There was no significant difference in TG levels between males and females. TG levels increased with age (P < 0.001). After adjusting for age, gender, site, season, and clinical indicators (including BMI, ALT, and Hgb), TG was independently and inversely associated with CD4 cell count and was most elevated in the lowest CD4 cell count category (P value for nonlinearity < 0.0001). TG levels increased at CD4 cell count levels below approximately 300 cells per cubic millimeter (Fig. 1B). There was a significant independent positive correlation between WHO stage and TG level (P < 0.001). In the lowest BMI category, the median TG was 127 mg/dL and decreased as the BMI increased (P < 0.001). There was a significant independent inverse relationship between TG and Hgb levels; more pronounced anemia (Hgb < 7.0 g/dL) was associated with higher TG levels (P < 0.001).
HDL levels were significantly lower in male versus female patients (P < 0.001). After adjusting for age, gender, site, season, and clinical indicators, HDL was independently positively associated with CD4 count (P value for nonlinearity < 0.0001) (Fig. 1B). WHO stage was inversely related to HDL. As the patient population progressed from stage I to stage IV, HDL decreased significantly (P ≤ 0.001). HDL was significantly correlated with BMI; the lowest HDL levels were seen in the lowest BMI category (P ≤ 0.005).
LDL was significantly lower in male patients versus female patients (P ≤ 0.001). As age increased, there was a significant increase in LDL (P = 0.037). After adjusting for age, gender, site, season, and clinical indicators, LDL was lowest in patients with BMI <17 and increased with higher BMI's (P ≤ 0.001). There was an independent positive association between LDL and CD4 cell count (P ≤ 0.002) and LDL and Hgb (P value < 0.001).
TC was significantly lower in male versus female patients (P ≤ 0.001). As age increased, there was a significant positive trend with increasing TC (P = 0.003). After adjusting for age, gender, site, season, and clinical indicators, the TC was lowest in patients with BMI <17 and increased at higher BMI's (P ≤ 0.001). TC increased with increasing CD4 cell count (P ≤ 0.001). WHO stage was independently inversely correlated with TC; as WHO stage increased from I to IV, TC decreased (P ≤ 0.001). Hgb was lower in patients with lower TC levels (P = 0.001).
Non-HDL was significantly lower in the male versus female patients (P ≤ 0.001).
As age increased, there was a significant positive trend (P = 0.001) with increasing non-HDL. After adjusting for age, gender, site, season, and clinical indicators, non-HDL trended up with increasing BMI (P ≤ 0.001). Hgb was lower in patients with lower non-HDL levels (P = 0.001). There was no significant relationship found between non-HDL and CD4 count or WHO stage.
In the largest study of HIV-infected ART-naive patients in the developing world to date, we observed a high prevalence of dyslipidemia and noted significant differences in the type and extent of dyslipidemia based on the degree of immunosuppression. In our cohort of HIV-infected ART-naive patients, a large percentage met criteria for dyslipidemia, which was significantly higher than that observed in HIV-negative patients from other Tanzanian settings.17 In studies from developed countries, HIV-infected patients seem to be at significantly higher risk of CVD than noninfected individuals.18-20 In the DAD cohort, where elevated rates of dyslipidemia were evident but a different definition of dyslipidemia was used, a 26% increase in risk in the frequency of myocardial infarction (MI) was observed per year of exposure to ART (P < 0.001). The increased risk of MI was attenuated controlling for dyslipidemia, suggesting dyslipidemia contributed in part to the increased MI rates.19 Considering the increasing rates of obesity, diabetes and other CVD risk factors observed among HIV-noninfected persons in RLS,21-24 similar trends in CVD morbidity and mortality would be expected to occur among HIV-infected patients in RLS as ART rollout continues.
In our cohort, the majority of dyslipidemia was characterized by abnormal HDL or TG levels, with normal or low TC, non-HDL, and LDL levels as previously observed in other treatment-naive HIV-infected populations.3,4,5,25,26 It should be noted that the pattern of dyslipidemia that has been observed in ART-naive patients is different from the pattern seen in ART-treated individuals, who tend to have higher levels of LDL, non-HDL, and TC. Data on dyslipidemia among HIV-infected patients in RLS is scarce. In a study by Manuthu et al,8 which compared lipid values among 295 ART-naive and treated patients in Kenya, the overall prevalence of dyslipidemia was 63.1%. The majority of dyslipidemia was characterized by high TG (22.5%) and low HDL (51.3%) levels in ART-naive patients. In 2 other recent studies from Rwanda and Uganda, a similar pattern was found.9,10 The clinical relevance of this pattern of dyslipidemia lies in the potential risk it confers for the development of premature CVD.10
We observed a distinct pattern of rising TG and decreasing HDL, LDL, and TC levels with progressive immune dysfunction. This pattern of dyslipidemia, and its strong correlation with disease stage, has also been observed in other treatment-naive populations in both developed and developing countries.25-27 In a study by Feingold et al,26 hypertriglyceridemia was also found to be associated with disease progression and HIV viremia. Recently, studies suggest that low CD4 count is associated with atherosclerotic disease and increased MI rates among HIV patients.28-30
The pathogenesis underlying the association between immune dysfunction and dyslipidemia remains unclear. Hypertriglyceridemia may be related to inflammation and subsequent cytokine effects seen in advanced disease.25 Hypertriglyceridemia may also be related to decreased hepatic clearance possibly related to the role of apolipoprotein E.4,25,31 Rose et al32 has proposed that low HDL levels may be linked to an HIV-secreted soluble transactivator protein (Tat) in the plasma causing reduced cholesterol mobilization from hepatic cells. Finally, HDL hepatic metabolism may be redirected towards apo-B-containing lipoproteins by factors related to HIV infection and inflammation.27,32
This study had several limitations. It was a retrospective analysis that did not include a negative control group and, therefore cannot provide proof of causality between HIV, immunosuppression, and the development of dyslipidemia. We were limited in fully assessing CVD risk because our database lacked detailed information regarding the patients' medical, social, nutritional, and family history. Another limitation was that lipid samples were nonfasting. As a result, TG levels may be falsely elevated and thus the prevalence of dyslipidemia may be less than we observed. If the triglyceride measures over 400 mg/dL, the LDL sample, which is calculated indirectly by the Friedewald equation, will not be completely accurate.33 However, TG levels were over 400 mg/dL in only 1.08% of patients. To gain additional insight into this analysis in the setting of such limitations, we also chose to report non-HDL cholesterol which provides an assessment of all apolipoprotein B-containing lipoproteins considered to be atherogenic and improves accuracy in nonfasting lipid samples.34 The prevalence of increased non-HDL cholesterol was less than for the other lipid parameters. A smaller percentage of patients had all lipid parameters measured due to differing practice patterns among the physicians who cared for patients in this cohort, but full data were available in a large number of patients. Despite these limitations, this study provides a detailed analysis of dyslipidemia in very large cohort of HIV-infected patients in a RLS.
In summary, a high prevalence of dyslipidemia was seen among ART-naive HIV-positive patients in this cohort. Patients with the most advanced HIV disease had significantly elevated TG and low HDL levels, a pattern that may contribute to increased risk of CVD. These findings underline the importance of establishing a patient's CVD risk factor profile before ART initiation because subsequent ART choice depends on this.35 Further study is required to assess the impact of ART on CVD disease and its risk factors in the RLS. Given the increased prevalence of dyslipidemia, CVD risk prevention counseling and management should be integrated into HIV care in RLS.
1. UNAIDS, World Health Organization (WHO). AIDS Epidemic Update. UNAIDS. Geneva, Switzerland: WHO; 2009.
2. The Writing Committee of the DAD Study Group. Cardio and cerebrovascular events in HIV infected persons. AIDS
3. Riddler SA, Smit E, Cole SR, et al. Impact of HIV infection and HAART on serum lipids in men. JAMA
4. Grunfeld C, Doerrler W, Pang M, et al. Abnormalities of apolipoprotein E in the acquired immunodeficiency syndrome. J Clin Endocrinol Metab
5. Hellerstein MK, Grunfeld C, Wu K, et al. Increased de novo hepatic lipogenesis in human immunodeficiency virus infection. J Clin Endocrinol Metab
6. Fourie CM, Van Rooyen JM, Kruger A, et al. Lipid abnormalities in a Never-treated HIV-1 subtype C-Infected african population. Lipids
7. Pujari SN, Dravid A, Naik E, et al. Lipodystrophy and dyslipidemia
among patients taking firstline, World Health Organization-recommended highly active antiretroviral therapy regimens in western India. J Acquir Immune Defic Syndr
8. Manuthu EM, Joshi, MD, Lule GN, et al. Prevalence of dyslipidemia
in HIV infected patients. East Afr Med J
9. Buchacz K, Weidle PJ, Moore D, et al. Changes in lipid profile over 24 months among adults on first-line highly active antiretroviral therapy in the home based aids care program in rural Uganda. J Acquir Immune Defic Syndr
10. Anastos K, Ndamage F, Lu D, et al. Lipoprotein levels and cardiovascular risk in HIVinfected and uninfected Rwandan women. AIDS Res Ther
. 2010; 7:1-6.
11. Hemelaar J, Gouws E, Ghys PD, et al. Global and regional distribution of HIV-1 genetic subtypes and recombinants in 2004. AIDS
Commission for AIDS (TACAIDS). Tanzania
HIV/AIDS and Malaria Indicator Survey 2007-2008: Preliminary Report. July 2008.
13. The United Republic of Tanzania
, Ministry of Health and Social Welfare. National Guidelines for the Management of HIV and AIDS, National AIDS Control Programme (NACP). 3rd ed. 2008.
14. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem
15. NCEP Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation
16. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika
17. Swai AB, McLarty DG, Kitange HM, et al. Low prevalence of risk factors for coronary heart disease in rural Tanzania
. Int J Epidemiol
18. Triant VA, Lee H, Hadigan C, et al. Increased acute myocardial infarction rates and cardiovascular risk factors among patients with Human Immunodeficiency Virus disease. J Clin Endocrinol Metab
. 2007;92:2506. E-pub: April 24, 2007.
19. Friis-Moller N, Sabin CA, Weber R, et al. Data Collection on Adverse Events of Anti-HIV Drugs (DAD) Study Group 2003 Combination antiretroviral therapy and the risk of myocardial infarction. N Engl J Med
20. Mary-Krause M, Cotte L, Simon A, et al. Clinical Epidemiology Group from the French Hospital Database Increased risk of myocardial infarction with duration of protease inhibitor therapy in HIV-infected men. AIDS
21. World Health Organization (WHO). Mortality Report Cause of Death. Geneva, Switzerland: WHO; 2007:1-250.
22. Wild S, Roglic G, Green A, et al. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care
23. Stewart S, Wilkinson D, Becker A, et al. Mapping the Emergence of Heart Disease in a Black Urban Population in Africa: The heart of Soweto Study. Int J Cardiol
24. Akinboboye O, Idris O, Akinkugbe O. Trends in coronary artery disease and associated risk factors in Sub Saharan Africans. J Hum Hypertens
25. Grunfeld C, Kotler DP, Shigenaga JK, et al. Circulating interferon-alpha levels and hypertriglyceridemia in the acquired immunodeficiency syndrome AIDS. Am J Med
26. Feingold KR, Krauss RM, Pang M, et al. The hypertriglyceridemia of acquired immunodeficiency syndrome is associated with an increased prevalence of LDL subclass B. J Clin Endocrinol Metab
27. Shor-Posner G, Basit A, Lu Y, et al. Hypocholesterolemia is associated with immune dysfunction in early human immunodeficiency virus-1 infection. Am J Med
28. Kaplan RC, Kingsley LA, Gange SJ, et al. Low CD4+ T-cell count as a major atherosclerosis risk factor in HIV-infected women and men. AIDS
29. Lichtenstein KA, Armon C, Buchacz K, et al. Initiation of antiretroviral therapy at CD4 cell counts ≥350 cells/mm3
does not increase incidence or risk of peripheral neuropathy, anemia, or renal insufficiency. J Acquir Immune Defic Syndr
30. Triant VA, Regan S, Lee H, et al. Association of immunologic and virologic factors with myocardial infarction rates in a US healthcare system. J Acquir Immune Defic Syndr
. 2010. E-pub ahead of print.
31. Grunfeld C, Pang M, Doerrler W, et al. Lipids, lipoprotein, triglyceride clearance and cytokines in HIV/AIDS. J Clin Endocrinol Metab
32. Rose H, Hoy J, Woolley I, et al. HIV infection and high density lipoprotein metabolism. Atherosclerosis
33. McNamara JR, Cohn JS, Wilson PW, et al. Calculated values for low density lipoprotein cholesterol in the assessment of lipid abnormalities and coronary disease risk. Clin Chem
34. Lu W, Resnick HE, Jabionski KA, et al. Non-HDL Cholesterol as a predictor of cardiovascular disease
in Type 2 Diabetes: the Strong Heart Study. Diabetes Care
35. van Leth F, Phanuphak P, Stroes E, et al. Nevirapine and efavirenz elicit different changes in lipid profiles in antiretroviral-therapy-naive patients infected with HIV-1. PLoS Med
36. Govindarajulu US, Malloy EJ, Ganguli B, et al. The Comparison of Alternative Smoothing Methods for Fitting Non-Linear Exposure-Response Relationships with Cox Models in a Simulation Study. Int J Biostat
Keywords:© 2011 Lippincott Williams & Wilkins, Inc.
ART-naive; cardiovascular disease; dyslipidemia; HIV positive; Tanzania