Associations of age, immunosuppression, and AIDS among homosexual men in the Tricontinental Seroconverter Study

Inferring HIV incidence from case surveillance with CD4+ cell counts

BACKGROUND

In some countries, HIV surveillance is based on case-reporting of newly diagnosed infections. We present a new back-projection method for estimating HIV-incidence trends using individuals' CD4 cell counts at diagnosis.

METHODS

On the basis of a review of CD4 cell count distributions among HIV-uninfected people, CD4 cell count following primary infection, and rates of CD4 cell count decline over time among people with HIV, we simulate the expected distribution in time between infection and diagnosis. Applying this to all diagnosed individuals provides a distribution of likely infection times and estimates for population incidence, level of undiagnosed HIV, and the average time from infection to diagnosis each year. We applied this method to the national HIV case surveillance data of Australia for 1983-2013.

RESULTS

The estimated number of new HIV infections in Australia in 2013 was 912 (95% uncertainty bound 835-1002). We estimate that 2280 (95% uncertainty bound 1900-2830) people were living with undiagnosed HIV at the end of 2013, corresponding to approximately 9.4% (95% uncertainty bound 7.8-10.1%) of all people living with HIV. With increases in the average CD4 count at diagnosis, the inferred HIV testing rate has been increasing over time and the estimated mean and median times between infection and diagnosis have decreased substantially. However, the estimated mean time between infection and diagnosis is considerably greater than the median, indicating that some people remain undiagnosed for long periods. Differences were found between cases attributable to male homosexual exposure versus other cases.

CONCLUSION

This methodology provides a novel way of estimating population incidence by combining diagnosis dates and CD4 cell counts at diagnosis.

Disease progression by infecting HIV-1 subtype in a seroconverter cohort in sub-Saharan Africa

Objective:

To describe immunologic, virologic, and clinical HIV disease progression by HIV-1 subtype among Africans with well documented estimated dates of HIV infection (EDIs).

Design:

Prospective cohort.

Methods:

Adults and youth with documented HIV-1 infection in the past 12 months were recruited from seroincidence cohorts in East and Southern Africa and followed at 3–6 month intervals. Blood for lymphocyte subset and viral load determination was collected at each visit. Pol was sequenced from the first positive specimen to ascertain subtype. Preantiretroviral therapy disease progression was measured by three time-to-event endpoints: CD4⁺ cell count 350 cells/μl or less, viral load measurement at least 1 × 10⁵ copies/ml, and clinical AIDS.

Results:

From 2006 to 2011, 615 participants were enrolled at nine research centers in Kenya, Rwanda, South Africa, Uganda, and Zambia; 579 (94.1%) had viral subtyping completed. Predominant subtypes were C (256, 44.2%), A (209, 36.1%), and D (84, 14.5%). After adjustment for age, sex, and human leukocyte antigen alleles in Cox regression analyses, subtype C-infected participants progressed faster than subtype A to all three endpoints [CD4⁺ hazard ratio 1.60, 95% (confidence interval) CI 1.16, 2.20; viral load hazard ratio 1.59, 95% CI 1.12, 2.25; and AIDS hazard ratio 1.60, 95% CI 1.11, 2.31). Subtype D-infected participants reached high viral load more rapidly (hazard ratio 1.61, 95% CI 1.01, 2.57) and progressed nearly twice as fast to AIDS compared to subtype A (hazard ratio 1.93, 95% CI 1.21, 3.09).

Conclusion:

Subtype-specific differences in HIV disease progression suggest that the local subtype distribution be considered when planning HIV programs and designing and defining clinical endpoints for HIV prevention trials.

Substance Abuse, Hepatitis C, and Aging in HIV: Common Cofactors that Contribute to Neurobehavioral Disturbances

Although the prevalence of neurocognitive disturbances among individuals with HIV has decreased in recent years, rates of impairment still remain high. This review presents findings from comorbid conditions that may contribute to further neurocognitive impairments in this already vulnerable population. We will focus on three co-factors that have received substantial attention in the neuroAIDS literature: drug use, hepatitis C co-infection (HCV), and aging. All three conditions commonly co-occur with HIV and likely interact with HIV in complex ways. Collectively, the extant literature suggests that drug use, HCV, and aging serve to worsen the neurocognitive profile of HIV through several overlapping mechanisms. A better understanding of how specific comorbidities interact with HIV may reveal specific phenotypes of HIV-associated neurocognitive disorder that may aid in the development of more targeted behavioral and pharmacological treatment efforts.

Co-factors in HIV neurobehavioural disturbances: substance abuse, hepatitis C and aging

Neurocognitive disturbances associated with HIV infection may be modulated or confounded by coexisting and comorbid conditions that reflect the changing populations affected by the disease. HIV infection is often accompanied by substance dependence and/or hepatitis C co-infection. Both of these cofactors that may lead to brain dysfunction on their own, and therefore can affect the nature and course neurocognitive functioning in HIV. Improvements in antiretroviral therapies translate into greater longevity for people infected with HIV, many of whom are now entering their 6th and 7th decade of life and beyond. The increasing proportion of older persons with HIV is also the result of new infections in this age group. As aging confers additional metabolic, neurologic, and neuropsychiatric vulnerability, it is important to understand how this constellation of changes affects neurocognitive functioning in the context of HIV.

Molecular genetics of Kaposi's sarcoma-associated herpesvirus (human herpesvirus-8) epidemiology and pathogenesis

Kaposi's sarcoma had been recognized as unique human cancer for a century before it manifested as an AIDS-defining illness with a suspected infectious etiology. The discovery of Kaposi's sarcoma-associated herpesvirus (KSHV), also known as human herpesvirus-8, in 1994 by using representational difference analysis, a subtractive method previously employed for cloning differences in human genomic DNA, was a fitting harbinger for the powerful bioinformatic approaches since employed to understand its pathogenesis in KS. Indeed, the discovery of KSHV was rapidly followed by publication of its complete sequence, which revealed that the virus had coopted a wide armamentarium of human genes; in the short time since then, the functions of many of these viral gene variants in cell growth control, signaling apoptosis, angiogenesis, and immunomodulation have been characterized. This critical literature review explores the pathogenic potential of these genes within the framework of current knowledge of the basic herpesvirology of KSHV, including the relationships between viral genotypic variation and the four clinicoepidemiologic forms of Kaposi's sarcoma, current viral detection methods and their utility, primary infection by KSHV, tissue culture and animal models of latent- and lytic-cycle gene expression and pathogenesis, and viral reactivation from latency. Recent advances in models of de novo endothelial infection, microarray analyses of the host response to infection, receptor identification, and cloning of full-length, infectious KSHV genomic DNA promise to reveal key molecular mechanisms of the candidate pathogeneic genes when expressed in the context of viral infection.

Update on Kaposi's sarcoma and other HHV8 associated diseases. Part 1: epidemiology, environmental predispositions, clinical manifestations, and therapy

Kaposi's sarcoma (KS) is a mesenchymal tumour involving blood and lymphatic vessels. Only recently has the pathogenesis of this extraordinary neoplasm been elucidated. Viral oncogenesis and cytokine-induced growth together with some state of immunocompromise represent important conditions for this tumour to develop. In 1994, a novel virus was discovered and termed human herpesvirus 8 (HHV8), also known as Kaposi's sarcoma-associated herpes virus, which can be found in all types of KS, whether related to HIV or not. In the era of highly active antiretroviral therapy (HAART), the incidence of AIDS-KS has considerably declined, probably due to enhanced immune reconstitution and anti-HHV8-specific immune responses. If HAART is able to prevent spreading of KS, local therapy of KS may become an essential component of patient management. Part 1 of the review covers the epidemiology, environmental predispositions, clinical manifestations, and therapy of KS. Newer treatments such as pegylated liposomal anthracyclines and experimental strategies are discussed. We also present rationales and graduated treatment algorithms for local and systemic therapy in patients with KS to appropriately meet the challenges of this extraordinary neoplasm. Part 2, to be published next month, will summarise recent insights in the pathogenesis of KS and will discuss other HHV8-related diseases such as Castleman's disease and primary effusion lymphoma.

On the inclusion of prevalent cases in HIV/AIDS natural history studies through a marker-based estimate of time since seroconversion

In most cohort studies of HIV infection and AIDS, seroprevalent cases provide a substantial amount of information. Inclusion of these people in natural history studies requires a fairly unbiased method to estimate their seroconversion distribution. When a cohort-based estimate is not feasible, an alternative is to estimate individual seroconversion distributions, based on marker values at entry. In this paper, a non-parametric marker-based estimation method is developed. The method is applied to data from the Amsterdam cohort study on homosexual men. For seroprevalent cases who entered the study between October 1984 and April 1985, individual seroconversion distributions are estimated based on their first measured CD4 count. In subsequent survival analyses, dates of seroconversion are estimated via conditional mean imputation. Inclusion of these seroprevalent cases greatly improves the quality of the data. Age at seroconversion is a significant cofactor for disease progression, a result not found when analysis is restricted to those who seroconvert. To incorporate the uncertainty in the imputed date of seroconversion, a bootstrap procedure is developed for the computation of p-values and confidence intervals. In our analyses, standard procedures, which ignore the uncertainty in the imputed date of seroconversion, perform almost as well.