Clinical Manifestations of Kaposi Sarcoma Herpesvirus Lytic Activation: Multicentric Castleman Disease (KSHV–MCD) and the KSHV Inflammatory Cytokine Syndrome

Soon after the discovery of Kaposi sarcoma (KS)-associated herpesvirus (KSHV), it was appreciated that this virus was associated with most cases of multicentric Castleman disease (MCD) arising in patients infected with human immunodeficiency virus. It has subsequently been recognized that KSHV–MCD is a distinct entity from other forms of MCD. Like MCD that is unrelated to KSHV, the clinical presentation of KSHV–MCD is dominated by systemic inflammatory symptoms including fevers, cachexia, and laboratory abnormalities including cytopenias, hypoalbuminemia, hyponatremia, and elevated C-reactive protein. Pathologically KSHV–MCD is characterized by polyclonal, IgM-lambda restricted plasmacytoid cells in the intrafollicular areas of affected lymph nodes. A portion of these cells are infected with KSHV and a sizable subset of these cells express KSHV lytic genes including a viral homolog of interleukin-6 (vIL-6). Patients with KSHV–MCD generally have elevated KSHV viral loads in their peripheral blood. Production of vIL-6 and induction of human (h) IL-6 both contribute to symptoms, perhaps in combination with overproduction of IL-10 and other cytokines. Until recently, the prognosis of patients with KSHV–MCD was poor. Recent therapeutic advances targeting KSHV-infected B cells with the anti-CD20 monoclonal antibody rituximab and utilizing KSHV enzymes to target KSHV-infected cells have substantially improved patient outcomes. Recently another KSHV-associated condition, the KSHV inflammatory cytokine syndrome (KICS) has been described. Its clinical manifestations resemble those of KSHV–MCD but lymphadenopathy is not prominent and the pathologic nodal changes of KSHV–MCD are absent. Patients with KICS exhibit elevated KSHV viral loads and elevation of vIL-6, homolog of human interleukin-6 and IL-10 comparable to those seen in KSHV–MCD; the cellular origin of these is a matter of investigation. KICS may contribute to the inflammatory symptoms seen in some patients with severe KS or primary effusion lymphoma. Additional research is needed to better define the clinical spectrum of KICS and its relationship to KSHV–MCD. In additional, research is needed to better understand the pathogenesis and epidemiology of both KICS and KSHV–MCD, as well as the optimal therapy for both of these disorders

Incidence of hypertension in people with HIV who are treated with integrase inhibitors versus other antiretroviral regimens in the RESPOND cohort consortium

OBJECTIVE To compare the incidence of hypertension in people living with HIV receiving integrase strand transfer inhibitor (INSTI)-based antiretroviral therapy (ART) versus non-nucleoside reverse transcriptase inhibitors (NNRTIs) or boosted protease inhibitors (PIs) in the RESPOND consortium of HIV cohorts. METHODS Eligible people with HIV were aged ≥18 years who initiated a new three-drug ART regimen for the first time (baseline), did not have hypertension, and had at least two follow-up blood pressure (BP) measurements. Hypertension was defined as two consecutive systolic BP measurements ≥140 mmHg and/or diastolic BP ≥90 mmHg or initiation of antihypertensives. Multivariable Poisson regression was used to determine adjusted incidence rate ratios (aIRRs) of hypertension, overall and in those who were ART naïve or experienced at baseline. RESULTS Overall, 4606 people living with HIV were eligible (INSTIs 3164, NNRTIs 807, PIs 635). The median baseline systolic BP, diastolic BP, and age were 120 (interquartile range [IQR] 113-130) mmHg, 78 (70-82) mmHg, and 43 (34-50) years, respectively. Over 8380.4 person-years (median follow-up 1.5 [IQR 1.0-2.7] years), 1058 (23.0%) participants developed hypertension (incidence rate 126.2/1000 person-years, 95% confidence interval [CI] 118.9-134.1). Participants receiving INSTIs had a higher incidence of hypertension than those receiving NNRTIs (aIRR 1.76; 95% CI 1.47-2.11), whereas the incidence was no different in those receiving PIs (aIRR 1.07; 95% CI 0.89-1.29). The results were similar when the analysis was stratified by ART status at baseline. CONCLUSION Although unmeasured confounding and channelling bias cannot be excluded, INSTIs were associated with a higher incidence of hypertension than were NNRTIs, but rates were similar to those of PIs overall, in ART-naïve and ART-experienced participants within RESPOND

Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV

Clinical data usually cannot be freely distributed due to their highly confidential nature and this hampers the development of machine learning in the healthcare domain. One way to mitigate this problem is by generating realistic synthetic datasets using generative adversarial networks (GANs). However, GANs are known to suffer from mode collapse thus creating outputs of low diversity. This lowers the quality of the synthetic healthcare data, and may cause it to omit patients of minority demographics or neglect less common clinical practices. In this paper, we extend the classic GAN setup with an additional variational autoencoder (VAE) and include an external memory to replay latent features observed from the real samples to the GAN generator. Using antiretroviral therapy for human immunodeficiency virus (ART for HIV) as a case study, we show that our extended setup overcomes mode collapse and generates a synthetic dataset that accurately describes severely imbalanced class distributions commonly found in real-world clinical variables. In addition, we demonstrate that our synthetic dataset is associated with a very low patient disclosure risk, and that it retains a high level of utility from the ground truth dataset to support the development of downstream machine learning algorithms.Comment: In the near future, we will make our codes and synthetic datasets publicly available to facilitate future research. Follow us on https://healthgym.ai

Derivation of a Protein Risk Score for Cardiovascular Disease Among a Multiracial and Multiethnic HIV+ Cohort

Background Cardiovascular disease risk prediction models underestimate CVD risk in people living with HIV (PLWH). Our goal is to derive a risk score based on protein biomarkers that could be used to predict CVD in PLWH. Methods and Results In a matched case-control study, we analyzed normalized protein expression data for participants enrolled in 1 of 4 trials conducted by INSIGHT (International Network for Strategic Initiatives in Global HIV Trials). We used dimension reduction, variable selection and resampling methods, and multivariable conditional logistic regression models to determine candidate protein biomarkers and to generate a protein score for predicting CVD in PLWH. We internally validated our findings using bootstrap. A protein score that was derived from 8 proteins (including HGF [hepatocyte growth factor] and interleukin-6) was found to be associated with an increased risk of CVD after adjustment for CVD and HIV factors (odds ratio: 2.17 [95% CI: 1.58-2.99]). The protein score improved CVD prediction when compared with predicting CVD risk using the individual proteins that comprised the protein score. Individuals with a protein score above the median score were 3.10 (95% CI, 1.83-5.41) times more likely to develop CVD than those with a protein score below the median score. Conclusions A panel of blood biomarkers may help identify PLWH at a high risk for developing CVD. If validated, such a score could be used in conjunction with established factors to identify CVD at-risk individuals who might benefit from aggressive risk reduction, ultimately shedding light on CVD pathogenesis in PLWH