Immunological non-response (INR) refers to a condition in which HIV-infected individuals exhibit poor or suboptimal CD4+ T lymphocyte recovery despite achieving viral suppression. Individuals with INR are at increased risk of poor health outcomes or death. To investigate the genetic characteristics and gene expression profiles associated with INR, we compared genomic, transcriptomic, and clinical data between 11 INR individuals and a control group comprising 5 HIV-infected individuals classified as either good responders or poor responders. This study confirmed that INR individuals had the lowest initial CD4 counts upon infection (median CD4 count: 19.5 cells/mm³; range: 1–200 cells/mm³). Interestingly, the HLA-C*12:02 allele—previously associated with protection against CRF01_AE infection in Vietnamese populations—was detected in both the INR and good response groups. Further analyses revealed that ABCA1, ABCC4, ARHGEF1, DNAJB6, ITGA6, SMAD3, and SMARCA4 harbored significant variants in both the genome and transcriptome of the INR group. Additionally, unique variants detected exclusively at the transcriptomic level were identified in ATM, IL4R, SLC11A1, SMARCA4, and STK11—genes involved in T-cell proliferation and differentiation. These findings suggest that the aforementioned genes, affected by variants with varying degrees of pathogenic impact, may contribute to T-cell exhaustion (manifested as persistently low CD4 counts) in certain individuals at the onset of HIV-1 infection, ultimately leading to an immunological non-response status. Moreover, this study developed a tool named HIV-64148, which enables rapid and efficient reporting of HIV-1 subtypes and circulating recombinant forms (CRFs) detected in infected patients, along with a list of identified drug resistance mutations. The HIV-64148 tool holds promise for facilitating the effective surveillance of drug-resistant HIV-1 strains.

Immunological non-response (INR) refers to a condition in which HIV-infected individuals exhibit poor or suboptimal CD4+ T lymphocyte recovery despite achieving viral suppression. Individuals with INR are at increased risk of poor health outcomes or death. To investigate the genetic characteristics and gene expression profiles associated with INR, we compared genomic, transcriptomic, and clinical data between 11 INR individuals and a control group comprising 5 HIV-infected individuals classified as either good responders or poor responders. This study confirmed that INR individuals had the lowest initial CD4 counts upon infection (median CD4 count: 19.5 cells/mm³; range: 1–200 cells/mm³). Interestingly, the HLA-C*12:02 allele—previously associated with protection against CRF01_AE infection in Vietnamese populations—was detected in both the INR and good response groups. Further analyses revealed that ABCA1, ABCC4, ARHGEF1, DNAJB6, ITGA6, SMAD3, and SMARCA4 harbored significant variants in both the genome and transcriptome of the INR group. Additionally, unique variants detected exclusively at the transcriptomic level were identified in ATM, IL4R, SLC11A1, SMARCA4, and STK11—genes involved in T-cell proliferation and differentiation. These findings suggest that the aforementioned genes, affected by variants with varying degrees of pathogenic impact, may contribute to T-cell exhaustion (manifested as persistently low CD4 counts) in certain individuals at the onset of HIV-1 infection, ultimately leading to an immunological non-response status. Moreover, this study developed a tool named HIV-64148, which enables rapid and efficient reporting of HIV-1 subtypes and circulating recombinant forms (CRFs) detected in infected patients, along with a list of identified drug resistance mutations. The HIV-64148 tool holds promise for facilitating the effective surveillance of drug-resistant HIV-1 strains.