Current HIV Research (v.14, #2)

Meet Our Editorial Board Member by Paul Spearman (81-81).

Preface by Avi Nath, Charles Wood (82-82).

Background: As persons with HIV are living longer, there is a growing need to investigate factors associated with chronic disease, rate of disease progression and survivorship. Many risk factors for this high-risk population change over time, such as participation in treatment, alcohol consumption and drug abuse. Longitudinal datasets are increasingly available, particularly clinical data that contain multiple observations of health exposures and outcomes over time. Several analytic options are available for assessment of longitudinal data; however, it can be challenging to choose the appropriate analytic method for specific combinations of research questions and types of data. The purpose of this review is to help researchers choose the appropriate methods to analyze longitudinal data, using alcohol consumption as an example of a time-varying exposure variable. When selecting the optimal analytic method, one must consider aspects of exposure (e.g. timing, pattern, and amount) and outcome (fixed or time-varying), while also addressing minimizing bias. In this article, we will describe several analytic approaches for longitudinal data, including developmental trajectory analysis, generalized estimating equations, and mixed effect models. For each analytic strategy, we describe appropriate situations to use the method and provide an example that demonstrates the use of the method. Clinical data related to alcohol consumption and HIV are used to illustrate these methods.

Modeling Drinking Behavior Progression in Youth with Cross-sectional Data: Solving an Under-identified Probabilistic Discrete Event System by Xingdi Hu, Xinguang Chen, Robert L. Cook, Ding-Geng Chen, Chukwuemeka Okafor (93-100).
Background: The probabilistic discrete event systems (PDES) method provides a promising approach to study dynamics of underage drinking using cross-sectional data. However, the utility of this approach is often limited because the constructed PDES model is often non-identifiable. The purpose of the current study is to attempt a new method to solve the model.
Methods: A PDES-based model of alcohol use behavior was developed with four progression stages (never-drinkers [ND], light/moderate-drinker [LMD], heavy-drinker [HD], and ex-drinker [XD]) linked with 13 possible transition paths. We tested the proposed model with data for participants aged 12-21 from the 2012 National Survey on Drug Use and Health (NSDUH). The Moore-Penrose (M-P) generalized inverse matrix method was applied to solve the proposed model.
Results: Annual transitional probabilities by age groups for the 13 drinking progression pathways were successfully estimated with the M-P generalized inverse matrix approach. Result from our analysis indicates an inverse “J” shape curve characterizing pattern of experimental use of alcohol from adolescence to young adulthood. We also observed a dramatic increase for the initiation of LMD and HD after age 18 and a sharp decline in quitting light and heavy drinking.
Conclusion: Our findings are consistent with the developmental perspective regarding the dynamics of underage drinking, demonstrating the utility of the M-P method in obtaining a unique solution for the partially-observed PDES drinking behavior model. The M-P approach we tested in this study will facilitate the use of the PDES approach to examine many health behaviors with the widely available cross-sectional data.

Background: Resistance to antiretroviral drugs is a complex and evolving area with relevant implications in the treatment of human immunodeficiency virus (HIV) infection. Several rules, algorithms and full-fledged computer programs have been developed to assist the HIV specialist in the choice of the best patient-tailored therapy.
Methods: Experts' rules and statistical/machine learning algorithms for interpreting HIV drug resistance, along with their program implementations, were retrieved from PubMed and other on-line resources to be critically reviewed in terms of technical approach, performance, usability, update, and evolution (i.e. inclusion of novel drugs or expansion to other viral agents).
Results: Several drug resistance prediction algorithms for the nucleotide/nucleoside/non-nucleoside reverse transcriptase, protease and integrase inhibitors as well as coreceptor antagonists are currently available, routinely used, and have been validated thoroughly in independent studies. Computer tools that combine single-drug genotypic/phenotypic resistance interpretation and optimize combination antiretroviral therapy have been also developed and implemented as web applications. Most of the systems have been updated timely to incorporate new drugs and few have recently been expanded to meet a similar need in the Hepatitis C area. Prototype systems aiming at predicting virological response from both virus and patient indicators have been recently developed but they are not yet being routinely used.
Conclusion: Computing HIV genotype to predict drug susceptibility in vitro or response to combination antiretroviral therapy in vivo is a continuous and productive research field, translating into successful treatment decision support tools, an essential component of the management of HIV patients.

Background: The ability of the human immunodeficiency virus type 1 (HIV-1) to persist in anatomic compartments and cellular reservoirs is a major obstacle for eradication of replicationcompetent virus in the infected host.
Approach: We extensively review recent advancements in phylogenetic and phylogeographic techniques that provide a unique opportunity for studies of intra-host HIV-1 compartmentalization and the detection of potential reservoirs.
Conclusion: We show that infected macrophages in the central nervous system (CNS) harbor viral subpopulations that play a key role in the emergence of escape variants and viral rebound following discontinuation of antiretroviral therapy. An HIV cure, therefore, cannot be achieved without the effective targeting of the virus in the CNS, for which in depth knowledge of viral population dynamics contributing to the development and maintenance of latent reservoirs is critical.

Applying Triple-Matrix Masking for Privacy Preserving Data Collection and Sharing in HIV Studies by Qinglin Pei, Shigang Chen, Yao Xiao, Samuel S. Wu (121-129).
Background: Many HIV research projects are plagued by the high missing rate of selfreported information during data collection. Also, due to the sensitive nature of the HIV research data, privacy protection is always a concern for data sharing in HIV studies.
Methods: This paper applies a data masking approach, called triple-matrix masking [1], to the context of HIV research for ensuring privacy protection during the process of data collection and data sharing.
Results: Using a set of generated HIV patient data, we show step by step how the data are randomly transformed (masked) before leaving the patients' individual data collection device (which ensures that nobody sees the actual data) and how the masked data are further transformed by a masking service provider and a data collector. We demonstrate that the masked data retain statistical utility of the original data, yielding the exactly same inference results in the planned logistic regression on the effect of age on the adherence to antiretroviral therapy and in the Cox proportional hazard model for the age effect on time to viral load suppression.
Conclusion: Privacy-preserving data collection method may help resolve the privacy protection issue in HIV research. The individual sensitive data can be completely hidden while the same inference results can still be obtained from the masked data, with the use of common statistical analysis methods.

Background: Better decisions for the control of HIV/AIDS and other infectious diseases require better information. The large amount of available public health data makes it possible to extract such information to monitor and predict significant disease events in disease epidemic. The detection of unusual events often involves a combination of a forecasting and a decision mechanism assessing the extent to which an observed event differs significantly from a forecast event. A number of methods and models have been proposed to monitor the trend of infectious disease and to detect unusual events. Although these existing methods and models are useful, many new issues remain to be addressed, including the complicated data structure and the infectious disease dynamics. To overcome these issues, we introduced the statistical tool using statistical process control, and proposed a new method under that framework.
Methods: In this paper, we first reviewed the most commonly used methods and models, including the historical limit method, the time series analysis, the hidden Markov models, and the process control charts. Then, we further discussed issues with the current available methods. We proposed a new method using statistical process control. A major feature of the new method is that it prospectively monitors the disease incidence using sequentially collected data over time. It also takes into account a wide variety of longitudinal patterns and possible autocorrelation in the data.
Results: We test this novel method with the recorded data of the number of AIDS cases in different states of US from 1985 to 2011. The results show that our new method is effective in detecting and predicting the time trends of AIDS epidemic for individual states and for US as a whole. Although AIDS data are used in our demonstration, this method can be used for monitoring other infectious diseases.

Background: In the past decade, HIV/AIDS epidemic in Taiwan experienced an outbreak of HIV-1 CRF07_BC among intravenous drug users (IDU) in 2004-2006 that led to the reported HIV/AIDS case number more than doubled in less than 3 years and subsequent changes in free antiretroviral therapy (ART) treatment program for persons living with HIV/AIDS (PLWHA).
Methods: We investigate HIV underreporting in Taiwan by utilizing a discrete-time compartmental mathematical model for disease transmission and HIV/AIDS surveillance data during 2001-2011. Results: The estimated underreporting ratio in 2011 is 0.45:1, down from 1:1 ratio in 2000. We also provide future projections of the numbers of reported and unreported PLWHA in Taiwan, assuming that model parameters remain unchanged in the near future.
Conclusion: N-step-ahead forecasting comparison with 2012-2014 observed data indicates lower than expected number of known PLWHA and new deaths, perhaps attributable to increased treatment, but higher number of newly reported HIV/AIDS cases, which requires further investigation.

HIV-1 is spreading out of former high-risk population through heterosexual transmission in Hebei, China by Tao Gui, Xinli Lu, Hanping Li, Tianyi Li, Yongjian Liu, Zuoyi Bao, Lin Li, Jingyun Li (148-153).
Introduction: Multiple specific populations, including MSMs, IDUs, and FPDs, are involved in HIV epidemic in China. In the recent years, HIV transmission due to heterosexual transmission also contributed greatly to HIV epidemic in China. Very few studies have been fulfilled to characterize relationships of HIV-1 strains prevalent in different populations. In this study, the phylogenetic relationships of HIV-1 spreading in different populations were investigated.
Materials and Methods: HIV-1 sero-positive patients infected through different routes were enrolled into the study. Nested RT-PCR was used to amplify HIV gag and pol genes followed by sequencing.
Results: Multiple subtypes, including subtype B (52.1%), CRF01_AE (34.4%), CRF07_BC (6.3%), subtype C (4.2%), CRF02_AG (1.0%), CRF08_BC (1.0%) and unique recombination forms (1.0%) were identified. Phylogenetic analysis showed that strains from MSM, IDU, and FPDs grouped into clusters separately. However, strains identified in heterosexual transmitted population intermixed with all of other high risk populations.
Discussion and Conclusion: The genetic data supposed that HIV-1 was spreading out of MSMs, IDUs, and FPDs through heterosexual transmission in Hebei, China. Urgent prevention and behavior intervention in the population will be necessary. Furthermore, the detailed sequence data will help the design of HIV-1 vaccines in China.
Sequence Data: All of sequences have been deposited into the GenBank with the accession number: KJ820007-KJ820144.

The Effects of IGF-1 on Trk Expressing DRG Neurons with HIV-gp120- Induced Neurotoxicity by Hao Li, Zhen Liu, Heng Chi, Yanwen Bi, Lijun Song, Huaxiang Liu (154-164).
Background: HIV envelope glycoprotein gp120 is the main protein that causes HIVassociated sensory neuropathy. However, the underlying mechanisms of gp120-induced neurotoxicity are still unclear. There are lack effective treatments for relieving HIV-related neuropathic symptoms caused by gp120-induced neurotoxicity.
Methods: In the present study, tyrosine kinase receptor (Trk)A, TrkB, and TrkC expression in primary cultured dorsal root ganglion (DRG) neurons with gp120-induced neurotoxicity was investigated. The effects of IGF-1 on distinct Trk-positive DRG neurons with gp120-induced neurotoxicity were also determined.
Results: The results showed that gp120 not only dose-dependently induced DRG neuronal apoptosis and inhibited neuronal survival and neurite outgrowth, but also decreased distinct Trk expression levels. IGF-1 rescued DRG neurons from apoptosis and improved neuronal survival of gp120 neurotoxic DRG neurons in vitro. IGF-1 also improved TrkA and TrkB, but not TrkC, expression in gp120 neurotoxic conditions. The effects of IGF-1 could be blocked by preincubation with the phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002.
Conclusion: These results suggested that gp120 may have a wide range of neurotoxicity on different subpopulations of DRG neurons, while IGF-1 might only relieve some subpopulations of DRG neurons with gp120-induced neurotoxicity. These data provide novel information of mechanisms of gp120 neurotoxicity on primary sensory neurons and the potential therapeutic effects of IGF-1 on gp120-induced neurotoxicity.

High Burden of HBV-Infection and Atypical HBV Strains among HIV-infected Cameroonians by Romina Salpini, Joseph Fokam, Laura Ceccarelli, Maria-Mercedes Santoro, Aubin Nanfack, Samuel Martin Sosso, Mathurin Kowo, Valeria Cento, Judith Torimiro, Loredana Sarmati, Massimo Andreoni, Vittorio Colizzi, Carlo Federico Perno, Oudou Njoya (165-171).
Aim: To investigate the prevalence and genotypic profile of overt and occult hepatitis-B infection (OBI) among HIV-infected individuals in Cameroon.
Methods: 212 HIV-infected Cameroonians, aged 37.6 [IQR: 32.6-46.6] followed-up at the University Health Centre in Yaounde, were tested for HBsAg, anti-HBs, anti-HBc IgG/IgM, HBV-DNA and anti-HCV IgG. HBV positive cases were tested for Hepatitis Delta virus (HDV) using anti-HDV IgG and HDV-RNA. Liver function was assessed by alanine and aspartate aminotransaminases. OBI was defined as negative-HBsAg and detectable HBV-DNA. In occult or overt HBVinfected participants, HBV reverse transcriptase (RT)/surface (S) sequences were analyzed for drug resistance, immuneescape mutants, and phylogeny.
Results: Overall, 78.3% (166/212) participants had past/ongoing HBV-exposure, with 39.1% (83/212) carrying “HBcAbpositive alone”. Prevalence of overt HBV (positive-HBsAg) was 11.8% (25/212), prevalence of HBV and HDV was respectively 6.9% (12/175) and 12% (3/25). Phylogeny of HBV-RT/S revealed the co-circulation of genotypes A and E. All HBV-coinfected participants harbored HBV strains with at least one immune-escape mutation. Of note, one HBV variant carried the vaccine-escape mutation G145R that hinders HBsAg neutralization by antibodies. For the first time, a novel 9 aa-deletion (s115-s123), located in the HBsAg “a” determinant, was found concomitantly with OBI. A stop codon in the S region (associated with increased risk of hepatocellular carcinoma) was found in six cases.
Conclusion: High prevalence of overt/occult HBV-infection and circulating atypical strains highlight the importance of HBV-surveillance among HIV-infected Cameroonians and strategies to detect OBI in highly endemic countries.