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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Antivir Ther. Author manuscript; available in PMC 2010 April 28.
Published in final edited form as:
Antivir Ther. 2009; 14(5): 673–678.
PMCID: PMC2860724

Transmitted Antiretroviral Drug Resistance among Acute and Recent HIV Infections in North Carolina, 1998 to 2007

Christopher B. Hurt, MD,1 Sandra I. McCoy, MPH, PhD,2 JoAnn Kuruc, MSN, RN,1 Julie Nelson, PhD,3,4 Melissa Kerkau, BS,3,4 Susan Fiscus, PhD,3,4 Kara McGee, PA,5 Joseph Sebastian, PhD,6 Peter Leone, MD, MPH,1,7 Christopher Pilcher, MD,8 Charles Hicks, MD,5 and Joseph Eron, Jr., MD1,3



Transmitted drug resistance (TDR) limits antiretroviral options, complicating management of HIV-positive patients. HIV disproportionately affects the Southern United States (US), but available national estimates of TDR prevalence principally reflect large metropolitan centers outside this region.


The Duke/UNC Acute HIV Program has collected data on acute or recent HIV infections (ARHI) in North Carolina (NC) since 1998. Acute infections represent antibody-negative, RNA-positive subjects; recent infection was determined by history of HIV testing, or concordance between detuned ELISA and antibody avidity assays. Genotypic sequence data from the earliest collected pre-treatment plasma sample were analyzed with the Stanford HIV Database and screened for Surveillance Drug Resistance Mutations (SDRMs).


253 individuals with ARHI between 1998 and May 2007 had complete genotypic sequence data for analysis; 39.5% were acute infections, 78.7% were male, 64.8% were non-white, and 53.8% were men who have sex with men. The overall prevalence of TDR was 17.8%, with SDRMs for non-nucleoside reverse transcriptase inhibitors (NNRTIs) in 9.5% of the cohort. Mutations for nucleos(t)ide RT inhibitors (NRTIs) were detected in 7.5%, and for protease inhibitors (PIs) in 3.2%. K103N was the most common mutation (7.5%). Thymidine analogue mutations were found in 4.7% of samples; the most common PI SDRM was L90M (2.4%). Dual-or triple-class antiretroviral resistance was rare, encountered in only six samples (2.4%).


The prevalence of TDR in NC is similar to estimates from US metropolitan areas. These findings have implications for initial regimen selection and secondary prevention efforts outside of large, metropolitan HIV epicenters.

Keywords (MeSH) HIV Infections/epidemiology, HIV Infections/transmission, North Carolina/epidemiology, Drug resistance, viral, Antiretroviral therapy, highly active

Although estimates vary, transmitted drug resistance (TDR) to at least one antiretroviral (ARV) class occurs in approximately 10–15% of all new HIV infections.16 Following the introduction of combination ARV therapy, resistance to the nucleos(t)ide reverse transcriptase inhibitors (NRTIs) has generally declined, while mutations affecting protease (PI) and non-nucleoside reverse transcriptase inhibitors (NNRTIs) have increased.2, 7

These general trends were described using cohorts from urban, metropolitan settings, whose populations may differ substantially from less-dense population centers in terms of demographics, healthcare access8, 9, and HIV risks.1013 This is particularly true for the Southern US: while the national death rate from HIV in 2005 was 4.2 per 100,000 population, more than half of Southern states surpassed that.14 In the first large-scale US study of TDR among persons with acute or recent HIV infection (ARHI), the South was underrepresented, with <15% of subjects recruited from the region (principally Baltimore and Dallas.)3

The purpose of this study was to assess the prevalence of TDR in NC, using data on individuals with known or suspected ARHI. Subjects started contributing to a research database in 1998, and enrollment increased after the November 2002 implementation of a statewide program to identify ARHI using nucleic acid amplification test (NAAT)-based screening (described previously).15, 16 Our primary goal was to compare our prevalence of TDR to reports from more urbanized areas; secondarily, we sought to assess factors associated with acquisition of TDR.


Patient data

Data were drawn from two cohorts: the Duke/UNC/Emory Acute HIV Consortium database17, with contributions from May 1998 to May 2007 (“clinical cohort”); and the Screening and Tracing of Acute Transmission (STAT) Program Evaluation Database16, containing anonymized information on clients presenting to publicly funded HIV testing sites distributed throughout NC from November 2002 to May 2007 (“surveillance cohort”). Our sample is representative of a substantially less metropolitan population than in prior studies of TDR, with only 65% of NC’s population residing in a metropolitan area.18 For this study, eligibility was limited to individuals with serologically-confirmed ARHI. Baseline HIV RNA viral load (VL) measurements were available in both cohorts, but CD4+ T-lymphocyte counts were available only from the clinical cohort.17 From the earliest possible sample for each subject, the HIV genotype was determined for the HIV pol region spanning the protease and reverse transcriptase genes, from codons 1–400 or 38–250 using Genosure primers (CMBP, Labcorp, Research Triangle Park, NC) or the TRUGENE HIV-1 assay (Siemens Healthcare Diagnostics, Tarrytown, NY), respectively.

Definitions of acute and recent HIV infection

For subjects in both cohorts, we defined acute infection as either a combination of non-reactive enzyme-linked immunosorbent assay (ELISA) or an indeterminate Western blot (WB) paired with a positive HIV RNA16, 17 or p24 antigen test17 or a negative ELISA and WB within 45 days preceding a documented positive ELISA or WB.

For the clinical cohort, we defined recent HIV infection as a documented negative ELISA or WB between 45 and 180 days of a documented positive test. For the surveillance cohort, recent infection was defined by: the client’s denial of previous positive HIV testing at the time of the visit, a positive HIV RNA, no detectable evidence of ARVs1921 based on high peformance liquid chromatography with ultraviolet detection (Clinical Pharmacology and Analytical Chemistry Laboratory, Center for AIDS Research (CFAR), University of North Carolina, Chapel Hill, NC; lower limit of detection 10–25 ng/mL), and results consistent with a duration of infection <180 days on both a less-sensitive enzyme immunoassay (LS-EIA; Vironostika, bioMérieux, Marcy-L’Étoile, France; SOD cutoff <1.0) and an avidity-modified third-generation immunoassay (Biorad Laboratories, Hercules, CA; avidity index cutoff <40).

Resistance analysis

Raw sequence data was analyzed using the Stanford University HIV Drug Resistance Database’s genotypic resistance interpretation algorithm (, accessed between January and May, 2007.22 For each subject, amino acid changes were recorded and filtered using the Surveillance Drug Resistance Mutations (SDRMs),23 a set of sentinel mutations more indicative of TDR than those of the International AIDS Society-USA (IAS).24

Statistical methods

Demographic, clinical, and behavioral characteristics of the study population, as well as the frequency and type of TDR, were assessed with descriptive statistics. To determine factors associated with TDR, we performed bivariate analyses describing the presence or absence of any SDRM as the outcome. Unadjusted prevalence ratios (PR) with 95% confidence intervals (95% CI) were then calculated. Comparisons of VL utilized Student’s t test. Temporal trends in the data were assessed using a two-sided Cochran-Armitage test and 95% exact binomial CIs calculated. We considered p<0.05 statistically significant for all analyses. All computations utilized SAS v9.12 (SAS Corporation, Cary, NC).



Complete genotypic sequence data were available for 253 individuals identified with ARHI in NC between May 1998 and May 2007. The majority were detected after November 2002, when statewide NAAT became a routine part of HIV screening (n=225, 88.9%), and 39.5% met the definition of acute infection. The geographic distribution of the subjects included in this analysis is shown in Figure 1. The median age was 29 (range, 16–66); most were male (78.7%) and non-white (64.8%). Approximately half were men who have sex with men (MSM) (53.8%). Among the 224 cases with VL measurements available, the median VL was significantly higher among acute infections (n=97; 5.57 log10 copies per mL [interquartile range, IQR 4.80–6.14]) than recent infections (n=127; 4.44 log10 copies per mL [IQR 3.95–4.92]; p < 0.001).

Figure 1
Acute or recent HIV infections in North Carolina, 1998 to 2007

Detection of drug resistance mutations

The overall prevalence of TDR was 17.8%, with a higher frequency of NNRTI resistance (9.5%) relative to either NRTIs (7.5%) or PIs (3.2%). K103N was detected in 19 subjects (7.5%), making it the most commonly detected mutation. Less frequently seen NNRTI SDRMs included Y181C (n=3), G190A/S (n=2), and Y188L (n=1).

Nineteen subjects had NRTI SDRMs, 12 with thymidine analogue mutations (TAMs), and 10 with T215 “revertants,”25, 26 indicative of previous selection of 215Y or F in an ancestor virus. Seven recently infected subjects harbored T215C or T215D revertant mutations, which represent the first back-mutation away from T215Y. The most common TAM was M41L, occurring in 5 cases; D67N and K219Q were each present in 3 samples. M184V was seen only in samples from two recently infected individuals. K65R was detected only once.

For PIs, L90M appeared most often (n=6), followed by I84V (n=3). M46I, F53L, and G73S were each seen in only two samples each. Dual-class ARV resistance, in which a single individual harbored SDRMs impacting two drug classes, was identified four times (1.6%); three of these involved combined NRTI–NNRTI resistance, and one had NRTI–PI resistance. Two additional subjects – both of whom were identified as recent infections – showed triple-class resistance.

Temporal trends

The study period was divided into four segments to assess changes in TDR over time (Figure 2). While the proportion of subjects with any SDRM seemed to increase slightly, this was not statistically significant. NNRTI SDRMs were not observed until 2001, and their prevalence has since remained near 10%.

Figure 2
Time trends in prevalence of SDRM mutations, 1998 to 2007

Bivariate models

Analyses of the influence of demographic characteristics and risk factors for HIV on acquisition of an SDRM appear in Table 1. None of the factors were significantly associated with the prevalence of SDRMs.

Table 1
Characteristics and Prevelance Ratios of Acutely and Recently HIV-Infected Subjects with and without Surveillance Drug Resistance Mutations (SDRMs)


This study is the first to describe the prevalence of TDR among individuals with ARHI outside of a major metropolitan center in the US, and the first to describe this population in the South. Using data only from rigorously evaluated cohorts of ARHI, we found the overall 17.8% prevalence of TDR in NC comparable to previously published estimates of 10–15% among subjects with varying durations of HIV infection, principally from urban areas.16 We noted a similar increasing prevalence of NNRTI resistance over time, and a trend toward increasing prevalence of TDR.

Given the proven efficacy27, 28, cost savings29, and the availability of fixed-dose, once-daily cART utilizing NNRTIs, the frequency of mutations affecting this class – especially the 8% overall prevalence of K103N – significantly restricts therapeutic options available to the newly infected. In many locations throughout the rural South, public health departments are responsible for providing HIV services. Budget constraints often restrict their use of resistance testing to those felt to be failing a regimen, rather than as recommended for all HIV-positive patients newly entering care.30 Given the high frequency of TDR encountered in this study, approximately 1 out of every 10 new patients empirically initiated on an NNRTI-based first-line regimen is at risk for early virologic failure.

Our cohort had comparatively fewer MSM, more women, and more black subjects than other studies.16 These results suggest that the dynamics of TDR are not necessarily a feature of urban epidemics, and may be consistent across geographic or demographic boundaries. By collecting data through both clinical research and statewide universal surveillance programs conducted in NC’s public HIV testing sites, we obtained a uniquely representative sample of the leading edge of the state’s epidemic. We are confident that our findings are generalizable to the public health system in NC. This effort may represent a model for surveillance of TDR by other states who participate in Centers for Disease Control and Prevention (CDC)-funded surveillance activities that include testing for recent HIV infection.

Our data have several limitations. Assembly of a cohort of ARHI is limited by inherent difficulties in case identification. Although the statewide program for detection of acute infection has improved our ability to find acutely infected individuals, our overall numbers remain relatively small. Sampling during ARHI improves the accuracy of our TDR prevalence estimate, yet it remains possible that some mutations were missed if their frequency fell below the limit of detection of “bulk” sequencing by the time of resistance testing. This would result in an underestimation of TDR prevalence – the same problem faced by TDR studies relying on chronically infected subjects.1, 5, 6 Because we pooled data from multiple sources, differences in data collection methods precluded us from evaluating associations between immunologic markers and TDR. Finally, we chose to use SDRMs as our standard, which may limit direct comparisons of our findings to other studies that utilize the IAS list of drug resistance mutations (IAS-DRMs). A few potentially relevant IAS-DRMs (e.g., the NRTI mutation, E44D) are not included in the more parsimonious SDRM list. However, Green et al recently showed that, when compared to SDRMs as the reference standard, the overall sensitivity of IAS-DRMs was inferior (93.5%) for detecting TDR.31 Further, because they are not specifically selected to measure TDR, IAS-DRMs may overestimate the prevalence of resistance by as much as 7%.31

In conclusion, the frequency of TDR in NC mirrors that seen in major metropolitan areas, with approximately 10% of new infections having baseline NNRTI class resistance. Our data underscore the importance of obtaining ARV resistance testing prior to initiating therapy whenever possible – regardless of the clinical setting.


Presented in part at the XVI International HIV Drug Resistance Workshop, June 2007 (Abstract #48). Portions of this work were supported by the UNC CFAR (AI 50410-04). We appreciate the technical assistance of Angela D.M. Kashuba, PharmD, for ARV drug-level testing in clinical samples; and Ann Dennis, MD for the map of the case distribution statewide. We thank John Barnhart, Delbert Williams, Rhonda Ashby, and the Disease Intervention Specialists of the NC Department of Health and Human Services.


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