Background: The tropism of HIV-1 is determined by the use of either or both chemokine coreceptors CCR5 (R5) and CXCR4 (X4) for entry into the target cell. The coreceptor usage of HIV-1 is mainly determined by the third variable loop (V3) of the envelope glycoprotein gp120. Materials and Methods: We assembled a training dataset of 3071 V3 sequences with known tropism: 2428 R5-tropic, 358 dual R5X4-tropic, and 285 X4-tropic. We analyzed this dataset by using univariate statistics (t-Student, chi-square contingency table, and Cramer’s V index), bivariate statistics (Pearson’s correlation coefficient), and multivariate statistics (principal component analysis and Fisher’s linear discriminant analysis). Results: One third of the 35 amino acid positions in the V3 loop are key drivers of transition from R5 to R5X4 and X4 tropism. Principal component analysis (PCA) indicates that the switch between the three tropism states is a gradual process involving variation for several biochemical features. Linear discriminant analysis (LDA) is a good predictor of coreceptor usage. When applied to the training dataset, it showed a high sensitivity (92% of X4-tropic sequences predicted correctly) and a high specificity (90% of R5-tropic sequences predicted correctly). Discussion: The finding that the sensitivity and specificity of LDA are similar, or better than that of four widely used prediction methods (Geno2pheno, WebPSSM, 11/24/25 charge rule, and net charge rule) indicates that LDA is a valuable complement to the existing models for prediction of coreceptor usage. Conclusion: Parametric multivariate statistics is a useful tool to investigate the switch of HIV-1 tropism and to predict the CCR5 or CXCR4 coreceptor usage.
Introduction: Understanding the characteristics of undiagnosed HIV is essential for targeted testing and anticipating severe cases. This study quantified the time distribution since infection among individuals with undiagnosed HIV infection in Japan, and clarified how undiagnosed individuals accumulated over time and by chronological age. Methods: We analyzed national surveillance data for HIV/AIDS in Japan from 1985 to 2024. A back-calculation model handled the competing risks between HIV diagnosis and AIDS onset, estimating HIV incidence by calendar time and chronological age and reconstructing the time-since-infection distribution among undiagnosed individuals. CD4 count data at diagnosis (2019–2024) were also used to back-cast time since infection among diagnosed individuals. We projected future HIV incidence using the actual reproduction number as a function of diagnosis rate. Results: Undiagnosed HIV infections peaked at 7,585 persons in 2009; however, long-term undiagnosed infections (≥10 years since infection) persisted at over 300 persons. Long-term undiagnosed infections peaked in 2018, accounting for 12.5% of undiagnosed individuals. The infection-age distribution showed gradual aging over time, and older chronological age was associated with older infection age at diagnosis. Discussion: The visualized infection-age distribution aged over the calendar year. Infected individuals aged ≥40 years accounted for a substantial proportion of undiagnosed individuals over a long period. With the projected plateaued yearly rate of diagnosis, more than 100 HIV notifications may be expected each year up to 2040. Conclusion: Long-term undiagnosed individuals were frequently seen among those aged ≥40 years. Our findings underscore the need for age-tailored testing strategies.
Introduction: Early identification of Primary HIV İnfection (PHI) is essential to reduce onward transmission and enable prompt initiation of Antiretroviral Therapy (ART). Despite increasing HIV diagnoses in Türkiye, data on the prevalence and characteristics of PHI remain limited. This study aimed to determine the proportion of PHI among newly diagnosed individuals and to describe and compare the sociodemographic and laboratory characteristics of individuals with PHI and CHI. Materials and Methods: This retrospective observational study included 225 individuals newly diagnosed with HIV at a tertiary-care center in Istanbul between June 2024 and October 2025. PHI was defined as a documented negative HIV test within the preceding six months together with a history of unprotected high-risk exposure within 2–6 weeks prior to diagnosis. Sociodemographic and laboratory characteristics were compared between PHI and Chronic HIV İnfection (CHI) groups using univariate analyses. Receiver Operating Characteristic (ROC) analysis was performed to evaluate the discriminative ability of HIV RNA levels. A multivariable logistic regression analysis was additionally performed to assess adjusted associations with PHI. Results: Twenty-five individuals (11.1%; 95% CI 7.6–15.9%) met the criteria for PHI. The PHI group tended to be younger and predominantly men who have sex with men. Median HIV RNA levels were significantly higher in PHI than in CHI (693,000 vs. 66,150 copies/mL, p < 0.001), and HIV RNA >1,000,000 copies/mL was more frequent (39.1% vs. 3.0%, p < 0.001). ROC analysis demonstrated moderate discrimination (AUC 0.76; 95% CI 0.62–0.89), with high specificity but limited sensitivity. In multivariable logistic regression adjusted for age, university-level education remained associated with PHI (adjusted OR 5.97, 95% CI 1.28–27.74; p = 0.023). Discussion: PHI constituted a substantial proportion of newly diagnosed cases in this study, within the range reported in comparable settings. The observed differences in age and transmission category (predominantly men who have sex with men) may reflect both transmission dynamics and testing patterns. Elevated HIV RNA levels during PHI support its role in increased transmission risk; however, the moderate discriminative performance and limited sensitivity of viral load indicate that it should not be used as a standalone diagnostic marker. These findings highlight the importance of integrating clinical history and exposure risk with laboratory parameters. Conclusion: PHI represents a clinically significant proportion of newly diagnosed HIV cases. Improving early recognition through targeted testing strategies and combined clinical and laboratory assessment may enhance early diagnosis and reduce onward transmission.
Introduction: This study aimed to determine the prevalence of depression among people living with Human Immunodeficiency Virus (HIV) and to examine the sociodemographic, clinical, and immunologic factors associated with depressive symptoms. Methods: This retrospective cross-sectional study included 258 people living with HIV. Depressive symptoms were assessed using the Beck Depression Inventory-I (BDI). Sociodemographic characteristics, clinical variables, adherence to antiretroviral therapy, immunologic parameters, and level of social support were examined. Appropriate parametric and nonparametric tests, as well as multivariable logistic regression analysis, were used for the statistical analyses. Results: The mean age of the participants was 41.4 ± 11.3 years, and 90.7% were male. The mean BDI score was 9.6 ± 7.7. In the univariable analysis, depressive symptoms were significantly associated with a lower CD4 cell count (p < 0.001), a higher HIV RNA level (p < 0.001), a family history of depression (p = 0.002), and a lower level of social support. In the multivariable analysis, a family history of depression (p = 0.009), a lower CD4 cell count (p = 0.005), and a higher viral load (p < 0.001) were independently associated with depressive symptoms. Discussion: Depressive symptoms are an important comorbidity among people living with HIV and are independently associated with a family history of depression, a low CD4 cell count, and high HIV RNA levels. However, the modest discriminatory ability of these immunologic and virologic parameters indicates that they are insufficient when used alone for depression screening or diagnosis. These findings support the integration of psychological assessment into routine HIV care to facilitate the early recognition of depressive symptoms. Conclusion: Depressive symptoms were independently associated with a lower CD4 cell count, a higher HIV RNA level, and a family history of depression. Therefore, assessing depressive symptoms during the routine follow-up of people living with HIV and integrating appropriate psychosocial support into HIV care are important.
Background: HIV/HCV coinfection accelerates liver fibrosis progression and increases liver-related morbidity and mortality. In Brazil, where chronic liver diseases remain a major public health concern and access to specialized diagnostic methods may be limited, accurate non-invasive biomarkers are essential for assessing liver fibrosis. However, data validating these biomarkers and establishing optimal cut-off values for Brazilian individuals with HIV/HCV coinfection remain scarce. Methods: We retrospectively evaluated 109 HIV/HCV coinfected individuals. APRI, FIB-4, FibroIndex, Forns, GUCI, and Lok index were calculated from patients' electronic medical records. Diagnostic accuracy was assessed using area under the receiver operating characteristic curve (AUROC) analysis, with liver biopsy as the reference standard. Optimal cohort-specific cut-off values were derived for each biomarker. Results: For cirrhosis, the highest diagnostic accuracy was observed for Lok (AUROC=0.893; cut-off >0.4570), FibroIndex (0.869; >1.9092), FIB-4 (0.849; >1.6555), GUCI (0.841; >1.0323), and APRI (0.822; >1.0212). For advanced fibrosis, the highest diagnostic accuracy was observed for FibroIndex (AUROC=0.871; cut-off >1.7183), FIB-4 (0.838; >1.6555), GUCI (0.836; >1.0323), Lok (0.836; >0.3865), and APRI (0.824; >1.0179). For significant fibrosis, the highest diagnostic accuracy was observed for GUCI (AUROC=0.822; cut-off >1.0323), APRI (0.817; >0.9948), and FIB-4 (0.806; >1.5118). Discussion: For the assessment of advanced fibrosis and cirrhosis, most of the evaluated biomarkers achieved AUROC >0.80, indicating very good diagnostic performance. These findings support the use of non-invasive biomarkers as practical tools for screening individuals at increased risk of chronic liver disease, including those with viral hepatitis. Conclusions: Non-invasive fibrosis biomarkers showed robust diagnostic performance for identifying advanced fibrosis and cirrhosis in Brazilian HIV/HCV coinfected individuals.
