Immune restoration affects 10-year survival in people living with HIV/AIDS.

INTRODUCTION: In recent years, a reduction in the life expectancy gap between people living with HIV (PLWH) and the general population has been observed, irrespective of CD4 lymphocyte count, due to widespread access to antiretroviral treatment. The increase in the life expectancy of PLWH has increased awareness of both the ageing process and gender discrepancies in immune restoration and survival. MATERIALS AND METHODS: Longitudinal data were collected for 2240 patients followed up at the Hospital for Infectious Diseases in Warsaw, Poland (n = 1482), and the Department of Acquired Immunodeficiency, Pomeranian Medical University, Szczecin, Poland (n = 758). Immune restoration was measured from the time of starting combination antiretroviral therapy until achieving 500 CD4 lymphocytes/µL, 800 CD4 lymphocytes/µL, and CD4/CD8 lymphocyte ratios of > 0.8 and > 1.0. Full recovery was achieved when the patient was restored to both 800 CD4 lymphocytes/µL and a CD4/CD8 lymphocyte ratio > 1.0. RESULTS: For all endpoints, immune restoration had a protective effect by reducing mortality. Patients who achieved immune restoration had a greater chance of reduced mortality than those who did not achieve immune restoration: for CD4 count > 500 cells/µL, HR = 5.4 (interquartile range: 3.09-9.41), p < 0.001; for CD4 > 800 cells/µL, HR = 5.37 (2.52-11.43), p < 0.001; for CD4/CD8 ratio > 0.8, HR = 3.16 (1.81-5.51), p < 0.001; for CD4/CD8 ratio > 1.0, HR = 2.67 (1.49-5.24), p = 0.001, and for full immune recovery, HR = 3.62 (1.63-8.04), p = 0.002. CONCLUSIONS: Immune restoration remains a powerful factor in improving the survival of PLWH, regardless of the speed of recovery.

Factors Influencing Immune Restoration in People Living with HIV/AIDS.

Introduction: Immune restoration is a key clinical aspect that is pursued in the care of human immunodeficiency virus (HIV)-infected patients. Despite effective antiretroviral treatment and undetectable viremia, immune recovery is often incomplete. Materials and methods: Data from 311 Caucasian patients were collected. SNP in CCR2(rs1799864), CX3CR1(rs3732378), HLAC-35(rs9264942), and CCR5(promoter, rs1799988); a 32bp deletion(Δ32) in CCR5; and HLA-B*5701 genotypes were correlated with clinical data and selected endpoints. Kaplan−Meier and Cox proportional hazards models were used to analyze the effects of genetic factors over time. Results: For HLA-B*5701, the effect on the CD4+/CD8+ >0.8 cell ratio was lost within 48 months (HR = 2.04, 95% CI: 1.04−4.03), and the effect on the CD4+ cell count >500 cells/µL was lost within 12 months (HR = 2.12, CI: 1.11−4.04). The effect of CCR2 GG on the CD4+/CD8+ >0.8 cell ratio was lost within 36 months (HR = 1.7, CI: 1.05−2.75). For CCR5 wt/Δ32, the effect on the CD4+/CD8+ >1.0 cell ratio was lost within 24 months (HR = 2.0, CI: 1.08−3.69), and the effect on the CD4+ >800 cells/µL cell count was lost within 18 months (HR = 1.98, CI: 1.14−4.73). Conclusions: Selected genetic polymorphisms, namely CCR2 GG and CCR5 Δ32, and the presence of the HLA-B*5701 allele positively influenced immune restoration in cART-treated patients with HIV/AIDS.

Molecular Evolution and Epidemiological Characteristics of SARS COV-2 in (Northwestern) Poland.

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) evolved into a worldwide outbreak, with the first Polish cases in February/March 2020. This study aimed to investigate the molecular epidemiology of the circulating virus lineages between March 2020 and February 2021. We performed variant identification, spike mutation pattern analysis, and phylogenetic and evolutionary analyses for 1106 high-coverage whole-genome sequences, implementing maximum likelihood, multiple continuous-time Markov chain, and Bayesian birth-death skyline models. For time trends, logistic regression was used. In the dataset, virus B.1.221 lineage was predominant (15.37%), followed by B.1.258 (15.01%) and B.1.1.29 (11.48%) strains. Three clades were identified, being responsible for 74.41% of infections over the analyzed period. Expansion in variant diversity was observed since September 2020 with increasing frequency of the number in spike substitutions, mainly H69V70 deletion, P681H, N439K, and S98F. In population dynamics inferences, three periods with exponential increase in infection were observed, beginning in March, July, and September 2020, respectively, and were driven by different virus clades. Additionally, a notable increase in infections caused by the B.1.1.7 lineage since February 2021 was noted. Over time, the virus accumulated mutations related to optimized transmissibility; therefore, faster dissemination is reflected by the second wave of epidemics in Poland.