Abstract
Background
Children living with HIV (CLHIV) on prolonged antiretroviral therapy (ART) are at risk for lipid and glucose abnormalities. Prevalence and associated factors were assessed in a multicentre, Asian longitudinal paediatric cohort.
Methods
CLHIV were considered to have lipid or glucose abnormalities if they had total cholesterol ≥200 mg/dL, high-density lipoprotein (HDL) ≤35 mg/dL, low-density lipoprotein (LDL) ≥100 mg/dL, triglycerides (TG) ≥110 mg/dL, or fasting glucose >110 mg/dL. Factors associated with lipid and glucose abnormalities were assessed by logistic regression.
Results
Of 951 CLHIV, 52% were male with a median age of 8.0 (interquartile range [IQR] 5.0–12.0) years at ART start and 15.0 (IQR 12.0–18.0) years at their last clinic visit. 89% acquired HIV perinatally, and 30% had ever used protease inhibitors (PIs). Overall, 225 (24%) had hypercholesterolemia, 105 (27%) low HDL, 213 (58%) high LDL, 369 (54%) hypertriglyceridemia, and 130 (17%) hyperglycemia. Hypercholesterolemia was more likely among females (versus males, aOR 1.93, 95% CI 1.40–2.67). Current PIs use was associated with hypercholesterolemia (current use: aOR 1.54, 95% CI 1.09–2.20); low HDL (current use: aOR 3.16, 95% CI 1.94–5.15; prior use: aOR 10.55, 95% CI 2.53–43.95); hypertriglyceridemia (current use: aOR 3.90, 95% CI 2.65–5.74; prior use: aOR 2.89, 95% CI 1.31–6.39); high LDL (current use: aOR 1.74, 95% CI 1.09–2.76); and hyperglycemia (prior use: aOR 2.43, 95% CI 1.42–4.18).
Conclusion
More than half and one-fifth of CLHIV have dyslipidemia and hyperglycemia, respectively. Routine paediatric HIV care should include metabolic monitoring. The association between PIs use and dyslipidemia emphasizes the importance of rapidly transitioning to integrase inhibitor-containing regimens.
Introduction
In 2020, there were an estimated 1.7 million children below 15 years of age living with HIV globally, with 54% receiving antiretroviral therapy (ART).1,2 Long-term studies on children living with HIV (CLHIV) in Asian and African countries have shown that lipid abnormalities occur among both ART-naïve children and those on combination ART (cART), highlighting the importance of regular monitoring for lipid abnormalities to assess risks for early cardiovascular events.3–5
As more children in low- and middle-income countries fail first-line non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens and are switched to second-line protease inhibitors (PIs), lipid and glucose abnormalities are likely to become more prevalent. However, there are limited resources in these contexts to include these tests in routine pediatric HIV care, missing an opportunity to identify associated risks and guide clinical and dietary interventions.3,5–6 Our study aimed to evaluate the prevalence of lipid and glucose abnormalities, and associated factors among CLHIV in the Asian region.
Methods
Study populations
We conducted a cross-sectional analysis using the TREAT Asia pediatric HIV Observational Database (TApHOD) study of IeDEA Asia-Pacific, an observational cohort including data of 7,385 children and adolescents living with HIV from eighteen clinical centres across six countries: Cambodia, India, Indonesia, Malaysia, Thailand, and Vietnam. The study structure and methods have been described in detail elsewhere. 7
We included CLHIV who initiated cART after 1 January 2008 and had at least one lipid or glucose measurement available between June 2015 and March 2020. We evaluated and defined four lipid abnormality outcomes: total cholesterol ≥200 mg/dL, high-density lipoprotein (HDL) ≤35 mg/dL, triglyceride ≥110 mg/dL, and low-density lipoprotein (LDL) ≥100 mg/dL. 8 A glucose abnormality was defined as fasting glucose >110 mg/dL. All lipid and glucose values were obtained after fasting for at least 6–8 h. In order to look at the prevalence of lipid or glucose abnormalities in our study population, we included those who had these outcomes at cART initiation. If a patient had multiple occurrences of the same outcome over the study period, only the first outcome was considered.
Statistical analysis
Patients included in the study were followed from the start of combination antiretroviral therapy (cART) till the date of first outcome for those with an outcome or date of death, date transferred, or last clinic visit date for those who did not have an outcome. Prevalence data were analyzed descriptively, with the denominator being the total number of test results available for each outcome. Factors associated with each lipid and glucose abnormalities were analyzed using four separate logistic regression models. The SAS program for the 2000 US Centers for Disease Control (CDC) growth charts for children up to 20 years of age was used to calculate the age standardized z-score for body mass index (BMI). 9 The z-scores calculated were grouped into BMI groups defined by the CDC guidelines. 10 PI regimen at the time of outcome was categorized as “never exposed to protease inhibitors” if they were never exposed to PIs, “prior use” if patients had stopped PIs more than 2 weeks before the test, and “current use” if patients were currently on PIs or stopped not longer than 2 weeks before the test date. Covariates with p < 0.05 were considered significant in the multivariate model.
Results
Characteristics of children living with HIV at the time of cART initiation.
Note.
- n: number with test; IQR: interquartile range; ART: antiretroviral therapy; cART: three or more antiretrovirals; NNRTI: non-nucleoside reverse transcriptase inhibitor; PI: protease inhibitor; mono/dual: single or two drugs; ABC: abacavir; 3 TC: lamivudine; NVP: nevirapine; TDF: tenofovir disoproxil fumarate; FTC: emtricitabine; EFV: efavirenz; AZT: zidovudine; LPV/r: lopinavir/ritonavir; EVG: elvitegravir; COBI: cobicistat.
- Data are presented as n (%) unless otherwise noted.
- Age standardized z-scores for BMI were obtained using the US CDC z-scores for BMI for ages 2–20 years (https://www.cdc.gov/growthcharts/zscore.htm).
- Median cART duration (years) presented from cART start to last available measurement for those patients with total cholesterol, HDL, LDL, triglycerides, and glucose measurements within normal limits, and from cART start to date of lipid or glucose abnormality for those patients who had these outcomes.
At the last clinic visit, this study population had a median age of 15.0 years (IQR 12.0–18.0). 70% were on an NNRTI regimen, 23% on a PI regimen, and 7% were on regimens that did not contain NNRTIs or PIs. The median duration of PI exposure was 4.0 (IQR 2.2–6.6) years per patient, and 30% were ever exposed to regimens containing PIs. Of the total 951 children included, 711 remained in active follow, 18 patients died, and 240 patients became lost to follow-up.
Of this study population, 54% (510/951 participants) had one or more lipid abnormalities. Total cholesterol measurements were available for 919 CLHIV, of whom 225 (24%) had hypercholesterolemia (Table 1). Hypercholesterolemia was more likely to occur among females (adjusted odds ratio [aOR] 1.93, 95% CI 1.40–2.67, p < 0.001) compared to males, those currently using PIs (aOR 1.54, 95% CI 1.09–2.20, p = 0.016) compared to those never exposed to a PI, and those in Malaysia (aOR 2.08, 95% CI 1.32–3.26, p = 0.001) compared to those in Thailand. Hypercholesterolemia was less likely among those in India (aOR 0.47, 95% CI 0.27–0.58, p = 0.007) and Vietnam (aOR 0.49, 95% CI 0.33–0.75, p = 0.001) (Figure 1(a)). Factors associated with lipid and glucose outcomes in children living with HIV. (a) Factors associated with hypercholesterolemia. (b) Factors associated with low HDL outcomes. (c) Factors associated with hypertriglyceridemia. (d) Factors associated with high LDL outcomes. (e) Factors associated with hyperglycemia. Hypercholesterolemia was defined as a total cholesterol level ≥200 mg/dL, low HDL was defined as level <35 mg/dL, high LDL was defined as level ≥100 mg/dL, hypertriglyceridemia was defined as a TG level ≥110 mg/dL, and high fasting glucose was defined as level >110 mg/dL.
A total of 385 CLHIV had an HDL test, of whom 105 (27%) had low HDL (Table 1). Participants aged ≥10 years were more likely than those aged 3–4 years to have low HDL (5–9 years: aOR 2.24, 95% CI 1.23–4.79, p = 0.011; ≥15 years: aOR 3.85, 95% CI 1.52–9.78, p = 0.005). Those ever exposed to PIs (current use: aOR 3.16, 95% CI 1.94–5.15, p < 0.001; prior use: aOR 10.55, 95% CI 2.53–43.95, p = 0.001) were more likely to experience a low HDL compared to those never exposed to PIs (Figure 1(b)).
There were 682 CLHIV with a triglyceride test, of whom 369 (54%) had hypertriglyceridemia (Table 1). Hypertriglyceridemia was more common in Malaysia than Thailand (aOR 2.41, 95% CI 1.45–4.02, p = 0.001) and those who had current or prior use of PIs (current use: aOR 3.9, 95% CI 2.65–5.47, p < 0.001; prior use: aOR 2.89, 95% CI 1.31–6.39, p = 0.009). Older adolescents had a lower risk of hypertriglyceridemia than younger children (≥15 years versus 3–4 years; aOR 0.34, 95% CI 0.16–0.70, p = 0.004) (Figure 1(c)).
Of the 365 CLHIV with at least one LDL test available, 213 (58%) had high LDL (Table 1). Those from Malaysia compared to Thailand (aOR 2.93, 95% CI 1.69–5.08, p < 0.001) and those on current PI use compared to those never used PIs (aOR 1.74, 95% CI 1.09–2.76, p = 0.019) were more likely to have high LDL (Figure 1(d)).
Of the 756 who had at least one fasting glucose test, 130 (17%) had hyperglycemia (Table 1). Hyperglycemia was likely among those from India and Malaysia (India: aOR 4.18, 95% CI 2.47–7.08, p < 0.001); Malaysia: aOR 2.25, 95% CI 1.08–4.67, p = 0.03) compared to those from Thailand, and among CLHIV who previously used PIs (aOR 2.43, 95% CI 1.42–4.18, p = 0.001) compared to those who never used PIs (Figure 1(e)).
Discussion
There was a high prevalence of dyslipidemia among our cohort of Asian CLHIV with primarily perinatally acquired HIV infection. Among those tested, about one-fourth had hyper-cholesterol or low HDL, and over half had hypertriglyceridemia or high LDL; with 17% who had increased fasting glucose levels. Current or prior PI use was associated with abnormal lipid profiles, and prior PI use was associated with hyperglycemia.
Our findings are comparable to other studies of CLHIV in low- and middle-income countries.6,11–13 A study by Mandal A et al. 11 among 81 children in North India found 38% had dyslipidemia, 15% had hypercholesterolemia, 3.7% had low HDL, 22% had hypertriglyceridemia, and 9.9% had high LDL. No clinically significant risk factors for dyslipidemia were identified. Sonego M et al. 12 study on dyslipidemia among 173 Salvadoran CLHIV whose mean age was 10 years found 14.5% had hypercholesterolemia, 22% had low HDL, 48% had hypertriglyceridemia, and 9.8% had high LDL. Children on PIs were more likely to have hypertriglyceridemia and hypercholesterolemia than those not receiving PIs. Similar findings were found by Irira ME et al. 13 in 260 Tanzanian CLHIV with a median age 3 years, of whom 46.5% had dyslipidemia, 11% had hypercholesterolemia, 23% had low HDL, 12% had hypertriglyceridemia, and 7.7% had had high LDL. In this study, current use of a PI was also associated with dyslipidemia. Children in our study who were 15 years and older had lower rates of hypertriglyceridemia than those who were 3–4 years old. The reason for this reduced effect among older kids is unclear, however, it is possible that the disproportionate sample size between the two age groups, and the possibility of testing on samples taken without fasting, may cause this effect. 14 We observed the exposure period of 2 weeks or greater to PIs to be associated with hyperglycemia. This is comparable to a study in Nigeria which found the median ART duration among those with impaired fasting glucose was longer than those with normal glucose levels. 15
Our cohort was larger than these, and we observed a higher prevalence of dyslipidemia and strong association between PI exposure and low HDL and hypertriglyceridemia. Collectively, these findings highlight the need for close clinical and laboratory monitoring especially during PI therapy to help improve CLHIV’s lipid levels, as well as the need to more rapidly transition to the integrase inhibitor class of antiretrovirals (i.e., dolutegravir), as has been recommended by the World Health Organization.
Our study was limited by inconsistencies in the frequency of lipid and glucose monitoring across our study sites, which may have been biased towards CLHIV on PIs. Although HDL and LDL measurements were less frequently obtained, 97% of CLHIV had total cholesterol and 79% had fasting glucose tests. Additionally, the CLHIV in the study had varying lengths of time on cART, with those in the earliest-treated groups potentially exposed to PIs known to have more serious dyslipidemic side effects than current drugs (e.g., indinavir versus lopinavir). Nevertheless, it was notable that the associations between dyslipidemia and PI exposure persisted in those with prior use. Furthermore, HIV viral load measurements were inconsistently collected in the cohort leading to high proportion of missing. Due to this, HIV viral load was presented at cART initiation for those available and was not included in the multivariate analysis. Therefore, we were unable to confirm if HIV viremia is the factor associated with low HDL and hypertriglyceridemia as found in other studies.5,16–18 Furthermore, the nature of this study design and analysis do not allow us to assess the duration of the lipid and glucose abnormalities, nor to assume causality. Although we have adjusted for major confounders, residual confounding (e.g., around the use of lipid-lowering medication, disease severity influencing cART selection) cannot be excluded due to the observational nature of the study and data limitations.
Following timely introduction and sustained treatment with cART, children with perinatally acquired HIV infection are living longer lives. Our results highlight the need to routinely monitor their risks for non-communicable diseases that could develop sooner than their HIV-negative peers, particularly cardio-metabolic disease. Lipid and glucose monitoring should remain a priority because CLHIV age into adolescence and adulthood.19,20 Longitudinal cohort analyses can evaluate long-term trends in HIV treatment outcomes but are most informative when comprehensive monitoring data are available.
Footnotes
Acknowledgements
The authors wish to thank the children and staff at the participating centres who have given their time so generously during the course of this study. The authors also thank Annette Sohn for her review of the manuscript.
The TREAT Asia Pediatric HIV Network:
V Khol, O Vichea, C Pov, National Centre for HIV/AIDS, Dermatology and STDs, Phnom Penh, Cambodia; J Tucker, New Hope for Cambodian Children, Phnom Penh, Cambodia; N Kumarasamy, C Ezhilarasi, VHS-Infectious Diseases Medical Centre, Chennai Antiviral Research and Treatment Clinical Research Site (CART CRS), Voluntary Health Services, Chennai, India; A Kinikar, V Mave, S Nimkar, BJ Medical College and Sassoon General Hospitals, Maharashtra, India; DK Wati, D Vedaswari, IB Ramajaya, Prof. Dr. I.G.N.G Ngoerah Hospital, Udayana University, Bali, Indonesia; N Kurniati, D Muktiarti, Cipto Mangunkusumo – Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia; SM Fong, M Lim, F Daut, Hospital Likas, Kota Kinabalu, Malaysia; NK Nik Yusoff, P Mohamad, Hospital Raja Perempuan Zainab II, Kelantan, Malaysia; TJ Mohamed, MR Drawis, Department of Pediatrics, Women and Children Hospital Kuala Lumpur (WCHKL), Kuala Lumpur, Malaysia; R Nallusamy, KC Chan, Penang Hospital, Penang, Malaysia; T Sudjaritruk, V Sirisanthana, L Aurpibul, Department of Pediatrics, Faculty of Medicine, and Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand; P Ounchanum, R Hansudewechakul, S Denjanta, A Kongphonoi, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; P Lumbiganon, P Kosalaraksa, P Tharnprisan, T Udomphanit, Division of Infectious Diseases, Department of Pediatrics, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; T Puthanakit, S Anugulruengkit, W Jantarabenjakul, R Nadsasarn, Department of Pediatrics and Center of Excellence for Pediatric Infectious Diseases and Vaccines, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; K Chokephaibulkit, K Lapphra, W Phongsamart, S Sricharoenchai, Department of Pediatrics, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand; QT Du, KH Truong, CH Nguyen, Children’s Hospital 1, Ho Chi Minh City, Vietnam; QD Nguyen, NM Nguyen, VC Do, VT An, YDH Nguyen, TLT Huynh, LTT Van, Children’s Hospital 2, Ho Chi Minh City, Vietnam; LV Nguyen, DM Trang, HTT Tran, TTT Giang, National Hospital of Pediatrics, Hanoi, Vietnam; ON Le, Worldwide Orphans Foundation, Ho Chi Minh City, Vietnam; AH Sohn, JL Ross, T Suwanlerk, TREAT Asia/amfAR - The Foundation for AIDS Research, Bangkok, Thailand; MG Law, A Kariminia, The Kirby Institute, UNSW Australia, Sydney, Australia.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the The TREAT Asia Pediatric HIV Observational Database which is an initiative of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the US National Institutes of Health’s National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Cancer Institute, National Institute of Mental Health, National Institute on Drug Abuse, the National Heart, Lung, and Blood Institute, the National Institute on Alcohol Abuse and Alcoholism, the National Institute of Diabetes and Digestive and Kidney Diseases, and the Fogarty International Center, as part of the International Epidemiology Databases to Evaluate AIDS (IeDEA; U01AI069907). The Kirby Institute is funded by the Australian Government Department of Health and Ageing and is affiliated with the Faculty of Medicine, UNSW Australia. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the governments or institutions mentioned above.
