Background: Marijuana’s putative anti-inflammatory properties may benefit HIV-associated comorbidities. How recreational marijuana use affects gene expression in peripheral blood cells (PBC) among youth with HIV-1 (YWH) is unknown. Approach: YWH with defined substance use (n = 54) receiving similar antiretroviral therapy (ART) were assigned to one of four analysis groups: YWH with detectable plasma HIV-1 (> 50 RNA copies/ml) who did not use substances (H+V+S−), and YWH with undetectable plasma HIV-1 who did not use substances (H+V−S−), or used marijuana alone (H+V−S+[M]), or marijuana in combination with tobacco (H+V−S+[M/T]). Non-substance using youth without HIV infection (H−S−, n = 25) provided a reference group. PBC mRNA was profiled by Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. Differentially expressed genes (DEG) within outcome groups were identified by Significance Analysis of Microarrays and used for Hierarchical Clustering, Principal Component Analysis, and Ingenuity Pathways Analysis. Results: HIV-1 replication resulted in > 3000 DEG involving 27 perturbed pathways. Viral suppression reduced DEG to 313, normalized all 27 pathways, and down-regulated two additional pathways, while marijuana use among virally suppressed YWH resulted in 434 DEG and no perturbed pathways. Relative to H+V−S−, multiple DEG normalized in H+V−S+[M]. In contrast, H+V−S+[M/T] had 1140 DEG and 10 dysregulated pathways, including multiple proinflammatory genes and six pathways shared by H+V+S−. Conclusions: YWH receiving ART display unique transcriptome bioprofiles based on viral replication and substance use. In the context of HIV suppression, marijuana use, alone or combined with tobacco, has opposing effects on inflammatory gene expression.

Combination antiretroviral therapy (ART) suppresses detectible HIV-1 replication, but latent reservoirs and persistent immune activation contribute to residual viral-associated morbidities and potential viral reactivation. youth with HIV (YWH) virally suppressed on ART early in infection before CD4 T cell decline with fewer comorbidities compared to adults represent a critical population for identifying markers associated with viral control and predictors of viral breakthrough. This study employed a multi-omics approach to evaluate plasma biomarkers and cellular gene expression profiles in 52 participants, including 27 YWH on ART for 144 weeks and 25 youth with no infection (NI) (ages 18–24). Among the 27 YWH, 19 were virally suppressed (VS; 50 RNA copies/mL). VS YWH displayed unique bioprofiles distinct from either VNS or NI. Early viral suppression mitigates inflammatory pathways and normalizes key biomarkers associated with HIV-related comorbidities. Genes upregulated in pathways linked to cellular homeostasis such as DNA repair, RNA processing, and transcription regulation may diminish viral breakthrough and maintain sustained HIV control on ART. Candidate markers and putative molecular mechanisms were identified, offering potential therapeutic targets to limit viral persistence, enhance HIV treatment strategies, and pave the way for improved clinical outcomes.

Gene expression analysis is crucial in understanding cellular processes, development, health, and disease. With RNA-seq outpacing microarray as the chosen platform for gene expression, is there space for array data in future profiling? This study involved 35 participants from the Adolescent Medicine Trials Network for HIV/AIDS Intervention protocol. RNA was isolated from whole blood samples and analyzed using both microarray and RNA-seq technologies. Data processing included quality control, normalization, and statistical analysis using non-parametric Mann–Whitney U tests. Differential expression analysis and pathway analysis were conducted to compare the outputs of the two platforms. The study found a high correlation in gene expression profiles between microarray and RNA-seq, with a median Pearson correlation coefficient of 0.76. RNA-seq identified 2395 differentially expressed genes (DEGs), while microarray identified 427 DEGs, with 223 DEGs shared between the two platforms. Pathway analysis revealed 205 perturbed pathways by RNA-seq and 47 by microarray, with 30 pathways shared. Both microarray and RNA-seq technologies provide highly concordant results when analyzed with consistent non-parametric statistical methods. The findings emphasize that both methods are reliable for gene expression analysis and can be used complementarily to enhance the robustness of biological insights.

Gene expression analysis is crucial in understanding cellular processes, development, health, and disease. With RNA-seq outpacing microarray as the chosen platform for gene expression, is there space for array data in future profiling? The study involved 35 participants from the Adolescent Medicine Trials Network for HIV/AIDS Intervention protocol. RNA was isolated from whole blood samples and analyzed using both microarray and RNA-seq technologies. Data processing included quality control, normalization, and statistical analysis using non-parametric Mann-Whitney U tests. Differential expression analysis and pathway analysis were conducted to compare the outputs of the two platforms. The study found a high correlation in gene expression profiles between microarray and RNA-seq, with a median Pearson correlation coefficient of 0.76. RNA-seq identified 2,395 differentially expressed genes (DEGs), while microarray identified 427 DEGs, with 223 DEGs shared between the two platforms. Pathway analysis revealed 205 perturbed pathways by RNA-seq and 47 by microarray, with 30 pathways shared. Both microarray and RNA-seq technologies provide highly concordant results when analyzed with consistent non-parametric statistical methods. The findings emphasize that both methods are reliable for gene expression analysis and can be used complementarily to enhance the robustness of biological insights.

HIV-1 transmission through breastfeeding accounts for 39% of MTCT and continues as a major route of pediatric infection in developing countries where access to interventions for interrupting transmission is limited. Identifying women who are likely to transmit HIV-1 during breastfeeding would focus therapies, such as broad neutralizing HIV monoclonal antibodies (bn-HIV-Abs), during the breastfeeding period to reduce MTCT. Findings from our pilot study identify novel characteristics of gestational viral MPER quasispecies related to transmission outcomes and raise the possibility for predicting MTCT by breastfeeding based on identifying mothers with high-risk viral populations.