on EFVor NVP-based first-line ART regimens.

S1 Table. Multivariable linear regression analysis identifying factors associated with a change in bone mineral density.

S2 Table. Multivariable linear regression analysis identifying factors associated with change in bone turnover markers.

Acknowledgments

References