Detecting and Characterizing HIV Intraclade Dual Infection

Mary Pacold, University of California San Diego
Advisor: Douglas Richman
Training in Basic Biomedical Sciences
Dissertation Award
2009

Background: HIV dual infection occurs when the same host is infected with two different strains of HIV. It can be subcategorized into either coinfection, in which the two infections occur simultaneously or within a one-month period, or superinfection, in which the second infection occurs at least a month after the first. Intraclade cases (in which the two infecting strains are from the same clade) are difficult to detect because of the genetic similarity of infecting strains. This is particularly pertinent for the HIV epidemic in Callifornia, because >95% of all Californians infected with HIV are infected with clade B virus.

Specific Aims: This study has three specific aims. Aim 1 is to develop 454 ultra-deep sequencing as a screening method for HIV intraclade dual infection. Aim 2 is to determine the incidence and prevalence of intraclade dual infection (coinfection and superinfection). Aim 3 is to determine the clinical consequences of dual infection, as measured by viral load and CD4 progression.

Methods: I propose a retrospective observational cohort study by using a well-characterized primary infection cohort (San Diego and Los Angeles sites of the Acute and Early Infection and Disease Research Program) consisting of 120 participants to determine the prevalence of HIV intraclade dual infection and the incidence of superinfection every year after initial infection. Dual infections will be identified through a two-step screening and confirmation process. I will develop a novel screening method by performing 454 sequencing of three HIV coding regions for two time point samples from each participant. Dual infection will be interpreted when sequences from the same sample are no more closely related to one another than to at least one epidemiologically unlinked sequence. For individuals exhibiting dual infection, additional samples from other time points will be submitted for sequencing to determine the timing of superinfection. I will validate the 454 results with single genome sequencing. The prevalence of dual infection will be calculated as the total number of dual infection cases divided by the cohort size. The incidence of superinfection will be calculated as the number of new cases per year for every year after initial infection.
After establishing the timing of superinfection for all confirmed cases in the cohort, I will perform statistical tests on available viral load and CD4 data to determine retrospectively whether their progressions for dually infected participants differ significantly from those of monoinfected participants.

Expected Impact: The investigations in this proposal will develop sensitive methods to identify HIV intraclade dual infection, which will be used to identify the largest set of intraclade dually infected samples to date. These studies will also determine the incidence of HIV dual infection among newly infected individuals followed longitudinally into chronic infection. This will be clinically important for counseling HIV-infected people about the risks of dual and superinfection. When significant numbers of occurrences of HIV dual infection have been identified, the immunologic and virologic correlates of dual infection can be studied in future work in the ultimate pursuit of a protective vaccine.