The HIV, Adipose Tissue Immunology, and Metabolism Study
Conditions: Hiv, Diabetes Mellitus, Type 2
Sponsor: Vanderbilt University Medical Center

Version 1.1 
Date: 5/12/17 
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The HIV, Adipose Tissue Immunology, and Metabolism 
(HATIM) Study 
 
 
Vanderbilt University Medical Center 
 
 
Clinical Visit Protocol 
 
Protocol v1.1    May 12, 2017 
 
 
 
 
ClinicalTrials.gov:  NCT04451980 
 
 
Supported by NIH grant R01DK112262

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Table of Contents: 
 
1.0 
Background and Rationale  
2.0 
Preliminary Studies 
3.0 
Hypotheses and Specific Aims 
4.0 
Study Methods 
4.1 Study Overview 
4.2 Participant Recruitment 
4.3 Inclusion Criteria for HIV+ Participants 
4.4 Inclusion Criteria for HIV-negative Participants 
4.5 Study Procedures 
5.0 
Risks to Study Participants 
5.1 
Potential Risks 
5.2 
Biohazard Risks 
5.3 
Protections against Risk 
5.4 
Potential Benefits of the Research 
6.0 
Data Safety and Monitoring Plan 
7.0 
Reporting of Adverse Events  
8.0 
Study Withdrawal/Discontinuation 
9.0 
Privacy/Confidentiality Issues 
10.0 Follow-up and Record Retention 
11.0 ClinicalTrials.gov Requirements 
12.0 References 
 

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1.0 Background and Rationale 
 
With the introduction of effective antiretroviral therapy (ART), HIV-infected persons can now 
survive for decades, but this success has been accompanied by an increased risk of developing 
metabolic disease compared HIV-negative persons. In the Multicenter AIDS Cohort Study, HIV-
infected men had a greater than 4-fold increased incidence of a new diabetes diagnosis 
compared to HIV-negative men after adjusting for age and body mass index (BMI).1 Prevalence 
studies of diabetes in HIV-infected individuals on ART have reported incidence rates of 3.1 to 14 
per 1000 patient-years.2, 3 Furthermore, treated HIV infection appears to act synergistically with 
other risk factors, and diabetes prevalence is especially high among HIV-infected individuals 
with obesity and advanced age.2, 4 
 
While early studies found inflammation (i.e., innate immune activation) was associated with 
diabetes risk in persons with HIV, more recent data suggest chronic cellular immune activation 
may have a central role in diabetes pathogenesis. Recent studies from HIV-negative subjects 
identified several associations between adaptive immune cell populations and impaired glucose 
tolerance. Peripheral T regulatory (Treg) cells are significantly lower in patients with type-2 
diabetes and inversely proportional to HbA1c levels, while the numbers of CD25+ (activated)  T 
cells and the proportion of TH1 (pro-inflammatory) cells are higher in diabetics.5-7 More recently, 
an analysis of the Multi-Ethnic Study of Atherosclerosis (MESA) cohort found a higher 
proportion of circulating memory CD4+ T cells and TH1 cells was associated with insulin levels 
and prevalent type 2 diabetes.8 Our group found a similar association between memory CD4+ T 
cells and incident diabetes for HIV patients in the Veterans Aging Cohort Study (VACS; see 
preliminary data). 
 
T cells and macrophages are present in the stromal fraction of adipose tissue and affect 
adipocyte function. The striking increase in adipose tissue CD4+ TH1 cells and CD8+ T cells, and 
a decrease in Treg cells, observed in obesity may have an important role in the development of 
insulin resistance.9-12 Secretion of the proinflammatory cytokines IFN-γ and IL-17 by TH1 and 
TH17 cells are implicated in the induction of proinflammatory M1 macrophages, which express 
IL-6 and tumor necrosis factor alpha (TNF-α) and inhibit adipocyte insulin signaling by 
promoting phosphorylation of insulin receptor substrate 1.13-1515, 17, 18  T cell infiltration into 
adipose tissue appears to be an early and necessary step preceding macrophage recruitment 
into adipose tissue, and in murine models antibody-induced CD8+ T cell depletion resulted in 
reduced M1 macrophage infiltration.9  
 
HIV offers a unique model to study linkages between peripheral T cells, adipose-resident T 
cells, adipose tissue function, and glucose tolerance. The changes in peripheral T cell subsets 
observed in chronic HIV-related immune activation are similar to those associated with insulin 
resistance in obese HIV-negative individuals. Immune cells translocate from the peripheral 
circulation into adipose tissue in a dynamic process, and we hypothesize that the chronic, HIV-
related activation of peripheral CD4+ and CD8+ T cells may be accompanied by the 
accumulation of activated T cells in adipose tissue with adverse effects on metabolic activity. In 
this study, we will test the hypothesis that the oligoclonal expansion of chronically activated 
peripheral T cells in adipose tissue is a primary driver of macrophage inflammation and reduced 
adipocyte insulin sensitivity. Furthermore, we propose that this represents a central mechanistic 
linkage underlying the association between circulating T cell activation and incident diabetes 
risk observed in HIV-infected and HIV-negative individuals. 
 

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2.0 Preliminary Studies 
 
2.1. Adipose tissue from HIV+ persons is enriched for activated CD8+ T cells and there is 
a correlation between the percentage of circulating and adipose-resident memory CD4+ T 
cells: To assess the relationships between circulating and adipose tissue T cell subset 
distributions, we conduced pilot study to compare T cell populations in adipose tissue biopsies 
and peripheral blood in 10 HIV infected subjects on long-term ART with sustained viral 
suppression. We collected 5-10 ml of abdominal subcutaneous adipose tissue using a 2.7 mm 
liposuction cannula. All subjects were fasting. Adipose tissue biopsies were repeatedly washed 
to eliminate any blood contamination and T cells extracted. Flow cytometry was performed on 
the adipose tissue T cells in addition to paired peripheral blood samples to measure CD3, CD4, 
and CD8 surface marker expression, and markers of activation (CD38, HLA-DR, CD69), 
senescence (CD57, PD-1), and memory cells (CD45RO).  
 
We found adipose tissue to be enriched for activated CD8+ T cells (CD38+ and HLA-DR+) 
compared to blood – a cell type shown to promote adipose-resident macrophage activation in 
animal studies (Table 1). Furthermore, the relative percentages of CD4+ and CD8+ T cells were 
highly correlated between blood and adipose tissue, as were the percentages of activated 
(DR+) CD8+ T cells and memory (CD45RO+) CD4+ T cells. This finding supports our 
hypothesis that the distribution of T cell subsets in blood reflects the distribution of these T cell 
subsets in adipose tissue.  
 
 
2.2. Adipose resident CD8+ T cell density and TCR clonality is higher in obese mice fed a 
high-fat diet for 16 weeks compared to mice fed a low-fat diet. To understand whether 
adipose-resident CD8+ T cell receptor oligoclonality varies with changes in adipose tissue, we 
assigned C57BL/6 mice to a chow, low-fat, or high-fat diet for 16 weeks (n=9 total) and then 
collected epididymal fat samples for T cell extraction, sorting, and T cell receptor surveillance 
Table 1. Pilot study comparing T cell subsets in blood and adipose tissue from HIV+ patients 
with long-term (>4 years) ART treatment and viral suppression (n=10) 
 
Comparison of median values in 
blood vs. adipose tissue 
 
Correlation between 
blood and adipose tissue 
T cell subset 
Median in 
blood 
Median in 
adipose 
tissue 
p-value 
 
Spearman 
rho 
p-value 
CD4+ %* 
43.2 
34.0 
0.06 
 
0.95 
<0.01 
 
CD4+ PD1+% 
24.6 
24.8 
0.93 
 
0.42 
0.27 
 
CD4+ CD57+% 
2.2 
5.4 
0.06 
 
0.95 
<0.01 
 
CD4+ CD38+% 
4.0 
2.4 
0.44 
 
0.16 
0.68 
 
CD4+ DR+% 
1.0 
2.5 
0.001 
 
0.52 
0.15 
 
CD4+ CD69+% 
0.25 
0.80 
0.08 
 
0.23 
0.56 
 
CD4+ CD45RO+% 
50.3 
57.4 
0.86 
 
0.83 
0.005 
 
CD8+ %* 
50.4 
60.9 
0.11 
 
0.85 
0.004 
 
CD8+ PD1+% 
22.1 
21.8 
0.99 
 
0.80 
0.01 
 
CD8+ CD57+% 
22.7 
35.1 
0.01 
 
0.38 
0.31 
 
CD8+ CD38+% 
0.50 
0.90 
0.02 
 
0.32 
0.40 
 
CD8+ DR+% 
0.90 
5.3 
<0.001 
 
0.67 
<0.05 
 
CD8+ CD69+% 
0.55 
1.00 
0.44 
 
0.59 
0.10 
 
CD8+ CD45RO+% 
31.3 
33.6 
0.73 
 
0.23 
0.55 
*Represents the percentage of CD3+ T cells that expressed CD4 or CD8. All other values represent the 
percentage of CD4+ or CD8+ population expressing selected surface markers. 

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sequencing and clonality score calculation (a measure based on Shannon’s entropy of the 
distribution of all TCR sequences – a higher clonality score indicates less entropy). Mice fed a 
high-fat diet were more obese and demonstrated the greatest number of CD8+ T cells per gram  
of adipose tissue (10,254 CD8+ cells/gram in high-fat; 9,940 cells/g in low-fat; and 3,922 cells/g 
in chow diet) and high-fat diet adipose tissue had greater expression of CD11b and F4/80 
macrophage markers and IL-6 compared 
to low-fat diet (p<0.05 for all). More 
striking, adipose-resident CD8+ T cell 
density was significantly correlated with T 
cell receptor clonality score (r=0.78, 
p=0.01, Table 2), suggesting the 
increased CD8+ density in the obese 
mice represented an oligoclonal 
expansion. 
 
2.3. Greater circulating CD4+ memory T cells are associated with the odds of incident 
diabetes in HIV+ persons on ART: In pilot data from 76 male HIV+ Veterans Aging Cohort 
Study Biospecimen Cohort (VACS-BC) subjects, a higher proportion of memory T cells (CD4+ 
CD45RO+) was associated with a higher odds ratio for incident diabetes (OR= 10.0 for highest 
tertile of CD45RO+ cells versus lowest tertile; Table 3). There was also a positive relationship 
between TH1 cytokine producing cells and the odds of incident diabetes that was not statistically 
significant (p=0.16), which may have been due to 
insufficient power. There were no significant 
findings for CD4+ or CD8+ T cell markers of 
activation or senescence. This finding, and similar 
results from the MESA cohort in non-HIV infected 
persons, supports our hypothesis that chronic 
immune activation of circulating T cells affects the 
insulin sensitivity of adipose and other 
metabolically active tissues.  
 
 
Table 2. Correlation between adipose-resident T 
cell density and clonality score in mice fed a chow, 
low-fat, or high-fat diet for 16 weeks (n=9) 
 
Pearson’s r 
p-value 
CD8+ cells  
0.78 
0.01 
CD4+ cells 
0.82 
0.06 
Density is calculated as the number of cells per gram of 
adipose tissue. CD4+ T cell recovery from chow mice was 
below the limit for sequencing (<1000 cells) 
Table 3. Relationships of CD4+ memory cell and 
TH1 cell populations with incident diabetes in a 
pilot study of HIV+ VACS subjects  
CD4+ T cell subset 
Odds ratio for 
incident diabetes 
p-value 
Memory (CD45RO+) 
10.0 
0.01 
TH1 (helper cell) 
2.9 
0.16 
• Odds ratio for highest tertile of cells versus lowest tertile 
• Logistic regression models adjusted for age, race, BMI, hepatitis 
C status, alcohol use, cocaine use, CD4 count, HIV-1 RNA, and 
CT visceral fat quantity.  

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3.0 Hypotheses and Specific Aims 
 
This study will assess the relationships of peripheral T cell distribution, adipose-resident T cell 
distribution, and adipose tissue inflammation in HIV-infected individuals, with the goal of 
understanding how chronic peripheral and tissue T cell activation may affect the risk of HIV-
associated metabolic disease. If our hypotheses are correct, we will demonstrate that chronic 
peripheral immune activation (i.e., high memory T cells, low naïve cells, and increased 
expression of activation surface markers) is associated with greater adipose-resident CD4+ and 
CD8+ T cell expression of activation markers, the oligoclonal expansion of T cells expressing a 
restricted TCR repertoire, and adipose tissue inflammation.  
 
Aim 1:  To test the hypothesis that a higher percentage of activated CD4+ and CD8+ T cells in 
circulating blood is associated with a higher percentage of activated T cells in adipose tissue. 
 
Aim 2: To test the hypothesis that activated T cells in adipose tissue contribute to macrophage 
activation, abnormal adipocyte gene expression, and glucose intolerance in HIV+ persons. 
 
Aim 3: To test the hypothesis that adipose tissue from HIV+ patients with greater glucose 
intolerance is characterized by higher CD8+ T cell receptor oligoclonality, potentially reflecting 
an antigen-driven process. 
 
 
4.0 Study Methods  
 
4.1 Study Overview: The study design incorporates a 3 year, two-visit longitudinal cohort study 
of 96 HIV+ subjects who are non-diabetic at enrollment but either at high risk (i.e., pre-diabetic) 
or lower risk (i.e., not pre-diabetic) of progressing to clinical diabetes, in addition to a cross-
sectional study which will compare these non-diabetic HIV+ subjects to an additional 40 HIV+ 
diabetics and 40 HIV-negative diabetics (see Figure). The baseline and follow-up study visits 
will include fasting peripheral blood collection, glucose tolerance testing, CT quantification of 
adipose tissue, and subcutaneous abdominal adipose tissue biopsies using a liposuction 
cannula system to collect approximately 10 ml of tissue. 
 
4.2 Participant Recruitment: HIV+ participants will be recruited from the Vanderbilt 
Comprehensive Care Clinic (VCCC), the largest HIV provider in central Tennessee and a 
principal study site for the AIDS Clinical Trials Group (ACTG). In 2014, a total of 2,954 HIV+ 
patients had at least one VCCC visit, including 358 new patients (up from 297 in 2013), and 
over 250 antiretroviral therapy-naïve adults start treatment yearly. Diabetic patients without HIV 
will be recruited from the Vanderbilt ResearchMatch cohort, an electronic clinical study 
volunteer registry. In March 2016 there were 180 adult volunteers with Type 2 diabetes mellitus 
within 50 miles of Vanderbilt University.  
 
4.3 Inclusion Criteria for HIV+ Participants: 
• 
On antiretroviral therapy for at least 18 months 
• 
HIV-1 RNA <50 copies/ml for the prior 12 months 
• 
CD4+ count >350 cells/µl in the prior 12 months 
• 
HbA1c in prior 6 months within specified limits (See Figure) 
• 
Pre-menopausal by self-report 
• 
No known inflammatory or rheumatologic conditions  
• 
No heavy alcohol (>11 drinks per week) or cocaine, amphetamine, or illicit (non-

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prescribed) opiate abuse by self-report 
• 
Not on on GLP-1 agonists or DPP-4 inhibitors (diabetic participants only) 
 
4.4 Inclusion Criteria for HIV-negative Participants: 
• 
A HbA1c >6.5% or a fasting glucose >126mg/dl, or on anti-diabetic medications for at 
least 6 months 
• 
Pre-menopausal by self-report 
• 
No known inflammatory or rheumatologic conditions  
• 
No heavy alcohol (>11 drinks per week) or cocaine, amphetamine, or illicit (non-
prescribed) opiate abuse by self-report 
• 
Not on a GLP-1 agonist or DPP-4 inhibitor 
 
 
The fasting glucose, hemoglobin A1c (HbA1c), and/or anti-diabetic medication requirements for 
inclusion in one of the 
three HIV+ groups or the 
one HIV-negative group 
are shown in the Figure. 
The fasting glucose of 
100mg/dl and HbA1c of 
5.7% separating the two 
HIV+ non-diabetic groups 
are based on American 
Diabetes Association 
cutoffs for pre-diabetes.16 
 
In selecting HIV+ 
participants, we will 
maintain a similar median 
age in each group, and 
we will recruit roughly 
equal numbers of white 
and non-white 
participants (reflecting 
the VCCC 
demographics), equal 
men and women, and an 
equal number of obese 
and non-obese (BMI >30 
kg/m2) in each group. We 
will also strive to enroll at 
least half our participants 
on an integrase strand 
transfer inhibitor (INSTI)-
based regimen. INSTIs 
are becoming a preferred 
antiretroviral agent to the 
exclusion of some older 
agents. This strategy will 
aid in understanding 
Figure: Subject groups, study design, and proposed assays 
 
Group 3: HIV+ diabetic (n=40)
•
HbA1c >=6.5%, or
•
Fasting glucose  >=126 mg/dl, or
•
On anti-diabetic medications
Group 1: HIV+ with normal 
glucose tolerance (n=48)
•
HbA1c <5.7%
•
Fasting glucose  <100 mg/dl
Baseline
clinical visit
Follow-up visit
3 years later
(B) Compare HIV+  
diabetics and non-diabetics
(A) Assess temporal 
changes in HIV+ 
metabolism 
Assays performed at each clinical visit          :
Adipose 
tissue
Extracted T cells :
•
Flow cytometry & FACS sorting
•
CD4+ & CD8+ single T cell RNA expression profiling*   
•
CD4+ digital droplet latent HIV quantification (HIV+ only)
•
CD8+ T cell receptor sequencing*
Tissue : Quantitative mRNA expression (macrophage 
activation and M1 vs. M2 phenotype cytokines, and adipocyte 
regulatory proteins)
•
T cell flow cytometry 
•
CD4+ digital droplet latent HIV quantification (HIV+ only)
Peripheral 
blood
Clinical
•
Glucose tolerance testing 
•
CT fat quantification
Group 2: HIV+ and 
pre-diabetic (n=48)
•
HbA1c 5.7% to 6.4%, or
•
Fasting glucose 100 to 125 mg/dl
Group 4: Uninfected  diabetic 
controls (n=40)
(C) Compare diabetics by 
HIV status
 
 
*Single T cell RNA expression profiling and CD8+ T cell receptor sequencing will only be 
performed at the baseline visit. Cells will be stored from the follow-up visit. 
 

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potential racial, sex, and antiretroviral medication factors in our analysis.  
 
As with the HIV+ subjects, we will aim to recruit roughly equal numbers of white and non-white 
participants, equal men and women, and an equal number of obese and non-obese HIV-
negative subjects. 
.   
The enrollment schedule is shown in Table 4. We have estimated at least 80% of the HIV+ non-
diabetic participants will be retained for the follow-up visit 3 years later (>=40 per group) based 
on loss and refusal rates in VCCC ACTG longitudinal studies. Participants will be actively 
followed by the research nurse and asked to complete the second visit early if they plan to move 
out of the area or start on anti-diabetic medication.  
. 
 
 
4.5 Study Procedures 
 
Blood collection: We will collect 80 ml of fasting peripheral blood by percutaneous venipunture 
on the left or right upper extremity. We will collect an additional 5 ml of blood at -15, 0, 30, 60, 
90, and 120 min after ingestion of the oral glucose tolerance test (the 90 minute collection may 
be omitted if CT scan is performed during this time). 
 
Adipose tissue biopsy: We will collect approximately 10 ml of subcutaneous adipose tissue 
(equivalent to roughly 9.5 g) using a specialized 2.7 mm blunt, side-ported peripheral liposuction 
catheter (Tulip CellFriendly™ GEMS system, Tulip Medical Products) designed for the efficient 
extraction of viable adipocytes and stromal vascular cells for outpatient cosmetic re-injection 
procedures.19 The GEMS system is ideal for our study due to the quantity of adipose tissue 
which can be obtained without injury to the cells. The procedure takes less than 15 minutes and 
blood loss is generally zero. This liposuction procedure is a standard technique for outpatient 
collection of subcutaneous adipose tissue and has been performed over 300 times at 
Vanderbilt. 
 
Oral glucose tolerance test: All subjects will be fasting. We will draw blood at -15, 0, 30, 60, 
90, and 120 min after oral administration of 75 g glucose syrup for measurement of serum 
glucose, insulin and C-peptide (the 90 minute collection may be omitted if CT scan is performed 
during this time). Glucose tolerance will be classified according to current American Diabetes 
Table 4. Enrollment by study group and year 
 
Year 1 
Year 2 
Year 3 
Year 4 
Year 5 
 
Clinical 
visits 
Q
1 
Q
2 
Q
3 
Q
4 
Q
1 
Q
2 
Q
3 
Q
4 
Q
1 
Q
2 
Q
3 
Q
4 
Q
1 
Q
2 
Q
3 
Q
4 
Q
1 
Q
2 
Q
3 
Q4 
Total 
visits 
Baseline 
visit: 
HIV+ non-
diabetics 
 
10 
20 
20 
20 
20 
6 
 
 
 
 
 
 
 
 
 
 
 
 
 
96 
Baseline 
visit: 
HIV+ 
diabetics 
 
 
 
 
 
 
10 
10 
7 
7 
6 
 
 
 
 
 
 
 
 
 
40 
Baseline 
visit: HIV-
negative 
diabetics 
 
 
 
 
 
 
 
 
6 
7 
7 
10 
10 
 
 
 
 
 
 
 
40 
Follow-up 
visit: HIV+ 
non-
diabetics  
 
 
 
 
 
 
 
 
 
 
 
 
 
20 
20 
20 
20 
 
 
 
80 

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Association guidelines.20 Although the primary outcome will be two-hour glucose, we will 
calculate insulin sensitivity as the homeostasis model assessment (HOMA2) of insulin sensitivity 
(www.dru/ox.ac.uk).21-24 We will also calculate the Matsuda Index as 10,000/sqrt(Glucose0 x 
Insulin0 x mean glucose x mean insulin) and the Insulinogenic Index defined as ΔInsulin (0-30, 
pmol/L)/ΔGlucose (0-30, mmol/L).25, 26  
 
CT adipose tissue quantification: A noninvasive CT scanning protocol will be performed using 
established methods previously used in NHLBI/NIA cohort studies to measure adipose tissue 
mass and distribution, including abdominal subcutaneous and visceral fat, liver adiposity, 
pericardial adiposity, and thigh adipose tissue and muscle.27-36 Appendix 1 describes the 
scanning protocol. 
 
Health and behavior assessment: We will assess diet, activity level, alcohol intake, family 
history, and health behaviors using a modified version of the Wellspring Health Risk 
Assessment (see Appendix 2).37 Selected variables will be included in the statistical models if 
associated with the outcomes. 
 
 
5.0 Risks to Study Participants 
 
5.1. Potential Risks: The procedures presenting potential risks of this clinical study include 
phlebotomy, percutaneous adipose tissue biopsy, radiographic imaging, oral glucose tolerance 
testing, pregnancy testing and a breach of confidential information. Common risks of 
phlebotomy include pain, local skin irritation, and formation of a superficial hematoma; more 
severe risks would include local or systemic infection or accidental cannulation of an artery (all 
uncommon).   
 
Risks from the adipose tissue biopsy include pain, local skin irritation, bruising, bleeding, and 
formation of a hematoma in the subcutaneous tissue; more severe risks would include local or 
systemic infection, or difficult to control bleeding (all uncommon). Lidocaine may cause local 
discomfort during injection or a rash, redness or soreness at the injection site, and in rare cases 
could induce a transient alteration in heart rhythm (suction is applied to the syringe prior to 
injection to ensure the lidocaine is not being injected into a vessel).  
 
The risks of the oral glucose tolerance test include nausea or vomiting following ingestion of the 
75 g glucose solution.  
 
The CT scan will include imaging of the abdomen, the thigh, and the chest (pericardial fat). The 
average amount of radiation a person will receive from the CT scan is estimated to be 7 mSv 
(range 3.5 -14 mSv), or 14 mSv for those patients seen at both the baseline and follow-up visits 
(separated by more than 3 years). This can be compared to the radiation people in the U.S. 
receive every year from natural sources (about 3 mSv).  By contrast, people who work with 
radiation have a yearly exposure limit of 50 mSv. Therefore, the estimated total radiation 
exposure at the initial and follow-up visits will be approximately equal to slightly more than four 
years of background radiation from natural sources.  
 
All female patients will receive a pregnancy test, and a negative test result will be a prerequisite 
for any further study procedures. The major risk of the pregnancy test is disclosure of a 
previously unknown pregnancy.  
 
To reduce the risk of potential disclosure of identifying information, study participants will be 

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assigned a study number (not derived from any personal information) to identify all samples and 
study records, and the key linking study numbers to medical record numbers will be maintained 
in a locked file in the locked, private office of the PI. We believe this system will provide a high 
degree of security to maintain the confidentiality of personal health information. 
 
5.2. Biohazard Risks: Participants in this study will not be treated with any biological agents or 
administered any substances that could present a biohazard risk (aside from lidocaine). 
However, the serum samples, adipose tissue biopsies, and mononuclear cells collected from 
participants in this study represent biohazardous specimens and will be handled according to 
biohazard protocols in place at Vanderbilt University. Since each participant will undergo study 
procedures individually, study volunteers are not expected to be at risk of exposure to biological 
samples from other participants at any time. Samples will be collected by trained research staff 
and needles and other equipment will be disposed of in the appropriate containers for 
processing by the Medical Center waste facility. 
 
5.3. Protections against Risk: The planned study procedures are all commonly used in 
immunologic and metabolic clinical research and will be performed by personnel with 
specialized training. The VCCC ACTG research facility has a long history of successful 
participation in complex multi-center clinical studies and a competent, professional research 
staff. To reduce the risk of loss of confidentiality, each study participant will be assigned a 
unique study ID number that is not derived from any personal identifier. All participant computer 
data entry forms, imaging results, and samples will be labeled with this unique study number; no 
specimens or data forms will include any personal identifiers. Only the PI will have access to the 
key linking the study ID to a VUMC medical record number, and this information will be 
maintained in a locked filing cabinet in the locked office of the PI (who will be responsible for 
maintaining the confidentiality of this document). All study data will be collected and stored in 
the REDCap database, a centralized, password protected electronic research database created 
and maintained by the Vanderbilt Institute for Clinical and Translational Research. Data 
collection at the time of the visit will be computer-based to the extent feasible, reducing the need 
for paper data reports or forms. The electronic data will be uploaded to REDCap. The only 
patient identifiers included in the REDCap database (as defined by HIPPA) will be dates 
(month/date/year) related to clinical care (e.g., date of treatment start). Only the PI and the 
project biostatisticians (Bryan Shepherd PhD and Cathy Jenkins MS) will have access to the 
REDCap study database.  
 
5.4. Potential Benefits of the Research: While the proposed research will not have direct 
benefits to the study participants, the risks of the study are reasonable in relation to the benefit 
to HIV-infected adults as a population. The study findings will be directly relevant to the design 
of intervention trials to reduce metabolic disease risk in HIV-infected adults, which could lead to 
changes in clinical practice that benefit study participants in the future. 
 
 
6.0. Data and Safety Monitoring Plan 
 
A data safety monitoring board (DSMB) will be convened prior to the study start, preliminarily 
comprised of clinical researchers and a statistician not affiliated with the study. All adverse 
events will be submitted to the DSMB and IRB in progress reports (at required time intervals) 
and serious adverse events will be reported immediately to the DSMB and IRB.  
 
 
7.0 Reporting of Adverse Events  

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Appropriate medical personnel will be present during study procedures and adverse events will 
be recorded.  Adverse events will be reported according to IRB policy. 
 
An Adverse Event (AE) is any untoward medical occurrence in a patient during the conduct of 
this study, and which does not necessarily have a causal relationship with the study.  An AE can 
therefore be any unfavorable and unintended sign (including an abnormal laboratory finding, for 
example), symptom, or disease temporally associated with participation in the study.  
 
Any AE that results in any of the following outcomes will be considered a Serious Adverse Event 
(SAE).  The following outcomes would represent examples of SAEs. 
 
• 
Death 
• 
Life-threatening situation (subject was at risk of death at the time of the event; this does 
not refer to an event that might have caused death if it was of greater intensity). 
• 
Inpatient hospitalization  
• 
Persistent or significant incapacity or substantial disruption of the ability to conduct 
normal life functions. 
• 
Important medical events that may not result in death, be life-threatening, or require 
hospitalization but may jeopardize the subject and may require medical or surgical 
intervention to prevent one of the above outcomes. 
 
 
8.0 Study Withdrawal/Discontinuation 
 
Study withdrawal will be based on subject decision. All study procedures will cease if the 
subject elects to withdraw at any time during the study visit. There are no indications for PI 
withdrawal. 
 
 
9.0 Privacy/Confidentiality Issues 
 
Each potential study participant will be assigned a unique study ID number not derived from any 
personal identifier. All participant computer data entry forms, imaging results, and samples will 
be labeled with this unique study number; no specimens or data forms will include any personal 
identifiers. Only the PI will have access to the key linking the study ID to a VUMC medical 
record number, and this information will be maintained in a locked filing cabinet in the locked 
office of the PI (who will be responsible for maintaining the confidentiality of this document). All 
study data will be stored in the RedCap database, a centralized, password protected electronic 
research database created and maintained by the Vanderbilt Institute for Clinical and 
Translational Research. All electronic data (e.g., lab results) will be uploaded to RedCap or, if 
necessary, re-entered in RedCap by the PI. The only patient identifiers included in the RedCap 
database (as defined by HIPPA) will be dates (month/date/year) related to clinical care (e.g., 
date of treatment start). Only the PI and the co-investigators will have access to the study 
database. At the conclusion of the study all identifying information will be destroyed. The de-
identified data will be maintained in the RedCap system. 
 
 
10.0 Follow-up and Record Retention 
 

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The study will last approximately 5 years, including recruitment, data collection, and data 
analysis. De-identified research records and/or limited datasets will be maintained by the PI 
indefinitely as outlined in the IRB application and informed consent document.  
 
 
11.0. ClinicalTrials.gov Requirements 
 
This application does not include a clinical trial of a drug, biologic, or device.  
 
 
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