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Hypertension and immune activation in antiretroviral therapy naïve people living with human immunodeficiency virus

Abstract

Background

The pathogenesis of hypertension (HTN) in people living with HIV/AIDS (PLHIV) is complex and remains not fully understood. Chronic immune activation (IA) is postulated to be one of the culprits. This notion is derived from studies in HIV-uninfected populations and/or animals while data on HTN and how it relates to IA in PLHIV remains scarce. We determined the relationship between HTN and IA among antiretroviral therapy (ART) naïve PLHIV.

Methods

We analysed baseline data of 365 out of 430 clinical trial participants whose main aim was to investigate the effect of low-dose aspirin on HIV disease progression in PLHIV starting ART. Soluble CD14 (sCD14), T cells co-expressing CD38 and HLA-DR, and PD-1 were the IA and exhaustion markers, respectively studied and were analysed by flow cytometry. Mann-Whitney U-test was used for comparison of the markers by HTN status. A robust Poisson regression model was used to determine the predictors for HTN.

Results

A quarter of the 365 were hypertensive (25.3%, 95% CI 20.9–29.8%), and, had higher median (IQR) body mass index (kg/m2) (23.4 (19.6, 28.0) versus 21.9 (19.3, 25.1)) and lower median (IQR) estimated glomerular filtration rate (mL/min/1.73m2) (101.2 (79.4, 126.9) versus 113.6 (92.7, 138.8)) than normotensive participants (p < 0.05). Participants with HTN had higher median frequencies of all markers of IA and exhaustion but lower sCD14 (p > 0.05). None of these markers significantly predicted the occurrence of HTN.

Conclusion

Studied markers of IA and exhaustion were higher in PLHIV with HTN than those without but were unpredictive of HTN. Larger multicentre studies with a wider range of markers are needed to confirm the role of IA in HIV-associated HTN.

Peer Review reports

Introduction

Non-AIDS complications such as cardiovascular diseases (CVDs) have become important causes of morbidity and mortality among people living with HIV/AIDS (PLHIV) in the antiretroviral therapy (ART) era, globally and in Africa [1,2,3].

Of the CVDs, hypertension (HTN) is of paramount importance not only as a CVD but also as a topmost risk factor for other CVDs. In PLHIV, HTN is an important contributor to cardiovascular (CV) illness and deaths. Western literature shows that the risk for CV events and deaths from all causes is higher in adult hypertensive PLHIV than in adult non-hypertensive PLHIV and adult hypertensives in the general population [4,5,6]. Furthermore, the risk for incident acute myocardial infarction (AMI) is higher in hypertensive PLHIV than in hypertensive HIV- uninfected population [4]. However, there is limited data on the impact of HTN on CVDs and mortality among PLHIV in the African population. A study conducted in Kenya among PLHIV revealed that men with HTN, but without advanced HIV disease, had a higher mortality risk compared to HIV- infected men who were not hypertensive [7].

Data from many parts of the globe including Africa show that the prevalence of HTN in PLHIV is high and is increasing where up to a quarter of PLHIV irrespective of antiretroviral therapy (ART) status have HTN [8]. Although the prevalence of HTN in HIV-uninfected population and/or ART exposed PLHIV is higher than in ART naïve PLHIV [8,9,10,11,12], there is evidence to show that HTN also is a problem in ART naïve PLHIV. Indeed, a study conducted in Cameroon has shown HTN to be more prevalent in ART naïve PLHIV than in ART-exposed PLHIV and the HIV-uninfected population [9]. A recent review has reported that 12.7% of ART naïve PLHIV in the world have HTN [8]. In Sub-Saharan Africa (SSA), prevalence of HTN, up to 41%, in ART naïve PLHIV has been reported [9]. Tanzania too, has a high burden of HTN among ART naïve PLHIV ranging from 5.3 to 24.8% [10, 11, 13,14,15,16].

Many factors contribute to HIV-associated HTN, and these may partly explain the conflicting data on the prevalence of HTN in the literature between ART-exposed and ART naïve PLHIV. ART may have a role in the aetiology of HIV-associated HTN. For example, dolutegravir (DTG)-based regimens (which are currently the first-line choice for HIV- infection in most of SSA including Tanzania) have been associated with HTN [17, 18]. This is alarming because ART naïve PLHIV are initiated on a lifelong treatment with ART and hence will be likely faced with more HTN in the future.

The underlying mechanism behind HIV-associated HTN may be complex and remains poorly understood. Apart from ART, pathophysiologic mechanisms for HIV- associated HTN including microbial translocation, immune suppression/ reconstitution, and chronic immune activation (IA) [9, 19] have been postulated.

Chronic IA appears to play a central role in the pathogenesis of HIV- associated HTN. ART naïve PLHIV have higher levels of chronic IA than HIV-uninfected and ART exposed population [20, 21]. Furthermore, the levels of IA are higher in ART naïve and do not normalize even with successful ART [20,21,22,23,24], underscoring a need for an anti-inflammatory drug. The exaggerated chronic IA in ART naïve PLHIV and the residual chronic IA in ART-treated PLHIV may be responsible for non-AIDS complications like HTN.

Of the immune cells, it appears that the activation of T-cells and monocytes plays a significant role in the development of CVDs including HTN. However, there is a paucity of data on the relationship between IA and HTN in PLHIV reported in the literature, and most reported data were obtained from studies in the general population and/or animal models of HTN [9, 25]. Furthermore, most studies of HIV and IA/ inflammation have not looked at IA specifically as it relates to HTN [9, 25]. In view of this knowledge gap, we studied some of the cellular and plasma markers of IA and their relationship to HTN in ART naïve PLHIV. The knowledge of IA is important in HIV-associated HTN as it may offer new potential therapeutic targets for the prevention and improvement in the clinical management of HTN in PLHIV.

Methods

Study design, study setting, study population

This article presents the findings of the analysis of baseline data from a clinical trial whose main aim was to investigate the effect of low-dose aspirin (ASA) on HIV disease progression in PLHIV starting ART. The trial was registered in both the Pan African Clinical Trial Registry (PACTR202003522049711) and ClinicalTrials.gov (NCT05525156). An elaborate methodology of the trial has been previously described [26]. Briefly, the trial participants were recruited from three different care and treatment centres (CTCs). The selected CTCs, situated in two regional referral and one district public hospitals in Dar es Salaam, Tanzania’s largest city and financial centre, contribute to catering to a population where HIV prevalence among adults stands at 4.2%. The services in these CTCs are coordinated by the Tanzanian government through the National AIDS Control Programme and supported by Management and Development for Health, a non-profit non-governmental organisation. These CTCs specialise in HIV outpatient care and provide free HIV/AIDS testing and counselling; treatment, and monitoring. The CTCs are equipped with staff, including clinicians, nurses, pharmacists, laboratory officers, and counsellors, who are trained in HIV care. Being situated in district and regional referral hospitals these CTCs serve individuals from various socioeconomic backgrounds within their districts and neighbouring areas outside Dar es Salaam.

Recruitment was between March 2020 and June 2022 with a three-month temporary suspension due to the COVID-19 pandemic. The inclusion criteria involved being newly diagnosed with HIV, ART naïve, starting ART at the time of enrolment, aged 18 years or older, and being willing to participate for six consecutive months. Exclusion criteria included asthma, pregnancy, bleeding predisposition, use of antithrombotic drugs, use of trial-prohibited drugs (see supplementary file 1), peptic ulcer disease, ASA intolerance or allergy, and/or severe kidney disease (estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73m2).

Data collection

Participants who fulfilled eligibility criteria underwent interviews, physical examinations, and data recording of their sociodemographic and clinical information. Details of age, alcohol consumption, cigarette smoking, individual history of CVDs and diabetes mellitus (DM), and family history of CVDs were recorded. Current and previous medication history including use of antidiabetics, antihypertensives, and antidyslipidaemics was also documented. Body weight was measured in kilograms using a digital weighing scale (Health O Meter, 500KL, China), and body height was measured in centimetres using a stadiometer (Health O Meter, 500KL, China). These measurements were used to calculate the body mass index (BMI) [27]. Blood pressure (BP) measurements were taken from the left arm while sitting for each participant using a digital sphygmomanometer (Yuwell YE660D, Jiangsu Province, China). Two readings were recorded, with a time gap of five to ten minutes, and the average of the two readings was calculated and used as the participant’s BP [28].

Laboratory procedures

Each participant provided a total of 20mL of non-fasting antecubital venous blood sample that was aliquoted thrice and transported, in a cool box, to the Muhimbili University of Health and Allied Sciences (MUHAS) laboratories. At MUHAS, two 4mL aliquots: one for full blood picture (FBP) and CD4, and another for serum creatinine and lipid profile, were sent to the MUHAS Clinical Research Laboratory (MCRL) where 50µ of the aliquot in K2 EDTA vacutainer tube underwent FBP analysis (Sysmex analyser, Sysmex Corporation, Japan) while the remaining volume of this sample was kept in the cool box and later transported to the Infectious Disease Centre laboratory (IDC) within Dar es Salaam for CD4 count (FACSPresto; BD Biosciences, San Jose, California, USA). The aliquot for serum creatinine and lipid profile was centrifuged to obtain serum and analysed (creatinine, total cholesterol (TC), High-density lipoprotein cholesterol (HDL-C), and Triglycerides (TG) (COBAS Integra 400 Plus, Roche Instruments Centre AG, Rotkreuz, Switzerland). The sample processing and analysis window for FBP, serum creatinine and lipid profile was six hours and 24 h for CD4 count. The 12mL aliquot (sterile K2 EDTA tubes) was sent to the Immunology laboratory (IL) where it was immediately centrifuged at 1500 times gravity (x g) for 10 min at minimum acceleration and deceleration to obtain plasma and cellular sediment. The obtained plasma was aliquoted to 1.5 mL and 4.5 mL and immediately stored at -80 °C. From the cellular sediment, peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation using Ficoll-Paque Plus media solution (GE Healthcare Life Sciences Inc., Chicago, Illinois), re-suspended in 2 mL of Fetal Cow Serum containing 10% Dimethyl Sulfoxide and stored in liquid nitrogen. At the end of the study, the 1.5 mL plasma was sent to the Muhimbili National Hospital Central Pathology laboratory for viral load analysis. The 4.5 mL plasma and the PBMCs were shipped, in dry ice, to the Joint Research Center for Human Retrovirus Infection laboratory at Kumamoto University, Kumamoto, Japan where they were stored (plasma at -80 °C, PBMCs in liquid nitrogen) until analysis for monocyte activation marker (soluble CD14), platelet activation marker (soluble P-selectin) and T lymphocyte activation.

In our study, serum creatinine was used for calculating eGFR (Modification of Diet in Renal Disease study equation) that was used for staging chronic kidney disease (Kidney Disease Improving Global Outcomes staging system [29]. Low-density lipoprotein cholesterol (LDL-C) was estimated by the Friedewald equation [30].

Soluble CD14 (sCD14) and soluble P-selectin (sP-selectin) analyses

Thawed plasma were diluted at 1:50 for sP-selectin and 1:1000 for sCD14 and respective biomarkers measured using a customised BDTM Cytometric Bead Array kit (BD Biosciences, San Jose, California, USA) according to the manufacturer’s instruction manual. Standards from lowest to highest concentrations followed by test samples were acquired by flow cytometry (BD FACSCanto™ II, BD Biosciences, San Jose, California, USA) using FACSDiva software (BD Biosciences, San Jose, California, USA) at 400 events before analysis by flow cytometric analysis program array software (Soft Flow Hungary Ltd., Hungary).

PBMCs analysis for markers of T lymphocyte activation

Liquid nitrogen-frozen PBMCs were thawed, stained in the dark with diluted (1:100) antibodies: CD3 FITC, CD14 PerCP, CD19 PerCP, CD8 APCcy7, CD4 BV510, CD38 PE, PD-1 PEcy7 and HLA-DR APC and fixed with 1% paraformaldehyde. About 100,000 events were acquired for each sample using FACSDiva software (BD Biosciences, San Jose, California, USA) by flow cytometry (BD FACSCanto™ II, BD Biosciences, San Jose, California, USA). Frequencies of activated (CD38 + HLA-DR+) and exhausted (PD-1+) T lymphocytes (CD4 + and CD8+) were determined by gating based on isotype controls using FACSDiva software (BD Biosciences, San Jose, California, USA) (Fig. 1). Data were obtained on FlowJo™ version 10.8.2 software (TreeStar, Ashland, Oregon).

Fig. 1
figure 1

Expression of activation (CD38 and HLA-DR) and exhaustion (PD-1) markers on CD4 + and CD8 + T cells. (e). Activation marker to define PD-1 + CD4 + T cells. (f). Activation marker to define CD38 + HLA-DR + CD4 + T cells. (g). Activation marker to define PD-1 + CD8 + T cells. (h). Activation marker to define CD38 + HLA-DR + CD8 + T cells

Definitions of variables

Hypertension was defined as the individual’s systolic BP (SBP) of ≥140 mmHg and/or the individual’s diastolic BP (DBP) of ≥ 90 mmHg and/or history of HTN and/or current or past use of antihypertensives [31]. The age considered at risk for HTN was 45 years or older for men and 55 years or older for women [32]. Alcohol consumption was defined as the current or past regular use of alcohol. Cigarette smoking was defined as the current or past regular smoking of cigarettes. Diabetes mellitus (DM) was defined as a history of DM and/ or current or past use of antidiabetic medication. A history of CVDs was defined as a participant’s previous occurrence of stroke and/or MI [32]. Family history of CVDs was defined as the presence of HTN and/or stroke and/or MI in the immediate relatives of the participant [32]. Overweight was defined as a BMI of 25.0 to 29.9 kg/m2 and obesity as a BMI of ≥ 30.0 kg/m2. Dyslipidaemia was defined as non-fasting serum TC ≥5.17 mmol/ L and/or LDL-C ≥ 3.36 mmol/ L and/or TG ≥ 1.70 mmol/ L and/or current use of antidyslipidaemics regardless of sex and/or HDL-C <1.03 mmol/ L for men or HDL-C <1.29 mmol/ L< for women [32].

Data management and statistical analysis

Data in case report forms (CRFs) were compared to data on the source document for accuracy and completeness. Double data entry, verification and cleaning were done on a password-secured computer followed by analysis on statistical software for social sciences (SPSS) for Windows version 26 (Inc., Chicago, Illinois). Study participants’ characteristics were described using descriptive statistics. Mean ± standard deviation (SD) or median (interquartile range (IQR)) were used to present continuous variables based on the distribution of the data. Frequencies and percentages were used to express categorical variables.

Mann-Whitney U test was used to compare levels of IA and exhaustion; and platelet activation between participants with HTN and those without HTN. A robust Poisson regression model was used to examine the predictors for HTN because, in this study, the prevalence of HTN (25.3%) was high (> 10%). The variables that had a p-value < 0.2 in the univariable analysis were included in the multivariable analysis. A p-value of < 0.05 in the multivariable analysis was considered statistically significant.

Results

Socio-demographic and clinical characteristics

Three hundred sixty-five participants who had at least one marker of the immune or platelet activation measured out of 430 total clinical trial participants were included in this analysis. Majority of hypertensive participants were self-employed and living with partner compared to the normotensive participants (p < 0.05). More normotensive participants had a history of bacterial infection at enrolment than hypertensive participants (p = 0.009). Median BMI was higher among hypertensive participants than among normotensive participants (p = 0.006). Median eGFR was lower among hypertensive participants than among normotensive participants (p = 0.003). Participants with HTN had higher median (IQR) frequencies of markers of T cell activation and exhaustion compared to non-hypertensive participants, but these were not statistically significantly different. Site of recruitment, level of education and other clinical characteristics were comparable between the two groups of participants (Table 1).

Table 1 Socio-demographic and clinical characteristics of HIV-infected treatment naïve individuals initiating ART overall (*N = 363), and by hypertension status

Prevalence and predictors of hypertension

The prevalence of hypertension was 92/363 (25.3%, 95% CI 20.9–29.8%). Among all participants, the mean Systolic BP ± SD was 123.3 ± 17.3 mmHg and the median Diastolic BP (IQR) was 74.0 (70.0, 81.5) mmHg.

In univariable and multivariable analyses, none of the immune and platelet activation markers predicted the occurrence of HTN. Regarding traditional risk factors for CVDs, those participants who were overweight or obese had 69% more occurrence of HTN (aPR 1.69 (95% CI 1.17–2.44) compared to those participants who had underweight or normal weight. Additionally, the participants in CKD stage 2 had 97% more occurrence of HTN (aPR 1.97 (95% CI 1.34–2.88) compared to participants in CKD stage 1 (Table 2).

Table 2 Predictors of hypertension among HIV-infected treatment naïve individuals initiating ART

Discussion

The current study examined the relationship between HTN and both soluble and cellular markers of IA (sCD14, HLA-DR+CD38+ on CD4+ and CD8+ T cells) and exhaustion (PD-1+ on CD4+ and CD8+ T cells) and marker of platelet activation (sP-selectin) in ART naïve PLHIV who were starting ART. HTN is a problem among PLHIV with a reported prevalence higher than HIV-uninfected population [9, 10]. Understanding its pathogenesis is essential for potential preventive and therapeutic interventions. The established traditional risk factors for HTN cannot solely explain the increased risk of HTN in PLHIV. There is evidence to suggest that HIV-related factors, ART, and chronic IA may play a role [9, 19].

Our study involved a cross-sectional analysis of the baseline data of 365 participants of a clinical trial to determine the effect of low-dose ASA on HIV disease progression among HIV-infected individuals initiating ART. A quarter of the participants were hypertensive. While the median values of IA (excluding monocyte activation which was lower) and exhaustion markers and platelet activation marker were higher in hypertensive participants, none of these markers was found to significantly predict HTN.

In this study, there was no statistically significant difference in the median value of the marker of monocyte activation, sCD14 between participants with HTN and those without HTN. In fact, a lower median value of sCD14 was observed in the hypertensive participants. Our findings are in keeping with those of a study also conducted in East Africa - Uganda whereby sCD14 was not associated with incident HTN and the relationship between sCD14 and incident HTN was inverse [33]. Despite the similarity in findings, the Ugandan study was among ART-exposed PLHIV on six months of therapy [33]. This is not surprising, as previous studies have shown that even with successful treatment with ART the higher-than-normal levels of sCD14 in PLHIV persist or decrease but do not normalise [21, 24, 34].

Although the expression of sCD14 has a genetic basis [35], other studies conducted in Europe, Australia and the US also, among ART-exposed PLHIV, reported no significant association between sCD14 and HTN and/or BP parameters [34, 36,37,38]. On the contrary, a Norwegian study found higher levels of sCD14 among hypertensive PLHIV compared to non-hypertensive PLHIV. Furthermore, the study found sCD14 to be an independent predictor of only DBP but not SBP [39]. These reports altogether indicate that data on the association between sCD14 and HIV-associated HTN is still conflicting regardless of ART status and/or ethnicity. Further studies are required to establish convincingly the actual relationship between sCD14 and HIV-associated HTN.

The role of activated and/ or exhausted T lymphocytes in the pathogenesis of non-AIDS complications such as HTN among PLHIV has not been extensively studied. Contradictory to our hypothesis, we found that T lymphocyte activation and exhaustion did not predict HTN among our study participants. Similarly, T cell activation was unpredictive of HTN in a US-based study among African Americans and Hispanics untreated and treated HIV-infected women [40]. Two additional studies were also conducted in the US: one exploring the relationship between T cell activation and exhaustion and non-AIDS defining events generally; while the other looked at the relationship specifically with HTN [38, 41]. The former found no association between T cell activation markers and non-AIDS defining events including stroke. However, in this study marker of CD4+ T cell exhaustion had an association with the non-AIDS defining events that became insignificant after adjusting for CD4+ T cell count [41]. The latter study conducted among ART-exposed virologically suppressed PLHIV reported no association between dual expression of CD38 and HLA-DR antigens or expression of PD-1 on CD4 + and CD8 + T cells and HTN [38]. However, in this study, HTN was associated with lower CD4 + but not CD8 + T cells expressing CD38 singly. Drawing from our findings and these previous reports, T cell activation and exhaustion may not have a role in the pathophysiology of HTN in PLHIV of different races, gender, HIV viraemia and/or ART status. However, more evidence needs to be gathered from larger multi-centre studies to come to this conclusion as available reports are scant.

Our study was not primarily designed to study the relationship between HTN and IA and exhaustion among PLHIV. We conducted a cross-sectional analysis of available baseline data of clinical trial participants aiming at determining the effect of low-dose ASA among treatment naïve PLHIV initiating ART. The data, although large, may be not sufficient to establish the relationship between HTN and the studied markers of IA and exhaustion. Additionally, our study explored a narrow range of both soluble and cellular markers of IA and exhaustion. However, these markers were selected based on their reported roles in the pathogenesis of CVDs in the general population and/or experimental animals.

Conclusion and recommendations

Although markers of IA and exhaustion were higher in hypertensive PLHIV among our study participants, they did not significantly predict HTN. In this study, only traditional risk factors for CVDs specifically CKD staging, and BMI significantly predicted the occurrence of HTN. Further larger multi-centric studies with a wider range of IA markers are needed to establish the relationship between HTN and immune activation and exhaustion among PLHIV.

Data availability

All data generated or analysed during this study are included in this published article [and its supplementary files].

Abbreviations

AMI:

Acute Myocardial Infarction

ART:

Antiretroviral Therapy

ASA:

Aspirin

BMI:

Body Mass Index

BP:

Blood Pressure

CKD:

Chronic Kidney Disease

CRFs:

Case Report Forms

CTCs:

Care and Treatment Centers

CV:

Cardiovascular

CVDs:

Cardiovascular Diseases

DBP:

Diastolic Blood Pressure

DM:

Diabetes Mellitus

DTG:

Dolutegravir

eGFR:

Estimated Glomerular Filtration Rate

FBP:

Full Blood Picture

HDL:

C-high-density lipoprotein cholesterol

HTN:

Hypertension

IA:

Immune Activation

IL:

Immunology Laboratory

IQR:

Interquartile Range

LDL:

C-low-density lipoprotein Cholesterol

MCRL:

MUHAS Clinical Research Laboratory

IDC:

Infectious Disease Centre Laboratory

MRRH:

Mwananyamala Regional Referral Hospital

MRTH:

Mbagala Rangi Tatu Hospital

MUHAS:

Muhimbili University of Health and Allied Sciences

NIMR:

National Institute for Medical Research

PBMCs:

Peripheral Blood Mononuclear Cells

PLHIV:

People Living with HIV and/or AIDS

SBP:

Systolic Blood Pressure

sCD14:

Soluble CD14

SD:

Standard Deviation

sP:

Selectin-soluble P-selectin

SPSS:

Statistical Software for Social Sciences

SSA:

Sub-Saharan Africa

TC:

Total Cholesterol

TG:

Triglycerides

TRRH:

Temeke Regional Referral Hospital

References

  1. Ka HW, Chan KCW, Shui SL. Delayed progression to death and to AIDS in a Hong Kong cohort of patients with advanced HIV type 1 disease during the era of highly active antiretroviral therapy. Clin Infect Dis. 2004;39(6):853–60.

    Article  Google Scholar 

  2. Palella FJ, Baker RK, Moorman AC, Chmiel JS, Wood KC, Brooks JT et al. Mortality in the highly active antiretroviral therapy era: Changing causes of death and disease in the HIV outpatient study. J Acquir Immune Defic Syndr (1988). 2006;43(1):27–34.

  3. Farahani M, Mulinder H, Farahani A, Marlink R. Prevalence and distribution of non-AIDS causes of death among HIV-infected individuals receiving antiretroviral therapy: a systematic review and meta-analysis. Int J STD AIDS. 2017;28(7):636–50.

    Article  PubMed  Google Scholar 

  4. Armah KA, Chang C, chou H, Baker JV, Vasan S, Budoff MJ, Crane HM et al. Prehypertension, Hypertension, and the Risk of Acute Myocardial Infarction in HIV-Infected and -Uninfected Veterans. 2014.

  5. Triant VA, Lee H, Hadigan C, Grinspoon SK. Increased acute myocardial infarction rates and cardiovascular risk factors among patients with human immunodeficiency virus disease. J Clin Endocrinol Metab. 2007;92(7):2506–12.

    Article  CAS  PubMed  Google Scholar 

  6. Nüesch R, Wang Q, Elzi L, Bernasconi E, Weber R, Cavassini M et al. Risk of cardiovascular events and blood pressure control in hypertensive HIV-infected patients: Swiss HIV cohort study (SHCS). J Acquir Immune Defic Syndr (1988). 2013;62(4):396–404.

  7. Bloomfield GS, Hogan JW, Keter A, Holland TL, Sang E, Kimaiyo S, et al. Blood pressure level impacts risk of death among HIV seropositive adults in Kenya: a retrospective analysis of electronic health records. BMC Infect Dis. 2014;14(1):1–10.

    Article  Google Scholar 

  8. Xu Y, Chen X, Wang K. Global prevalence of hypertension among people living with HIV: a systematic review and meta-analysis. J Am Soc Hypertens. 2017;11(8):530–40.

    Article  PubMed  Google Scholar 

  9. Masenga SK, Hamooya BM, Nzala S, Kwenda G, Heimburger DC, Mutale W et al. Patho-immune mechanisms of hypertension in HIV: a systematic and thematic review. Curr Hypertens Rep. 2019;21(7).

  10. Peck RN, Shedafa R, Kalluvya S, Downs JA, Todd J, Suthanthiran M, et al. Hypertension, kidney disease, HIV and antiretroviral therapy among Tanzanian adults: a cross-sectional study. BMC Med. 2014;12(1):1–11.

    Article  Google Scholar 

  11. Kato I, Basil Tumaini, Pallangyo K. Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar Es Salaam. PLoS ONE. 2020;1–13.

  12. Pangmekeh PJ, Awolu MM, Gustave S, Gladys T, Cumber SN. Association between highly active antiretroviral therapy (HAART) and hypertension in persons living with HIV/AIDS at the Bamenda regional hospital, Cameroon. Pan Afr Med J. 2019;8688:1–11.

    Google Scholar 

  13. Kingery JR, Alfred Y, Smart LR, Nash E, Todd J, Naguib MR, et al. Short and long term cardiovascular risk, metabolic syndrome prevalence and HIV in Tanzania: a cross-sectional study. Heart. 2016;102(15):1200–5.

    Article  PubMed  Google Scholar 

  14. Njelekela M, Muhihi A, Aveika A, Spiegelman D, Hawkins C, Armstrong C et al. Prevalence of hypertension and its associated risk factors among 34,111 HAART Naïve HIV-Infected adults in Dar es Salaam, Tanzania. Int J Hypertens. 2016;2016.

  15. RodrõÂguez-ArbolõÂ E, Mwamelo K, Kalinjuma AV, Furrer H, Hatz C, Tanner M, et al. Incidence and risk factors for hypertension among HIV patients in rural Tanzania-A prospective cohort study. PLoS ONE. 2017;12(3):1–14.

    Google Scholar 

  16. Mwakyandile TM, Shayo GA, Sasi PG, Mugusi FM, Barabona G, Ueno T, et al. Hypertension and traditional risk factors for cardiovascular diseases among treatment naïve HIV- infected adults initiating antiretroviral therapy in Urban Tanzania. BMC Cardiovasc Disord. 2023;23(1):1–9.

    Article  Google Scholar 

  17. Brennan AT, Nattey C, Kileel EM, Rosen S, Maskew M, Stokes AC, et al. Change in body weight and risk of hypertension after switching from efavirenz to dolutegravir in adults living with HIV: evidence from routine care in Johannesburg, South Africa. EClinicalMedicine. 2023;57:101836.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Byonanebye DM, Polizzotto MN, Neesgaard B, Sarcletti M, Matulionyte R, Braun DL, et al. Incidence of hypertension in people with HIV who are treated with integrase inhibitors versus other antiretroviral regimens in the RESPOND cohort consortium. HIV Med. 2022;23(8):895–910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Fahme S, Bloomfield GS, Peck RN. Hypertension in HIV-infected adults: novel pathophysiologic mechanisms. Hypertension. 2019;72(1):44–55.

    Article  Google Scholar 

  20. Hunt PW, Martin JN, Sinclair E, Bredt B, Hagos E, Lampiris H, et al. T cell activation is associated with lower CD4 + T cell gains in human immunodeficiency vires-infected patients with sustained viral suppression during antiretroviral therapy. J Infect Dis. 2003;187(10):1534–43.

    Article  CAS  PubMed  Google Scholar 

  21. Malherbe G, Steel HC, Cassol S, De Oliveira T, Seebregts CJ, Anderson R et al. Circulating biomarkers of immune activation distinguish viral suppression from nonsuppression in HAART-treated patients with advanced HIV-1 subtype C infection. Mediators Inflamm. 2014;2014.

  22. Hattab S, Guiguet M, Carcelain G, Fourati S, Guihot A, Autran B et al. Soluble biomarkers of immune activation and inflammation in HIV infection: impact of 2 years of effective first-line combination antiretroviral therapy. 16, HIV Medicine. 2015. p. 553–62.

  23. Wada NI, Jacobson LP, Margolick JB, Breen EC, Macatangay B, Penugonda S, et al. The effect of HAART-induced HIV suppression on circulating markers of inflammation and immune activation. Aids. 2015;29(4):463–71.

    Article  CAS  PubMed  Google Scholar 

  24. O’Halloran JA, Dunne E, Gurwith MMP, Lambert JJS, Sheehan GJ, Feeney ER et al. The effect of initiation of antiretroviral therapy on monocyte, endothelial and platelet function in HIV-1 infection. 16, HIV Medicine. 2015. p. 608–19.

  25. Van Zoest RA, Van Den Born BJH, Reiss P. Hypertension in people living with HIV. Curr Opin HIV AIDS. 2017;12(6):513–22.

    Article  PubMed  Google Scholar 

  26. Mwakyandile T, Shayo G, Mugusi S, Sunguya B, Sasi P, Moshiro C, et al. Effect of aspirin on HIV disease progression among HIV-infected individuals initiating antiretroviral therapy: study protocol for a randomised controlled trial. BMJ Open. 2021;11(11):1–9.

    Article  Google Scholar 

  27. Consultation WHO. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. Vol. 894, World Health Organization - Technical Report Series. 2000.

  28. Xu SK, Chen X, Sheng CS, Cheng YB, Wang HY, Yu W, et al. Comparison of the mean of the first two blood pressure readings with the overall mean of three readings on a single occasion. J Hypertens. 2022;40(4):699–703.

    Article  CAS  PubMed  Google Scholar 

  29. KDIGO. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Vol. 3, IFAC Proceedings Volumes (IFAC-PapersOnline). 2013.

  30. 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. 1972;18(6):499–502.

    Article  CAS  PubMed  Google Scholar 

  31. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, et al. Seventh report of the Joint National Committee on Prevention, detection, evaluation, and treatment of high blood pressure. Hypertension. 2003;42(6):1206–52.

    Article  CAS  PubMed  Google Scholar 

  32. Grundy SM. National Cholesterol education program: second report of the expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). Circulation. 1994;89(3):1329–443.

    Google Scholar 

  33. Okello S, Asiimwe SB, Kanyesigye M, Muyindike WR, Boum Y, Mwebesa BB et al. D-Dimer levels and traditional risk factors are associated with incident hypertension among HIV-infected individuals initiating antiretroviral therapy in Uganda. J Acquir Immune Defic Syndr (1988). 2016;73(4):396–402.

  34. Castley A, Williams L, James I, Guelfi G, Berry C, Nolan D. Plasma CXCL10, sCD163 and sCD14 levels have distinct associations with antiretroviral treatment and cardiovascular disease risk factors. PLoS ONE. 2016;11(6):1–14.

    Article  Google Scholar 

  35. Reiner AP, Lange EM, Jenny NS, Chaves PHM, Ellis J, Li J, et al. Soluble CD14: genomewide association analysis and relationship to cardiovascular risk and mortality in older adults. Arterioscler Thromb Vasc Biol. 2013;33(1):158–64.

    Article  CAS  PubMed  Google Scholar 

  36. van Zoest RA, Wit FW, Kooij KW, van der Valk M, Schouten J, Kootstra NA, et al. Higher prevalence of hypertension in HIV-1-infected patients on combination antiretroviral therapy is associated with changes in body composition and prior stavudine exposure. Clin Infect Dis. 2021;63(2):205–13.

    Article  Google Scholar 

  37. Knudsen AD, Bouazzi R, Afzal S, Gelpi M, Benfield T, Høgh J, et al. Monocyte count and soluble markers of monocyte activation in people living with HIV and uninfected controls. BMC Infect Dis. 2022;22(1):1–9.

    Article  Google Scholar 

  38. Masenga SK, Elijovich F, Hamooya BM, Nzala S, Kwenda G, Heimburger DC et al. Elevated eosinophils as a feature of inflammation Associated with Hypertension in Virally Suppressed people Living with HIV. J Am Heart Assoc. 2020;9(4).

  39. Manner IW, Baekken M, Kvale D, Oektedalen O, Pedersen M, Nielsen SD, et al. Markers of microbial translocation predict hypertension in HIV-infected individuals. HIV Med. 2013;14(6):354–61.

    Article  CAS  PubMed  Google Scholar 

  40. Kaplan RC, Sinclair E, Landay AL, Lurain N, Sharrett AR, Gange SJ, et al. T cell activation and senescence predict subclinical carotid artery disease in HIV-infected women. J Infect Dis. 2011;203(4):452–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Tenorio AR, Zheng Y, Bosch RJ, Krishnan S, Rodriguez B, Hunt PW, et al. Soluble markers of inflammation and coagulation but not T-cell activation predict non-AIDS-defining morbid events during suppressive antiretroviral treatment. J Infect Dis. 2014;210(8):1248–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the District Executive Director of Temeke district, Dar es Salaam and the administrations of Mwananyamala and Temeke regional referral hospitals and Mbagala Rangi Tatu Hospital for permitting us to conduct this study. We also thank the CTCs staff of the study sites, all the trial participants, and staff at the MCRL, IL, IDC, and Joint Research Centre for Human Retrovirus Infection.

Funding

This study was partially funded by Fogarty International Center (FIC) of the National Institutes of Health (NIH) (Award Number 1R25TW011227-01) through the Transforming Health Education in Tanzania (THET) project and 5D43 TW009775-03, the Swedish International Development Cooperation Agency (Sida), the Japan Society of Promotion of Sciences (JSPS) namely, JSPS KAKENHI Grant-in-Aid for Scientific Research 21K19657, 22H03119, 22KK0148, JSPS Bilateral Open Partnership Joint Research Project, JPJSBP120219933 and JPJSBP120239932, JSPS Core-to-Core Program, JPJSCCB20190009 and, JPJSCCB20220010 and the Japan Student Service Organization (JASSO). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health and the other funders.

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Contributions

T.M.M., G.A.S., P.G.S., F.M.M., and E.F.L. designed the study. T.M.M. collected data, analysed, and drafted the initial manuscript. T.M.M., G.A.S., P.G.S., F.M.M., G.B., T.U. and E.F.L. edited and reviewed the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Tosi M. Mwakyandile.

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Ethics approval and consent to participate

The study was conducted according to ICH GCP guidelines and the Declaration of Helsinki (Version 2013). Ethical approval for the trial was granted by the Muhimbili University of Health and Allied Sciences’ (MUHAS) Senate Research and Publications Committee (reference number DA.282/298/01 /C) and the National Health Research Ethics Committee at the Tanzania National Institute for Medical Research (NIMR) (reference number NIMR/HQ/R.8a/Vol. IX/3001). Permission to conduct the trial was sought from and granted by the respective hospitals’ administration. Each participant gave written informed consent before being enrolled in the trial. For illiterate participants, informed consent to participate was taken by thumbprint witnessed by treatment supporter of illiterate participant. The study participants were given a study-specific number to conceal their identity to maintain confidentiality. No participants’ names were used in the study.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Mwakyandile, T.M., Shayo, G.A., Sasi, P.G. et al. Hypertension and immune activation in antiretroviral therapy naïve people living with human immunodeficiency virus. BMC Infect Dis 24, 630 (2024). https://doi.org/10.1186/s12879-024-09548-x

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