Defining differential genetic signatures in CXCR4- and the CCR5-utilizing HIV-1 co-linear sequences.

The adaptation of human immunodeficiency virus type-1 (HIV-1) to an array of physiologic niches is advantaged by the plasticity of the viral genome, encoded proteins, and promoter. CXCR4-utilizing (X4) viruses preferentially, but not universally, infect CD4+ T cells, generating high levels of virus within activated HIV-1-infected T cells that can be detected in regional lymph nodes and peripheral blood. By comparison, the CCR5-utilizing (R5) viruses have a greater preference for cells of the monocyte-macrophage lineage; however, while R5 viruses also display a propensity to enter and replicate in T cells, they infect a smaller percentage of CD4+ T cells in comparison to X4 viruses. Additionally, R5 viruses have been associated with viral transmission and CNS disease and are also more prevalent during HIV-1 disease. Specific adaptive changes associated with X4 and R5 viruses were identified in co-linear viral sequences beyond the Env-V3. The in silico position-specific scoring matrix (PSSM) algorithm was used to define distinct groups of X4 and R5 sequences based solely on sequences in Env-V3. Bioinformatic tools were used to identify genetic signatures involving specific protein domains or long terminal repeat (LTR) transcription factor sites within co-linear viral protein R (Vpr), trans-activator of transcription (Tat), or LTR sequences that were preferentially associated with X4 or R5 Env-V3 sequences. A number of differential amino acid and nucleotide changes were identified across the co-linear Vpr, Tat, and LTR sequences, suggesting the presence of specific genetic signatures that preferentially associate with X4 or R5 viruses. Investigation of the genetic relatedness between X4 and R5 viruses utilizing phylogenetic analyses of complete sequences could not be used to definitively and uniquely identify groups of R5 or X4 sequences; in contrast, differences in the genetic diversities between X4 and R5 were readily identified within these co-linear sequences in HIV-1-infected patients.

Cocaine alters cytokine profiles in HIV-1-infected African American individuals in the DrexelMed HIV/AIDS genetic analysis cohort.

BACKGROUND: This study evaluated the relationship between illicit drug use and HIV-1 disease severity in HIV-1-infected patients enrolled in the DREXELMED HIV/AIDS Genetic Analysis Cohort. Because cocaine is known to have immunomodulatory effects, the cytokine profiles of preferential nonusers, cocaine users, and multidrug users were analyzed to understand the effects of cocaine on cytokine modulation and HIV-1 disease severity. METHODS: Patients within the cohort were assessed approximately every 6 months for HIV-1 clinical markers and for history of illicit drug, alcohol, and tobacco use. The Luminex human cytokine 30-plex panel was used for cytokine quantitation. Analysis was performed using a newly developed biostatistical model. RESULTS: Substance abuse was common within the cohort. Using the drug screens at the time of each visit, the subjects in the cohort were categorized as preferential nonusers, cocaine users, or multidrug users. The overall health of the nonuser population was better than that of the cocaine users, with peak and current viral loads in nonusers substantially lower than those in cocaine and multidrug users. Among the 30 cytokines investigated, differential levels were established within the 3 populations. The T-helper 2 cytokines, interleukin-4 and -10, known to play a critical role during HIV-1 infection, were positively associated with increasing cocaine use. Clinical parameters such as latest viral load, CD4 T-cell counts, and CD4:CD8 ratio were also significantly associated with cocaine use, depending on the statistical model used. CONCLUSIONS: Based on these assessments, cocaine use seems to be associated with more severe HIV-1 disease.