Longitudinal Viral Load Research Articles

Distinct virologic trajectories in chronic hepatitis B identify heterogeneity in response to nucleos/tide analogue therapy

Background & AimsThe dynamics of HBV viral load (VL) in patients with chronic hepatitis B (CHB) on nucleos/tide analogue (NA) treatment and its relationship with liver disease are poorly understood. We aimed to study longitudinal VL patterns and their associations with CHB clinical outcomes. MethodsUtilising large scale, routinely collected electronic health records from six centres in England, collated by the National Institute for Health and Care Research Health Informatics Collaborative (NIHR HIC), we applied latent class mixed models to investigate VL trajectory patterns in adults receiving NA treatment. We assessed associations of VL trajectory with alanine transaminase (ALT), and with liver fibrosis/cirrhosis. ResultsWe retrieved data from 1885 adults on NA treatment (median follow-up 6.2 years, interquartile range (IQR) 3.7-9.3 years), with 21,691 VL measurements (median 10 per patient, IQR 5-17). Five VL classes were identified from the derivation cohort (n=1367, discrimination: 0.93, entropy: 0.90): class 1 ‘long term suppression’ (n=827, 60.5%), class 2 ‘timely virological suppression’ (n=254, 18.6%), class 3 ‘persistent moderate viraemia’ (n=140, 10.2%), class 4 ‘persistent high-level viraemia’ (n=44, 3.2%), and class 5 ‘slow virological suppression’ (n=102, 7.5%). The model demonstrated a discrimination of 0.93 and entropy of 0.88 for the validation cohort (n=518). ALT decreased variably over time in VL-suppressed groups (classes 1, 2, 5; all p<0.001), but did not significantly improve in those with persistent viraemia (classes 3, 4). Patients in class 5 had 2-fold increased hazards of fibrosis/cirrhosis compared to class 1 (adjusted hazard ratio, 2.00; 95% CI, 1.33-3.02). ConclusionsHeterogeneity exists in virological response to NA therapy in CHB patients, with over 20% showing potentially suboptimal responses. Slow virological suppression is associated with liver disease progression.

Brief Report: Group-Based Trajectory Modeling to Determine Long-Term HIV Viral Load Trends Among Children With HIV in Kenya.

Identifying determinants of longitudinal HIV viral load (VL) trajectories using group-based trajectory modeling (GBTM) can inform clinical strategies and mechanisms of nonadherence among children. Children under 12 months old who were newly diagnosed with HIV were enrolled in the Optimizing Pediatric HIV therapy cohort (NCT00428116) from 2007 to 2010. Children initiated antiretroviral therapy at enrollment, and VL was assessed every 3 months for 24 months post-antiretroviral therapy and every 6 months thereafter up to 8 years old. VL trajectory groups were defined using GBTM. Fisher's exact and Kruskal-Wallis tests were used to determine the correlates of each trajectory group compared with the sustained-low VL group. Five VL trajectory groups were identified among 89 children with 522 VL visits from 6 to 24 months: sustained-low (63% of children), sustained-very-high (16%), sustained-high (9%), low-to-high (7%), and high-with-periods-of-low (6%). Children in the sustained-high group were more frequently on a first-line protease inhibitor (PI)-based regimen (63% vs 38%; P = 0.03) and had younger caregivers (median: 22 vs 28 years; P = 0.02). Among 54 children with 560 VL visits followed from 48 to 96 months, 5 trajectory groups were identified: sustained-low (74%), mid-range (4%), periods-of-low (7%), high-to-low (7%), and sustained-high (7%). Those in the high-to-low group had younger caregivers (21 vs 29 years; P = 0.01). GBTM identified unique VL patterns among children with unsuppressed VL. Caregiver and regimen-related characteristics were associated with patterns of nonsuppression. Younger caregivers may benefit from tailored counseling to help them support child antiretroviral therapy adherence. Palatable regimens are necessary for viral suppression among children with HIV.

HIV Viral Load Patterns and Risk Factors Among Women in Prevention of Mother-To-Child Transmission Programs to Inform Differentiated Service Delivery.

Differentiated service delivery (DSD) approaches decrease frequency of clinic visits for individuals who are stable on antiretroviral therapy. It is unclear how to optimize DSD models for postpartum women living with HIV (PWLH). We evaluated longitudinal HIV viral load (VL) and cofactors, and modelled DSD eligibility with virologic failure (VF) among PWLH in prevention of mother-to-child transmission programs. This analysis used programmatic data from participants in the Mobile WAChX trial (NCT02400671). Women were assessed for DSD eligibility using the World Health Organization criteria among general people living with HIV (receiving antiretroviral therapy for ≥6 months and having at least 1 suppressed VL [<1000 copies/mL] within the past 6 months). Longitudinal VL patterns were summarized using group-based trajectory modelling. VF was defined as having a subsequent VL ≥1000 copies/mL after being assessed as DSD-eligible. Predictors of VF were determined using log-binomial models among DSD-eligible PWLH. Among 761 women with 3359 VL results (median 5 VL per woman), a 3-trajectory model optimally summarized longitudinal VL, with most (80.8%) women having sustained low probability of unsuppressed VL. Among women who met DSD criteria at 6 months postpartum, most (83.8%) maintained viral suppression until 24 months. Residence in Western Kenya, depression, reported interpersonal abuse, unintended pregnancy, nevirapine-based antiretroviral therapy, low-level viremia (VL 200-1000 copies/mL), and drug resistance were associated with VF among DSD-eligible PWLH. Most postpartum women maintained viral suppression from early postpartum to 24 months and may be suitable for DSD referral. Women with depression, drug resistance, and detectable VL need enhanced services.

Sexual orientation and gender identity measures and viral suppression for people living with HIV: a protocol for a population-based cohort study

IntroductionThe measure of sexual orientation and gender identity (SOGI) data in electronic health records (EHR) has been critical for addressing health disparities and inequalities, especially for HIV care. Given that...

A joint survival model for estimating the association between viral load outcome and survival time to death among HIV/AIDS patients attending health care and treatment centers in Tanzania

BackgroundGlobally, HIV/AIDS is one of the diseases that have a huge burden in terms of cost and health of individuals; and Sub-Sahara Africa is the highly affected region by the pandemic. Tanzania is among the countries that have a higher prevalence of HIV/AIDS-related mortality. This study aimed at using the joint survival model to estimate the association between viral load outcome and survival outcome to death adjusting for age, sex, adherence, and visit date.MethodsSecondary data from a retrospective cohort of HIV patients attending health care and treatment centers were used to analyze the association between the longitudinal viral load and time-to-death outcomes. The three-step analysis was based on the individual mixed effects linear model and the Cox proportional hazards models to estimate the significance of the independent outcomes, and the joint survival model as a final model. The joint model was used to estimate the factors affecting the average change in log viral load over time and the risk factors for the survival time of HIV patients. The exposures for both models were ART adherence status, age, male, and visit date whereas the outcome for the LMM was log viral load and the outcome for the Cox PH model was time-to-death in years.ResultsThe joint survival model results revealed that a 10-year increase in age was associated with a 37% increased risk of death (HR = 1.369, 95% CI: 1.253–1.844), and being male was associated with a 49% higher risk of death (HR = 1.489, 95% CI: 1.202–1.844) compared to females. The results also provided evidence of an association between the longitudinal log viral load and the survival time to death ) whereby a unit increase in the log viral load was associated with a 26% increase in the risk of death (HR = 1.262, 95% CI: 1.226–1.301).ConclusionThe joint survival model analysis provided valuable insights into the associations between time to death and log viral load with adherence to ART, age, visit date, and sex of the patients. This implies that viral load suppression, as well as sex and age-specific interventions, are necessary for reducing HIV/AIDS-related deaths.

Virus kinetics and biochemical derangements among children with Ebolavirus disease.

SummaryBackgroundA paucity of data is available on virologic and biochemical characteristics of paediatric Ebolavirus disease (EVD), compared to adults.MethodsWe conducted a retrospective chart review of children (<16 years old) and a comparator group of young adults (16–44 years) from two treatment centres during the 2018–2020 EVD epidemic in Eastern Democratic Republic of the Congo. Statistical methods included chi-squared and Fisher's exact tests (dichotomous and categorical variables), Mann-Whitney U-test (continuous variables), multivariable linear regression (for determinants of admission viral load), linear mixed-effects models (for analysis of longitudinal viral load), and Cox proportional hazard models (to examine risk factors for mortality).FindingsWe included 73 children and 234 adults admitted from April to October 2019. Paediatric patients commonly had electrolytes imbalances: hypokalaemia in 26/73 (36%), hyperkalaemia in 38/73 (52%), and hyponatraemia in 54/73 (74%). Hypoglycaemia occurred in 20/73 (27%), acute kidney injury in 43/73 (59%), and rhabdomyolysis in 35/73 (48%). Biochemical abnormalities were detected in a similar proportion of children and adults. The viral load (VL, log10 copies/mL) at admission (7.2 versus 6.5, p=0.0001), the peak viral load (7.5 versus 6.7, p=<0.0001), and the time for viraemia clearance (16 days versus 12 days, p=<0.0001) were significantly different in children. The duration of hospital stay was prolonged in children (20 versus 16 days, p=<0.0001). Risk factors for mortality in children were: VL >7.6 log10copies/mL, alanine transaminase >525 U/L, C-reactive protein >100 mg/L, blood urea nitrogen >7.5 mmol/L, rhabdomyolysis, and.acute kidney injury.InterpretationPaediatric EVD patients, like adults, experience multiorgan dysfunction with life-threatening electrolyte imbalances, hypoglycaemia, kidney injury, liver injury, and rhabdomyolysis. Paediatric patients have significantly higher VLs throughout the course of EVD than adults.FundingThis study was not funded.

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms.

SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. Empirical evidence points to the prominent roles of innate immune and CD8 T-cell responses in determining the outcomes. However, how these immune arms act in concert to elicit the outcomes remains unclear. Here, we developed a mathematical model of within-host SARS-CoV-2 infection that incorporates the essential features of the innate immune and CD8 T-cell responses. Remarkably, by varying the strengths and timings of the two immune arms, the model recapitulated the entire spectrum of outcomes realized. Furthermore, model predictions offered plausible explanations of several confounding clinical observations, including the occurrence of multiple peaks in viral load, viral recrudescence after symptom loss, and prolonged viral positivity. We applied the model to analyze published datasets of longitudinal viral load measurements from patients exhibiting diverse outcomes. The model provided excellent fits to the data. The best-fit parameter estimates indicated a nearly 80-fold stronger innate immune response and an over 200-fold more sensitive CD8 T-cell response in patients with mild compared to severe infection. These estimates provide quantitative insights into the likely origins of the dramatic inter-patient variability in the outcomes of SARS-CoV-2 infection. The insights have implications for interventions aimed at preventing severe disease and for understanding the differences between viral variants.

Menopausal status, age and management among women living with HIV in the UK.

There is currently little evidence exploring menopausal status, age at last menstrual period (LMP) and management of menopause among women living with HIV aged 45-60 years in England. Socio-demographic, lifestyle and clinical data were collected through a self-completed cross-sectional survey. Longitudinal CD4 count and viral load data were available from linkage to clinical records, if consent was provided. Women were categorised as pre-, peri- or post-menopausal. Factors associated with menopausal stage were examined using ordinal logistic regression adjusting for age. Age at LMP was estimated using Kaplan-Meier survival analysis. The 847 women had a median age of 49 [interquartile range (IQR): 47-52] years. Most were of black ethnicity (81.3%), were born outside the UK (85.0%) and had completed secondary education (88.7%); 177 (20.4%), 373 (43.0%) and 297 (34.2%) were pre-, peri- or post-menopausal, respectively. After adjusting for age, associations of menopausal status with non-cohabiting relationship [adjusted odds ratio = 0.63 (95% confidence interval: 0.43-0.91)], baseline viral load ≥100000 copies/mL [2.67 (1.20-5.94)] and unemployment [1.34 (0.97-1.84)] remained significant. Median (IQR) age at LMP was 54 (51-55) years in the group. In total, 27.9% (233/836) of women reported severe menopausal symptoms; 45.6% of those with somatic symptoms had heard of hormone replacement therapy and 8.7% had used it. Only 5.6% of women with urogenital symptoms had used topical oestrogen. Our findings highlight the importance of educating both women and their healthcare providers about menopausal symptoms and management options.

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study.

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d-1 (95% CI: 1.06 to 1.27 d-1), 0.777 d-1 (0.716 to 0.838 d-1), and 0.450 d-1 (0.378 to 0.522 d-1) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

Mechanistic basis of post-treatment control of SIV after anti-α4β7 antibody therapy.

Treating macaques with an anti-α4β7 antibody under the umbrella of combination antiretroviral therapy (cART) during early SIV infection can lead to viral remission, with viral loads maintained at < 50 SIV RNA copies/ml after removal of all treatment in a subset of animals. Depletion of CD8+ lymphocytes in controllers resulted in transient recrudescence of viremia, suggesting that the combination of cART and anti-α4β7 antibody treatment led to a state where ongoing immune responses kept the virus undetectable in the absence of treatment. A previous mathematical model of HIV infection and cART incorporates immune effector cell responses and exhibits the property of two different viral load set-points. While the lower set-point could correspond to the attainment of long-term viral remission, attaining the higher set-point may be the result of viral rebound. Here we expand that model to include possible mechanisms of action of an anti-α4β7 antibody operating in these treated animals. We show that the model can fit the longitudinal viral load data from both IgG control and anti-α4β7 antibody treated macaques, suggesting explanations for the viral control associated with cART and an anti-α4β7 antibody treatment. This effective perturbation to the virus-host interaction can also explain observations in other nonhuman primate experiments in which cART and immunotherapy have led to post-treatment control or resetting of the viral load set-point. Interestingly, because the viral kinetics in the various treated animals differed—some animals exhibited large fluctuations in viral load after cART cessation—the model suggests that anti-α4β7 treatment could act by different primary mechanisms in different animals and still lead to post-treatment viral control. This outcome is nonetheless in accordance with a model with two stable viral load set-points, in which therapy can perturb the system from one set-point to a lower one through different biological mechanisms.

The impact of viraemia on inflammatory biomarkers and CD4+ cell subpopulations in HIV-infected children in sub-Saharan Africa.

To determine the impact of virological control on inflammation and cluster of differentiation 4 depletion among HIV-infected children initiating antiretroviral therapy (ART) in sub-Saharan Africa. Longitudinal cohort study. In a sub-study of the ARROW trial (ISRCTN24791884), we measured longitudinal HIV viral loads, inflammatory biomarkers (C-reactive protein, tumour necrosis factor alpha, interleukin 6 (IL-6), soluble CD14) and (Uganda only) whole blood immunophenotype by flow cytometry in 311 Zimbabwean and Ugandan children followed for median 3.5 years on first-line ART. We classified each viral load measurement as consistent suppression, blip/post-blip, persistent low-level viral load or rebound. We used multi-level models to estimate rates of increase or decrease in laboratory markers, and Poisson regression to estimate the incidence of clinical events. Overall, 42% children experienced viral blips, but these had no significant impact on immune reconstitution or inflammation. Persistent detectable viraemia occurred in one-third of children and prevented further immune reconstitution, but had little impact on inflammatory biomarkers. Virological rebound to ≥5000 copies/ml was associated with arrested immune reconstitution, rising IL-6 and increased risk of clinical disease progression. As viral load testing becomes more available in sub-Saharan Africa, repeat testing algorithms will be required to identify those with virological rebound, who need switching to prevent disease progression, whilst preventing unnecessary second-line regimen initiation in the majority of children with detectable viraemia who remain at low risk of disease progression.

Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model.

Viral tests including polymerase chain reaction (PCR) tests are recommended to diagnose COVID-19 infection during the acute phase of infection. A test should have high sensitivity; however, the sensitivity of the PCR test is highly influenced by viral load, which changes over time. Because it is difficult to collect data before the onset of symptoms, the current literature on the sensitivity of the PCR test before symptom onset is limited. In this study, we used a viral dynamics model to track the probability of failing to detect a case of PCR testing over time, including the presymptomatic period. The model was parametrized by using longitudinal viral load data collected from 30 hospitalized patients. The probability of failing to detect a case decreased toward symptom onset, and the lowest probability was observed 2 days after symptom onset and increased afterwards. The probability on the day of symptom onset was 1.0% (95% CI: 0.5 to 1.9) and that 2 days before symptom onset was 60.2% (95% CI: 57.1 to 63.2). Our study suggests that the diagnosis of COVID-19 by PCR testing should be done carefully, especially when the test is performed before or way after symptom onset. Further study is needed of patient groups with potentially different viral dynamics, such as asymptomatic cases.

Estimation of time of HIV seroconversion using a modified CD4 depletion model.

IntroductionSeveral methods have been proposed to estimate the time of HIV seroconversion, including those based on CD4 cell depletion models. However, previous models have failed to consider the heterogeneity that exists in CD4 trajectories among different sub-populations. Our objective was to estimate the time from HIV seroconversion relative to the HIV diagnosis date in a population-based cohort of people living with HIV (PLWH) in the province of British Columbia, Canada.MethodsWe used linked administrative and clinical data from the British Columbia Seek and Treat for Optimal Prevention of HIV/AIDS (STOP HIV/AIDS) cohort, which contains longitudinal individual-level data on all PLWH ever diagnosed in the province. Eligible participants were aged ≥18 years and diagnosed with HIV between 1989 and 2013. The outcome was pre-antiretroviral treatment CD4 cell count measurements assessed every six months. Models were stratified by age and stage of HIV infection at diagnosis. Several explanatory variables were considered including longitudinal viral load measurements. Longitudinal CD4, square root transformed, was modeled via a non-linear mixed effects model; time was modeled using an exponential decay function. We assumed a Gaussian distribution (identity link), an AR(1) correlation structure, and a random intercept and slope for the longitudinal viral load measurements. Due to the population variation in CD4 count among uninfected individuals, we assumed 500 to 1500 cells/mm3 as the normal range when estimating the time of HIV seroconversion.ResultsLongitudinal data on 1,253 individuals were analysed: 80% male, 33% White, and the median age at diagnosis was 38 years (25th-75th percentile [Q1-Q3], 31 to 45). CD4 decay differed by stage of infection at diagnosis and age, with those ≥50 years in Stages 1 and 2 experiencing a faster decline in CD4 over time. The median duration of infection from seroconversion until HIV diagnosis was 6.9 (Q1-Q3, 3.9 to 10.1) years.ConclusionsConsidering the heterogeneity that exists in individual CD4 cell trajectories in a population, we presented a methodology that only relies on routinely collected HIV-related data, which can be further extended to estimate other epidemic measures.

Everything counts - a method to determine viral suppression among people living with HIV using longitudinal data for the HIV care continuum - results of two large, German, multi-center real-life cohort studies over 20\u2009years (1999\u20132018)

BackgroundThe aim of this study was to develop a standardized method to reconstruct persons’ individual viral load (VL) courses to determine viral suppression and duration of viremia for the HIV care continuum in Germany using longitudinal cohort data.MethodsWe analyzed data from two large, multi-center German cohort studies under the direction of the Robert Koch Institute. We included data from 1999 to 2018 of all diagnosed people and of people who initiated antiretroviral treatment (ART). We developed a model generating virtual VL values and an individual VL course corresponding to real VL measurements with a maximum distance of 180 days, considering ART status and VL dynamics. If the distance between VL measurements was > 180 days, the time between was defined as gap time. Additionally, we considered blips, which we defined as a single detectable VL < 1000 copies/ml within 180 days.ResultsA total of 22,120 people (164,691 person-years, PY) after ART initiation were included in the analyses. The proportion of people with viral suppression (VL < 50 copies/ml) increased from 34% in 1999 to 93% in 2018. The proportion of people with VL < 200 copies/ml increased from 47% in 1999 to 96% in 2018. The proportion of people with viremia > 1000 copies/ml decreased from 37% in 1999 to 3% in 2018. The proportion of people with gap time fluctuated and ranged between 18 and 28%. An analysis of the first VL after gap time showed that 90% showed viral suppression, 5% VL between 50- < 1000 copies/ml and 5% VL > 1000 copies/ml.ConclusionWe provide a method for estimating viral suppression and duration of viremia using longitudinal VL data. We observed a continuous and remarkable increase of viral suppression. Furthermore, a notable proportion of those with viremia showed low-level viremia and were therefore unlikely to transmit HIV. Individual health risks and HIV drug resistance among those with low-level viremia are problematic, and viral suppression remains the goal. In 2018, 93 and 96% of people after ART initiation showed VL < 50 copies/ml and VL < 200 copies/ml, respectively. Therefore, using the threshold of VL < 200 copies/ml, Germany reached the UNAIDS 95 target of viral suppression since 2017.

Upper Respiratory Tract Levels of Severe Acute Respiratory Syndrome Coronavirus 2 RNA and Duration of Viral RNA Shedding Do Not Differ Between Patients With Mild and Severe/Critical Coronavirus Disease 2019.

This study reports longitudinal viral RNA loads from the nasopharynx/throat in patients with mild and severe/critical coronavirus disease 2019 (COVID-19). We also investigated whether the duration of symptoms correlated with the duration of viral RNA shedding. A total of 56 patients were included. The highest viral loads occurred early after onset of symptoms. Neither the viral RNA loads in the upper respiratory tract nor the time to viral RNA clearance differed between patients with mild or severe/critical disease. There was a moderate correlation between number of days with symptoms and number of days with viral RNA shedding in patients with mild COVID-19.

Longitudinal Viral Load Monitoring Using Home-Collected Dried Blood Spot Specimens of MSM Living with HIV: Results from a Feasibility Pilot Study.

Novel viral load monitoring strategies are needed to help individuals maintain an undetectable viral load (UVL). In 2018, U.S. MSM living with HIV with a past detectable VL received a dried blood spot (DBS) kit at baseline and 3-month follow-up and returned specimens to a research laboratory. Of 56 consenting participants, 91% returned specimens at baseline and 77% at 3-month follow-up; 74% who returned two specimens had UVL at both time points. At-home DBS collection and longitudinal VL monitoring is feasible among U.S. MSM with fluctuating viral load. This complementary approach to clinical care could improve viral suppression maintenance.

Early exposure to broadly neutralizing antibodies may trigger a dynamical switch from progressive disease to lasting control of SHIV infection.

Antiretroviral therapy (ART) for HIV-1 infection is life-long. Stopping therapy typically leads to the reignition of infection and progressive disease. In a major breakthrough, recent studies have shown that early initiation of ART can lead to sustained post-treatment control of viremia, raising hopes of long-term HIV-1 remission. ART, however, elicits post-treatment control in a small fraction of individuals treated. Strikingly, passive immunization with broadly neutralizing antibodies (bNAbs) of HIV-1 early in infection was found recently to elicit long-term control in a majority of SHIV-infected macaques, suggesting that HIV-1 remission may be more widely achievable. The mechanisms underlying the control elicited by bNAb therapy, however, remain unclear. Untreated infection typically leads to progressive disease. We hypothesized that viremic control represents an alternative but rarely realized outcome of the infection and that early bNAb therapy triggers a dynamical switch to this outcome. To test this hypothesis, we constructed a model of viral dynamics with bNAb therapy and applied it to analyse clinical data. The model fit quantitatively the complex longitudinal viral load data from macaques that achieved lasting control. The model predicted, consistently with our hypothesis, that the underlying system exhibited bistability, indicating two potential outcomes of infection. The first had high viremia, weak cytotoxic effector responses, and high effector exhaustion, marking progressive disease. The second had low viremia, strong effector responses, and low effector exhaustion, indicating lasting viremic control. Further, model predictions suggest that early bNAb therapy elicited lasting control via pleiotropic effects. bNAb therapy lowers viremia, which would also limit immune exhaustion. Simultaneously, it can improve effector stimulation via cross-presentation. Consequently, viremia may resurge post-therapy, but would encounter a primed effector population and eventually get controlled. ART suppresses viremia but does not enhance effector stimulation, explaining its limited ability to elicit post-treatment control relative to bNAb therapy.

A flexible nonlinear mixed effects model for HIV viral load rebound after treatment interruption.

Characterization of HIV viral rebound after the discontinuation of antiretroviral therapy is central to HIV cure research. We propose a parametric nonlinear mixed effects model for the viral rebound trajectory, which often has a rapid rise to a peak value followed by a decrease to a viral load set point. We choose a flexible functional form that captures the shapes of viral rebound trajectories and can also provide biological insights regarding the rebound process. Each parameter can incorporate a random effect to allow for variation in parameters across individuals. Key features of viral rebound trajectories such as viral set points are represented by the parameters in the model, which facilitates assessment of intervention effects and identification of important pretreatment interruption predictors for these features. We employ a stochastic expectation-maximization (StEM) algorithm to incorporate HIV-1 RNA values that are below the lower limit of assay quantification. We evaluate the performance of our model in simulation studies and apply the proposed model to longitudinal HIV-1 viral load data from five AIDS Clinical Trials Group treatment interruption studies.

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

BackgroundPatients 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.MethodsThe 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.ResultsViral 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.ConclusionOverall, 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.

Longitudinal study of BK Polyomavirus outcomes, risk factors, and kinetics in renal transplantation patients

BackgroundIn the immunocompromised conditions following renal transplantation, BK virus can reactivate and cause BK virus associated nephropathy (BKVN). Increased BK viral loads and extended duration of infection have been linked to development of BKVN. The aim of this study was to observe the incidence of BKV infection and BKVN, and kinetics of infection and disease in renal transplantation recipients. MethodsFrom 2014 to 2018, we conducted a longitudinal cohort observational study of 139 renal transplantation patients treated at a single clinic. Quantitative PCR assay was conducted to assess longitudinal BK viral loads. Analysis of patient clinical characteristics was performed to determine risk factors for BKV infection and associated disease. ResultsOf our cohort, 29 (20.9%) patients developed high BK viremia, and 7 (5.0%) developed biopsy-confirmed BKVN. Clinical parameters associated with diabetes (FBS, HbA1c) and hyperlipidemia (TG, TC, LDL-C) were found to be correlated with development of high BK viremia or BKVN. In 3 of 4 patients receiving intravenous immunoglobulin (IVIG) treatment, BK viral loads were reduced by at least 1 log within 2–3 months of administration. Significant differences were measured in BK viral loads and kidney function between BK viremic patients and BKVN patients by 3–9 months post-transplantation. ConclusionsWe identified diabetes and hyperlipidemia as potential risk factors for development of high BK viremia and/or BKVN. IVIG was seen to be effective in reducing viral titers. The period 3–9 months post-transplantation was identified as important for development of BKVN from high BK viremia.