Clinical trial NCT03201939
Conditions: HIV/AIDS Albuminuria Kidney Diseases Genetic Predisposition
Keywords: HIV/AIDS sub-Saharan Africa Kidney disease Albuminuria Genetic risk
Sponsor: Vanderbilt University Medical Center
Start date: 2021-04-01; Completion date: 2025-02-01
Enrollment: 66 participants; Allocation: RANDOMIZED; Intervention model: PARALLEL

Brief summary:
In this study, the Investigators plan to determine the optimal means to prevent or slow the progression of kidney disease among genetically at-risk northern Nigerian HIV-infected adults. Based on data from studies of diabetic kidney disease that used medications that block the renin angiotensin aldosterone system (RAAS), we plan to evaluate whether or not RAAS inhibition (using a widely available medication that blocks RAAS) in HIV-infected adults produces similarly promising results.

Detailed description:
Individuals of African descent have a much higher risk for glomerular diseases. Specifically, there are two risk variants in the chromosome 22 APOL1 gene (G1/G2) and persons possessing 2 copies of these risk variants (G1/G1, G1/G2, or G2/G2), referred to as the high-risk (HR) genotype, are at high risk for non-diabetic kidney disease. Kopp et al. have shown that the APOL1 high-risk genotype confers sizeable odds ratios (OR) for FSGS (OR = 17), HIVAN (OR = 29 in the US; 89 in S. Africa), and hypertension-attributed end stage kidney disease (OR = 7). The presence of these risk variants is highest in West Africa, and specifically in Nigeria among persons of Hausa, Fulani, and Igbo descent. In the setting of untreated HIV infection, we have estimated that \~50% of individuals carrying the APOL1 HR genotype will develop chronic kidney disease (CKD). However, there is limited availability of dialysis and kidney transplantation in Nigeria, and most individuals will die soon after developing ESKD. Markers of kidney disease include microalbuminuria, proteinuria, and/or reduced estimated glomerular filtration rate (eGFR). All 3 have been associated with increased mortality in HIV+ adults. Increased urinary albumin excretion has diagnostic and prognostic value in the identification and confirmation of renal disease, and changes in albuminuria can be useful in assessing treatment efficacy as well as disease progression. Microalbuminuria, i.e., urine albumin to creatinine ratio (uACR) in the 30-300 mg/g range, is likely the earliest stage of CKD, analogous to diabetic microalbuminuria. The renin-angiotensin aldosterone system (RAAS) is the central player in the pathophysiology of CKD and blocking RAAS with angiotensin converting enzyme inhibitors (ACEi) is a well-recognized strategy to slow or halt renal disease progression in diabetics with CKD. To determine whether the presence of APOL1 HR genotype alters or predicts responsiveness to conventional therapy and if the addition of an ACEi to standard antiretroviral therapy (ART) reduces the risk for renal complications among West African adults, we will screen 2,600 HIV+ ART-experienced adults; to conduct the following Specific Aims:

1. To determine the prevalence of APOL1 renal risk variants and assess whether APOL1 HR status correlates with prevalent albuminuria, eGFR, and/or prevalent CKD in a West African population.
2. To assess whether RAAS inhibition (with the ACEi lisinopril) in addition to ART, compared to the existing standard-of-care (SOC), will significantly reduce the incidence of additional kidney disease manifestations. We will randomize ART-experienced (6+ months) adults with prevalent microalbuminuria (uACR 30-300 mg/g) and an eGFR of \> 30 ml/min/1.73m2 to lisinopril (n=140) vs. SOC (n=140); and
3. To determine whether the APOL1 HR genotype is associated with worse longitudinal renal outcomes in Nigerians with prevalent albuminuria.

Arms: arm 1: ACE-inhibitor lisinopril arm 2: Matched placebo
Interventions: intervention 1: Lisinopril intervention 2: Placebo Oral Tablet
Intervention descriptions: intervention 1: ACE-inhibitor (lisinopril)(intervention arm intervention 2: Comparator placebo (control arm)

Protocol documents:
Prot_SAP_000.pdf: 
OPTIMAL MANAGEMENT OF HIV-INFECTED ADULTS AT RISK FOR 
KIDNEY DISEASE IN NIGERIA 
U01DK112271 
 
NCT03201939 
 
STUDY PROTOCOL AND ANALYSIS PLAN 
JULY 24, 2021. 


Protocol Date: July 24, 2021 
 
 
 
www.niddk.nih.gov 
 
Optimal Management of HIV Positive Adults at 
Risk for Kidney Disease in Nigeria 
U01 DK112271 
 
Principal Investigators: 
 
C. William Wester, MD, MPH (Contact PI) 
Professor of Medicine 
Vanderbilt University Medical Center 
Vanderbilt Institute for Global Health (VIGH) 
 
Muktar H. Aliyu, MD, DrPH, MPH (Multi-PI) 
Professor of Health Policy and Medicine 
Vanderbilt University Medical Center 
Vanderbilt Institute for Global Health (VIGH) 
Co-Investigators: 
 
Baba M. Musa, MBBS, MPH, FCCP, FWACP 
Associate Professor & Consultant Physician 
Aminu Kano Teaching Hospital, Kano, Nigeria 
babamaiyaki2000@yahoo.co.uk 
 
Aliyu Abdu, MBBS, FWACP 
Professor of Medicine & Consultant Nephrologist 
Aminu Kano Teaching Hospital, Kano, Nigeria 
aliyuabdu2000@yahoo.co.uk 
 
Aisha M. Nalado, MBBS, FWACP 
Assistant Professor of Medicine & Consultant Nephrologist 
Aminu Kano Teaching Hospital, Kano, Nigeria 
aishnld@yahoo.co.uk 
 
Mahmoud U. Sani, MBBS, FACP, FWACP, PhD 
Professor of Medicine & Consultant Cardiologist 
Aminu Kano Teaching Hospital, Kano, Nigeria 
sanimahmoud@yahoo.com 
 
Muhammad Hamza, MBBS, FWACPath 
Assistant Professor of Medicine & Consultant Pathologist 
Aminu Kano Teaching Hospital, Kano, Nigeria 
drhamza1020@ymail.com 
 
Protocol Version #: 10.0 


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Akinfenwa Atanda, MBBS, FMCPath 
Assistant Professor of Medicine & Consultant Pathologist 
Aminu Kano Teaching Hospital, Kano, Nigeria 
akinzo123@gmail.com 
 
Kabiru Abdussalam, MBBS, FMCPath 
Assistant Professor of Pathology 
Aminu Kano Teaching Hospital, Kano, Nigeria 
kabirabdulsalam2004@gmail.com 
Bryan E. Shepherd, PhD 
Professor of Biostatistics 
Vanderbilt University School of Medicine 
bryan.shepherd@vanderbilt.edu 
 
 
Aima Ahonkhai, MD, MPH, A.B. 
Assistant Professor of Medicine 
Vanderbilt University Medical Center 
Vanderbilt Institute for Global Health (VIGH) 
aimalohi.a.ahonkhai@vumc.org 
Anna Burgner, MD 
Assistant Professor of Medicine 
Vanderbilt University Medical Center 
anna.burgner@vanderbilt.edu 


Protocol Version #: 10.0 
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Table of Contents: 
 
Study Schema 
1.0 
Background 
2.0 
Rationale and Specific Aims 
2.1 
Specific Aim 1 
2.2 
Specific Aim 2 
2.3 
Specific Aim 3 
3.0 
Preliminary Data 
4.0 
Inclusion/Exclusion Criteria 
5.0 
Enrollment/Randomization 
6.0 
Study Procedures 
7.0 
Data and Safety Monitoring Plan 
8.0 
Study Withdrawal/Discontinuation 
9.0 
Statistical Considerations 
10.0 
Follow-up and Record Retention 
11.0 
Foreign Justification 
 
Appendices 
Appendix A Study timeline 
Appendix B Supplemental tables - Statistical calculations for secondary 
endpoints 


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Background 
 
HIV and non-communicable diseases (NCDs) are increasing in Africa. Effective 
antiretroviral therapy (ART) has promoted immunologic recovery, but at the cost of 
adverse metabolic complications and negative health outcomes, most commonly 
referred to as non-communicable diseases (NCDs), that have emerged as a major 
health concern among long-term ART-treated adults.1-5 We are faced with a new 
challenge: namely, addressing morbidity and mortality from NCDs4specifically kidney 
disease plus heart disease, stroke, diabetes, and metabolic complications, and non- 
AIDS associated cancers4that increase with age and may be related to HIV, its 
treatment, host genetic factors, and/or modifiable risk factors.6-11 Deaths due to NCDs 
are rapidly trending to occupy a larger share of deaths and disability-adjusted life years 
(DALYs) in resource-constrained settings. More than 38 million persons die each year 
from NCDs, with the vast majority (82%) residing in low- and middle-income countries 
(LMICs).12 Current projections show that by 2020, 73% of all deaths worldwide will be 
due to NCDs and that the burden of NCDs will rise by more than 60% in LMICs, with the 
largest increases in NCD deaths in Africa. HIV infection and ART interact with NCD risk 
factors in complex ways, and research into this important area has so far been largely 
based on data from high income countries.13 Figure 1 (below) displays the share of age- 
standardized disability-adjusted life years (DALYs) among reproductive-aged adults for 
NCDs (blue), communicable diseases (red), and external causes (green) for Western 
sub-Saharan Africa (SSA) and North America, from the Global Burden of Disease 
project.13 Darker color shades represent diseases that are increasing more rapidly. 
 
Figure 1: Distribution of DALYs by region of the world (North America vs. Western 
SSA), ages 15-49 years, 2016. 
North America 
Western SSA 
 
 
The burden of HIV-associated kidney disease in Africa is substantial. Although ART 
has substantially reduced the impact of HIV-associated kidney disease in the U.S., the 
HIV epidemic continues globally in kidney disease-susceptible African-descent 
populations.14,15 Chronic kidney disease (CKD), defined as the presence of proteinuria 
(defined as urine albumin/creatinine ratio >300 mg/g) and/or reduced eGFR (defined as. 
<60 mL/min/1.73m2), is at least 334 times more frequent in Africa than in developed 
countries.16-18 The reported prevalence of CKD in HIV positive ART-naive patients varies 
across SSA, ranging from 6 to 48%, with the highest prevalence reported in Nigeria, the 
most populous nation in Africa.17-22 Stanifer et al 23, in their recent meta-analysis of 90 
studies in SSA, found that the overall prevalence of CKD from 21 medium- and high- 
quality studies was 13.9% [95% CI: 12.2-15.7], and that among people with HIV, the 
prevalence of CKD was highest in Nigeria, Zimbabwe, and Uganda. In studies 
conducted by Mulenga et al.19, the prevalence of kidney dysfunction (defined as eGFR of 
< 90 mL/min/1.73m2), was 33.5% among HIV positive ART-naïve adults presenting for 
care at a large urban clinic in Lusaka, Zambia. Mulenga et al.19 also showed that ART- 
naïve patients with kidney dysfunction in Zambia had a 4-fold higher mortality rate 
compared to those with normal renal function. CKD affects an estimated 14% of adults in 
SSA, but very little research has been done on the cause, progression, and prevention 
of CKD in this region.21 As part of the Human Heredity and Health in Africa (H3Africa) 
Initiative, the H3Africa Kidney Disease Research Network 24 was established to study 
prevalent forms of kidney disease in SSA and increase the capacity for genetics and 


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genomics research. Dr(s) Winkler and Kopp are involved with the H3Africa initiative. Our 
proposed work does not overlap with any ongoing/planned work in this consortium, and 
we will share all study findings with them. 
 
Host genetics play an important role in CKD risk. Because certain HIV-related kidney 
diseases (HIV-associated nephropathy [HIVAN] and focal segmental glomerulosclerosis 
[FSGS]) emerge exclusively (HIVAN) or largely (FSGS) in persons of African descent 
(~20-fold greater risk than non-African descent counterparts), several studies have 
sought associations between genetics and a predisposition to CKD in these patients.25-37 
Genovese et al.37 described two risk alleles in the APOL1 gene, a 2-allele haplotype 
(G1) that consists of the 2 derived non-synonymous coding variants rs73885319 
(S342G) and rs60910145 (I384M), and a G2 allele that consists of a 6-base pair deletion 
(rs71785313) that removes 2 amino acids (NYK388K ).37 Kopp, Winkler, Pollak et al.30,36- 
38 have shown that the APOL1 high-risk genotype (defined by the carriage of two APOL1 
risk alleles) confers sizeable odds ratios (OR) for FSGS (OR = 17), HIVAN (OR = 29 in 
the US; 89 in South Africa), and hypertension-attributed end stage kidney disease 
(ESKD) (OR = 7). These variants are present only on African-origin chromosomes. The 
frequency of the risk alleles is highest in West Africa, specifically in Nigeria among 
persons of Yoruba (>50%) and Igbo (>50%) descent.39,40 As the APOL1 effect is largely 
recessive (2 risk variants), ~25% of the population is at substantially increased risk of 
kidney disease. In the setting of untreated HIV infection, we have estimated that ~50% 
of individuals carrying high-risk genotypes will develop CKD.41,42 Even when HIV 
replication is suppressed, APOL1 high-risk individuals remain at greatly increased risk 
for FSGS and hypertension-attributed ESKD, similar to HIV-negative APOL1 risk 
individuals.25 
 
Microalbuminuria is an important early marker of kidney disease, including in HIV 
positive adults. There is a continuum of kidney disease, typically defined by increasing 
stages of CKD. In some forms of kidney disease, such as diabetic nephropathy, the 
earliest detectable abnormality is microalbuminuria, which may progress to 
macroalbuminuria and finally to nephrotic range proteinuria. Albuminuria is an 
independent risk factor for cardiovascular and renal disease and a predictor of end 
organ damage.43 Microalbuminuria (urine albumin/creatinine ratio (uACR) = 30-300 
mg/g) can signify either glomerulosclerosis or glomerular microvascular dysfunction 
(often associated with systemic microvascular dysfunction) has been used in the early 
detection of several disease states, i.e. preeclampsia, diabetic nephropathy, and 
medication-induced nephrotoxicity.43 As a result, various guidelines have recommended 
assessment of urinary protein in adults with hypertension or diabetes, and even in the 
general population to identify at-risk persons. Proteinuria has also been associated with 
decreased CD4+ cell counts and higher plasma viral loads among HIV-positive 
individuals, as well as increased systemic T-cell activation and more rapid progression to 
AIDS.44-46 Microalbuminuria and macroalbuminuria are also important risk factors for 
mortality in ART-treated HIV-positive individuals, probably due to their role as a marker 
for inflammation and endothelial activation.47-49 Even very low levels of albuminuria 
(uACR = 10-30 mg/g) have been associated with adverse cardiovascular and renal 
events.44,50 Gerstein et al., 44 evaluating older patients with at least one risk factor for 
cardiovascular disease, found that routine screening for albuminuria identifies people at 
high risk for cardiovascular events.44 Current guidelines recommend that all HIV positive 
adults with significant proteinuria of grade g 1+ (by dipstick analysis) and/or reduced 
kidney function (eGFR < 60 ml/min per 1.73m2) be referred to a nephrologist for 
additional quantification of urinary protein excretion and/or a kidney biopsy. While 


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therapy for HIV-associated kidney disease needs to be individualized, waiting for overt 
proteinuria may miss a potential earlier window for intervention to more effectively 
forestall progression to the more advanced stages of CKD. Microalbuminuria is an 
established screening test to detect early diabetic nephropathy, and there is growing 
interest to screen for microalbuminuria to identify early HIV-associated kidney disease in 
patients. Hadigan et al.51 found the period prevalence of microalbuminuria in their U.S.- 
based HIV cohort to be 14%, and patients with microalbuminuria were more likely to 
have hypertension, metabolic syndrome, and immunosuppression (CD4+ cell count < 
200 cells/mm).32,51 Lastly, they determined that a single normal uACR determination 
effectively excluded microalbuminuria, whereas an elevated uACR required 
confirmation.51 The UK National Institute of Health and Clinical Excellence (NICE) 
guidelines for CKD suggest defining pathologic albuminuria by a random urine 
albumin/creatinine ratio (uACR) > 30 mg/mmol (~300 mg/d).52 Gansevoort et al.53 
demonstrated that progressively higher levels of ACR were predictive of worse renal 
outcomes across a range of eGFR values. In particular, detection of an increase in 
protein excretion had diagnostic and prognostic value in the initial identification and 
confirmation of kidney disease, and the quantification of protein excretion could be of 
considerable value in assessing disease progression, as well as treatment 
efficacy.43,45,49,54 24-hour urine collection has been considered the <gold standard= for 
urinary protein collection, but this technique is cumbersome.54 Furthermore, Heerspink et 
al.55 recently showed that in diabetic patients, first morning void uACR was superior to 
24-hour urine protein or albumin in predicting renal outcomes. This suggests that 24- 
hour urine protein collections are no longer the gold standard. Easier alternatives include 
first morning voided or spot (random) samples, with data supporting the use of random 
uACR to accurately characterize protein and albumin excretion in adults with renal 
disease.56-65 However, uACR measurements are not standard practice when screening 
HIV-positive patients for underlying kidney abnormalities, although their routine use is 
gaining popularity. 
 
HIV-associated kidney disease is common in Africa. HIV-positive adults are at risk 
for several chronic kidney diseases, including glomerular disease (collapsing 
glomerulopathy; commonly referred to as HIVAN, immune complex glomerulonephritis, 
FSGS, thrombotic microangiopathy, etc.), and tubulointerstitial disease associated with 
infections and specific medications (i.e. tenofovir). 34,66-73 The most severe of these, 
HIVAN, is a direct result of HIV replication in the kidney and occurs almost exclusively in 
persons of African descent.71-73 Other hallmarks include proteinuria and 
normal/increased kidney size with increased echogenicity.74-76 Renal disease, especially 
glomerular disease, is more prevalent in Africa and seems to be of a more severe form 
than that found in Western countries.76 The true prevalence of HIVAN worldwide is not 
known- earlier studies suggested that approximately 10% of HIV positive, untreated 
persons with recent African ancestry develop HIVAN at some point in their HIV disease 
course;77-80 however, a paucity of African data exists describing the prevalence of 
HIVAN.80 We will not be performing renal biopsies in this study and therefore will 
examine HIV-associated kidney disease (not HIVAN specifically). Of relevance to our 
proposed study as we aim to intervene aggressively and early in the course of our 
Nigerian patients’ kidney disease continuum, Han et al.80 found 6 of 7 (86%) patients in 
their cohort with persistent microalbuminuria, when biopsied, to have structural kidney 
disease (HIVAN). Given the lack of dialysis and renal transplant options for the majority 
of Nigerians with HIV infection, our pharmacological research approach to halt or slow 
progression of CKD is especially urgent for SSA and may also be relevant for higher 
resource settings. 


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Renin angiotensin aldosterone system (RAAS) inhibition can be used to reduce 
kidney complications. The renin-angiotensin aldosterone system (RAAS) is recognized 
as a central driver of the pathophysiology of CKD, based on numerous clinical trials in 
individuals with diabetes.81,82 Renal dysfunction can be regarded as a continuum that 
extends from endothelial dysfunction to microalbuminuria, macroalbuminuria, ESKD, and 
ultimately death. All stages of this continuum are associated with progressively 
increasing cardiovascular risk.83 Preventing the development and progression of kidney 
disease does require tight blood pressure control, but due to the important role of the 
RAAS in the pathogenesis of diabetic kidney disease, agents that inhibit this system 
(angiotensin converting enzyme inhibitors (ACEis) or angiotensin receptor blockers 
(ARB’s) are recognized first line therapy,83 offering both effective blood pressure 
lowering and direct actions on the kidney. Numerous studies have documented the 
efficacy of RAAS inhibition as a means to slow the progression to CKD among at-risk 
diabetics.81,82,84-90 Maione et al.,91 in their systematic review of ACEi’s and ARBs in 
patients with microalbuminuria, found a significant reduction in the risk of all kidney 
outcomes with ACEi’s compared to placebo or no treatment (ESKD: 9 RCTs, 7988 
patients, RR 0.67 [0.5430.84]; doubling of serum creatinine: 9 RCTs, 8460 patients, RR 
0.62 [0.4630.84] and progression from micro- to macroalbuminuria: 18 RCTs, 2888 
patients, RR 0.49, [0.3630.65]. There was also a significant increase in the likelihood of 
regression from micro- to normoalbuminuria (15 RCTs, 1860 patients, RR 2.99 [1.823 
4.91] (see Section D.2 Sample size justifications). The end-organ protective effects of 
ACEis appear strongly related to their reactive oxygen species (ROS) lowering effects, 
and it has been hypothesized that high levels of ROS contribute to the pathogenesis of 
NCDs, including end-organ kidney complications.85,92-97 
 
 
1.0 
Rationale and Specific Aims 
 
Nigeria is home to the fourth largest HIV-positive population in the world, having an 
estimated ~ 1,900,000 people living with HIV and 53,000 AIDS-related deaths 
annually.98 Non-communicable diseases (NCDs), including kidney disease, among HIV- 
positive and HIV-negative adults in sub-Saharan Africa (SSA) represent a burgeoning 
epidemic. This study will be the first of its kind providing randomized controlled trial 
(RCT) evidence informing the optimal strategy to manage HIV-positive adults with 
albuminuria, particularly those with APOL1 risk alleles who are genetically susceptible to 
kidney disease and potentially other life-threatening (i.e. cardiovascular) end-organ 
complications. Confirmation of the highest rates of adult HIV-positive populations 
globally carrying APOL1 high-risk genotypes (~ 25%) would have significant implications 
for clinical care (including monitoring strategy) of persons in Nigeria and the West 
African region as a whole. 
This study of HIV kidney disease is innovative for the following reasons: 
 
1) Microalbuminuria among HIV-positive adults in Nigeria most likely represents 
underlying early structural kidney disease. This was the case in a small kidney biopsy 
series performed among HIV-positive adults presenting with persistent microalbuminuria 
in South Africa, of whom 6 of 7 were found to have HIV-associated nephropathy.80 The 
present study will be the first to evaluate therapy to treat microalbuminuria in this 
population with the goal of preventing the progression of kidney disease. 


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2) APOL1 variants are a major driver of kidney disease in HIV-positive persons. Most 
existing data on APOL1 risk variant prevalence are based on DNA from studies with very 
small sample sizes among specific African ethnic groups. This will be the largest genetic 
risk variant survey to date among individuals in West Africa, the region of the world with 
the highest documented carriage rates of the APOL1 high-risk (HR) genotype. 
3) If early therapy can reduce albuminuria, it could also reduce the burden of HIV- 
associated CKD and associated morbidity and premature mortality. Such findings would 
make a strong case for the adoption of population-based screening for albuminuria using 
uACR measurements (compared to less accurate urine dipstick and cumbersome 24- 
hour urine protein measurements). This testing would also greatly assist in the 
identification of persons in need of early intervention. In resource-poor settings, where 
access to therapies for ESKD (dialysis and kidney transplantation) are not widely 
available, prevention of CKD may prolong life. 
 
4) Determining if the presence of an APOL1 risk genotype correlates with ESKD risk 
(microalbuminuria, reduced eGFR, and/or early CKD), as well as determining whether it 
influences longitudinal renal outcomes among patients with prevalent albuminuria, is 
novel and will inform treatment guidelines and result in significant public health benefits, 
particularly if our results show that affordable and readily available treatment can be 
instituted early in the disease continuum; AND 
 
5) Various interventional studies involving small numbers of subjects have been 
performed showing that the provision of RAAS inhibition is safe and may be beneficial 
when given to HIV-positive adults with HIV-associated nephropathy manifesting with 
varying levels of proteinuria.99-106 Despite strong rationale and encouraging preliminary 
data, the role of RAAS inhibition in HIV-positive subjects with or at-risk for HIV- 
associated kidney disease remains to be confirmed by well-designed and adequately 
powered randomized controlled trials. The R3 study as designed is well poised to be the 
first RCT to provide definitive evidence regarding the role RAAS inhibition as adjunctive 
therapy to standard ART could play in the large numbers of HIV-positive adults at risk for 
long-term kidney complications. Such guidance is especially relevant in West Africa 
where the prevalence of the APOL1 high risk genotype is highest globally. In addition, 
the promising pharmaceutical approach of the R3 study is particularly important in sub- 
Saharan Africa, where treatment options for ESKD (i.e. dialysis and transplantation) are 
extremely limited. 
 
 
 
To accomplish our goals, we will pursue the following Specific Aims: 
 
1.1 
Specific Aim 1 
 
Specific Aim 1: To determine the prevalence of APOL1 renal risk variants among 2,600 
HIV-positive individuals in Nigeria and assess whether APOL1 HR status correlates with 
prevalent albuminuria, eGFR, and/or prevalent CKD (defined as macroalbuminuria or 
eGFR <60 ml/min/1.73 m2) in this population. 


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Hypothesis: ~25% of those screened will carry the APOL1 HR genotype, which will be 
associated with albuminuria, lower baseline eGFR, higher uACR, and higher rates of 
prevalent CKD. 
 
Definitions: Microalbuminuria will be defined as having a mean uACR of 30-300 mg/g. 
CKD will be defined by the presence of proteinuria or an eGFR of < 60 ml/min/1.73m2. 
Study Population: We will determine the prevalence of APOL1 risk variants in a large 
group of HIV-positive adults (n = 2,600) in Nigeria and correlate them with early markers 
of kidney disease; namely microalbuminuria, reduced eGFR, and CKD. All consecutively 
seen HIV-positive ART-experienced (6+ months) adults (g18-70 years of age) presenting 
for care at AKTH will be approached for enrolment into this study. NOTE: We will be 
enrolling ART-experienced adults (on ART for 6+ months). Specifically, if on ART for 6- 
12 months, then subjects need to have a plasma viral load value < 20 copies/mL from 
their 6-month blood draw, and if on ART for > 12 months, then enrolled participants need 
to have a suppressed viral load result (i.e. < 20 copies/mL) on their most recent viral 
load blood draw---which needs to be within the past 6 months). Routine viral load 
monitoring has only recently been implemented at our study site in north-central Nigeria, 
and by enrolling only patients with recent evidence of viral suppression, we will do our 
best to eliminate ongoing HIV-associated viral replication in non-adherent persons as a 
potential contributing cause to immune activation and therefore NCD end-organ 
complications, including kidney disease. 
 
 
1.2 
Specific Aim 2 
 
Specific Aim 2: To assess whether RAAS inhibition with an ACEi compared to 
placebo, significantly reduces incidence of albuminuria or reduced eGFR among 280 
HIV-positive individuals with microalbuminuria who are receiving ART. 
Hypothesis: After two years, 
• 
A significantly higher proportion of participants in the intervention vs. SOC arm 
will regress from microalbuminuria to normoalbuminuria (uACR<30 mg/g); 
anticipated hazard ratio = 2.5. 
• 
Significantly higher proportions of participants in the SOC arm (60% vs. 25% in 
the intervention arm) will progress from microalbuminuria to macroalbuminuria 
(uACR>300 mg/g). 
• 
Albuminuria will fall by an average of 40% in the intervention arm and increase 
by an average of 10% in the SOC arm. 
Study population: All HIV-positive ART-experienced (6+ months) screened individuals 
(n = 2,600) found to have i) confirmed microalbuminuria (mean uACR between 30-300 
mg/d obtained at 2 separate measurements at least 4 and no more than 8 weeks apart), 
(NOTE: based on variability of individual uACR measurements, we also plan to call 
back Aim 1 participants having normoalbuminuria (especially those with an average 
uACR value in the 20-29 mg/g range) as well as Aim 1 participants having 
macroalbuminuria), and ii) fairly well-preserved renal function, namely an eGFR > 60 
ml/min/1.73m2; will be approached for enrollment into this study. Based on recent 
studies at AKTH among HIV positive adults, we anticipate that a minimum of 18% of 
screened patients (n~460) will be eligible. Therefore, with a target sample size equal to 


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280 (see Section 10.0), 59% of eligible patients would need to consent for this Aim 2 
study. 
Primary Endpoints: 
i) 
Regression from microalbuminuria (uACR=30-300 mg/g) to 
normoalbuminuria (uACR < 30 mg/g) 
ii) 
Progression from microalbuminuria (uACR=30-300 mg/g) to 
macroalbuminuria (uACR > 300 mg/g) by study arm 
iii) 
Mean change in uACR 
Secondary Endpoints: 
i) Doubling of serum creatinine from baseline; ii) All-cause mortality (NOTE: Planned 
follow-up is two years for all participants), iii) Proportion experiencing a 40% decline in 
eGFR (using CKD-EPI-Cr-CyC equation), iv) Mean change in eGFR over time (using 
CKD-EPI-Cr-CyC equation), and v) change in clinical/performance status (as 
ascertained via two measures, specifically the WHO quality of life (WHOQOL-HIV) tool 
(31 questions)107,108 and the Karnofsky performance score)109. 
 
 
1.3 
Specific Aim 3 
 
Specific Aim 3: To determine whether the APOL1 HR genotype is associated with 
worse longitudinal kidney outcomes among HIV-positive Nigerians with prevalent 
albuminuria, with regard to progression of albuminuria and eGFR decline. 
Hypothesis: After two years of follow-up, independent of baseline uACR, eGFR, and/or 
treatment assignment: 
• 
Study participants with the HR genotype will have a more rapid kidney function 
decline (median eGFR change) compared to those with the LR genotype. 
• 
Study participants with the LR genotype will have 30% lower mean uACR values 
(compared to baseline) compared to study participants with the HR genotype. 
Study population: All enrolled Aim 2 study participants who completed the study, 
namely, two years of study follow-up. However, to improve our power to evaluate the 
influence of APOL1 risk allele status on key renal outcomes, we will include all enrolled 
Aim 2 study participants that completed a minimum of one year of clinical follow-up, 
meaning that if they were lost to follow-up after completing their one-year study visit, we 
will include them in our Aim 3 genetics outcome analyses. 
 
2.0 
Preliminary data 
 
NCD incidence is high in SSA. We previously compared NCD incidence between a 
large urban U.S. setting (Nashville, TN) and a large urban African setting (Gaborone, 
Botswana). Standardized to an older, predominantly male U.S population, the overall 
NCD incidence rates were higher in Botswana (18.7 per 1000 PY).11 Standardized rates 
differed most for cardiovascular events (8.4 vs. 5.0 per 1000 person-years) and non- 
AIDS-defining malignancies (8.0 vs. 0.5 per 1000 PY) - both higher in Botswana. This 
was one of the initial publications indicating that NCDs appeared to be a significant 
problem in our SSA setting and that monitoring, prevention, and treatment of NCDs 
should be a critical component of care in resource-limited settings.11 


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Angiotensin receptor blocker (ARB) and ACEi exposure is associated with 
decreased all-cause mortality in HIV positive adults.88 Adults (g18 years of age) who 
achieved virologic suppression within 180 days of ART initiation and were from one of 
four North American AIDS Cohort Collaboration on Research and Design (NA ACCORD) 
sites were included. Primary analysis assessed the effect of time-varying ACEi/ARB 
exposure on all-cause mortality, using a marginal structural model to control for time- 
dependent confounders. Among 5252 participants, ACEi or ARB use was associated 
with significantly lower odds of death among HIV positive adults receiving suppressive 
ART when properly accounting for time-dependent confounding.88 
 
Kidney disease is common among HIV positive adults presenting for care at 
AKTH.110 400 consecutive treatment-naïve HIV-positive patients with no other condition 
known to cause kidney disease were screened for proteinuria and eGFR. Kidney 
disease was found in 227 patients (56.8%), and proteinuria, including persistent 
microalbuminuria, was found in 211 (52.8%), with reduced eGFR (<60 mL/min/1.73m2) 
being identified in 64 persons (16.0%). Of note, the investigators biopsied a small series 
of patients (n = 20); among those with microalbuminuria, 2 of 5 (40%) had structural 
kidney disease in the form of collapsing FSGS (HIVAN). These findings confirmed that 
renal disease in HIV positive patients is high in Kano, Nigeria, and that microalbuminuria 
appears to be an important manifestation of collapsing FSGS.110 
APOL1 influences albuminuria in young African American adults: Kopp and Winkler 
have published data from the CARDIA study 111 (n=3,031) showing that the onset of 
APOL1 kidney disease manifests as incident albuminuria and declining eGFR using 
serum cystatin C. Having APOL1 HR genotypes was associated with a decline in eGFR 
only among those with albuminuria, compared to white adults (p=0.001).There were no 
differences in eGFR slopes for APOL1 high-risk black adults without albuminuria or other 
blacks without albuminuria compared to the white adult reference group (Figure 2).111 
 
Table 1. APOL1 high-risk (HR) genotype and the risk for glomerular disease among African 
Americans and black Africans in South Africa 
Percent APOL1 risk genotypes in black patients from U.S. and South Africa (SA) 
US published case/control studies 
S. Africa published studies 
(Kasembeli JASN 201530) 
No. 
OR 
[95% CI] 
APOL1 
HR 
Ref 
No. 
OR 
[95% CI] 
APOL1 
HR 
HIVAN 
54 
29 [13- 
68.5] 
72% 
Kopp36 
38 
89 [18-911] 
78.9% 
Primary FSGS 
217 
17 [11- 
26] 
72% 
Kopp36 
18 
3.1 [0.04-249] 
5.6% 
HIV 
POSITIVEFSGS 
- 
- 
19 
3.6 [0.2-42] 
10.5% 
HIVICK 
- 
- 
28 
6.2 [0.4-97] 
20.0% 
US published biopsy studies 
LEGEND: HIVICK (HIV-associated 
immune complex disease); HIVAN 
(HIV-associated nephropathy) 
FSGS (focal segmental 
glomerulosclerosis). Population 
frequencies for carriage of APOL1 
high-risk genotype: US ~ 14%, SA 
~ 2-3%, Nigeria ~ 25%. 
HIVAN 
60 
- 
62% 
Atta35 
HIV 
POSITIVEFSGS 
35 
- 
63% 
Fine112 
HIVICK 
31 
- 
3% 
Fine112 


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While the CARDIA population was largely HIV-negative, these data show that APOL1 
kidney disease presents early as albuminuria and supports our hypothesis that HIV 
interaction with APOL1 high-risk status may be associated with worse outcomes in 
Nigerians with albuminuria (Aims 1 and 3). 
 
APOL1 high-risk genotype is associated with glomerular disease among African 
Americans and black Africans in South Africa: In a series of published studies, Kopp 
and Winkler1,7-9,12,13 have shown that carriage of the APOL1 HR genotype is strongly 
associated with primary FSGS and with HIVAN, with greater than 70% of individuals 
having these diagnoses possessing the APOL1 HR genotype in the U.S. (Table 1). 
Interestingly, while the association for HIVAN was similar in African Americans (AA) and 
South African (SA) blacks, the enrichment of APOL1 HR with primary FSGS (72%) in AA 
is strikingly higher compared to FSGS in SA blacks (5-10%) (Table 1). In a case-only 
biopsy series, we showed that the pathology of renal biopsies of HIVAN patients did not 
differ by APOL1 genotype.6 
 
Table 2. Selected relevant preliminary studies and data sources published by the project team 
Study/setting/country 
Study Methodology 
Key findings, lessons learned 
Comprehensive HIV and ART outcomes 
Pregnancy rates & birth outcomes 
among women on efavirenz (EFV)- 
containing ART, Botswana 
(Wester113) 
Prospective 
cohort 
High pregnancy rates in women on EFV 
(7.9/100 person-years), indicating unmet 
need for family spacing services. 
Mortality with ART initiation in 
advanced HIV-1, Botswana 
(Wester114) 
Retrospective 
cohort 
Significant clinical benefit with ART, 
even for advanced immunosuppression. 
Non-nucleoside reverse 
transcriptase inhibitor outcomes in 
Botswana 
(Wester115,116) 
RCT 
Higher rates of treatment-modifying 
toxicities with nevirapine (NVP) (vs. 
EFV). NVP-treated women trended 
towards higher virologic failure with 
resistance vs. women on EFV. 
Risk factors for symptomatic 
hyperlactatemia and lactic acidosis 
among combination ART-treated 
adults in Botswana (Wester117) 
RCT 
Higher rates of symptomatic 
hyperlactatemia/lactic acidosis in 
overweight (BMI>25) females 
Non-communicable diseases 
End stage renal disease among HIV 
positive adults in North America 
(Wester33) 
Large, retrospective 
observational cohort 
High rates of end stage renal disease 
among blacks 
Incidence rates of NCDs in a large 
U.S. center (Vanderbilt) versus a 
large  African  setting,  Botswana 
(Wester11) 
RCT (Botswana) vs. 
retrospective 
observational data 
(U.S.) 
Higher rates of age-standardized NCDs 
in Botswana 
Clinical Trials 
Determine the optimal means 
(intervention package) for 
prevention of mother-to-child HIV 
transmission (PMTCT) in Nigeria 
(Aliyu) 
(Aliyu118) 
Cluster RCT 
An integrated PMTCT package 
significantly improved a) ART initiation 
(adjusted RR (aRR)=3.3 (1.4-7.8)] and 
b) 12 week maternal and infant retention 
in care (aRR = 9.1 [5.2-15.9] in rural 
Nigeria 
Stroke prevention in Nigerian 
children with sickle cell disease 
(SCD) trial (SPIN trial) 
First NIH-sponsored 
sickle cell disease 
RCT in SSA 
A hydroxyurea trial for children with SCD 
is feasible in SSA, but requires extensive 
capacity building 


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3.0 
Inclusion/Exclusion Criteria 
Inclusion and exclusion criteria to be used for participant enrollment into Study 
Aim 1 are shown below. 
 
Inclusion criteria: 
• 
18-70 years of age 
• 
HIV-positive (as documented by HIV-1 ELISA testing) 
• 
On ART for a minimum of six (6) months 
Exclusion criteria: 
• 
Patients unwilling to consent to participate in this study 
• 
On ART for < 6 months 
Recruitment strategies: 
NOTE: Although the eligible population of the HIV clinic at AKTH is 40% male, we 
anticipate that females will be more likely to enroll in this study, given our previous 
experience. Therefore, study staff will specifically target males for enrollment in order to 
achieve a gender balance in our study enrollment. Strategies that will be utilized by staff 
include use of male counselors in the clinic, utilization of male peer counselors for 
targeted recruitment, and extension of clinic hours to accommodate male participants 
who may not be able to attend otherwise due to work engagements. These strategies 
have all been utilized successfully by our team in previous studies and HIV scale-up 
efforts within Nigeria and Mozambique.118-120 In addition, given preliminary Aim 1 data, 
with the mean duration of ART among enrolled aim 1 participants being > 8 years, 
strategies will be utilized by staff to prioritize the identification of persons more recently 
(within the past 6-24 months) in order to enroll a large cohort of HIV-positive adults with 
a more balanced duration of time on ART. Lastly, also given preliminary Aim 1 data 
review coupled with DSMB feedback (January 23, 2019), it was seen that ~ 75% of 
enrolled aim 1 participants (n = 380) had a self-reported ethnicity of Hausa/Fulani; with 
only ~ 4-5% self-reporting their ethnicity as Yoruba. Based on published literature to 
date39,40, carriage of the APOL1 high risk (HR) genotype has been shown to be highest 
among persons of Yoruba descent and other ethnic groups (i.e. Igbo) and more 
prevalent in the southern part of Nigeria. To address this in order to increase enrolment 
of persons of Yoruba descent, we will plan to open a second study site; namely the 
Infectious Disease Hospital that is also in Kano, as the demographics of the population 
this hospital serves is quite different when compared to AKTH in that they service 
significantly higher proportions of persons of Yoruba and other ethnicities from southern 
Nigeria; where proportions of the population possessing the APOL1 HR genotype are 
highest39,4039-40. 
Inclusion and exclusion criteria to be used for participant enrollment into Study 
Aim 2 are shown below. 
Inclusion criteria: 


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• 
Participated in Study Aim 1: prevalence of APOL1 high risk status and clinical 
correlates 
• 
Suppressed plasma viral load result (f 20 copies/mL) within the past 6 months, 
and no unsuppressed viral load during that time. Routine viral load monitoring 
has only recently been implemented at AKTH. By enrolling only patients with 
recent evidence of viral suppression, we will reduce the impact of ongoing HIV- 
associated viral replication in non-adherent persons as a contributing cause of 
immune activation and therefore end-organ complications, including kidney 
disease. 
• 
Completing Aim 1 of the study AND having a repeat single uACR value between 
30-300 mg/g (based on first morning voided specimen) at time of Aim 2 
screening to confirm eligibility. 
• 
f 1+ hematuria on urine dipstick 
• 
eGFR g 60 ml/min/1.73m2 based on serum creatinine value obtained during Aim 
1 AND based on repeat serum creatinine value obtained at time of Aim 2 
screening to confirm eligibility (NOTE: eGFR for Aim 1 and Aim 2 calculated 
using the CKD-EPI-Cr-CyC equation). 
AND 
• 
If female, non-pregnant (documentation of negative urine pregnancy test) and not 
breastfeeding/lactating. In addition, if female (with reproductive potential), needs 
to be reliably/consistently be receiving contraceptives (including documentation 
of being receiving reliable/consistent contraceptives; including enrolment in 
family planning/consultative services). 
Exclusion criteria: 
• 
eGFR of < 60 ml/min/1.73m2 
• 
uACR < 30 mg/g or > 300 mg/g (on Aim 2 screening) 
• 
K+ > 5.0 mmol/L, or reasons to be concerned about hyperkalemia 
• 
History of diabetes mellitus (would qualify for treatment with an ACEi/ARB) 
[NOTE: Standardized diabetes screening procedure (fasting or random glucose 
g 6.1 mmol/L)] 
• 
g 2+ hematuria on urine dipstick (assuming they might have glomerulonephritis 
from chronic active hepatitis B and/or C as both conditions can also cause 
albuminuria/proteinuria) 
• 
Poorly controlled hypertension (Mean BP readings > 160/110 mm Hg in past 6 
months) 
• 
Persistent symptomatic hypotension (BP < 90/60 mm Hg) (on 2 or more 
successive readings) 
• 
Known history of chronic congestive heart failure 
• 
Initial screening uACR value > 300 mg/g plus urine dipstick g 2+ for protein 
• 
Currently receiving an ACEi and/or ARB; 
OR 
• 
Lack of suitability as a study candidate (i.e. active substance use disorder, active 
use of potentially nephrotoxic medication(s) [e.g. traditional medicines, etc.] 
and/or history of poor compliance [e.g. multiple missed scheduled clinic 
appointments, etc.]) 
4.0 
Enrollment/Randomization 


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Participants will be enrolled at Aminu Kano Teaching Hospital (AKTH), Kano, Nigeria. All 
HIV-positive ART-experienced (g6 months on ART) individuals found to meet the 
inclusion criteria will be approached by a study coordinator for enrollment into this study. 
The study coordinator will describe the purpose of the study and the included activities 
and will review the informed consent with the potential participant. Those who provide 
written informed consent will be enrolled. 
 
Aim 2 will be a randomized double-blind (both participants and study physicians involved 
in the conduct of this study), placebo-controlled study to minimize crossovers and bias in 
the classification of outcomes and potential adverse effects secondary to ACE-inhibitor 
therapy (lisinopril), which we anticipate will be minimal. We will apply block 
randomization to ensure balance of baseline uACR between randomization arms. Using 
this block randomization, stratifying patients at time of study enrollment, we plan to enroll 
equal numbers of patients in each stratum. 
 
5.0 
Study Procedures 
 
Aim 1 Study Procedures 
Each consenting patient will have a full medical evaluation and will provide two first- 
morning void urine specimens (5 mL) because of variability. We will measure urinary 
albumin and creatinine levels to calculate a mean (2 sample) uACR value. The second 
first-morning uACR will be obtained 4-8 weeks after the first specimen. Assays will be 
performed using the Roche Hitachi Cobas C 311 (Roche Diagnostics, Indianapolis, IN) 
system, using pyrogallol red urine creatinine by a kinetic Jaffe method and urine albumin 
by immunoturbidimetry.121,122 Each consenting patient will also provide one blood sample 
for serum creatinine and cystatin C, from which we will calculate eGFR using the CKD 
epidemiology collaboration (CKD-EPI-Cr-CyC)123,124 equation. NOTE: We will use both 
serum cystatin C125 and CKD-EPI123,124 to calculate eGFR. Although the CKD-EPI 
equation is preferred/more accurate, Shlipak et al.125 have shown that the use of both 
serum cystatin C and serum creatinine for eGFR estimations strengthens the association 
between eGFR and the risk of ESKD and death across diverse populations. During their 
first AKTH clinic visit, all screened patients will have their confirmatory HIV-1 ELISA test 
result as well as the most recent CD4+ count and viral load results obtained from their 
medical records/charts, per existing standard-of-care. Each screened patient will be 
given a unique study ID number, which the study team will maintain. The study ID can 
be linked back to individual patients (and will therefore be kept in a locked cabinet4 all 
information linking patients to ID numbers will be destroyed once study follow-up for 
Aims 1-3 is complete). Individual patient data that will be collected and maintained by 
de-identified study ID include: age, race/ethnicity, sex, weight, BMI, and comorbid 
medical conditions (prior/current opportunistic infections, syphilis, cancer, hypertension, 
other cardiovascular diseases). 
 
Genetics specimen collection and analysis: From all consenting patients, peripheral 
blood will be collected in one 10 mL EDTA vacutainer tube. Blood will be processed for 
buffy coat and whole blood, and will be aliquoted into multiple separate 1.0- and 2.0-mL 
vials (following the SOP for processing DNA blood specimens in Dr. Cheryl Winkler’s 
laboratory) for and stored at -80 C. DNA (buffy coat and whole blood) specimens will be 
stored and shipped in batches to Dr. Winkler’s laboratory for DNA extraction using 
Qiagen extraction kits and genetic testing of APOL1 risk variants. Genotyping will be 
performed to identify the genetic correlates of risk for kidney and potentially other end 
organ complications.17,38,126. Genotyping will be done using TaqMan assays (San Diego, 


Protocol Version #: 10.0 
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16 
 
CA) targeting the 3 chromosome 22 APOL1 variants (rs73885319 [G1], rs60910145 
[G1], and rs 71785313 [G2]) associated with CKD and HIV-associated kidney disease. 
The APOL1 risk alleles are defined by the G1 haplotypes (rs73885319-G/rs60910145-G 
and rs73885319-G/rs60910145-T) and by the G2 haplotype (rs71785313-deletion). We 
will infer the APOL1 genotype from the number of risk alleles: individuals exhibiting two 
risk alleles (G1/G1, G1/G2, or G2/G2) will be assigned to the <high-risk (HR)= group, 
while individuals carrying no or one risk allele (G0/G0, G0/G1, and G0/G2) will be 
attributed to the <low-risk (LR)= group. We will also examine the risk allele groups in a 
categorical manner (0 vs. 1 vs. 2 alleles and 0 vs. 1 risk alleles) to determine whether 
presence of a single risk allele poses increased risk. We will then determine the overall 
prevalence of APOL1 risk alleles, including odds ratios for baseline CKD and 
albuminuria, and the standard error for beta comparing levels of microalbuminuria and 
eGFR stratified by genotype (including testing for association between the APOL1 
genotype and longitudinal eGFR slope using linear regressions). In addition, we will 
perform crude and adjusted linear regression analyses (modified Poisson regression) to 
test for associations with mean uACR, eGFR, and CKD, adjusting for sex, blood 
pressure, and age. Based on previous genetic association work in HIVAN, we will test 
both additive and recessive genetic models to capture all potential risk alleles associated 
with microalbuminuria and CKD. Because of the strong associations reported for APOL1 
with HIVAN (OR=29, U.S. and OR 89, South African, recessive model), our cohort 
exhibits substantial power to detect the effects of APOL1 in the recessive model. For 
APOL1, we anticipate that 12% of controls and 36% of cases will carry the APOL1 HR 
genotype; this is a strong epidemiological association, but modest on the scale of known 
effects of APOL1 risk alleles on kidney disease. 
 
NOTE: We also plan to collect and store plasma, sera, and urine specimens from all 
screened / consenting aim 1 study participants for future analyses that we will perform 
by obtaining separate/additional grant funding; specifically storing specimens (-80ºC) for 
future biomarker association and other relevant translational studies, and as a backup 
DNA source for quality control. We will also seek ancillary/supplemental funding to 
conduct 12- and 24-month follow-up of consenting Aim 1 patients for Aim 3 outcomes. 
 
Aim 2 Study Procedures 
 
Study Medication: Participants in the intervention arm will be given lisinopril at a 
starting dose of 5 mg/day at time of Aim 2 enrollment. Participants in the control arm 
will receive a matched placebo. Participants who are found to have symptomatic 
hypotension and/or new onset /persistent grade 3 (or higher) hyperkalemia after taking 
study medication (as evaluated at day 3 (safety phone call), week 1, month 1, or during 
an unscheduled visit will be removed from the study. 
 
Participants who tolerate the initial study dose (5 mg/day or placebo) will be increased 
to 10 mg/day lisinopril (or matched placebo) at their one (1)-month study visit. All 
study participants having a dose change/escalation from 5 to 10 mg active medication 
(or matched placebo), will also (as was done following study enrollment) undergo safety 
monitoring in the form of a 3-day post dose escalation safety phone call, a 1-week post 
dose escalation study visit for blood draw/safety evaluation, and 1-month post dose 
escalation study visit for blood draw/safety evaluation. Those who do not tolerate an 
increase to the 10 mg/day dose will be returned to the 5 mg/day dose, while those who 
are able to tolerate an increase to the 10 mg/d dose will be closely monitored for 


Protocol Version #: 10.0 
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17 
 
adverse events and re-assessed (see below) at their 3-month study visit for a possible 
dose escalation to 20 mg/d of lisinopril. 
Participants who tolerate the 10 mg/day lisinopril (or matched placebo) will be 
increased to 20 mg/day lisinopril (or matched placebo) at their three (3)-month study 
visit. All study participants having a dose change/escalation from 10 to 20 mg active 
medication (or matched placebo), will also (as was done following study enrollment and 
following the 1 month lisinopril dose escalation (from 5 to 10 mg/day)) undergo safety 
monitoring in the form of a 3 day post dose escalation safety phone call, a 1 week post 
dose escalation study visit for blood draw/safety evaluation, and a 1 month post dose 
escalation study visit for blood draw/safety evaluation. Those who do not tolerate an 
increase to the 20 mg/day dose will be returned to the 10 mg/day dose, while those who 
are able to tolerate an increase to the 20 mg/day dose will be closely monitored for 
adverse events and re-assessed (see below) at their 5-month study visit for a possible 
dose escalation to 40 mg/d of lisinopril. 
 
 
Participants who tolerate the 20 mg/day lisinopril (or matched placebo) will be 
increased to 40 mg/day lisinopril (or matched placebo) at their five (5)-month study 
visit. All study participants having a dose change/escalation from 20 to 40 mg active 
medication (or matched placebo), will also (as was done following study enrollment and 
following the 1 month lisinopril dose escalation (from 10 to 20 mg/day)) undergo safety 
monitoring in the form of a 3 day post dose escalation safety phone call, a 1 week post 
dose escalation study visit for blood draw/safety evaluation, and a 1 month post dose 
escalation study visit for blood draw/safety evaluation. Those who do not tolerate an 
increase to the 40 mg/day dose will be returned to the 20 mg/day dose, while those who 
are able to tolerate an increase to the 40 mg/day dose will remain at 40 mg/day for the 
duration of the study. For specifics regarding criteria to be intensively monitored (i.e. 
blood pressure, serum K+ values, and changes in renal parameters (eGFR and serum 
creatinine) during all study medication (or matched placebo) dose titrations, please see 
<Table 3: Aim 2 Study Medication (Matched Placebo) Dose Titration Algorithm= on 
pages 25-26 for details. 
Alternative medications: Patients who develop side effects to lisinopril (particularly 
refractory cough) will be transitioned to the equivalent dose of an angiotensin receptor 
blocker (ARB), losartan, at a dose of 25 or 50 mg/day (depending on the dose of 
lisinopril (or matched placebo) they were receiving at the time of their adverse event). 
Most patients that develop a refractory cough on lisinopril (which we believe will be few) 
if they need anti-hypertensive control will be switched from lisinopril to 50 mg/d of 
losartan. A few patients may develop a refractory cough very early on study medication 
(within first 1-2 months of enrollment), and such patients, if they still require anti- 
hypertensive medication control may be switched to 25 mg/d of losartan. Patients in 
need of anti-hypertensive treatment that developed a refractory cough while on study 
medication will all need to be unblinded due to the severity of this adverse event and 
most importantly so it can be listed on the patient’s active list of medication side effects, 
so they will not be prescribed ACE inhibitors again in the future. Patients who do not 
tolerate either study medication (lisinopril or losartan) will be removed from the study and 
referred to care if needed (see Figure 2 for details). 
 
Figure 2. Flow diagram of study medication dosing. Endpoints are outlined in green. 
Symptomatic hypotension will be defined as a reading of lower than 90 mm Hg systolic 


Protocol Version #: 10.0 
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18 
 
or 60 mm Hg diastolic with associated symptoms (i.e. feeling of lightheadedness, 
weakness) (NOTE: All low blood pressure readings will be confirmed, orthostatic blood 
pressure will be obtained (when clinically indicated/appropriate), and all readings will be 
put in context of the individual’s normal BP readings). Patients removed from the study 
due to failure to tolerate either the primary (lisinopril) or alternative (losartan) study drug 
will be unblinded (outlined in red) so as to enable their physician to best treat any 
conditions. (NOTE: Hyperkalemia will be graded using established DAIDS Toxicity 
grading Scale (Version 2.1, July 2017); with grade 1 hyperkalemia = 5.6-5.99 mmol/L, 
grade 2 hyperkalemia = 6.0-6.49 mmol/L, grade 3 hyperkalemia = 6.5-6.99 mmol/L and 
grade 4 hyperkalemia (K+ values) being g 7.0 mmol/L). 
Nigeria standard of care: The Nigeria HIV/AIDS adult treatment guidelines recommend 
a baseline assessment of all HIV-positive patients to include a complete history and 
physical examination, staging of disease with clinical and immunological classification of 
the patient, and review of laboratory results. In addition, an evaluation of nutritional and 
psychosocial status, assessment of readiness for therapy, and development of patient- 
specific adherence strategy is recommended for all patients. All HIV-positive patients, 
regardless of CD4+ cell count (commonly referred to as the <Test-and-Start= or <Treat 
All= strategy) are started on ART. First line regimens include: tenofovir (TDF) + 
lamivudine (3TC) + efavirenz (EFV); TDF + 3TC + nevirapine (NVP); zidovudine (AZT) 
+3TC (or emtricitabine [FTC]) + EFV and AZT +3TC (or FTC) + NVP. A boosted 
protease inhibitor plus 2 nucleoside reverse transcriptase inhibitors (NRTIs) are 
recommended for second-line ART, and available protease inhibitors include ritonavir- 
boosted lopinavir and atazanavir. The government of Nigeria will be transitioning to TLD 
(tenofovir, lamivudine, plus the integrase strand inhibitor dolutegravir) during 2018-2019. 
As a result, all HIV positive persons (> 10 years of age and weighing > 30 kilograms) will 
be switched to TLD during this transition period in accordance with national 
guidelines/WHO recommendations. In patients with renal insufficiency, i.e. a 
documented increase in serum creatinine, the guidelines recommend ART regimen 
dosage modifications if the calculated creatinine clearance (CrCl) is reduced at baseline 
(i.e. not initiating tenofovir in adult patients having a calculated eGFR of < 50 
ml/min/1.73m2 or if at any time during follow-up their CrCl decreases significantly (i.e. 
confirmed to < 50 ml/min/1.73m2 from their baseline values). Modifications include 
switching patients from tenofovir to abacavir as well as investigating potential causes of 
their worsening renal function (i.e. looking for pre-renal causes such as dehydration, 
post-renal causes (prostatic obstruction, nephrolithiasis, and/or intra-renal causes such 
as initiation of new potentially nephrotoxic medications (such as traditional medicines, 
etc.). Of note, patients switched to dolutegravir (from efavirenz or nevirapine) as part of 
the soon to commence TLD rollout may also experience a sustained increase in their 
serum creatinine coupled with a corresponding decrease in their calculated eGFR. In 
brief, for a period of up to 48 weeks following dolutegravir (DTG) initiation, it is 
anticipated that study participants may experience a modest (0.2 mg/dL) increase in 
serum creatinine127-129 that will not lead to significant changes in uACR values but will be 
lead to aim 2 study participants having a <new baseline eGFR= that is unrelated to study 
medication and based on the literature using iohexol 130 will not represent a true change 
in eGFR; but nonetheless will still need to be accounted for in the analysis plan. NOTE: 
Given the known limitations of CysC-based equations for HIV-positive individuals, from 
an analysis standpoint, the team will utilize/rely on significant changes in serum 
creatinine (sCr) safety monitoring/reporting among DTG-treated study participants. 
Patients with reductions in CrCl should undergo an evaluation for potential causes of 
decreased renal function and have serum creatinine monitored more frequently until 


Protocol Version #: 10.0 
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19 
 
resolution of renal insufficiency or failure. Adjustments to medication dosages should be 
based on recommendations by drug manufacturers. The national treatment guidelines 
recommend that routine follow-up assessment of HIV-positive patients should cover: 
signs/symptoms of HIV-related conditions and potential medication toxicities; adherence; 
response to therapy; weight; and laboratory monitoring. Every 3 months, the patient 
should undergo a physical exam and clinical screening for tuberculosis (TB). Every 6 
months, the following tests should be performed: CD4+ cell count, hemoglobin (Hgb) 
and hematocrit (Hct), alanine aminotransferase (ALT), and calculated creatinine 
clearance (CrCl). Viral load testing is recommended every 6 months. Asparate 
aminotransferase (AST), alkaline phosphatase (alk phos), fasting blood glucose (FBG), 
glycosolated hemoglobin (Hgb A1C), amylase, urine pregnancy testing, lipid profiles 
(including total/LDL/HDL cholesterol and serum triglyceride levels), serum electrolytes 
(including sodium, potassium, chloride, bicarbonate, blood urea nitrogen, and 
creatinine), sputum for acid fast bacilli (AFB) (for TB screening using conventional 
microscopy and/or GeneXpert MTB/RIF technology), and chest radiography will be 
performed as clinically indicated. 
 
Longitudinal Study Assessments: All enrolled patients will undergo the following tests 
at baseline and then every 3 months while on study, until completing 2 years of follow- 
up: serum cystatin C, blood pressure, serum electrolytes (creatinine, potassium, 
sodium, chloride, bicarbonate, and urea), and uACR. Clinical performance status (as 
measured via the WHOQOL-HIV tool and the Karnofsky performance score) will be 
evaluated at baseline and at 12 and 24 months. If participant is a female with 
reproductive potential, she will undergo urine pregnancy testing every 3 months (please 
see below in NOTE). All enrolled aim 2 study participants will have their APOL1 
genotype data (i.e. whether HR or LR genotype) available prior to completing study 
follow-up (see Study Timeline). All patients will undergo routine standard laboratory 
monitoring as per existing guidelines; specifically, CD4+ cell count and viral load testing 
(q 6 monthly), liver function test monitoring (at month 1, 3, and 6, and then q 6 monthly 
following ART initiation), etc., as per Nigeria standard of care (SOC). All enrolled 
patients will undergo a blood pressure check and have serum electrolytes tested at week 
1 and month 1 following study initiation and any changes in dose as part of a brief safety 
check. All enrolled patients will undergo hepatitis B and C screening at baseline. 
Additional funds have been allocated for patients to undergo unscheduled safety 
monitoring (up to two additional times per year) as needed, while on study. 
 
NOTE: Females with reproductive potential will receive extensive education regarding 
the risks of ACEi therapy; namely the potential risk of congenital abnormalities during the 
first trimester (one study131) as well as the documented increased risk of fetal renal 
damage in the 2nd and 3rd trimesters.132 All reproductive-aged females will undergo pre- 
enrolment and q 3-monthly urine pregnancy testing and, if they test positive, they will be 
immediately unblinded and their study medication (if on active study medication; i.e. 
lisinopril) will be discontinued immediately and an appropriate substitution will be made if 
needed (i.e. anti-hypertensive).131,132 We will also educate all enrolled women having 
reproductive potential to immediately report to the study staff if they suspect being 
pregnant. If they do suspect being pregnant, they will immediately report to the research 
team, their ACEi will be discontinued, and they will undergo the necessary evaluations 
(i.e. urine pregnancy testing) with alternative anti-hypertensive medications being 
prescribed as needed among women confirmed as being pregnant. 


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Study medication and adherence: The medication or placebo will be provided to each 
study participant at no cost to the participant. Study medications will be stored at the 
clinical site in a locked storage cabinet that will be accessible to the study pharmacist 
and site PI. The study pharmacist will ensure the medicine is stored properly and 
dispensed only when needed for study participants. The site investigators will assure the 
medicine is stored properly and dispensed only when need for study participants to by 
the clinical pharmacist designated at the clinical site. The following will be monitored and 
completed on a continuous basis to assure the medicine is within study guidelines, 
onsite pharmaceutical compliance, and manufacturer guidelines: 
 
1. Delivery Log of Medication 
2. Drug Accountability Record 
3. Drug Safety and Handling Sheet 
We will ascertain adherence to study medication via self-report, medication possession 
ratio (using pharmacy prescription/dispensing data),133 and by measuring change in blood 
pressure (post hoc) among patients randomized to the intervention (ACEi) arm. We will 
also measure adherence using a modified version of the brief medication questionnaire 
(BMQ)134 every six months, and the score will be shared with the patient during this visit 
(i.e., high, average, or poor adherence). Using evidence-based strategies,22-24 we will 
implement educational and behavioral interventions that have proven successful in other 
studies for persons categorized as having poor adherence (g1 points). For persons 
demonstrating average to high adherence (<1 point), we will implement positive 
reinforcement with the continuation of educational interventions throughout the study.21,23 
 
 
 
 
Randomization procedures (including assignment of randomized participants into 
6 (six) strata based on uACR and APOL1 risk allele genotype: 
The randomization process will be a stratified randomization with varied block sizes and 
random block sequences. The stratified randomization addresses the need to balance 
the baseline uACR values and high-risk genotypes among the intervention and control 
groups. Enrolled patients will be stratified into six groups by uACR values and number of 
high risk alleles of range 30-59 + 2 high risk alleles, 30-59 + 1 high risk allele, 30-59 + 0 
high risk alleles, 60-300 + 2 high risk alleles, 60-300 + 1 high risk allele, and 60-300 + 0 
high risk alleles, and the six groups will have approximately 35, 35, 70, 35, 35, and 70 
patients respectively. These six strata are determined to make sure that the study arms 
are well-balanced and that we will have enough participants with high risk genotypes to 
be able to complete Aim 3 of the study. This decision tries to find a balance between 
recommendations to keep the number of strata as small as possible (3 to 4 strata is 
generally advisable with an average of 50-100 patients per stratum)135 while ensuring 
that we have adequate numbers of persons with high risk genotypes. Relatively small 
block sizes of 2, 4, and 6 will be used in order to ensure balanced group sizes among 
the two arms over time. To make the allocation of participants unpredictable, the 
sequence of blocks will also be randomized. Three series of randomly ordered letters of 
<A= and <B= will be generated using R software. The blockrand package of R will be used 
to generate random treatment assignment using the block design described above. To 
ensure there are enough random assignments for each group, we will generate lists of 
size 50, 50, 100, 50, 50, and 100 for the 6 strata. 


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6.0 
Study Safety Monitoring Plan 
 
Study participants will be recruited and consented at AKTH, Kano, Nigeria. Adherence to 
human subject regulations will primarily be the responsibility of the Multiple PIs. The study 
team will adhere to all requirements by: (i) developing a study protocol that is able to meet 
its stated research objectives, and thus reflect adequate risk-benefit ratios for human 
subjects; (ii) specifying study procedures in the protocol that protect the rights and safety 
of human subjects; (iii) developing a recruitment script and informed consent forms that 
include all elements of consent required by Federal regulations and accurately represents 
study requirements, risks, and benefits in language that is understandable to study 
participants, including human subject considerations; and (iv) monitoring adherence to 
protocol specifications and human subject requirements. The consent forms, protocol, and 
any subsequent modifications will be reviewed and approved by the Institutional Review 
Boards (IRB) at Vanderbilt University (FWA00005756), and AKTH (FWA00010841). 
 
A. Adverse Event (AE) Assessment 
1. Anticipated risks 
Risks that are expected/anticipated as part of participation in the study are detailed 
in the study information and consent forms that will be distributed to and reviewed 
with patients by trained study team members. These risks are described below, 
along with steps that will be taken to minimize these risks: 
 
Risks of blood draws: As described in Study Procedures (Section 6.0), blood 
specimens will be collected from each participant by routine venipuncture. The 
risks of venipuncture include discomfort at the site of puncture; possible bruising 
and swelling around the puncture site; and rarely an infection. We expect no 
additional psychological or social harms to occur. Other risks may include pain, 
bleeding, or bruising where the needle enters the skin; lightheadedness; and in 
rare cases, fainting or infection. These risks will be minimized by hiring study staff 
who are well trained in phlebotomy and other clinical procedures. 
Risks of study medication (lisinopril and losartan) 
The common side effects of lisinopril includes the following: cough, headache, 
dizziness, depressed mood, drowsiness, gastrointestinal symptoms such as 
nausea, upset stomach, vomiting or diarrhea, and skin symptoms such as mild 
itching or a rash. Any patients experiencing persistent/refractory cough that is 
deemed possibly related to their lisinopril therapy (as a refractory cough has been 
reported in as many as 6-8% of participants, with higher rates seen in person of 
African descent (up to 12% in some studies), will be switched to an equivalent dose 
of the ARB losartan, as described above. Patients switching from lisinopril to 
losartan will remain on study (Aim 2), as a switch from an ACEi to an ARB is an 
allowable study substitution. Common side effects of losartan include the following: 
cold or flu-like symptoms such as stuffy nose, sneezing, sore throat, fever; dry 
cough; muscle cramps; pain in legs or back; stomach pain or diarrhea; headache 
or dizziness; tired feeling or insomnia. 
 
Refractory Cough: Cough occurs in 5-15% of patients. It is not dose- or brand- 
related, is more frequent in women than men, and is more frequent in persons of 
African descent (blacks) than Caucasians (whites). It usually develops within 1 


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week to 6 months following ACEi initiation and typically resolves within 4 days of 
cessation. Study investigators need to be aware of a confounding congestive heart 
failure cough and remember that changing to another formulation sometimes 
helps. NOTE: Persons with a history of chronic h/o congestive heart failure are 
not eligible for aim 2. Cough is not a reason to discontinue treatment unless it 
persists (and or escalates in intensity/severity) and/or study participants feel that 
they cannot tolerate it. A few studies have looked at the use of nonsteroidal anti- 
inflammatory drugs (NSAIDs), nifedipine, cromolyn, or nebulized bupivacaine for 
managing cough, but further studies are needed. Any aim 2 participants 
developing a cough (that is deemed new and significant by the study participant; 
and/or is grade 2 or higher as per DAIDS toxicity grading criteria; needs to involve 
the SOC and SSC. Each case will be handled on a one-on-one basis and 
decisions to hold or discontinue study medication will be made depending on the 
severity, progression (or lack thereof) and response to holding/discontinuing study 
medication. (NOTE: Please refer to <Table 3: Aim 2 Study Medication 
(Matched Placebo) Dose Titration Algorithm= for specific details). 
 
Teratogenicity (Pregnancy Considerations): Lisinopril has been found to be 
teratogenic in mice and therefore is classified as class D by the FDA. All women 
of childbearing age (and potential) in this study will be extensively counseled about 
these potential risks and will be linked to family planning/spacing services, if 
desired. They will also undergo urine pregnancy testing at the beginning of the 
study and every three months at no cost. Any participant found to be pregnant will 
be withdrawn from the study. In addition, all women of childbearing age (and 
potential) will be extensively counseled and told to come immediately to clinic if 
they suspect for any reason that they may have become pregnant; i.e. 
missed/delayed menses, unexpected weight gain, etc. 
Hyperkalemia: Given the potential risk for hyperkalemia in this study population, 
all study team members will be trained to educate participants on the risk of 
hyperkalemia, as well as prevention measures (e.g. maintaining adequate 
hydration, avoiding potentially nephrotoxic substances such as traditional 
medicines, etc.). Study team members will also train participants to recognize 
signs and symptoms of hyperkalemia, and study clinicians will be specifically 
trained on the risk, diagnosis, and management of hyperkalemia. We will explain 
to all study participants that lisinopril may cause hyperkalemia, and we will explain 
this in detail in the consent also strongly encouraging all study participants to notify 
our study staff before initiating any new medications or over-the-counter remedies, 
as we want to be sure that none of the new medications they are planning to start 
are associated with the possible risk of precipitating hyperkalemia. To protect 
study subjects and monitor them for this possible side effect, we will be performing 
frequent serum electrolyte monitoring; scheduled at least every three months while 
on study (Aim 2), including one additional serum electrolyte safety check visit at 
one week and at one month for all Aim 2 participants. (NOTE: Please refer to 
<Table 3: Aim 2 Study Medication (Matched Placebo) Dose Titration 
Algorithm= below for specific details). Participants will be extensively educated 
and told to call or come into the clinic if they experience decreased urine output, 
fatigue, 
palpitations, 
dyspnea, 
lightheadedness, 
and/or 
generalized 
fatigue/malaise. Patients receiving concomitant medications that have also been 
known to potentially cause hyperkalemia (i.e. cotrimoxazole (Emtrim™), the ARV 


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medication dolutegravir (DTG), and other medications) will undergo more frequent 
serum electrolyte/safety monitoring. 
Angioneurotic edema: Angioneurotic edema, which occurs in 0.1- 0.2% 
of patients, usually develops within the first week of therapy but can occur at any 
time. This life-threatening adverse effect also occurs with angiotensin II receptor 
blockers but to a lesser extent. Any patient with a history of angioneurotic 
edema, whether related to an ACE inhibitor, angiotensin receptor blockers (ARBs), 
or another cause, should not be given an ACE inhibitor. (NOTE: any allergic 
reaction that is <definitely related= or <possibly related to study medication= that 
involves generalized urticaria OR angioedema with intervention indicated OR 
symptoms of mild bronchospasm is classified as a grade 3 acute allergic reaction 
and an SAE is needed and the participant is immediately unblinded, and if on active 
study medication (ACEi or ARB) it is to be discontinued immediately, and this 
allergic reaction is to be documented in their medical record. If the participant has 
acute anaphylaxis OR life-threatening bronchospasm OR laryngeal edema; this is 
a grade 4 acute allergic reaction and an SAE is needed and the participant is 
immediately unblinded, and if on active study medication (ACEi or ARB) it is to be 
discontinued immediately, and this allergic reaction is to be documented in their 
medical record. 
 
Changes in blood pressure (Hypotension): Lastly, lisinopril may also cause 
and/or exacerbate changes in blood pressure, specifically hypotension given its 
primary indication for use as an anti-hypertensive agent. Such changes can occur 
at any time (and at any dosage) while on lisinopril, but in most cases reductions in 
blood pressure +/- with the associated symptoms of hypotension (i.e. dizziness, 
lightheadedness, fatigue/malaise, new onset or worsening headache, etc.) occur 
within the first 1-4 weeks following lisinopril (ACEi) initiation. To protect study 
subjects and monitor them for this possible side effect, we will be performing 
frequent blood pressure (BP) monitoring; scheduled at least every three months 
while on study (Aim 2), including one additional blood pressure (BP) safety check 
visits at one week and at one month for all Aim 2 participants. (NOTE: Please refer 
to <Table 3: Aim 2 Study Medication (Matched Placebo) Dose Titration 
Algorithm= below for specific details). Participants will be extensively educated 
and told to call or come into the clinic if they experience lightheadedness, 
dizziness, fatigue/malaise, weakness, new onset or worsening headache, etc. 
Patients receiving concomitant medications that have also been known to 
potentially cause or exacerbate changes in blood pressure (i.e. other anti- 
hypertensive medications such as thiazide diuretics (i.e. hydrochlorothiazide 
(HCTZ), etc.), calcium channel blockers (i.e. nifedipine, amlodipine, diltiazem, 
etc.), ß (Beta) blockers (i.e. metoprolol, propranolol, atenolol, carvedilol, etc.) and 
other classes of/specific anti-hypertensive (i.e. hydralazine, clonidine, etc.) and/or 
anti-anginal/cardiac protective medications (i.e. nitroglycerin, isosorbide mono- 
and dinitrate, etc.) will undergo more frequent blood pressure/safety monitoring. 


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Table 3:  Aim 2 Study Medication (Matched Placebo) Dose Titration Algorithm 
Parameter / 
Guidelines to 
follow 
Systolic blood pressure (SBP) 
Serum potassium (K+) 
Step 1 to 2 
(5 mg/d ↑ to 10 
mg/d) 
SBP > 110 (ESCALATE) 
 
SBP 100-110 (Repeat BP and √ for 
symptoms/perform orthostatics) (Escalate 
only if repeat SBP > 110 or repeat SBP 
100-110 without symptoms and based on 
record review4confirmed that patient’s 
normal BP in this range) 
 
SBP < 100 (Hold and repeat BP; if repeat 
SBP < 100 and/or patient with + 
symptoms (low BP) then do not escalate); 
have patient come back in 1 week (or 
sooner) for safety visit (BP √) and re- 
assess (Involve SOC/SSC) 
NOTE: Any hypotensive episode when 
associated symptoms are corrected with 
oral fluid replacement is a grade 2 
hypotensive event; when symptoms AND 
IV fluids indicated it is grade 3; and when 
this hypotensive event is classified as 
shock requiring use of vasopressors or 
mechanical assistance to maintain blood 
pressure, this is a grade 4 event. 
K+ < 5.0 (ESCALATE) 
 
K+ 5.0 – 5.5 
(Repeat BMP and have patient come back in 
1-2 days for safety √); if repeat K+ < 5.0 and 
creatinine stable4ESCALATE; 
If repeat K+ 5.0 3 5.5; Hold and repeat BMP in 
1 week; and re-assess (if repeat still 5.0-5.5; 
Involve SOC/SSC) 
NOTE: If any repeat K+ between 5.5 3 6.0 and 
no other discernible cause (i.e. dehydration, 
etc.) then complete SAE and hold study 
medication and follow advice of SOC/SSC 
 
If any K+ > 6.0, complete SAE; and 
discontinue study medication 
Step 2 to 3 
(10 mg/d ↑ to 20 
mg/d) 
Same as above for Step 1 
K+ < 5.0 (ESCALATE) 
 
K+ 5.0 – 5.5 
(Repeat BMP and have patient come back in 
1-2 days for safety √); if repeat K+ < 5.0 and 
creatinine stable4ESCALATE; 
If repeat K+ 5.0 3 5.5; Hold and repeat BMP in 
1 week; and re-assess (if repeat still 5.0-5.5; 
Involve SOC/SSC) 
If repeat K+ 5.0 – 5.5; Hold and repeat BMP 
in 1 week; and consider re-initiating study 
medication at 50% of prior dose (monitoring 
K+ closely) 
If any K+ > 6.0, complete SAE and 
discontinue study medication 
Step 3 to 4 
(20 mg/d ↑ to 40 
mg/d) 
Same as above for Step 1 
Same as above for Step 1 
Parameter / 
Guidelines to 
follow 
Serum creatinine (sCr) 
Estimated glomerular filtration rate (eGFR) 


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Step 1 to 2 
(5 mg/d ↑ to 
10 mg/d) 
sCr < 90 μmol/L (or < 1.0 mg/dL) for 
FEMALES OR < 110 μmol/L (or < 1.2 
mg/dL) for MALES (ESCALATE) 
sCr remains < 1.2x below baseline 
(ESCALATE) 
sCr increases between 1.2 - 1.3x from 
baseline (Repeat ScR and monitor 
closely for signs of worsening kidney 
function; i.e. decreased urinary output, 
fatigue, palpitations, dyspnea, 
lightheadedness, and/or generalized 
fatigue/malaise). If repeat sCr normalizes 
(< 1.2x below baseline value) 
(ESCALATE) 
NOTE: Any time sCr increase 1.3 -1.8x 
the upper limit of normal (ULN) OR sCr 
increases between 1.3 - 1.49x from 
baseline; this constitutes a grade 2 event. 
Any time sCr increase 1.8 – 3.49x the 
ULN OR sCr increases between 1.5 – 
1.99x from baseline; this constitutes a 
grade 3 event (and requires an SAE to be 
completed) 
 
Anytime sCr increases by ≥ 1.3-fold; 
immediately HOLD study medication; 
look for other possible 
etiologies/contributing factors; and monitor 
closely; repeating BMP within 1 week; If 
repeat sCr normalizes (< 1.2-fold below 
baseline value) (ESCALATE); but if sCr 
elevations persist by ≥ 1.3-fold from 
baseline; continue to HOLD study 
medication; involve the SOC/SSC; as 
study medication may need to be 
discontinued and AE report done 
 
NOTE: All study participants receiving 
dolutegravir (DTG)-based ART may 
experience a sustained increase in serum 
creatinine (sCr) (up to 0.2 mg/dL) that 
may persist for up to 48 weeks (or 
possibly longer) so to account for these 
potential modest changes in renal 
function, all safety events involving kidney 
function deemed <possibly= or <definitely 
related= to study medication among DTG- 
treated study participants will be 
evaluated and graded using serum 
creatinine (sCr) measurements. 
eGFR remains stable (and if diminishes; 
does so by < 20% (ml/min/1.73m2 (using 
CKD-EPI-Cr-CyC equation)) when compared 
to baseline eGFR; (ESCALATE) 
eGFR decreases by 10-20% when 
compared to baseline; (Repeat eGFR within 
1 week and monitor closely for signs of 
worsening kidney function 
 
eGFR worsens by 20-29% when compared 
to baseline (Repeat eGFR within 1 week and 
monitor closely for signs of worsening kidney 
function; i.e. decreased urinary output, fatigue, 
palpitations, dyspnea, lightheadedness, and/or 
generalized fatigue/malaise). If repeat eGFR 
improves/normalizes (i.e. is reduced < 20% 
when compared to baseline) (ESCALATE) 
NOTE: A 10-20% decrease in eGFR in 
baseline constitutes a grade 2 event; and 
when any patient experiences a > 10% decline 
in eGFR (from baseline), their renal function 
needs to be more intensively monitored. A 
decrease in eGFR between 30-50% (from 
baseline) constitutes a grade 3 event (and 
requires an SAE to be completed) 
Anytime eGFR diminishes by > 30% from 
baseline; immediately HOLD study 
medication; look for other possible 
etiologies/contributing factors; and monitor 
closely; repeating eGFR within 1 week; If 
repeat eGFR improves/normalizes (< 20% 
below baseline value) (ESCALATE); but if 
eGFR reductions persist by ≥ 30% from 
baseline; continue to HOLD study 
medication; involve the SOC/SSC; as study 
medication may need to be discontinued 
and AE report done 
Any study participant experiencing a drop 
in eGFR (at any time) to < 50 ml/min/1.73m2 
(using CKD-EPI-Cr-CyC equation); 
immediately HOLD study medication; look 
for other possible etiologies/contributing 
factors; and monitor closely; repeating eGFR 
within 1 week; involve the SOC/SSC; as 
study medication may need to be discontinued 
and AE report done 
Step 2 to 3 
(10 mg/d ↑ to 
20 mg/d) 
Same as above for Step 1 
Same as above for Step 1 


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Step 23to 4 
(20 mg/d ↑ to 
40 mg/d) 
Same as above for Step 1 
Same as above for Step 1 
 
Risks of prescribed combination antiretroviral therapy (ART) (specifically tenofovir 
(TDF): 
All eligible/enrolled aim 2 study participants will be receiving ART for 6+ months, 
and we anticipate that a significant proportion (i.e. > 80%) of them will be receiving 
tenofovir (TDF)-based regimens. We mention this because of the potential 
adverse events that have been attributed to the nucleotide reverse transcriptase 
inhibitor TDF, namely kidney toxicity which may manifest as a reduction in eGFR. 
These potential TDF-associated kidney manifestations that include reduced 
eGFR, Fanconi’s syndrome, etc. are due to tubular (rather than glomerular) insults; 
and they often present within the first 1-2 years following TDF initiation and based 
on our preliminary analysis of enrolled aim 1 study participants (January 2019), the 
majority of aim 1 study participants (from which we will be screening/enrolling for 
aim 2) have been receiving ART for considerably longer periods of time (i.e. mean 
duration of ART > 8 years). 
 
Management of Worsening Renal Function Among Study Participants receiving 
tenofovir (TDF)-based ART regimens: 
At an eGFR of 30-49 ml/min/1.73m2, patients receiving a TDF-based regimen 
should ideally have their dose modified to 300 mg q48 hours. If the eGFR falls 
further into the 10-29 ml/min/1.73m2 range, the dose should be adjusted to 300 mg 
q72 hours. However, these recommended dose adjustments are difficult to 
implement as most of the ARV regimens are dispensed as fixed drug combinations 
(FDCs). In addition, adjusting the dose to alternate day dosing makes things very 
challenging logistically and may promote poor adherence due to the increased 
likelihood of patients missing/forgetting doses. Therefore, at an eGFR 30-49 
ml/min/1.73m2, the standard of care (SOC) is to switch tenofovir (TDF) to an 
alternative NRTI (i.e. abacavir (ABC)); realizing that if the person is receiving 
abacavir plus lamivudine (3TC), the 3TC will need to be renally adjusted given that 
it is renally excreted (and 3TC dosing will be adjusted/modified per established 
standards). The on-site study team is to notify/involve the SOC/SSC of any/all 
participants with worsening renal function (as outlined above) so they can assist in 
the management, tracking and development of AE/SAE forms (as needed). 
Management of worsening renal function among persons receiving TDF plus study 
medication (lisinopril/matched placebo) 
The study team needs to immediately investigate for a potential cause of declining 
eGFR (i.e. looking for pre-renal causes such as dehydration, post-renal causes 
(prostatic obstruction, nephrolithiasis, and/or intra-renal causes such as initiation 
of new potentially nephrotoxic medications (such as traditional medicines). We 
should not wait until the eGFR drops to <50 ml/min/1.73m2 before we discontinue 
the study medication. Further clinical decisions RE: management is to be based 
on the cause of declining eGFR. Please refer to <Table 3: Aim 2 Study 
Medication (Matched Placebo) Dose Titration Algorithm= for specific 
management details. In addition, in terms of specific management, if a study 


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participant’s calculated eGFR drops < 50 ml/min per 1.73m2, the team will need to 
complete an AE report (send to the SOC/SSC) and update as needed. At this 
level of kidney function decline (< 50 ml/min per 1.73m2), the study participant’s 
study medication needs to be immediately held and the patients need to be 
thoroughly evaluated for other potentially contributing causes of worsening kidney 
function; i.e. volume contraction (dehydration, sepsis, GI bleeding, etc.), 
obstruction, 
nephrotoxin 
(any 
potentially 
nephrotoxic 
medication 
(i.e. 
aminoglycosides, etc.), IV contrast, traditional medicines, etc.), and/or other 
causes (rhabdomyolysis, etc.). During this time of study medication hold, the 
participant needs to be monitored closely and have their blood pressure, 
electrolytes (specifically their K+), and kidney function (serum creatinine and 
calculated eGFR) monitored as deemed necessary by the study team in 
consultation with the SOC/SSC. Patients will need to have their eGFR re- 
evaluated within 7 days (or sooner at the discretion of the treating clinician). If 
their eGFR has not stabilized/improved, with no other apparent etiology for 
worsening kidney function, consider holding tenofovir (TDF)(if on TDF-based ART) 
and/or dose reducing study medication (on a case-by-case basis; also in close 
collaboration/communication with the SOC/SSC). Depending on the kidney 
function/other parameters (i.e. K+, etc.), the study participant may need to be 
switched to an alternative ART regimen (i.e. switch TDF to ABC) and continue to 
monitor; and if their study medication was dose reduced, the on-site team will 
continue to monitor them closely to determine next steps; i.e. permanently 
discontinue study medication and/or other medications or attempt to resume study 
medication and titrate up the dose as deemed appropriate. 
 
If the participants eGFR keeps on falling despite holding the study medication, and 
no other discernible causes for the kidney insult can be identified, we will 
discontinue tenofovir (TDF) and switch/substitute with abacavir (ABC). Please note 
that in Nigeria and other similar resource-constrained settings, the, initiation of 
abacavir (ABC) does not require genetic testing; specifically, HLA-B*5701 testing; 
the risk variant associated with risk for ABC-associated hypersensitivity reactions. 
To maintain integrity of the study, participants will be informed and consented 
about the chance of switching their ARV medications when the need arises. In 
addition, we have emphasized that in a significant proportion of cases, individual 
ARV medications will be substituted (only one medication in the ART regimen will 
be changed (i.e. TDF to ABC) and not the entire regimen, i.e. from first to second 
line ART regimens. 
 
2. Evaluation of subjects for adverse events 
Subjects will be evaluated by a study physician at each visit for AEs. In addition, 
additional safety monitoring visits in the form of scheduled clinic visits and phone 
calls have been included and can be summarized as follows: 
a) Study enrollment/initiation of study medication (5 mg of lisinopril or 
matched placebo) (study entry/enrollment); 
- 
3-day safety phone call (post initiation of study medication (or 
matched placebo) evaluating for possible adverse events (and if 
during phone safety check screening there is any suggestion of a 
possible adverse event, then the participant will be instructed to come 


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in to clinic for immediate evaluation including blood draw and blood 
pressure check) 
- 
7-day safety clinic visit (blood draw plus blood pressure check) 
- 
1-month safety clinic visit (blood draw plus blood pressure check) 
- 
Unscheduled study visit (study participants to contact study 
personnel at any time and if have signs/symptoms at suggestive of 
an adverse event, they will come to clinic for immediate assessment) 
b) b) Dose escalation of study medication (increase from 5 mg/d of lisinopril 
or matched placebo to 10 mg/d) (scheduled to take place at the 1- month 
study visit); 
- 
3-day safety phone call (post initiation of study medication (or 
matched placebo) evaluating for possible adverse events (and if 
during phone safety check screening there is any suggestion of a 
possible adverse event, then the participant will be instructed to come 
in to clinic for immediate evaluation including blood draw and blood 
pressure check) 
- 
7-day safety clinic visit (blood draw plus blood pressure check) 
- 
1-month safety clinic visit (blood draw plus blood pressure check) 
- 
Unscheduled study visit (study participants to contact study 
personnel at any time and if have signs/symptoms at suggestive of 
an adverse event, they will come to clinic for immediate assessment) 
 
 
c) Dose escalation of study medication (increase from 10 mg/d of lisinopril or 
matched placebo to 20 mg/d) (scheduled to take place at the 3- month 
study visit); 
- 
3-day safety phone call (post initiation of study medication (or 
matched placebo) evaluating for possible adverse events (and if 
during phone safety check screening there is any suggestion of a 
possible adverse event, then the participant will be instructed to come 
in to clinic for immediate evaluation including blood draw and blood 
pressure check) 
- 
7-day safety clinic visit (blood draw plus blood pressure check) 
- 
1-month safety clinic visit (blood draw plus blood pressure check) 
- 
Unscheduled study visit (study participants to contact study 
personnel at any time and if have signs/symptoms at suggestive of 
an adverse event, they will come to clinic for immediate assessment) 


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d) Dose escalation of study medication (increase from 20 mg/d of lisinopril or 
matched placebo to 40 mg/d) (scheduled to take place at the 5- month 
study visit); 
- 
3-day safety phone call (post initiation of study medication (or 
matched placebo) evaluating for possible adverse events (and if 
during phone safety check screening there is any suggestion of a 
possible adverse event, then the participant will be instructed to come 
in to clinic for immediate evaluation including blood draw and blood 
pressure check) 
- 
7-day safety clinic visit (blood draw plus blood pressure check) 
- 
1-month safety clinic visit (blood draw plus blood pressure check) 
- 
Unscheduled study visit (study participants to contact study 
personnel at any time and if have signs/symptoms at suggestive of 
an adverse event, they will come to clinic for immediate assessment 
Once participants complete their 4-month study visit including having their study 
medication dose (or matched placebo) increased to 40 mg/d and undergo the 
additional safety visits as outlined in b) and c) above, all study participants will 
continue to undergo scheduled safety/tolerability assessments (study visits during 
which time blood draws and blood pressure evaluations will be performed at a 
minimum of every 3 months. 
 
Additionally, all participants will be counseled to contact study staff or come in at 
any time (including unscheduled visits) if they feel ill, feel that their urine output 
may have diminished, and/or have questions about potential side effects or about 
the care and treatment they are receiving. An interval history of medical events and 
potential adverse events will be obtained at these visits. This information will 
continue to be collected for three (3) months after the participant has stopped the 
study medication. Monitoring for AEs (including unanticipated AEs) will be 
performed by reviewing patient laboratory and clinic data and querying patients at 
each follow-up visit about the occurrence of complications since the patient’s 
previous visit. All AEs will be characterized in terms of <relatedness= to study 
intervention (i.e. study medication) as follows: <definitely related=, <possibly 
related=, <unable to assess relatedness to study medication=, <definitely unrelated 
to study medication= or <possibly related to study medication.= In terms of severity, 
all AEs will be graded on the basis of severity (standard 1-5 grading scale using 
the DAIDS Toxicity Grading Scale; version 2.1, July 2017). 
 
B. Adverse Event Reporting 
 
Definitions 
Definitions are per the January 2007 Guidance on Reviewing and Reporting 
Unanticipated Problems Involving Risks to Participants or Others and Adverse Events, 
Office on Human Research Protection (OHRP) Guidance. 


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https://www.hhs.gov/ohrp/regulations-and-policy/guidance/reviewing-unanticipated- 
problems/index.html 
 
Adverse Event 
An adverse event (AE) is any untoward or unfavorable medical occurrence in a human 
study participant, including any abnormal sign (for example, abnormal physical 
examination or laboratory finding), symptom, and/or disease, temporally associated with 
the participant’s involvement in the research, whether or not this event is considered 
related to the participant’s participation in the research. 
 
Serious Adverse Event 
A serious adverse event (SAE) is any AE that is: 
• 
fatal or results in death 
• 
life-threatening 
• 
requires or prolongs hospital stay 
• 
results in persistent or significant disability or incapacity 
• 
results in congenital anomalies or birth defects 
• 
an important medical event* 
*Important medical events are those that may not be immediately life threatening but are 
clearly of major clinical significance. Based on expert medical judgment, this important 
medical event may jeopardize the subject’s health and may require medical or surgical 
intervention to prevent one of the other outcomes listed above 
 
<Unanticipated Event= Involving Risk to Participants or Others 
An <Unanticipated Event= is any incident, experience, or outcome that meets ALL of the 
following criteria: 
• 
it is unexpected (in terms of nature, severity, or frequency), given the research 
procedures that are described in the IRB-approved research protocol and informed 
consent document and the characteristics of the participant population being 
studied; 
• 
it is <definitely related= or <possibly related= to study medication/participation in the 
research, where <possibly related= means that there is a reasonable possibility that 
the incident, experience and/or outcome may have been caused by the procedures 
involved in the research, and 
• 
it suggests that the research places participants or others at a greater risk of harm 
(including physical, psychological, economic, and/or social harm) related to the 
research than was previously known or recognized. 
 
Pre-Existing Condition 
A <pre-existing condition= is one that is present at the start of the study. A <pre-existing 
condition= will be recorded as an AE if the frequency, intensity, or character of the 
condition worsens during the study period. 


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Adverse Event (AE) Reporting Period 
The study period during which AEs must be tracked and reported is defined as the 
period from the initiation of study procedures to study completion. 
 
Post-Study AEs 
All unresolved AEs will be followed by the investigator until the events are resolved, the 
participant is lost to follow-up, or the AE is otherwise explained. At the last scheduled 
visit, the investigator will instruct each participant to report any subsequent event(s) that 
the participant, or the participant’s personal physician, believes might reasonably be 
related to participation in this study. The investigator will notify the R3 Study Oversight 
Committee (SOC) and the Study Safety Committee (SSC) of any death or AE occurring 
at any time after a participant has discontinued or terminated study participation that 
may reasonably be related to the study. (NOTE: All enrolled aim 2 participants will be 
monitored/tracked for any AEs for 3 months after they complete the study; and any/all 
AEs that occur up to 3 months post study completion will be recorded/captured). 
NOTE: The R3 Study Oversight Committee (SOC) will consist of the MPIs (Drs. 
Wester and Aliyu), the Trial Coordinator, The Program Manager, and the in-country lead 
investigator (Dr. Musa). The Study Safety Committee (SSC) will function independently 
to maintain the integrity of investigations into AEs and will be overseen by two Clinical 
Trials Safety Specialists, namely Drs. Ahonkhai and Burgner. 
 
Recording of AEs 
At each contact with the participant, the Co-Investigators and/or Research Coordinators 
will seek information on AEs by specific questioning and, as appropriate, by 
examination. Information on AEs will be recorded in the source documents as well as on 
the AE log case report form (CRF). All signs, symptoms, and abnormal diagnostic 
procedure results relating to the same event will be recorded under one diagnosis name. 
 
All adverse events (AE), regardless of severity, that is reported to any study team 
member and meets the criteria for an AE, will be documented. This documentation will 
include the date the event occurred or began, the duration of the event (including 
resolution date when applicable), and the date and way in which the event was reported. 
Any clinical or other documentation to corroborate the event will be included in the 
report, as well as any determination of relatedness. All study staff will have access to an 
electronic structured report form in REDCap for these purposes. The form will include 
common side effects of lisinopril, and losartan and classifications based on seriousness, 
expectedness, and relatedness (i.e. <definitely related to study medication=, <possibly 
related to study medication=, <definitely not related to study medication=, or <unable to 
assess if related to study medication=). Unanticipated AEs will include adverse reactions 
that are not consistent (nature or severity) with the available information on lisinopril or 
losartan. The Division of AIDS Table for Grading the Severity of Adult and Pediatric 
Adverse Events (DAIDS AE Grading Table), Version 2.1, July 2017, will be used to 


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determine clinical and laboratory grades of any/all grade 1 or higher events (including 
signs and symptoms, laboratory abnormalities, and diagnoses). 
Anticipated AEs 
The following AEs are anticipated in HIV-positive adults that are initiated on combination 
antiretroviral therapy (ART) and are not considered Unanticipated Problems. As such, 
they would be considered Non-Reportable Events. Please note that most of these side 
effects are typically seen within the first 1-4 weeks following ART initiation. Given that we 
will be enrolling ART-experienced patients (on ART >6 months), we anticipate 
encountering very few (if any) such events in the context of our R3 study. Note that the 
designation <Non-reportable= does not imply that the event is not an SAE but relates to 
the regulatory definition of Unanticipated Problems as provided in previous section. 
• 
Gastrointestinal: Nausea and diarrhea (mild/grade 1) related to antiretroviral 
(ARV) medications; as mild to even moderate GI symptoms are often seen in 
persons in the first 1-6 weeks (sometimes up to 8 weeks) following initiation of 
most ART regimens, but this diarrhea/nausea is typically self-limited and resolves 
on its own. On rare occasions, it can continue/progress to grade 2 or higher and 
any persistent GI symptoms seen in R3 patients (all need to be on ART for 6+ 
months) will be captured/tracked if grade 1 or higher. 
• 
Hepatic: Mild (grade 1 or 2) elevations in total bilirubin among persons receiving 
the boosted protease inhibitor atazanavir/ritonavir (as atazanavir is also known to 
cause asymptomatic elevations in unconjugated hyperbilirubinemia [NOTE: We 
will report when grade 2 or higher or deemed <clinically significant= by study team 
personnel]. 
• 
Neurologic: Dizziness, lightheadedness, abnormal dreams (more vivid dreams, 
nightmares, etc.), and possibly hallucinations (rare) during the first 30 days 
following initiation of an ART regimen that contains the NNRTI efavirenz (EFV) 
[NOTE: We will report when grade 2 or higher or deemed <clinically significant= by 
study team personnel]. Renal: The integrase strand inhibitor dolutegravir (DTG) 
will be coming into wide use for first line ART regimens (and other subsequent ART 
regimen lines) in Nigeria during the study period (2019), pending final safety data, 
consistent with the WHO directive for wide-scale implementation of Tenofovir, 
Lamivudine, plus Dolutegravir (TLD) for first-line ART, given it considerably more 
favorable genotypic drug resistance profile (i.e. significantly higher genetic barrier 
for resistance to develop) and tolerability profile. Of note, DTG induces a 
noticeable increase in serum creatinine following initiation of therapy due to non- 
pathologic tubular blockade of creatinine secretion through the inhibition of 
OCT2.130 DTG can block the tubular uptake of creatinine from the blood, leading 
to increases in serum creatinine and decreased eGFR or creatinine clearance (Cr 
Cl), without changing the true GFR.130 Therefore, based on published literature, an 
anticipated change in renal parameters is expected in study participants shortly 
after switching to DTG-based therapy. Specifically, patients switched to 
dolutegravir (from efavirenz or nevirapine) may experience a sustained increase 
in their serum creatinine coupled with a corresponding decrease in their calculated 
eGFR.  In brief, for a period of up to 48 weeks following dolutegravir (DTG) 


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initiation, it is anticipated that study participants may experience a modest (0.2 
mg/dL) increase in serum creatinine127-129 that will not lead to significant changes 
in uACR values but will lead to aim 2 study participants having a <new baseline 
eGFR= that is unrelated to study medication and based on the literature using 
iohexol 130 will not represent a true change in eGFR; but nonetheless will still need 
to be accounted for in the analysis plan. NOTE: Given the known limitations of 
CysC-based equations for HIV-positive individuals, from an analysis standpoint, 
the team will utilize/rely on significant changes in serum creatinine (sCr) for safety 
monitoring/reporting among DTG-treated study participants. 
 
 
Non-Reportable Events 
Please see above <Anticipated AEs= section as the R3 study does not have any non- 
reportable events, other than these mild potential side effects (grade 1 only). 
 
Reporting of SAEs and Unanticipated Problems 
Study sites are required to report SAEs in REDCap to the R3 SOC and SSC within 24 
hours of first knowledge of the event. To report such events, an SAE form will be 
completed by the investigator and faxed or emailed to the SOC/SSC. The SOC/SSC will 
facilitate the timely medical review and reporting of the event and provide reports to the 
NIDDK and the Data and Safety Monitoring Board (DSMB) in accordance with DSMB- 
approved study policies and regulatory requirements. All AEs will be reviewed within 48 
hours, and an appropriate course of action will be determined. All study staff will also be 
encouraged to report any SAEs directly to the SOC and SSC by phone or direct email, 
as it is essential that they are notified with 24 hours of the study team member learning 
of the event. 
Any/all grade 3 (i.e. grade 3 = <severe=; grade 4 = <life-threatening= and grade 5 = <death=), 
grade 3 or higher events deemed <definitely related to study medication= or <possibly related 
to study medication=, and/or unanticipated adverse events will be reported to both IRBs (VU 
and AKTH), NIDDK, and the DSMB within 48 hours of the site becoming aware of the 
event. Non-serious (grade 1 or 2) unanticipated AEs will be reported to both IRBs and 
NIDDK within as outlined on Table 3 below; namely internally reviewed/reported from the 
study site to the SOC/SSC on a monthly basis and submitted/reported to the involved 
IRBs and NIDDK on a quarterly basis. All unanticipated events will be reported to the 
chair of the DSMB and the NIDDK Program Officer within 48 hours. Any determination by 
either IRB that results in a temporary or permanent suspension of the study will be 
immediately reported to NIDDK and the DSMB (within 24 hours of receiving notice from 
the IRB). Please refer to <Table 3: R3 Adverse Event Reporting Timeline= for 
full/specific details). 
 
The study leadership (i.e. the Vanderbilt-based SOC as well as on-site Co-Investigators 
and Research Coordinator) will keep a copy of the SAE form on file at the study site 
(AKTH). At the time of the initial report, the following information should be provided: 


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▪ 
Study identifier 
▪ 
Participant ID number 
▪ 
A description of the event 
▪ 
Date of onset 
▪ 
Current status 
▪ 
Whether 
study 
treatment 
was 
discontinued 
▪ 
The reason the event is classified as 
serious or unanticipated 
▪ 
Investigator 
assessment 
of 
the 
<relatedness= between the event and 
study participation 
 
 
Within the following 7 days, the investigator will provide the SOC and SSC further 
information on the SAE or the unanticipated problem in the form of a written 
narrative. This should include a copy of the completed SAE form, and any other 
diagnostic information that will assist in the understanding of the event. Significant new 
information on ongoing SAEs should be provided promptly to the SOC/SSC. 
If a participant becomes pregnant while participating in R3 will be reported as an AE and 
will trigger the collection of additional documentation about the pregnancy including the 
immediate unblinding of the participant and discontinuation of study medication 
(lisinopril) if they were randomized to the active /intervention arm. Pregnancy outcomes 
will be collected, including the outcome of the infant and if the pregnancy was 
terminated. This information will be submitted to the Vanderbilt University IRB, the 
AKTH (study site) IRB, and NIDDK (study funder---who will forward this along to the 
DSMB), as required. 
SAEs that are still ongoing at the end of the study period must be followed up to 
ascertain the definitive outcome. Any SAEs that occur after the study period (up to 3 
months post-study completion) and is considered to be <possibly related= to study 
treatment or study participation should be recorded and reported immediately. 
 
Investigator Reporting to the IRB 
Site investigators will report SAEs and Unanticipated events to their IRB in accordance 
with the reporting requirements of the local IRB or with the Office of Human Research 
Protections (OHRP) guidelines, whichever is sooner. OHRP recommends that: 
1) ALL unanticipated events (regardless of grade) that are <definitely related=, 
<possibly related= or <unable to assess relatedness to study medication= should be 
reported to involved IRBs and NIDDK within 48 hours of the investigator becoming 
aware of the event; 
2) ALL serious adverse events (SAEs) that are unanticipated (regardless of 
<relatedness= to study medication”) should be reported to involved IRBs and 
NIDDK within 48 hours of the investigator becoming aware of the event 


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Table 3: R3 Adverse Event Reporting Timeline 
 
* Other reportable events include the following: 
1. Any AE that causes SOC to modify protocol/informed consent or prompt 
other action by IRB to assure patient protection 
2. Breach of confidentiality 
3. Change to the protocol made without prior IRB review to eliminate apparent 
immediate hazard to a research participant 
4. Complaint of a participant that indicates unanticipated risks, or the complaint 
cannot be resolved by the study team 
5. Protocol violation 


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Reporting Process 
Unanticipated problems posing risks to participants or others as noted above will be 
reported using the appropriate IRB-designated form or as a written report of the event 
(including a description of the event with information regarding its fulfillment of the above 
criteria, follow-up/resolution and need for revision to consent form and/or other study 
documentation). 
Copies of each report and documentation of IRB notification and receipt will be 
maintained in the AKTH Study Site Investigator’s study file. 
 
Other Reportable Events (please also refer to LEGEND/FOOTNOTE at the bottom of 
Table 3): 
• 
Any AE that would cause the R3 SOC to modify the protocol or informed consent 
form or would prompt other action by the IRB to assure protection of human 
participants. Information that indicates a change to the risks or potential benefits 
of the research, in terms of severity or frequency. 
• 
Breach of confidentiality. 
• 
Change to the protocol made without prior IRB review to eliminate apparent 
immediate hazard to a research participant. 
• 
Complaint of a participant when the complaint indicates unexpected risks, or the 
complaint cannot be resolved by the research team. 
• 
Protocol violation (meaning an accidental or unintentional deviation from the IRB 
approved protocol) that in the opinion of the investigator placed one or more 
participants at increased risk or affects the rights or welfare of participants. 
NOTE: Any/all study events meeting <Other Reportable Events= criteria as outlined 
above should be reported to involved IRBs and NIDDK within 48 hours of the 
investigator becoming aware of the event. 
 
SSC Notification to Participating Study Investigators 
The R3 SCC will notify all on-site (AKTH-based) senior study leadership and the SOC, in 
a written safety report, of any AE that meets the criteria of an <unanticipated event= 
and/or AE <definitely related to study medication= or <possibly related to study 
medication= as described previously. The SOC will be responsible for notifying relevant 
other parties, including the Data and Safety Monitoring Board (DSMB), NIDDK, and 
involved IRBs. 
 
Medical Monitoring 
AKTH-based Co-Investigators and Research Coordinator will be responsible for 
overseeing the safety of the study at their study site. This safety monitoring will include 
careful assessment and appropriate reporting of AEs as noted above, as well as the 
implementation of a site data and approved Data Safety Monitoring Plan. Medical 
monitoring will include a regular assessment of the number and type of serious and/or 
unanticipated AEs. 


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C. Safety Monitoring Plan 
All AEs will initially be reviewed (after being sent from the on-site study team) and 
categorized by the study Program Manager and then by the SOC and SSC (when 
relevant; i.e. the SSC is involved), according to the timeline as outlined above in 
<Table 3: R3 Adverse Event Reporting Timeline=. Weekly meetings with the 
study team will also look at overall statistics for AEs. Reports that include AEs will 
also be sent to NIDDK and the Chair of the DSMB on a quarterly basis for review 
and dissemination to other DSMB members (as specified above in <Table 3: R3 
Adverse Event Reporting Timeline=). 
 
Study progress (including recruitment, consent procedures, retention, laboratory 
results, and protocol adherence measures) will be reviewed on a weekly basis by 
the study team leadership at VUMC and on-site at AKTH. 
 
Quarterly reports sent to NIDDK and the DSMB will include a list and summary of 
AEs, determination of whether these AE rates are consistent with pre-study 
assumptions (i.e. anticipated or unanticipated, etc.), a summary of recruitment and 
retention, as well as a summary of reasons for loss-to-follow-up, and whether the 
study is on track with respect to the original timeline and proposed milestones. 
Given the long recruitment period, the sample size, and the relatively short follow- 
up period, we will not have stopping rules for this trial. We will perform interim 
analyses at six months after enrollment into Aim 2 begins or after 50% enrollment 
into Aim 2 (n=70/arm, n=140 total) occurs to evaluate safety/toxicity and efficacy. 
These results will be shared with the DSMB and all relevant parties. 
 
D. Informed Consent 
Informed consent will be obtained from each participant at entry into Study Aim 1, 
and again for those who proceed to Aim 2 (a subset of the participants from Aim 
1). Informed consent will be collected in REDCap by trained study coordinators, 
who will provide a study information form and review the study consent form with 
the participant in the participant’s language of preference (form will be available in 
both English and Hausa). The consent form will include all potential study risks 
and will be approved by both IRBs (Vanderbilt and AKTH). Forms will be uploaded 
through the central secure study database, housed at Vanderbilt. 
 
E. Data Quality and Management 
 
Study data will be collected in REDCap. Form fields, where possible, have include 
restrictions on data input (numeric fields restricted to possible ranges, text fields 
prevented from allowing numeric entries, etc.) to make data entry less prone to 
errors and prevent false outliers. Data cleaning and preparation for analysis will be 
ongoing, with consent forms and study data reviewed monthly or more frequently. 
Data management and data quality will be regularly reviewed by the study team 


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39 
 
leadership (Multiple-PIs, Study Manager, and on-site AKTH study leadership). The 
study leadership will also provide results to the DSMB in twice-yearly reports. 
F. Confidentiality 
Study participants will be assigned a coded identification number at the time of 
study registration. In order to maintain patient confidentiality, all laboratory 
specimens, study case report forms, and reports will be identified using that coded 
number. Only research staff will have access to the coded number. Key study 
personnel including Dr(s). Wester and Aliyu (MPIs), Nalado, Abdu, Sani, Musa, 
Muhammad, Abdussalam, and Atanda will store research data including medical 
and laboratory records in locked cabinets and all e-files will be password protected. 
Data will be stored in password-protected files within secure buildings at AKTH 
and VUMC. We have additional measures to enhance security when data are 
housed at Vanderbilt. Access to all data will be ID and password-protected, 
including data warehouse software and computers managing and analyzing 
survey data. Clinical information will not be released without the written permission 
of the participant. No data will be released with any information that may directly 
or indirectly identify participants, their clinical information, or laboratory results to 
outside agencies. 
The data gathered will be entered into the research electronic data capture 
(REDCap) data system, with each ID having a unique identifier for each participant. 
REDCap is a secure, web-based application for building and managing online 
databases. All data will be de-identified and samples will only have a unique 
identifier that will link the unique identifier with the patient’s name. REDCap is a 
free, secure, web-based application designed to support data capture for research 
studies. The system was developed by a multi-institutional consortium initiated at 
Vanderbilt University. Data collection is customized for each study or clinical trial 
by the research team with guidance from Harvard Catalyst EDC Support Staff. 
REDCap is designed to comply with Health Insurance Portability and 
Accountability Act (HIPAA) regulations. REDCap provides user-friendly web- 
based case report forms, real-time data entry validation (e.g. for data types and 
range checks), audit trails, and the ability to set up a calendar to schedule and 
track critical study events such as blood-draws, participant visits, etc. Also, 
designated users can assign different levels of access for each member of the 
research team. 
 
REDCap and REDCap Survey (RS), as hosted by Vanderbilt, are available only to 
investigators from Vanderbilt University but can be used by investigators at other 
institutions as long as they are part of a project/group from Vanderbilt that is 
utilizing REDCap. REDCap and RS as software applications can be used at other 
institutions, when installed by and hosted at those institutions, if they are willing to 
sign a technology transfer agreement and join the REDCap Consortium. 
Investigators and research staff at AKTH are very comfortable with using REDCap, 
as Dr. Aliyu’s ongoing research studies there all utilize REDCap for data 
management. 
 
The REDCap clinical database will be maintained by the Vanderbilt Institute for 
Global Health under the direction of the MPIs. The study team members are 
trained in HIPAA privacy regulations and other applicable site privacy policies. No 


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information will be released, nor will participation in the research be acknowledged, 
to any party except where compulsory according to law or intuitional policy. 
 
 
 
G. Data and Safety Monitoring Board (DSMB) 
The information provided in this section of the protocol is a general description of the 
DSMB responsibilities and processes. 
A DSMB has been established by the NIDDK and provides input to the study team. The 
DSMB is comprised of individuals with expertise in clinical trials design and 
methodology, biostatistics, clinical nephrology and other relevant medical specialties. 
The DSMB members are not affiliated with the study and are appointed by the NIDDK. 
DSMB members will be free of conflicts of interest that could be affected by the 
outcomes of the study. During the study, DSMB members who develop real or 
perceived conflicts of interest that impact objectivity will disclose them to NIDDK project 
officers, who will arrange for replacement of the member, if indicated. 
The DSMB will review the protocol before initiation of the study. After initial approval and 
during the course of the study, the primary responsibilities of the DSMB will be to: 
 
• 
Review safety data and provide input to protect the safety of the study 
participants; 
• 
Provide input on major changes to the research protocol and plans for data and 
safety monitoring; 
• 
Provide input on the progress of the study, including periodic assessments of 
data quality and timeliness, participant recruitment, accrual and retention, 
participant risk versus benefit, performance of the study sites, and other factors 
that may affect study outcomes; 
• 
Consider factors external to the study when relevant information becomes 
available, such as scientific or therapeutic developments that may have an 
impact on the need for continuation of the study, safety of the participants or the 
ethics of the study; 
• 
Provide input on modification of the study protocol or possible early termination 
of the study because of attainment of study objectives, safety concerns, or 
inadequate performance (such as enrollment and retention problems). 
The DSMB will review study data reports, including primary endpoint analyses, at 
a minimum of every six months either in a meeting or on a conference call. 
 
7.0 
Study Withdrawal/Discontinuation 
 
Participants may decide to discontinue participation at any time during the study. If a 
patient voluntarily requests withdrawal from the trial, we request that the site investigator 


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elicit the reason for the withdrawal and provide documentation in the clinic record and 
complete the respective case report form. We will have a dedicated patient navigator on 
staff as well to help trace and re-engage all participants lost to follow-up, realizing that 
some may die or transfer their care and must be appropriately categorized. Those who 
drop out due to AEs or perceived AEs will be counseled by study physicians regarding 
their options and any potential risks for continuation. The site must invest time in trying to 
meet the needs of the patient and their caregivers in order to make the patient’s 
participation a success. The patient’s caregiver should provide the withdrawal in writing 
for the clinic record. All voluntary withdrawals must be communicated to the SOC located 
at Vanderbilt University Medical Center by completion of the case report form in REDCap 
and should be recorded in the participant’s study binder onsite. 
 
Principal Investigator-initiated Withdrawal 
Investigators may discontinue any participant at their discretion, if in their professional 
opinion the participant’s health, safety, and/or well-being is being threatened or at all 
jeopardized by continued participation in the study. The following circumstances require 
discontinuation of participants: 
1. Withdrawal of assent to participate; 
2. Parental withdrawal of consent to participate; 
3. Study physician determines that continuation in the study would not be in the 
best interest of the participant, e.g., pregnancy; 
4. Participant has experienced a serious and/or unanticipated adverse event. 
Adverse events caused by participation in the study may necessitate modifications to the 
level of participation of a subject or discontinuation of participation in the study. 
Participants who discontinue early from the study will not be replaced. They will continue 
to receive medical care at the AKTH HIV clinic as per standard care. 
 
 
8.0 
Statistical Considerations 
 
Specific Aim 1 
Sample size justification: A screening sample size of 2,600 participants will yield 
sufficient sample size for randomization in Specific Aim 2 detailed below. With 2,600 
persons screened for Aim 1, the prevalence of APOL1 renal risk variants may be 
estimated with precision (half-length of the 95% confidence interval) equal to 0.02 or 
better. Assuming a microalbuminuria prevalence of 17.5% based on recent data 
obtained from HIV-positive adults (n ~ 460) screened at AKTH,110 where this study will 
take place, we will have 90% power to detect a relative risk of microalbuminuria of 1.37 
or higher in participants with renal risk variants compared to participants without, and we 
anticipate that 1 in 4 participants will have renal risk variants. We estimate, based on our 
experience with our studies at this site, that enrollment for Aim 1 will take 12 months. In 
addition to analyzing APOL1 risk as a binary high/low risk status, we will also examine 
relative risk of microalbuminuria with APOL1 risk categorized based on the presence of 
0, 1, or 2 alleles, as this will lead to an increased understanding of the risk associated 
with the presence of a single risk allele. 


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Statistical analysis plan: We will estimate the prevalence and associated 95% 
confidence interval of APOL1 renal risk variants. We will test whether the presence of 
these variants is associated with log10uACR or eGFR using Wilcoxon rank sum test. 
Multivariable linear regression for each of log10uACR or eGFR will be used to adjust for 
potential confounders, including: sex, age, CD4+ cell count, viral load, and the 
presence/absence of specific comorbid medical conditions (hypertension, cardiovascular 
disease, diabetes mellitus, etc.). For linear regression, appropriate transformations of 
dependent variables will be used to satisfy modelling assumptions. To relax linearity 
assumptions, covariates will be modelled using restricted cubic splines.135 Modified 
Poisson regression 
adjusted for similar 
variables, will be used to 
assess associations with 
prevalent CKD, 
microalbuminuria, and 
reduced eGFR (< 60 
mL/min/1.73m2), and 
95% confidence intervals. 
 
Specific Aim 2 
Sample size 
justification: We will 
enroll 280 eligible patients from Specific Aim 1 for 1:1 randomization in our RCT for 
Specific Aim 2. Based on our prior experience with ongoing RCTs in the study location, 
we anticipate that enrollment into Aim 2 will take 12 months and there will be 10% loss to 
follow up at end of year 2, yielding 252 patients on study (126 per arm). Aim 2A: At 2 
years, we hypothesize that a higher proportion of intervention participants will regress 
from microalbuminuria to normoalbuminuria (uACR < 30 mg/g) with a hazard ratio (HR)= 
2.50. Using the logrank test, we will have approximately 80% power if the rate of 
regression in the SOC arm is at least 12%, and 90% power if that rate is 16% or higher 
with a 1.7% type I error136. (The type I error rate was set at 5%/3=1.7% to account for 
multiple testing and the fact that we have 3 primary endpoints.) See Tables 3 and 4. Aim 
2B: At 2 years, we hypothesize that a higher proportion of patients in the SOC arm, 
namely 60% vs. 25% in the intervention arm (HR≈0.42), will progress from 
microalbuminuria to macroalbuminuria (uACR > 300 mg/g). With 126 patients per arm 
(after removing 10% loss to follow-up), we will have >95% power for Aim 2B with a 1.7% 
type I error. See Tables 5 and 6. Figure 3 shows changes in Aim 2A power for varying 
SOC regression rates and changes in Aim 2B power for varying sample size. The 
sample size for Aim 2C is such that we will have approximately 80% power to detect at 
the alpha=0.017 level a difference in the log-transformed mean uACR of 0.24, which is 
approximately 0.41 standard deviations. These power calculations are likely 
conservative, as they do not incorporate baseline covariates, which will be included in 
the actual analyses (see below) and should improve power; in addition, the uACR 
analysis will incorporate multiple longitudinal measures per person whereas these power 
calculations only assume a single final measurement per person. 
The sample size was chosen to have sufficient power for all primary endpoints. Tables 
S1-S8, investigating power and detectable alternatives for the secondary endpoints with 
a total sample size of 280 are provided in Appendix B. In short, we anticipate low power 
to detect differences between intervention arms in the doubling of serum creatinine, all- 
Figure 3: Aim 2 Sample Size and Power Justification 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
43 
 
cause mortality, and tenofovir toxicity because the expected rates for these events in the 
placebo arm are anticipated to be small (i.e., 2-20%, <10%, and 2%, respectively). We 
should have sufficient power to detect meaningful differences in eGFR, quality of life 
scores, and blood pressure. 
 
Table 3. Power calculation for regression 
 
alpha 
Events 
Needed 
Approx 
Rate SOC 
Approx 
Rate Exp 
Patients 
per Arm 
Power 
0.010 
38 
0.12 
0.3 
100 
0.595 
0.010 
50 
0.16 
0.4 
100 
0.751 
0.010 
45 
0.12 
0.3 
120 
0.695 
0.010 
60 
0.16 
0.4 
120 
0.838 
0.010 
53 
0.12 
0.3 
140 
0.775 
0.010 
71 
0.16 
0.4 
140 
0.898 
0.010 
60 
0.12 
0.3 
160 
0.838 
0.010 
81 
0.16 
0.4 
160 
0.938 
0.010 
68 
0.12 
0.3 
180 
0.886 
0.010 
91 
0.16 
0.4 
180 
0.963 
0.017 
38 
0.12 
0.3 
100 
0.666 
0.017 
50 
0.16 
0.4 
100 
0.807 
0.017 
45 
0.12 
0.3 
120 
0.758 
0.017 
60 
0.16 
0.4 
120 
0.880 
0.017 
53 
0.12 
0.3 
140 
0.828 
0.017 
71 
0.16 
0.4 
140 
0.928 
0.017 
60 
0.12 
0.3 
160 
0.880 
0.017 
81 
0.16 
0.4 
160 
0.958 
0.017 
68 
0.12 
0.3 
180 
0.918 
0.017 
91 
0.16 
0.4 
180 
0.976 
0.025 
38 
0.12 
0.3 
100 
0.717 
0.025 
50 
0.16 
0.4 
100 
0.844 
0.025 
45 
0.12 
0.3 
120 
0.801 
0.025 
60 
0.16 
0.4 
120 
0.907 
0.025 
53 
0.12 
0.3 
140 
0.862 
0.025 
71 
0.16 
0.4 
140 
0.946 
0.025 
60 
0.12 
0.3 
160 
0.907 
0.025 
81 
0.16 
0.4 
160 
0.969 
0.025 
68 
0.12 
0.3 
180 
0.938 
0.025 
91 
0.16 
0.4 
180 
0.983 
0.050 
38 
0.12 
0.3 
100 
0.804 
0.050 
50 
0.16 
0.4 
100 
0.902 
0.050 
45 
0.12 
0.3 
120 
0.870 
0.050 
60 
0.16 
0.4 
120 
0.946 
0.050 
53 
0.12 
0.3 
140 
0.915 
0.050 
71 
0.16 
0.4 
140 
0.971 
0.050 
60 
0.12 
0.3 
160 
0.946 
0.050 
81 
0.16 
0.4 
160 
0.984 
0.050 
68 
0.12 
0.3 
180 
0.966 
0.050 
91 
0.16 
0.4 
180 
0.992 
For these calculations, an HR of 2.5 was assumed. 
 
Table 4. Detectable hazard ratios (HR) for regression 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
44 
 
alpha 
Events 
Needed 
Approx 
Rate SOC 
Approx 
Rate Exp 
Patients 
per Arm 
Detectable 
HR 
0.010 
42 
0.12 
0.35 
100 
2.88 
0.010 
52 
0.16 
0.41 
100 
2.59 
0.010 
48 
0.12 
0.32 
120 
2.69 
0.010 
59 
0.16 
0.39 
120 
2.43 
0.010 
54 
0.12 
0.31 
140 
2.54 
0.010 
67 
0.16 
0.37 
140 
2.31 
0.010 
59 
0.12 
0.29 
160 
2.43 
0.010 
74 
0.16 
0.35 
160 
2.21 
0.010 
65 
0.12 
0.28 
180 
2.34 
0.010 
81 
0.16 
0.34 
180 
2.13 
0.017 
41 
0.12 
0.33 
100 
2.76 
0.017 
50 
0.16 
0.40 
100 
2.49 
0.017 
46 
0.12 
0.31 
120 
2.58 
0.017 
58 
0.16 
0.37 
120 
2.34 
0.017 
52 
0.12 
0.29 
140 
2.45 
0.017 
65 
0.16 
0.36 
140 
2.23 
0.017 
58 
0.12 
0.28 
160 
2.34 
0.017 
72 
0.16 
0.34 
160 
2.14 
0.017 
63 
0.12 
0.27 
180 
2.25 
0.017 
79 
0.16 
0.33 
180 
2.06 
0.025 
40 
0.12 
0.32 
100 
2.66 
0.025 
49 
0.16 
0.39 
100 
2.41 
0.025 
45 
0.12 
0.30 
120 
2.50 
0.025 
57 
0.16 
0.36 
120 
2.27 
0.025 
51 
0.12 
0.28 
140 
2.37 
0.025 
64 
0.16 
0.35 
140 
2.16 
0.025 
57 
0.12 
0.27 
160 
2.27 
0.025 
71 
0.16 
0.33 
160 
2.08 
0.025 
62 
0.12 
0.26 
180 
2.19 
0.025 
78 
0.16 
0.32 
180 
2.01 
0.050 
38 
0.12 
0.30 
100 
2.49 
0.050 
47 
0.16 
0.36 
100 
2.26 
0.050 
43 
0.12 
0.28 
120 
2.34 
0.050 
54 
0.16 
0.34 
120 
2.14 
0.050 
49 
0.12 
0.27 
140 
2.23 
0.050 
61 
0.16 
0.33 
140 
2.04 
0.050 
54 
0.12 
0.26 
160 
2.14 
0.050 
68 
0.16 
0.32 
160 
1.97 
0.050 
60 
0.12 
0.25 
180 
2.07 
0.050 
75 
0.16 
0.31 
180 
1.91 
For these calculations, a power of 80% (0.80) was assumed. 
 
Table 5. Power calculation for progression 
alpha 
HR 
Progression 
events 
Patients 
per arm 
Power 
0.010 
0.42 
76 
100 
0.895 
0.010 
0.42 
92 
120 
0.947 
0.010 
0.42 
107 
140 
0.975 
0.010 
0.42 
122 
160 
0.988 
0.010 
0.42 
138 
180 
0.995 
0.017 
0.42 
76 
100 
0.925 


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Protocol Date: July 24, 2021 
45 
 
0.017 
0.42 
92 
120 
0.965 
0.017 
0.42 
107 
140 
0.984 
0.017 
0.42 
122 
160 
0.993 
0.017 
0.42 
138 
180 
0.997 
0.025 
0.42 
76 
100 
0.944 
0.025 
0.42 
92 
120 
0.975 
0.025 
0.42 
107 
140 
0.989 
0.025 
0.42 
122 
160 
0.995 
0.025 
0.42 
138 
180 
0.998 
0.050 
0.42 
76 
100 
0.969 
0.050 
0.42 
92 
120 
0.987 
0.050 
0.42 
107 
140 
0.995 
0.050 
0.42 
122 
160 
0.998 
0.050 
0.42 
138 
180 
0.999 
For these calculations, we assumed HR=0.42, approximate rate of progression in the SOC arm=0.6, and 
approximate rate of progression among those on the experimental arm=0.25. 
 
 
T able 6. Detectable hazard ratios for progression 
alpha 
Progression 
Events 
Approx. 
Rate Exp 
Patients per 
Arm 
HR 
0.010 
79 
0.28 
100 
0.46 
0.010 
97 
0.30 
120 
0.50 
0.010 
116 
0.32 
140 
0.53 
0.010 
134 
0.33 
160 
0.55 
0.010 
153 
0.35 
180 
0.58 
0.017 
80 
0.29 
100 
0.49 
0.017 
99 
0.31 
120 
0.52 
0.017 
117 
0.33 
140 
0.55 
0.017 
136 
0.34 
160 
0.57 
0.017 
155 
0.36 
180 
0.60 
0.025 
81 
0.30 
100 
0.50 
0.025 
100 
0.32 
120 
0.54 
0.025 
119 
0.34 
140 
0.57 
0.025 
137 
0.35 
160 
0.59 
0.025 
157 
0.37 
180 
0.61 
0.050 
83 
0.32 
100 
0.54 
0.050 
102 
0.34 
120 
0.57 
0.050 
121 
0.36 
140 
0.60 
0.050 
140 
0.37 
160 
0.62 
0.050 
160 
0.39 
180 
0.64 
For these calculations, we assumed a power of 80% (0.80) and an approximate rate of progression in the 
SOC arm of 60% (0.6). 
 
 
 
Statistical analysis plan: Our first approach will be to perform an intent-to-treat 
analysis, but we will also perform an on-treatment analysis to compare these data and 
present all available findings. Primary analysis: We will test the hypotheses that 
regression and progression rates are different across arms using multivariable Cox 
regression models with the intervention variable (randomization to RAAS [yes/no]) as the 
primary predictor variable, adjusting for baseline (pre-randomization) covariates 
including baseline uACR, APOL1 renal risk variants, CD4+ cell count, blood pressure 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
46 
 
ART regimen (DTG vs. other), and the presence/absence of comorbid medical 
conditions (hypertension, cardiovascular disease). To relax linearity assumptions, 
baseline uACR will be included in models using restricted cubic splines.138 Primary 
analyses will be intention to treat, although we also plan to perform <per protocol= 
analysis. We will also test the impact of study arm on uACR using a linear mixed effects 
model to account for within patient correlation with the outcome of 3-monthly uACR 
values (with primary endpoints obtained by evaluating the uACR and other key renal 
outcomes at 18 and 30 months given that all enrolled study participants will not be 
placed or sustained on their maximum tolerated lisinopril dose or matched placebo until 
6 months after study enrollment). The model will also adjust for the baseline covariates 
given above. For this analysis, we anticipate log-transforming uACR to meet modelling 
assumptions, although other transformations will be considered if needed. 
 
Secondary analyses: Analyses for secondary endpoints will be similar to that described 
above. Time-to-event outcomes (doubling of serum creatinine from baseline, all-cause 
mortality, 40% decline in eGFR, and tenofovir toxicity) will be assessed using 
multivariable Cox regression models. Continuous outcomes (eGFR, quality of life 
metrics, and blood pressure) will be analyzed using mixed effects models after proper 
transformation of the outcome variable, if necessary. Baseline covariates listed above 
will be included in all secondary analyses. 
 
In conversations with the DSMB, concerns were brought up regarding the nationwide 
switch to dolutegravir (DTG) and its potential impact on results. As sensitivity analyses, 
we will repeat the primary and secondary analyses listed above but also include any 
switch to a DTG-containing regimen post-randomization as a time-varying covariate. Our 
rationale for not including DTG-switch in the primary analysis, is that post-randomization 
variables (such as a switch to DTG) could be affected by treatment assignment and 
adjusting for it could therefore potentially bias results. However, we believe that the 
transition to DTG will not be affected by treatment assignment, in which case these 
analyses will be fine. If post-randomization DTG-uptake does differ by treatment arm 
(>5%), then we will investigate whether DTG-use is a mediator between treatment 
assignment and any of the primary or secondary outcomes listed above. Mediation 
analyses will follow the approaches outlined in VanderWeele TJ (2015) Explanation in 
Causal Inference. Finally, we will investigate whether the effect of assignment to ACEi 
could be modified by DTG-use. To do this, we will repeat the primary and secondary 
analyses but include an interaction between time-varying DTG-use and treatment 
assignment. 
 
 
 
 
Potential difficulty reaching desired sample size: Our microalbuminuria prevalence 
estimates among HIV positive adults engaged in care at AKTH are conservative, as they 
are based on published data from this same hospital among asymptomatic HIV positive 
adults, and we anticipate that only approximately 59% of those eligible for our aim 2 
study will need to consent/enroll in order for us to reach our target sample sizes. 
Therefore, with a target sample size equal to 280, 59% of eligible patients would need to 
consent for Study Aim 2. 


Protocol Version #: 10.0 
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47 
 
Retention Strategies: To increase the likelihood of retention in the trial, we plan to use 
several evidence-based methods that have been effective in clinical trials. The use of 
simple, clear, detailed written and verbal instructions regarding therapy, possible 
treatment side effects, and tests required for the study increases comprehension of the 
purpose and importance of the study, and yields better adherence to the trial.137-140 In 
terms of specifics: i) We will develop a brochure outlining the study protocol in simple 
terms that will be translated into Hausa (native language of majority of individuals that 
live in Kano, Nigeria); ii) the key to successful follow-up and retention will be attention to 
detail, consistency of the research team, and trust between participants and study and 
clinic staff. The research staff will contact participants immediately and reschedule 
appointments when missed; iii) Close monitoring of participants’ visits and need for 
return appointments with follow-up telephone calls are key elements for monitoring 
patient attendance and prevention of loss to follow-up. Every attempt will be made by the 
study team to contact participants prior to their scheduled visit based on the study 
schedule; and iv) identification of a trusted contact person who does not live with the 
study participant but always knows the participant's whereabouts will assist in tracking 
participants at risk of loss to follow-up and will decrease attrition. NOTE: The AKTH HIV 
clinic has historically had high retention rates. In a recent 10 year prospective cohort 
study conducted by our team (29,860 person-months of follow-up), 83% of our patients 
in the cohort were still in care after 10 years.141 We will employ the same retention 
initiatives that have been shown to be effective in our study setting, including: active 
engagement of peer mentors in recruitment, counseling and monitoring activities, 
community involvement, supportive home-based care services, early case detection, 
and close tracking of at-risk persons with missed visits. 
 
Specific Aim 3 
Statistical analysis and considerations: Analyses for Aim 3 will be the same as those 
outlined in Aim 2, except the predictor of interest will be APOL1 haplotype (high risk vs. 
low risk) instead of intervention arm; analyses will adjust for intervention arm (similar to 
how analyses of Aim 1 adjusted for APOL1 genotype). Assuming that ~30% (n = 84) of 
Aim 2 study participants have the high risk genotype, namely 2 copies of the risk 
variants (G1/G1, G1/G2, or G2/G2), with the remainder of Aim 2 study participants (n = 
196) having the low risk genotype (carrying no or one risk allele [G0/G0, G0/G1, and 
G0/G2]), and that the rate of progression will be similar to that hypothesized in Aim 2, we 
anticipate having 80% power to detect hazard ratios on the order of 2.4 to 3.2. 
Specifically, if the rate of regression is 22% (e.g., 10% and 25% in the SOC and 
intervention arms, respectively), we will have 80% power to detect a hazard ratio of 3.2 
between the low and high risk genotypes; if the rate of regression is 35% (e.g., 20% and 
40% in the SOC and intervention arms, respectively), we will have 80% power to detect 
a hazard ratio of 2.4. With regards to progression, if the overall event rate is 42.5%, we 
anticipate having 80% power to detect a hazard ratio of 2.1 between the high and low 
risk genotypes; if the overall rate of progression is 28%, we anticipate approximately 
80% power to detect a hazard ratio of 2.5. Analyses will be repeated treating number of 
risk alleles (0, 1, or 2) as a categorical variable to investigate differences in risks when 
having 0 vs. 1 risk allele. 
 
9.0 
Follow-up and Record Retention 
 
In total, this study will last five years (2017-2022), with patients remaining in follow-up for 
two years within that time frame. Patient information and research results will be de- 
identified to maintain participants’ privacy. Clinical records with identifiable information 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
48 
 
will be destroyed at the conclusion of the study. De-identified information used for 
analysis purposes (those described here and potential subsequent analyses with de- 
identified information) may be retained for an indefinite period of time following 
conclusion of the study. 
 
10.0 
Foreign Justification 
 
To be able to successfully answer the scientific questions posed by this study, the study 
setting must be one that has a high prevalence of three things: HIV, chronic kidney 
disease, and APOL1 risk alleles. As aforementioned, Nigeria has a significant HIV/AIDS 
burden, and while the prevalence of CKD in HIV positive ART-naive patients varies from 
6 to 48% across sub-Saharan Africa, the highest prevalence has been reported in 
Nigeria. The frequency of APOL1 risk alleles is also highest in West Africa, specifically in 
Nigeria among persons of Yoruba and Igbo descent. Furthermore, the study team has 
long-established collaborations in Nigeria, including the completion of NIH-funded 
clinical research studies (including an RCT). Therefore, Nigeria provides the optimal 
setting to conduct this study. 
 
Appendix A. Study Timeline 
 
 
ACTIVITIES 
MONTHS 
0-6 
6-12 
12-18 
18-24 
24-30 
30-36 
36-42 
42-48 
48-54 
54-60 
Introductory meeting 
Protocol development, including MOPs, 
CRFs 
IRB approvals 
DSMB review 
Hire and train study staff 
Pilot test surveys/forms, study kick-off 
Participant screening/enrollment-Aim 1 
Genotyping (APOL1 SNPs) Aim 1 
Participant enrollment/randomization- 
Aim 2 
Follow-up visits with lab assessments- 
Aim 2 
Data collection 
Data management and QC 
Data analysis 
Dissemination of study findings, 
manuscript writing 
LEGEND: MOP = manual of operations, CRF = Case review forms, QC = quality control 
 
 
 
 
Appendix B. Supplemental tables - Statistical calculations for secondary 
endpoints 
Table S1. Detectable differences in means of log-transformed uACR values. The 
outcome is uACR measurement (units= mg/g) and a t-test will be used to compare the 
two means of log-transformed uACR for the two arms after follow-up. Given the inclusion 
criteria with the uACR range of 30-300 mg/g, we assume the log-transformed uACR has 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
49 
 
a 95% probability interval from 3.4 to 5.7 and a standard deviation of 0.58. With 90 
subjects at the end of study after adjustment for 10% loss to follow up (LTFU), we will 
have 80% power to detect a difference of 0.42 units of standard deviation (0.24 on log- 
transformed means assuming standard 
deviation of 0.58). 
 
alpha Subjects per 
Arm 
Detectable 
Difference 
0.010 
100 
0.30 
0.010 
120 
0.27 
0.010 
140 
0.25 
0.010 
160 
0.23 
0.010 
180 
0.22 
0.017 
100 
0.28 
0.017 
120 
0.25 
0.017 
140 
0.24 
0.017 
160 
0.22 
0.017 
180 
0.21 
0.025 
100 
0.27 
0.025 
120 
0.24 
0.025 
140 
0.23 
0.025 
160 
0.21 
0.025 
180 
0.20 
0.050 
100 
0.24 
0.050 
120 
0.22 
0.050 
140 
0.20 
0.050 
160 
0.19 
0.050 
180 
0.18 
 
Table S2. Detectable differences in doubling of serum creatinine. Assuming 2% - 
20% of subjects in the SOC arm will be doubling of serum creatinine, we will use an 
uncorrected chi-squared test to detect the difference between the two arms. In case of 
10% of subjects on the SOC arm will have their serum creatinine doubled after follow up, 
we will have 80% power to detect a 9.3% decrease on the experimental arm to 0.7% 
(RR=0.07). 
 
Alpha 
Rate SOC 
arm 
Detectable 
RR 
Rate Exp 
arm 
0.01 
0.10 
0.050 
0.005 
0.01 
0.15 
0.193 
0.029 
0.01 
0.20 
0.290 
0.058 
0.05 
0.10 
0.180 
0.018 
0.05 
0.15 
0.307 
0.046 
0.05 
0.20 
0.395 
0.079 
 
Table S3. All-cause mortality. With 140 patients on each arm, we will have 126 
patients on each arm at the end of study assuming 10% LTFU. An uncorrected chi- 
square test will be used to test the difference of the all-cause mortality between the two 
arms. In case of the all-cause mortality is 10% on the SOC arm, we will have 80% power 
to detect an absolute 8.2% decrease on the treatment arm to 1.8%. 


Protocol Version #: 10.0 
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50 
 
Rate of SOC 
Power 
Detectable 
Difference 
RR 
Detectable Rate 
Exp Arm 
0.08 
0.8 
0.072 
0.10 
0.008 
0.08 
0.9 
0.079 
0.01 
0.001 
0.10 
0.8 
0.082 
0.18 
0.018 
0.10 
0.9 
0.091 
0.09 
0.009 
0.12 
0.8 
0.092 
0.23 
0.028 
0.12 
0.9 
0.102 
0.15 
0.018 
0.14 
0.8 
0.100 
0.29 
0.040 
0.14 
0.9 
0.112 
0.20 
0.028 
0.16 
0.8 
0.108 
0.32 
0.052 
0.16 
0.9 
0.121 
0.24 
0.039 
0.18 
0.8 
0.115 
0.36 
0.065 
0.18 
0.9 
0.129 
0.28 
0.051 
0.20 
0.8 
0.121 
0.39 
0.079 
0.20 
0.9 
0.136 
0.32 
0.064 
Table S4. Decline in eGFR. Proportion experiencing a 40% decline in eGFR (using 
CKD-EPI-Cr-CyC equation). With 140 patients per arm, assuming 10% LTFU, in case of 
50% patients experienced a 40% decline in eGFR on the SOC arm, we will have 80% 
power to detect a relative 34% decrease on the treatment arm to 33% with 5% type I 
error. 
 
Power 
Rate SOC 
arm 
RR 
Rate Exp 
Arm 
0.8 
0.20 
0.40 
0.08 
0.9 
0.20 
0.32 
0.06 
0.8 
0.25 
0.46 
0.12 
0.9 
0.25 
0.39 
0.10 
0.8 
0.30 
0.51 
0.15 
0.9 
0.30 
0.45 
0.13 
0.8 
0.35 
0.56 
0.20 
0.9 
0.35 
0.50 
0.17 
0.8 
0.40 
0.59 
0.24 
0.9 
0.40 
0.54 
0.22 
0.8 
0.45 
0.63 
0.28 
0.9 
0.45 
0.57 
0.26 
0.8 
0.50 
0.66 
0.33 
0.9 
0.50 
0.61 
0.30 
0.8 
0.55 
0.68 
0.38 
0.9 
0.55 
0.64 
0.35 
0.8 
0.60 
0.71 
0.43 
0.9 
0.60 
0.66 
0.40 
 
Table S5. Mean change in eGFR. Mean change in eGFR over time (using CKD-EPI-Cr- 
Cyc equation) with 126 patients per arm after LTFU. Detectable difference shown as unit 
of 1 SD. 


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51 
 
Power 
Detectable 
Difference 
0.8 
0.35 
0.9 
0.41 
 
Table S6. Change in quality of life (QOL) score. The change in clinical/performance 
status (as ascertained via two measures, specifically the WHO quality of life (WHOQOL- 
HIV) tool (31 questions) and the Karnofsky performance score. WHOQOL-HIV evaluates 
quality of life based on six domains (physical, psychological, level of independence, 
social relationships, environment, and spiritual/beliefs) and includes questions specific to 
HIV/AIDS. The brief version contains 31 questions and each question is rated on a 5- 
point Likert scale. For the analysis of the data, the scores of the questions within each 
domain are averaged to get the domain score. The final score 
will be the mean of domain scores multiplied by 4. The final score has a minimum value 
of 4 and maximum value of 20. Hence, we assume it has a standard deviation of 4. With 
126 subjects on each arm after LTFU, we will have 80% power to detect a 1.4 points 
difference in means of WHOQOL-HIV scores, and 90% power to detect a 1.6 points 
difference in the overall WHOQOL-HIV scores between two arms. The Karnofsky 
Performance Score has a range of values from 100 to 0, where 100 is <perfect= health 
and 0 is death. We assume it has standard deviation of 25. With 126 subjects on each 
arm after LTFU, we will have 80% power to detect an 8.7-point difference in means of 
Karnofsky Performance Score, and 90% power to detect a 10-point difference in the 
means of Karnofsky Performance Score between two arms. 
 
Power 
Detectable 
Difference 
0.8 
0.35 
0.9 
0.41 
 
Table S7. Change in TDF toxicity. Conservatively, we estimate 2% of patients will 
experience grade 3 or higher TDF toxicities. In this study, renal events are defined as i) 
a rise in serum creatinine to > 1.9 and ii) a drop in eGFR to < 50 ml/min. Given 126 
patients on each arm after LTFU, assuming 2% TDF toxicity on the SOC arm, we will 
have 31% power to detect a relative 95% decrease from 2% to 0.1% with 5% type I 
error, or we have 83% power to detect an increase of toxicity from 2% on the SOC arm 
to 11% on the treatment arm. 
 
Power 
Detectable 
   Difference 
RR 
Detectable Rate 
Exp Arm 
0.07 
0.01 
1.5 
0.03 
0.15 
0.02 
2.0 
0.04 
0.25 
0.03 
2.5 
0.05 
0.37 
0.04 
3.0 
0.06 
0.48 
0.05 
3.5 
0.07 
0.59 
0.06 
4.0 
0.08 
0.69 
0.07 
4.5 
0.09 
0.77 
0.08 
5.0 
0.10 


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52 
 
0.83 
0.09 
5.5 
0.11 
0.88 
0.10 
6.0 
0.12 
 
Table S8. Change in blood pressure (BP). Recent research (Sakajiki, et al. Kidney 
disease in HIV/AIDS patients, Annals of Nigerian Medicine. Jul-Dec 2014. Vol 8. Issue 2) 
indicates SBP or DBP with standard deviation from 13.81 to 20.18 mmHg. We 
conservatively assume that BP will have a SD of 20 mmHg. With 126 subjects on each 
arm after LTFU, we will have 80% power to detect a 7-mmHg difference in means of BP, 
and 90% power to detect an 8.2 mmHg difference in the means of BP between two arms 
with 5% type I error. 
 
Power 
Detectable 
Difference 
0.8 
0.35 
0.9 
0.41 


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BIBLIOGRAPHY 
1. 
Walensky RP, Paltiel AD, Losina E, et al. The survival benefits of AIDS 
treatment in the United States. The Journal of infectious diseases. 
2006;194(1):11-19. 
2. 
Palella FJ, Jr., Baker RK, Moorman AC, et al. Mortality in the highly active 
antiretroviral therapy era: changing causes of death and disease in the HIV 
outpatient study. Journal of acquired immune deficiency syndromes (1999). 
2006;43(1):27-34. 
3. 
The Antiretroviral Therapy Cohort C. Causes of Death in HIV-13Infected Patients 
Treated with Antiretroviral Therapy, 199632006: Collaborative Analysis of 13 
HIV Cohort Studies. Clinical infectious diseases : an official publication of the 
Infectious Diseases Society of America. 2010;50(10):1387-1396. 
4. 
Deeks SG, Phillips AN. HIV infection, antiretroviral treatment, ageing, and non- 
AIDS related morbidity. BMJ. 2009;338. 
5. 
Martinez E, Milinkovic A, Buira E, et al. Incidence and causes of death in HIV- 
infected persons receiving highly active antiretroviral therapy compared with 
estimates for the general population of similar age and from the same 
geographical area. HIV medicine. 2007;8(4):251-258. 
6. 
Venkat Narayan KM, Miotti PG, Anand NP, et al. HIV and Noncommunicable 
Disease Comorbidities in the Era of Antiretroviral Therapy: A Vital Agenda for 
Research in Low- and Middle-Income Country Settings. JAIDS Journal of 
Acquired Immune Deficiency Syndromes. 2014;67:S2-S7. 
7. 
Magee MJ, Narayan KM. Global confluence of infectious and non-communicable 
diseases -- the case of type 2 diabetes. Preventive medicine. 2013;57(3):149-151. 
8. 
Chu C, Selwyn PA. An epidemic in evolution: the need for new models of HIV 
care in the chronic disease era. Journal of urban health : bulletin of the New York 
Academy of Medicine. 2011;88(3):556-566. 
9. 
Bygbjerg IC. Double burden of noncommunicable and infectious diseases in 
developing countries. Science (New York, NY). 2012;337(6101):1499-1501. 
10. 
Geneau R, Hallen G. Toward a systemic research agenda for addressing the joint 
epidemics of HIV/AIDS and noncommunicable diseases. AIDS. 2012;26:S7-S10. 
11. 
Wester CW, Koethe JR, Shepherd BE, et al. Non-AIDS-defining events among 
HIV-1-infected adults receiving combination antiretroviral therapy in resource- 
replete versus resource-limited urban setting. Aids. 2011;25(12):1471-1479. 
12. 
Organization WH. Attaining the nine global non-communicable diseases targets; a 
shared responsibility. Global Status Report on non-communicable diseases; 2014; 
Geneva, Switzerland. 
13. 
Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 
291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the 
Global Burden of Disease Study 2010. Lancet (London, England). 
2012;380(9859):2197-2223. 
14. 
Wyatt CM, Meliambro K, Klotman PE. Recent progress in HIV-associated 
nephropathy. Annual review of medicine. 2012;63:147-159. 
15. 
Wools-Kaloustian KK, Gupta SK. Will there be an epidemic of HIV-related 
chronic kidney disease in sub-Saharan Africa? Too soon to tell. Kidney 
international. 2008;74(7):845-847. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
54 
 
16. 
Mallipattu SK, Salem F, Wyatt CM. The changing epidemiology of HIV-related 
chronic kidney disease in the era of antiretroviral therapy. Kidney international. 
2014;86(2):259-265. 
17. 
Naicker S. End-stage renal disease in sub-Saharan Africa. Ethnicity & disease. 
2009;19(1 Suppl 1):S1-13-15. 
18. 
Naicker S. Burden of end-stage renal disease in sub-Saharan Africa. Clin Nephrol. 
2010;74 Suppl 1:S13-16. 
19. 
Mulenga LB, Kruse G, Lakhi S, et al. Baseline renal insufficiency and risk of 
death among HIV-infected adults on antiretroviral therapy in Lusaka, Zambia. 
Aids. 2008;22(14):1821-1827. 
20. 
Wools-Kaloustian K, Gupta SK, Muloma E, et al. Renal disease in an 
antiretroviral-naive HIV-infected outpatient population in Western Kenya. 
Nephrology, dialysis, transplantation : official publication of the European 
Dialysis and Transplant Association - European Renal Association. 
2007;22(8):2208-2212. 
21. 
Emem CP, Arogundade F, Sanusi A, Adelusola K, Wokoma F, Akinsola A. Renal 
disease in HIV-seropositive patients in Nigeria: an assessment of prevalence, 
clinical features and risk factors. Nephrology, dialysis, transplantation : official 
publication of the European Dialysis and Transplant Association - European 
Renal Association. 2008;23(2):741-746. 
22. 
Okafor U, Unuigbe E, Chukwuonye E. Prevalence and clinical and laboratory 
characteristics of kidney disease in anti-retroviral-naive human immunodeficiency 
virus-infected patients in South-South Nigeria. Saudi Journal of Kidney Diseases 
and Transplantation. 2016;27(1):129-134. 
23. 
Stanifer JW, Jing B, Tolan S, et al. The epidemiology of chronic kidney disease in 
sub-Saharan Africa: a systematic review and meta-analysis. The Lancet Global 
health. 2014;2(3):e174-181. 
24. 
Osafo C, Raji YR, Burke D, et al. Human Heredity and Health (H3) in Africa 
Kidney Disease Research Network: A Focus on Methods in Sub-Saharan Africa. 
Clinical journal of the American Society of Nephrology : CJASN. 
2015;10(12):2279-2287. 
25. 
Estrella MM, Li M, Tin A, et al. The association between APOL1 risk alleles and 
longitudinal kidney function differs by HIV viral suppression status. Clinical 
infectious diseases : an official publication of the Infectious Diseases Society of 
America. 2015;60(4):646-652. 
26. 
Nelson GW, Freedman BI, Bowden DW, et al. Dense mapping of MYH9 
localizes the strongest kidney disease associations to the region of introns 13 to 
15. Human Molecular Genetics. 2010;19(9):1805-1815. 
27. 
Kopp JB, Smith MW, Nelson GW, et al. MYH9 is a major-effect risk gene for 
focal segmental glomerulosclerosis. Nature genetics. 2008;40(10):1175-1184. 
28. 
Linda Kao W, Klag MJ, Meoni LA, et al. A genome-wide admixture scan 
identifies MYH9 as a candidate locus associated with non-diabetic end stage renal 
disease in African Americans. Nature genetics. 2008;40(10):1185-1192. 
29. 
Winkler CA, Nelson G, Oleksyk TK, Nava MB, Kopp JB. Genetics of focal 
segmental glomerulosclerosis and HIV-associated collapsing glomerulopathy: the 
role of MYH9 genetic variation. Seminars in nephrology. 2010;30(2):111-125. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
55 
 
30. 
Kasembeli AN, Duarte R, Ramsay M, et al. APOL1 Risk Variants Are Strongly 
Associated with HIV-Associated Nephropathy in Black South Africans. Journal 
of the American Society of Nephrology : JASN. 2015;26(11):2882-2890. 
31. 
Okpechi IG, Ayodele OE, Rayner BL, Swanepoel CR. Kidney disease in elderly 
South Africans. Clin Nephrol. 2013;79(4):269-276. 
32. 
Melikian N, Wheatcroft SB, Ogah OS, et al. Asymmetric dimethylarginine and 
reduced nitric oxide bioavailability in young Black African men. Hypertension 
(Dallas, Tex : 1979). 2007;49(4):873-877. 
33. 
Abraham AG, Althoff KN, Jing Y, et al. End-stage renal disease among HIV- 
infected adults in North America. Clinical infectious diseases : an official 
publication of the Infectious Diseases Society of America. 2015;60(6):941-949. 
34. 
Kimmel PL, Barisoni L, Kopp JB. Pathogenesis and treatment of HIV-associated 
renal diseases: lessons from clinical and animal studies, molecular pathologic 
correlations, and genetic investigations. Annals of internal medicine. 
2003;139(3):214-226. 
35. 
Atta MG, Estrella MM, Kuperman M, et al. HIV-associated nephropathy patients 
with and without apolipoprotein L1 gene variants have similar clinical and 
pathological characteristics. Kidney international. 2012;82(3):338-343. 
36. 
Kopp JB, Nelson GW, Sampath K, et al. APOL1 genetic variants in focal 
segmental glomerulosclerosis and HIV-associated nephropathy. Journal of the 
American Society of Nephrology : JASN. 2011;22(11):2129-2137. 
37. 
Genovese G, Friedman DJ, Ross MD, et al. Association of trypanolytic ApoL1 
variants with kidney disease in African Americans. Science (New York, NY). 
2010;329(5993):841-845. 
38. 
Pollak MR, Genovese G, Friedman DJ. APOL1 and kidney disease. Current 
opinion in nephrology and hypertension. 2012;21(2):179-182. 
39. 
Ulasi, II, Tzur S, Wasser WG, et al. High population frequencies of APOL1 risk 
variants are associated with increased prevalence of non-diabetic chronic kidney 
disease in the Igbo people from south-eastern Nigeria. Nephron Clinical practice. 
2013;123(1-2):123-128. 
40. 
Tayo BO, Kramer H, Salako BL, et al. Genetic variation in APOL1 and MYH9 
genes is associated with chronic kidney disease among Nigerians. International 
urology and nephrology. 2013;45(2):485-494. 
41. 
Dummer PD, Limou S, Rosenberg AZ, et al. APOL1 Kidney Disease Risk 
Variants: An Evolving Landscape. Seminars in nephrology. 2015;35(3):222-236. 
42. 
Limou S, Dummer P, Nelson GW, Kopp JB, Winkler CA. APOL1 Toxin, Innate 
Immunity and Kidney Injury. Kidney international. 2015;88(1):28-34. 
43. 
Price CP, Newall RG, Boyd JC. Use of protein:creatinine ratio measurements on 
random urine samples for prediction of significant proteinuria: a systematic 
review. Clinical chemistry. 2005;51(9):1577-1586. 
44. 
Gerstein HC, Mann JF, Yi Q, et al. Albuminuria and risk of cardiovascular events, 
death, and heart failure in diabetic and nondiabetic individuals. Jama. 
2001;286(4):421-426. 
45. 
Choi A, Scherzer R, Bacchetti P, et al. Cystatin C, Albuminuria, and 5-Year All- 
Cause Mortality in HIV-Infected Persons. American journal of kidney diseases : 
the official journal of the National Kidney Foundation. 2010;56(5):872-882. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
56 
 
46. 
Farmer AJ, Stevens R, Hirst J, et al. Optimal strategies for identifying kidney 
disease in diabetes: properties of screening tests, progression of renal dysfunction 
and impact of treatment - systematic review and modelling of progression and 
cost-effectiveness. Health technology assessment (Winchester, England). 
2014;18(14):1-128. 
47. 
Keane WF, Eknoyan G. Proteinuria, albuminuria, risk, assessment, detection, 
elimination (PARADE): a position paper of the National Kidney Foundation. 
American journal of kidney diseases : the official journal of the National Kidney 
Foundation. 1999;33(5):1004-1010. 
48. 
Wyatt C, R Hoover D, Shi Q, et al. Pre-existing albuminuria predicts AIDS and 
non-AIDS mortality in women initiating antiretroviral therapy. Vol 162011. 
49. 
Estrella MM, Abraham AG, Jing Y, et al. Antiretroviral-treated HIV-infected 
women have similar long-term kidney function trajectories as HIV-uninfected 
women. AIDS Res Hum Retroviruses. 2013;29(5):755-760. 
50. 
Katz DH, Selvaraj S, Aguilar FG, et al. Association of low-grade albuminuria 
with adverse cardiac mechanics: findings from the hypertension genetic 
epidemiology network (HyperGEN) study. Circulation. 2014;129(1):42-50. 
51. 
Hadigan C, Edwards E, Rosenberg A, et al. Microalbuminuria in HIV disease. 
American journal of nephrology. 2013;37(5):443-451. 
52. 
Lamb EJ, MacKenzie F, Stevens PE. How should proteinuria be detected and 
measured? Annals of clinical biochemistry. 2009;46(Pt 3):205-217. 
53. 
Gansevoort RT, Matsushita K, van der Velde M, et al. Lower estimated GFR and 
higher albuminuria are associated with adverse kidney outcomes. A collaborative 
meta-analysis of general and high-risk population cohorts. Kidney international. 
2011;80(1):93-104. 
54. 
Witte EC, Lambers Heerspink HJ, de Zeeuw D, Bakker SJ, de Jong PE, 
Gansevoort R. First morning voids are more reliable than spot urine samples to 
assess microalbuminuria. Journal of the American Society of Nephrology : JASN. 
2009;20(2):436-443. 
55. 
Lambers Heerspink HJ, Gansevoort RT, Brenner BM, et al. Comparison of 
Different Measures of Urinary Protein Excretion for Prediction of Renal Events. 
Journal of the American Society of Nephrology : JASN. 2010;21(8):1355-1360. 
56. 
Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint 
National Committee on Prevention, Detection, Evaluation, and Treatment of High 
Blood Pressure: the JNC 7 report. Jama. 2003;289(19):2560-2572. 
57. 
Foundation NK. K/DOQI clinical practice guidelines for chronic kidney disease: 
evaluation, classification, and stratification. American journal of kidney diseases : 
the official journal of the National Kidney Foundation. 2002;39(2 Suppl 1):S1- 
266. 
58. 
Association AD. Standards of Medical Care in Diabetes42007. Diabetes Care. 
2007;30(suppl 1):S4. 
59. 
Guy M, Borzomato JK, Newall RG, Kalra PA, Price CP. Protein and albumin-to- 
creatinine ratios in random urines accurately predict 24 h protein and albumin loss 
in patients with kidney disease. Annals of clinical biochemistry. 2009;46(Pt 
6):468-476. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
57 
 
60. 
Newman DJ, Pugia MJ, Lott JA, Wallace JF, Hiar AM. Urinary protein and 
albumin excretion corrected by creatinine and specific gravity. Clinica chimica 
acta; international journal of clinical chemistry. 2000;294(1-2):139-155. 
61. 
Marshall SM. Screening for microalbuminuria: which measurement? Diabetic 
medicine : a journal of the British Diabetic Association. 1991;8(8):706-711. 
62. 
Cooper TCJG. Comparison of urinary albumin excretion rate in overnight urine 
and albumin creatinine ratio in spot urine in diabetic patients in general practice. 
Scandinavian Journal of Primary Health Care. 2001;19(4):247-248. 
63. 
Leanos-Miranda A, Marquez-Acosta J, Romero-Arauz F, et al. Protein:creatinine 
ratio in random urine samples is a reliable marker of increased 24-hour protein 
excretion in hospitalized women with hypertensive disorders of pregnancy. 
Clinical chemistry. 2007;53(9):1623-1628. 
64. 
Ruggenenti P, Perna A, Mosconi L, Pisoni R, Remuzzi G. Urinary protein 
excretion rate is the best independent predictor of ESRF in non-diabetic 
proteinuric chronic nephropathies. "Gruppo Italiano di Studi Epidemiologici in 
Nefrologia" (GISEN). Kidney international. 1998;53(5):1209-1216. 
65. 
Gupta SK, Komarow L, Gulick RM, et al. Proteinuria, CrCl, and Immune 
Activation in Antiretroviral-Naïve HIV-Infected Subjects. The Journal of 
infectious diseases. 2009;200(4):614-618. 
66. 
Gupta SK, Eustace JA, Winston JA, et al. Guidelines for the management of 
chronic kidney disease in HIV-infected patients: recommendations of the HIV 
Medicine Association of the Infectious Diseases Society of America. Clinical 
infectious diseases : an official publication of the Infectious Diseases Society of 
America. 2005;40(11):1559-1585. 
67. 
Szczech LA, Gange SJ, van der Horst C, et al. Predictors of proteinuria and renal 
failure among women with HIV infection. Kidney international. 2002;61(1):195- 
202. 
68. 
Gupta SK, Mamlin BW, Johnson CS, Dollins MD, Topf JM, Dube MP. 
Prevalence of proteinuria and the development of chronic kidney disease in HIV- 
infected patients. Clin Nephrol. 2004;61(1):1-6. 
69. 
Gardner LI, Holmberg SD, Williamson JM, et al. Development of proteinuria or 
elevated serum creatinine and mortality in HIV-infected women. Journal of 
acquired immune deficiency syndromes (1999). 2003;32(2):203-209. 
70. 
Szczech LA, Hoover DR, Feldman JG, et al. Association between renal disease 
and outcomes among HIV-infected women receiving or not receiving 
antiretroviral therapy. Clinical infectious diseases : an official publication of the 
Infectious Diseases Society of America. 2004;39(8):1199-1206. 
71. 
Bruggeman LA, Bark C, Kalayjian RC. HIV and the Kidney. Current infectious 
disease reports. 2009;11(6):479-485. 
72. 
Leventhal JS, Ross MJ. Pathogenesis of HIV-associated nephropathy. Seminars in 
nephrology. 2008;28(6):523-534. 
73. 
Lucas GM, Mehta SH, Atta MG, et al. End-stage renal disease and chronic kidney 
disease in a cohort of African-American HIV-infected and at-risk HIV- 
seronegative participants followed between 1988 and 2004. Aids. 
2007;21(18):2435-2443. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
58 
 
74. 
Post FA, Campbell LJ, Hamzah L, et al. Predictors of renal outcome in HIV- 
associated nephropathy. Clinical infectious diseases : an official publication of 
the Infectious Diseases Society of America. 2008;46(8):1282-1289. 
75. 
Röling J, Schmid H, Fischereder M, Draenert R, Goebel FD. HIV-Associated 
Renal Diseases and Highly Active Antiretroviral Therapy4Induced Nephropathy. 
Clinical Infectious Diseases. 2006;42(10):1488-1495. 
76. 
Naicker S. End-stage renal disease in sub-Saharan and South Africa. Kidney 
international Supplement. 2003(83):S119-122. 
77. 
Rao TK, Friedman EA, Nicastri AD. The types of renal disease in the acquired 
immunodeficiency syndrome. The New England journal of medicine. 
1987;316(17):1062-1068. 
78. 
Gardenswartz MH, Lerner CW, Seligson GR, et al. Renal disease in patients with 
AIDS: a clinicopathologic study. Clin Nephrol. 1984;21(4):197-204. 
79. 
Bourgoignie JJ, Meneses R, Ortiz C, Jaffe D, Pardo V. The clinical spectrum of 
renal disease associated with human immunodeficiency virus. American journal 
of kidney diseases : the official journal of the National Kidney Foundation. 
1988;12(2):131-137. 
80. 
Han TM, Naicker S, Ramdial PK, Assounga AG. A cross-sectional study of HIV- 
seropositive patients with varying degrees of proteinuria in South Africa. Kidney 
international. 2006;69(12):2243-2250. 
81. 
Fried LF, Emanuele N, Zhang JH, et al. Combined angiotensin inhibition for the 
treatment of diabetic nephropathy. The New England journal of medicine. 
2013;369(20):1892-1903. 
82. 
Mavrakanas TA, Gariani K, Martin PY. Mineralocorticoid receptor blockade in 
addition to angiotensin converting enzyme inhibitor or angiotensin II receptor 
blocker treatment: an emerging paradigm in diabetic nephropathy: a systematic 
review. European journal of internal medicine. 2014;25(2):173-176. 
83. 
Schmieder RE, Bakris G, Weir MR. Telmisartan in incipient and overt diabetic 
renal disease. Journal of nephrology. 2011;24(3):263-273. 
84. 
Karalliedde J, Viberti G. Proteinuria in diabetes: bystander or pathway to 
cardiorenal disease? Journal of the American Society of Nephrology : JASN. 
2010;21(12):2020-2027. 
85. 
Fraga-Silva RA, Costa-Fraga FP, Murca TM, et al. Angiotensin-converting 
enzyme 2 activation improves endothelial function. Hypertension (Dallas, Tex : 
1979). 2013;61(6):1233-1238. 
86. 
Mauer M, Zinman B, Gardiner R, et al. Renal and retinal effects of enalapril and 
losartan in type 1 diabetes. The New England journal of medicine. 
2009;361(1):40-51. 
87. 
Lozano JV, Llisterri JL, Aznar J, Redon J. Losartan reduces microalbuminuria in 
hypertensive microalbuminuric type 2 diabetics. Nephrology, dialysis, 
transplantation : official publication of the European Dialysis and Transplant 
Association - European Renal Association. 2001;16 Suppl 1:85-89. 
88. 
Brenner BM, Cooper ME, de Zeeuw D, et al. The losartan renal protection study-- 
rationale, study design and baseline characteristics of RENAAL (Reduction of 
Endpoints in NIDDM with the Angiotensin II Antagonist Losartan). Journal of 
the renin-angiotensin-aldosterone system : JRAAS. 2000;1(4):328-335. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
59 
 
89. 
Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and 
cardiovascular outcomes in patients with type 2 diabetes and nephropathy. The 
New England journal of medicine. 2001;345(12):861-869. 
90. 
Crepaldi G, Carta Q, Deferrari G, et al. Effects of lisinopril and nifedipine on the 
progression to overt albuminuria in IDDM patients with incipient nephropathy 
and normal blood pressure. The Italian Microalbuminuria Study Group in IDDM. 
Diabetes Care. 1998;21(1):104-110. 
91. 
Maione A, Navaneethan SD, Graziano G, et al. Angiotensin-converting enzyme 
inhibitors, angiotensin receptor blockers and combined therapy in patients with 
micro- and macroalbuminuria and other cardiovascular risk factors: a systematic 
review of randomized controlled trials. Nephrology, dialysis, transplantation : 
official publication of the European Dialysis and Transplant Association - 
European Renal Association. 2011;26(9):2827-2847. 
92. 
Fiordaliso F, Cuccovillo I, Bianchi R, et al. Cardiovascular oxidative stress is 
reduced by an ACE inhibitor in a rat model of streptozotocin-induced diabetes. 
Life sciences. 2006;79(2):121-129. 
93. 
Lewis EJ. The role of angiotensin II receptor blockers in preventing the 
progression of renal disease in patients with type 2 diabetes. American Journal of 
Hypertension. 2002;15(S5):123S-128S. 
94. 
Mayyas F, Alzoubi KH, Van Wagoner DR. Impact of aldosterone antagonists on 
the substrate for atrial fibrillation: aldosterone promotes oxidative stress and atrial 
structural/electrical remodeling. International journal of cardiology. 
2013;168(6):5135-5142. 
95. 
Hartono SP, Knudsen BE, Zubair AS, et al. Redox Signaling Is an Early Event in 
the Pathogenesis of Renovascular Hypertension. International Journal of 
Molecular Sciences. 2013;14(9):18640-18656. 
96. 
Whaley-Connell A, Habibi J, Rehmer N, et al. Renin inhibition and AT(1)R 
blockade improve metabolic signaling, oxidant stress and myocardial tissue 
remodeling. Metabolism: clinical and experimental. 2013;62(6):861-872. 
97. 
Whaley-Connell A, Sowers JR. Oxidative Stress in the Cardiorenal Metabolic 
Syndrome. Current hypertension reports. 2012;14(4):360-365. 
98. 
UNAIDS. Nigeria HIV and AIDS estimates (2018) 
http://www.unaids.org/en/regionscountries/countries/nigeria. Accessed 
September, 2019. 
99. 
Kimmel PL, Mishkin GJ, Umana WO. Captopril and renal survival in patients 
with human immunodeficiency virus nephropathy. American journal of kidney 
diseases : the official journal of the National Kidney Foundation. 1996;28(2):202- 
208. 
100. 
Burns GC, Paul SK, Toth IR, Sivak SL. Effect of angiotensin-converting enzyme 
inhibition in HIV-associated nephropathy. Journal of the American Society of 
Nephrology : JASN. 1997;8(7):1140-1146. 
101. 
Wei A, Burns GC, Williams BA, Mohammed NB, Visintainer P, Sivak SL. Long- 
term renal survival in HIV-associated nephropathy with angiotensin-converting 
enzyme inhibition. Kidney international. 2003;64(4):1462-1471. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
60 
 
102. 
Szczech LA, Gupta SK, Habash R, et al. The clinical epidemiology and course of 
the spectrum of renal diseases associated with HIV infection. Kidney 
international. 2004;66(3):1145-1152. 
103. 
Baker JV, Huppler Hullsiek K, Prosser R, et al. Angiotensin converting enzyme 
inhibitor and HMG-CoA reductase inhibitor as adjunct treatment for persons with 
HIV infection: a feasibility randomized trial. PloS one. 2012;7(10):e46894. 
104. 
Bige N, Lanternier F, Viard JP, et al. Presentation of HIV-associated nephropathy 
and outcome in HAART-treated patients. Nephrology, dialysis, transplantation : 
official publication of the European Dialysis and Transplant Association - 
European Renal Association. 2012;27(3):1114-1121. 
105. 
Yahaya I, Uthman OA, Uthman MM. Interventions for HIV-associated 
nephropathy. The Cochrane database of systematic reviews. 2013(1):Cd007183. 
106. 
Ucciferri C, Falasca K, Mancino P, Di Iorio A, Vecchiet J. Microalbuminuria and 
hypertension in HIV-infected patients: a preliminary study of telmisartan. 
European review for medical and pharmacological sciences. 2012;16(4):491-498. 
107. 
Whoqol Hiv G. WHOQOL-HIV for quality of life assessment among people 
living with HIV and AIDS: results from the field test. AIDS care. 2004;16(7):882- 
889. 
108. 
Group TW-H. Initial steps to developing the World Health Organization's Quality 
of Life Instrument (WHOQOL) module for international assessment in 
HIV/AIDS. AIDS care. 2003;15(3):347-357. 
109. 
Karnofsky DA BJ. The clinical evaluation of chemotherapeutic agents in cancer. 
In: CM M, ed. Evaluation of chemotherapeutic agents. New York: Columbia 
University Press; 1949:191-205. 
110. 
Sakajiki A, Adamu B, Arogundade F, Abdu A, Atanda A, Garba B. Prevalence, 
risk factors, and histological pattern of kidney disease in patients with Human 
Immunodeficiency Virus/Acquired Immunodeficiency Syndrome at Aminu Kano 
Teaching Hospital: A clinicopathologic study. Annals of Nigerian Medicine. 
2014;8(2):69-75. 
111. 
Peralta CA, Bibbins-Domingo K, Vittinghoff E, et al. APOL1 Genotype and Race 
Differences in Incident Albuminuria and Renal Function Decline. Journal of the 
American Society of Nephrology : JASN. 2016;27(3):887-893. 
112. 
Fine DM, Wasser WG, Estrella MM, et al. APOL1 Risk Variants Predict 
Histopathology and Progression to ESRD in HIV-Related Kidney Disease. 
Journal of the American Society of Nephrology : JASN. 2012;23(2):343-350. 
113. 
Bussmann H, Wester CW, Wester CN, et al. Pregnancy rates and birth outcomes 
among women on efavirenz-containing highly active antiretroviral therapy in 
Botswana. Journal of acquired immune deficiency syndromes (1999). 
2007;45(3):269-273. 
114. 
Mujugira A, Wester CW, Kim S, Bussmann H, Gaolathe T. Patients with 
advanced HIV type 1 infection initiating antiretroviral therapy in Botswana: 
treatment response and mortality. AIDS Res Hum Retroviruses. 2009;25(2):127- 
133. 
115. 
Wester CW, Stitelman OM, deGruttola V, Bussmann H, Marlink RG, van der 
Laan MJ. Effect Modification by Sex and Baseline CD4(+) Cell Count Among 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
61 
 
Adults Receiving Combination Antiretroviral Therapy in Botswana: Results from 
a Clinical Trial. AIDS Res Hum Retroviruses. 2012;28(9):781-788. 
116. 
Wester CW, Thomas AM, Bussmann H, et al. Non-Nucleoside Reverse 
Transcriptase Inhibitor Outcomes Among cART-Treated Adults in Botswana. 
Aids. 2010;24(Suppl 1):S27-36. 
117. 
Wester CW, Eden SK, Shepherd BE, et al. Risk factors for symptomatic 
hyperlactatemia and lactic acidosis among combination antiretroviral therapy- 
treated adults in Botswana: results from a clinical trial. AIDS Res Hum 
Retroviruses. 2012;28(8):759-765. 
118. 
Aliyu MH, Blevins M, Audet CM, et al. Integrated prevention of mother-to-child 
HIV transmission services, antiretroviral therapy initiation, and maternal and 
infant retention in care in rural north-central Nigeria: a cluster-randomised 
controlled trial. The lancet HIV. 2016;3(5):e202-211. 
119. 
Musa BM, Garbati MA, Nashabaru IM, et al. Sex disparities in outcomes among 
adults on long-term antiretroviral treatment in northern Nigeria. Int Health. 
2017;9(1):3-10. 
120. 
Audet CM, Blevins M, Chire YM, et al. Engagement of men in antenatal care 
services: Increased HIV testing and treatment uptake in a community 
participatory action program in Mozambique. AIDS and behavior. 
2016;20(9):2090-2100. 
121. 
Watanabe N, Kamei S, Ohkubo A, et al. Urinary protein as measured with a 
pyrogallol red-molybdate complex, manually and in a Hitachi 726 automated 
analyzer. Clinical chemistry. 1986;32(8):1551-1554. 
122. 
Bartels H, Bohmer M. [Micro-determination of creatinine]. Clinica chimica acta; 
international journal of clinical chemistry. 1971;32(1):81-85. 
123. 
Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate 
from serum creatinine and cystatin C. The New England journal of medicine. 
2012;367(1):20-29. 
124. 
Wyatt CM, Schwartz GJ, Owino Ong'or W, et al. Estimating kidney function in 
HIV-infected adults in Kenya: comparison to a direct measure of glomerular 
filtration rate by iohexol clearance. PloS one. 2013;8(8):e69601. 
125. 
Shlipak MG, Matsushita K, Arnlov J, et al. Cystatin C versus creatinine in 
determining risk based on kidney function. The New England journal of medicine. 
2013;369(10):932-943. 
126. 
Mehdi UF, Adams-Huet B, Raskin P, Vega GL, Toto RD. Addition of angiotensin 
receptor blockade or mineralocorticoid antagonism to maximal angiotensin- 
converting enzyme inhibition in diabetic nephropathy. Journal of the American 
Society of Nephrology : JASN. 2009;20(12):2641-2650. 
127. 
Stellbrink HJ, Reynes J, Lazzarin A, et al. Dolutegravir in antiretroviral-naive 
adults with HIV-1: 96-week results from a randomized dose-ranging study. Aids. 
2013;27(11):1771-1778. 
128. 
Eron JJ, Clotet B, Durant J, et al. Safety and efficacy of dolutegravir in treatment- 
experienced subjects with raltegravir-resistant HIV type 1 infection: 24-week 
results of the VIKING Study. The Journal of infectious diseases. 
2013;207(5):740-748. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
62 
 
129. 
Taha H, Das A, Das S. Clinical effectiveness of dolutegravir in the treatment of 
HIV/AIDS. Infection and drug resistance. 2015;8:339-352. 
130. 
Milburn J, Jones R, Levy JB. Renal effects of novel antiretroviral drugs. 
Nephrology, dialysis, transplantation : official publication of the European 
Dialysis and Transplant Association - European Renal Association. 
2017;32(3):434-439. 
131. 
Alwan S, Polifka JE, Friedman JM. Angiotensin II receptor antagonist treatment 
during pregnancy. Birth defects research Part A, Clinical and molecular 
teratology. 2005;73(2):123-130. 
132. 
Cooper WO, Hernandez-Diaz S, Arbogast PG, et al. Major congenital 
malformations after first-trimester exposure to ACE inhibitors. The New England 
journal of medicine. 2006;354(23):2443-2451. 
133. 
Andrade SE, Kahler KH, Frech F, Chan KA. Methods for evaluation of 
medication adherence and persistence using automated databases. 
Pharmacoepidemiology and drug safety. 2006;15(8):565-574; discussion 575- 
567. 
134. 
Svarstad BL, Chewning BA, Sleath BL, Claesson C. The Brief Medication 
Questionnaire: a tool for screening patient adherence and barriers to adherence. 
Patient education and counseling. 1999;37(2):113-124. 
135. 
Harrell F. Regression Modelling Strategies with Applications to Linear Models, 
Logistic and Ordinal Regression, and Survival Analysis. 2nd ed. New York: 
Springer; 2015. 
136. 
Collett D. Modelling Survival data in Medical Research 2nd ed. London: 
Chapman and Hall; 2003. 
137. 
Davis LL, Broome ME, Cox RP. Maximizing retention in community-based 
clinical trials. Journal of nursing scholarship : an official publication of Sigma 
Theta Tau International Honor Society of Nursing. 2002;34(1):47-53. 
138. 
Gul RB, Ali PA. Clinical trials: the challenge of recruitment and retention of 
participants. Journal of clinical nursing. 2010;19(1-2):227-233. 
139. 
Zweben A, Barrett D, Berger L, Murray KT. Recruiting and retaining participants 
in a combined behavioral and pharmacological clinical trial. Journal of studies on 
alcohol Supplement. 2005(15):72-81; discussion 65. 
140. 
Aitken L, Gallagher R, Madronio C. Principles of recruitment and retention in 
clinical trials. International journal of nursing practice. 2003;9(6):338-346. 
141. 
Musa BM, Coker M, Bussell S, et al. Long-term outcomes of antiretroviral 
therapy in an adult HIV program: a 10-year retrospective cohort study in Kano, 
Nigeria. Annals of Saudi medicine. 2015;35(4):303-311. 


Protocol Version #: 10.0 
Protocol Date: July 24, 2021 
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