Association between HIV-1 RNA level and CD4 cell count among untreated HIV-infected individuals

Expression of HSPA14 in patients with acute HIV-1 infection and its effect on HIV-1 replication

Introduction

Heat shock protein (HSPs) are important intracellular factors, which are often involved in the regulation of viral replication including HIV-1 in infected individuals as molecular chaperone proteins. Heat shock proteins 70 (HSP70/HSPA) family play important roles in HIV replication, but this family contain many subtypes, and it is unclear how these subtypes participate in and affect HIV replication.

Methods

To detect the interaction between HSPA14 and HspBP1 by CO-IP. Simulating HIV infection status in vitro to detect the change of intracellular HSPA14 expression after HIV infection in different cells. Constructing HSPA14 overexpression or knockdown cells to detect intracellular HIV replication levels after in vitro infection. Detecting the difference of HSPA expression levels in CD4+ T cells of untreated acute HIV-infected patients with different viral load.

Results

In this study, we found that HIV infection can lead to changes in the transcriptional level of many HSPA subtypes, among which HSPA14 interacts with HIV transcriptional inhibitor HspBP1. The expression of HSPA14 in Jurkat and primary CD4+T cells infected with HIV were inhibited, overexpression of HSPA14 inhibited HIV replication, while knocking down HSPA14 promoted HIV replication. We also found that the expression level of HSPA14 is higher in peripheral blood CD4+T cells of untreated acute HIV infection patients with low viral load.

Conclusion

HSPA14 is a potential HIV replication inhibitor and may restrict HIV replication by regulating the transcriptional inhibitor HspBP1. Further studies are needed to determine the specific mechanism by which HSPA14 regulates viral replication.

Markers of Immune Activation and Inflammation Are Associated with Higher Levels of Genetically-Intact HIV in HIV-HBV Co-Infected Individuals

Co-infection with hepatitis B (HBV) and human immunodeficiency virus (HIV) increases overall and liver-related mortality. In order to identify interactions between these two viruses in vivo, full-length HIV proviruses were sequenced from a cohort of HIV-HBV co-infected participants and from a cohort of HIV mono-infected participants recruited from Bangkok, Thailand, both before the initiation of antiretroviral therapy (ART) and after at least 2 years of ART. The co-infected individuals were found to have higher levels of genetically-intact HIV proviruses than did mono-infected individuals pre-therapy. In these co-infected individuals, higher levels of genetically-intact HIV proviruses or proviral genetic-diversity were also associated with higher levels of sCD14 and CXCL10, suggesting that immune activation is linked to more genetically-intact HIV proviruses. Three years of ART decreased the overall level of HIV proviruses, with fewer genetically-intact proviruses being identified in co-infected versus mono-infected individuals. However, ART increased the frequency of certain genetic defects within proviruses and the expansion of identical HIV sequences. IMPORTANCE With the increased availability and efficacy of ART, co-morbidities are now one of the leading causes of death in HIV-positive individuals. One of these co-morbidities is co-infection with HBV. However, co-infections are still relatively understudied, especially in countries where such co-infections are endemic. Furthermore, these countries have different subtypes of HIV circulating than the commonly studied HIV subtype B. We believe that our study serves this understudied niche and provides a novel approach to investigating the impact of HBV co-infection on HIV infection. We examine co-infection at the molecular level in order to investigate indirect associations between the two viruses through their interactions with the immune system. We demonstrate that increased immune inflammation and activation in HBV co-infected individuals is associated with higher HIV viremia and an increased number of genetically-intact HIV proviruses in peripheral blood cells. This leads us to hypothesize that inflammation could be a driver in the increased mortality rate of HIV-HBV co-infected individuals.

Socio-Demographic, Economic and Clinical Predictors for HAART Adherence Competence in HIV-Positive Adults at Felege Hiwot Teaching and Specialized Hospital, North West Ethiopia

Background

Currently, around 36.7 million people in the world are living with HIV. Among these, 52% are living in sub-Saharan Africa. The main objective of this study was to identify socio-demographic economic and clinical factors associated with HAART adherence competence in successive visits among adult HIV patients after commencement of their treatment.

Methods

A retrospective cohort study design was conducted on a random sample of 792 treatment attendants. The samples were selected using stratified random samples technique considering their residence area as strata. Secondary data were used in this study. Structural equation modeling (SEM) was applied to identify predictors of HAART adherence competence over time.

Results

In this longitudinal study, factors affecting long-term HAART adherence competence in successive visits were identified. Among the predictors, marital status (mean = 3.97, variance = 0.6, p = 0.021), level of disclosure of the disease (mean = 6.24, variance = 0.29, p = 0.012), residence area (mean = 3.97, variance = 0.6, p = 0.021), level of education (mean = 2.04, variance= 0.81, p = 0.012), ownership of cell phone (mean = 2.99, variance = 0.68, p = 0.034), household income (mean = 6.37, variance = 0.53, p = 0.002), age of patients (mean = –2.78, variance = 56.64, p = 0.023), sex of patients (mean = –1.25, variance = 0.88, p = 0.036), weight (mean = –2.89, 42.36, p = 0.001), initial CD4 cell count (mean = 2.57, variance = 158.48, p = 0.015) and WHO stages (mean = 2.37, variance = 0.78, p = 0.026) were directly associated with retention of medication care. On the other hand, medication care was significantly and independently associated with longitudinal adherence competence.

Conclusion

The outcome variable in successive visits increased with the number of follow-up visits, but the rate of increase was different for different groups, such as urban and rural, and for those patients disclosing and not disclosing the disease to family members. An integrated health-related education should be given for non-adherent patients like rural residents, patients living without partners, patients with no cell phone and aged patients.

Modelling of viral load dynamics and CD4 cell count progression in an antiretroviral naive cohort: using a joint linear mixed and multistate Markov model

Background

Patients infected with HIV may experience a succession of clinical stages before the disease diagnosis and their health status may be followed-up by tracking disease biomarkers. In this study, we present a joint multistate model for predicting the clinical progression of HIV infection which takes into account the viral load and CD4 count biomarkers.

Methods

The data is from an ongoing prospective cohort study conducted among antiretroviral treatment (ART) naïve HIV-infected women in the province of KwaZulu-Natal, South Africa. We presented a joint model that consists of two related submodels: a Markov multistate model for CD4 cell count transitions and a linear mixed effect model for longitudinal viral load dynamics.

Results

Viral load dynamics significantly affect the transition intensities of HIV/AIDS disease progression. The analysis also showed that patients with relatively high educational levels (β = − 0.004; 95% confidence interval [CI]:-0.207, − 0.064), high RBC indices scores (β = − 0.01; 95%CI:-0.017, − 0.002) and high physical health scores (β = − 0.001; 95%CI:-0.026, − 0.003) were significantly were associated with a lower rate of viral load increase over time. Patients with TB co-infection (β = 0.002; 95%CI:0.001, 0.004), having many sex partners (β = 0.007; 95%CI:0.003, 0.011), being younger age (β = 0.008; 95%CI:0.003, 0.012) and high liver abnormality scores (β = 0.004; 95%CI:0.001, 0.01) were associated with a higher rate of viral load increase over time. Moreover, patients with many sex partners (β = − 0.61; 95%CI:-0.94, − 0.28) and with a high liver abnormality score (β = − 0.17; 95%CI:-0.30, − 0.05) showed significantly reduced intensities of immunological recovery transitions. Furthermore, a high weight, high education levels, high QoL scores, high RBC parameters and being of middle age significantly increased the intensities of immunological recovery transitions.

Conclusion

Overall, from a clinical perspective, QoL measurement items, being of a younger age, clinical attributes, marital status, and educational status are associated with the current state of the patient, and are an important contributing factor to extend survival of the patients and guide clinical interventions. From a methodological perspective, it can be concluded that a joint multistate model approach provides wide-ranging information about the progression and assists to provide specific dynamic predictions and increasingly precise knowledge of diseases.

Prediction Model of Pre-treatment HIV RNA Levels in Naïve Thai HIV-infected Patients: Application for Resource-limited Settings

A prediction model for pretreatment HIV RNA level ≤100,000 copies/ml would provide a useful tool for selection of abacavir (ABC) or rilpivirine (RPV) in the first-line regimen in a resource-limited setting. Factors associated with pre-treatment HIV RNA ≤100,000 copies/ml were determined from a cohort of 1,223 patients divided into a derivation (n = 873) and the remaining in a validation group. Their median [interquartile range (IQR)] age was 36.3 (30.5-42.9) years, CD4 count 122 (39-216) cells/mm3 and pre-treatment HIV RNA level 100,000 (32,449-229,777) copies/ml. Factors associated with pretreatment HIV RNA ≤100,000 copies/ml were non-anemia [odds ratio (OR)= 2.05; 95% confidence interval (CI): 1.28-3.27, p= 0.003], CD4 count ≥200 cells/mm3 (OR= 3.00; 95% CI: 2.08-4.33, p<0.001) and non-heterosexual HIV exposure (OR= 1.61; 95% CI: 1.07-2.43, p= 0.021). The area under a receiver operating characteristic curve was 0.66 (95% CI: 0.62-0.69), but specificity was 97.3%. The prediction model identified a set of readily available clinical data but lacked the requisite predictive performance to fulfill its purpose.

The Effect of Detectable HIV Viral Load among HIV-Infected Children during Antiretroviral Treatment: A Cross-Sectional Study

The RNA viral load of human immunodeficiency virus (HIV) is initially used to determine the status of the HIV infection. The goal of therapy following treatment failure is to achieve and maintain virologic suppression. A detectable viral load may relate to the progression of HIV infection. A cross-sectional survey was conducted from January 2013 to December 2014 at the Bamrasnaradura Infectious Diseases Institute, Thailand. The aim was to determine the prevalence of detectable HIV viral load (dVL) and analyze the factors associated with post-dVL conditions that occur independently of a switch to a new antiretroviral agent. The prevalence of dVL was 27% (27 of 101). The mean ages of dVL and non-dVL children were 12.0 and 12.3 years, respectively. Age, sex, body mass index for age z-scores, previous tuberculosis disease history and parental tuberculosis history of both groups were not significantly different (p > 0.05). The prevalence of poor adherence (<95%), influenza-like illness (ILI) and opportunistic infections were higher in dVL than non-dVL children (p < 0.05). The mean nadir CD4 cell count during the study was lower in dVL than non-dVL children (646 compared to 867, respectively; p < 0.05). Other factors were not significant (all p > 0.05). In multivariable analysis, dVL was significantly associated with ILI (odds ratio (OR) = 9.6, 95% confidence interval (CI) = 1.3–69.4), adherence (OR = 0.195, 95% CI = 0.047–0.811) and nadir CD4 during the study (OR = 1.102, 95% CI = 1.100–1.305). The prevalence of dVL was 27% with this dVL among HIV-infected children found to be associated with ILI, poor adherence and lower nadir CD4 during the study.

Demographic and clinical correlates of HIV-1 RNA levels in antiretroviral therapy-naive adults attending a tertiary hospital in Jos, Nigeria

BACKGROUND

Plasma HIV-RNA viral load (VL) of HIV-infected persons is an important prognostic factor in HIV management. We determined the VL among antiretroviral therapy (ART)-naive patients to identify the association between patients' demographic, clinical and laboratory characteristics with VL.

METHOD

A cross-sectional study of 224 ART-naive HIV-1-infected patients (≥15 years of age) accessing care at the Jos University Teaching Hospital AIDS Prevention Initiative in Nigeria ART treatment centre, from October 2010 to April 2011. A log-linear model was used to determine if VL was related to demographic and clinical variables.

RESULTS

The patients had a median (interquartile range) age of 34 (28-41) years with females in the majority (59%). Females compared to males and pulmonary tuberculosis (PTB) co-infected compared to not co-infected patients had a significantly higher VL (14.9 log_e versus 11.5 log_e, P=0.003 and 11.31 log_e versus 11.89 log_e, P=0.047, respectively). VL tended to decrease with increasing CD4+ cell count levels in females, but remained relatively unchanged in males across all values of CD4+ cell counts. The difference (β) in the mean change in VL between males and females was log_e 0.64 copies/mL, P=0.005.

CONCLUSION

In ART-naive HIV-1-infected patients in our setting, females had significantly higher VL and lower CD4+ cell count, at the same VL threshold, compared to males, and hence were more likely to be at a higher risk of rapid progression to AIDS. Therefore, gender-based strategies for early identification and engaging females into care are required in this setting to mitigate against rapid progression to AIDS.

The interplay between CD4 cell count, viral load suppression and duration of antiretroviral therapy on mortality in a resource-limited setting

OBJECTIVE

To examine the interaction between CD4 cell count, viral load suppression and duration of antiretroviral therapy (ART) on mortality.

METHODS

Cohort analysis of HIV-infected patients initiating ART between April 2004 and June 2011 at a large public sector clinic in Johannesburg, South Africa. A log-linear model with Poisson distribution was used to estimate risk of death as a function of the interaction between current CD4 count, current viral load suppression and duration on ART in 12-month intervals. We calculated predicted mortality using estimated coefficients within combinations of predictors.

RESULTS

Amongst 14 932 ART patients, 1985 (13.3%) died. Current CD4 was the strongest predictor of death (<50 vs. ≥550 cells/mm(3) - RR: 46.3; 95% CI: 26.8-80), while unsuppressed current viral load vs. suppressed (RR: 1.8; 95% CI: 1.5-2.1) and short duration of ART (0-11.9 vs. 66-71.9 months RR: 1.7; 95% CI: 1.2-2.3) also predicted death. Our interaction model showed that mortality was highest in the first 12 months on treatment across all CD4 and viral load strata. As current CD4 and duration on ART increased and viral load suppression occurred, mortality dropped. CD4 count was the strongest predictor of death. The relative effect of current CD4 count varied strongly by viral load and duration of ART (from 1.3 to 55). Lack of suppression increased the risk of mortality upwards of six-fold depending on time on ART and current CD4.

CONCLUSIONS

Our findings show that while CD4 count is the strongest predictor of death, the effect is modified by viral load and the duration of ART. Assessment of risk should take into account all three factors.

Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification

BACKGROUND

Global programs of anti-HIV treatment depend on sustained laboratory capacity to assess treatment initiation thresholds and treatment response over time. Currently, there is no valid alternative to CD4 count testing for monitoring immunologic responses to treatment, but laboratory cost and capacity limit access to CD4 testing in resource-constrained settings. Thus, methods to prioritize patients for CD4 count testing could improve treatment monitoring by optimizing resource allocation.

METHODS AND FINDINGS

Using a prospective cohort of HIV-infected patients (n=1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4(+) T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4(+) T cell count of 200 or 350 cells/µl). The algorithm correctly classified 90% (cross-validation estimate=91.5%, standard deviation [SD]=4.5%) of CD4 count measurements <200 cells/µl in the first year of follow-up; if laboratory testing is applied only to patients predicted to be below the 200-cells/µl threshold, we estimate a potential savings of 54.3% (SD=4.2%) in CD4 testing capacity. A capacity savings of 34% (SD=3.9%) is predicted using a CD4 threshold of 350 cells/µl. Similar results were obtained over the 3 y of follow-up available (n=619). Limitations include a need for future economic healthcare outcome analysis, a need for assessment of extensibility beyond the 3-y observation time, and the need to assign a false positive threshold.

CONCLUSIONS

Our results support the use of PBC modeling as a triage point at the laboratory, lessening the need for laboratory-based CD4(+) T cell count testing; implementation of this tool could help optimize the use of laboratory resources, directing CD4 testing towards higher-risk patients. However, further prospective studies and economic analyses are needed to demonstrate that the PBC model can be effectively applied in clinical settings. Please see later in the article for the Editors' Summary.

Ongoing changes in HIV RNA levels during untreated HIV infection: implications for CD4 cell count depletion

BACKGROUND

Understanding of the interplay between plasma HIV RNA level and CD4 cell count depletion in untreated infection remains incomplete.

METHODS

We studied 1169 people with HIV seen for care at a major London clinic while naive to antiretroviral therapy. We considered pairs (n = 5940) of consecutive simultaneously measured CD4 cell count and plasma HIV RNA values from patients who had never started therapy. Baseline was the first date when both measures were known.

RESULTS

HIV RNA levels increased variably and often substantially from baseline (60% experience an increase of over 50 000 copies/ml by 5 years of follow-up). The current HIV RNA level (i.e. first value of the pair) was strongly associated with the time-standardized change in CD4 cell count, with a mean 106 cells/microl per year greater rate of CD4 cell count decline per log-copy/ml higher current HIV RNA level (P < 0.0001). After adjustment for the current level, higher baseline HIV RNA was not associated with CD4 cell count decline. There was no average CD4 cell count decline with current HIV RNA level below 3.0 log-copies/ml, compared with a 159 cells/microl per year decline for those with HIV RNA at least 5.5 log-copies/ml (P < 0.0001). Further, the current CD4 cell count predicted subsequent changes in HIV RNA level (0.04 log-copies/year greater increases per 100 cells/microl lower CD4 cell count; P < 0.0001).

CONCLUSION

The often substantial increases in HIV RNA level observed in untreated HIV infection appear fundamentally linked to CD4 cell count depletion. Research into mechanisms by which HIV RNA levels rise over time should yield insights into the causes of CD4 cell count depletion, as the two processes are intimately linked.

Copy-years viremia as a measure of cumulative human immunodeficiency virus viral burden

Plasma human immunodeficiency virus type 1 (HIV-1) viral load is a valuable tool for HIV research and clinical care but is often used in a noncumulative manner. The authors developed copy-years viremia as a measure of cumulative plasma HIV-1 viral load exposure among 297 HIV seroconverters from the Multicenter AIDS Cohort Study (1984-1996). Men were followed from seroconversion to incident acquired immunodeficiency syndrome (AIDS), death, or the beginning of the combination antiretroviral therapy era (January 1, 1996); the median duration of follow-up was 4.6 years (interquartile range (IQR), 2.7-6.5). The median viral load and level of copy-years viremia over 2,281 semiannual follow-up assessments were 29,628 copies/mL (IQR, 8,547-80,210) and 63,659 copies x years/mL (IQR, 15,935-180,341). A total of 127 men developed AIDS or died, and 170 survived AIDS-free and were censored on January 1, 1996, or lost to follow-up. Rank correlations between copy-years viremia and other measures of viral load were 0.56-0.87. Each log(10) increase in copy-years viremia was associated with a 1.70-fold increased hazard (95% confidence interval: 0.94, 3.07) of AIDS or death, independently of infection duration, age, race, CD4 cell count, set-point, peak viral load, or most recent viral load. Copy-years viremia, a novel measure of cumulative viral burden, may provide prognostic information beyond traditional single measures of viremia.