Transmitted drug-resistance (TDR) remains a critical aspect for the management of HIV-1-infected individuals. Thus, studying the dynamics of TDR is crucial to optimize HIV care. In total, 4323 HIV-1 protease/reverse-transcriptase sequences from drug-naive individuals diagnosed in north and central Italy between 2000 and 2014 were analysed. TDR was evaluated over time. Maximum-likelihood and Bayesian phylogenetic trees with bootstrap and Bayesian-probability supports defined transmission clusters. Most individuals were males (80.2%) and Italian (72.1%), with a median (IQR) age of 37 (30–45) years. MSM accounted for 42.2% of cases, followed by heterosexuals (36.4%). Non-B subtype infections accounted for 30.8% of the overall population and increased over time (<2005–14: 19.5%–38.5%, P < 0.0001), particularly among Italians (<2005–14: 6.5%–28.8%, P < 0.0001). TDR prevalence was 8.8% and increased over time in non-B subtypes (<2005–14: 2%–7.1%, P = 0.018). Overall, 467 transmission clusters (involving 1207 individuals; 27.9%) were identified. The prevalence of individuals grouping in transmission clusters increased over time in both B (<2005–14: 12.9%–33.5%, P = 0.001) and non-B subtypes (<2005–14: 18.4%–41.9%, P = 0.006). TDR transmission clusters were 13.3% within the overall cluster observed and dramatically increased in recent years (<2005–14: 14.3%–35.5%, P = 0.005). This recent increase was mainly due to non-B subtype-infected individuals, who were also more frequently involved in large transmission clusters than those infected with a B subtype [median number of individuals in transmission clusters: 7 (IQR 6–19) versus 4 (3–4), P = 0.047]. The epidemiology of HIV transmission changed greatly over time; the increasing number of transmission clusters (sometimes with drug resistance) shows that detection and proper treatment of the multi-transmitters is a major target for controlling HIV spread.
Next-generation sequencing (NGS) is gradually replacing Sanger sequencing for HIV genotypic drug resistance testing (GRT). This work evaluated the concordance among different NGS-GRT interpretation tools in a real-life setting.
Increasing evidences suggest that HBsAg-production varies across HBV-genotypes. HBsAg C-terminus plays a crucial role for HBsAg-secretion. Here, we evaluate HBsAg-levels in different HBV-genotypes in HBeAg-negative chronic infection, the correlation of specific mutations in HBsAg C-terminus with HBsAg-levels in-vivo, their impact on HBsAg-secretion in-vitro and on structural stability in-silico.HBsAg-levels were investigated in 323 drug-naïve HBeAg-negative patients chronically infected with HBV genotype-D(N = 228), -A(N = 65) and -E(N = 30). Genotype-D was characterized by HBsAg-levels lower than genotype-A and -E (3.3[2.7–3.8]IU/ml; 3.8[3.5–4.2]IU/ml and 3.9[3.7–4.2]IU/ml, P < 0.001). Results confirmed by multivariable analysis correcting for patients'demographics, HBV-DNA, ALT and infection-status.In genotype-D, specific C-terminus mutations (V190A-S204N-Y206C-Y206F-S210N) significantly correlate with HBsAg<1000IU/ml(P-value from <0.001 to 0.04). These mutations lie in divergent pathways involving other HBsAg C-terminus mutations: V190A + F220L (Phi = 0.41, P = 0.003), S204N + L205P (Phi = 0.36, P = 0.005), Y206F + S210R (Phi = 0.47, P < 0.001) and S210N + F220L (Phi = 0.40, P = 0.006). Notably, patients with these mutational pairs present HBsAg-levels 1log lower than patients without them(P-value from 0.003 to 0.02). In-vitro, the above-mentioned mutational pairs determined a significant decrease in HBsAg secretion-efficiency compared to wt(P-value from <0.001 to 0.02). Structurally, these mutational pairs reduced HBsAg C-terminus stability and determined a rearrangement of this domain.In conclusion, HBsAg-levels in genotype-D are significantly lower than in genotype-A and -E in HBeAg-negative patients. In genotype-D, specific mutational clusters in HBsAg C-terminus correlate with lower HBsAg-levels in-vivo, hamper HBsAg-release in-vitro and affect its structural stability, supporting their detrimental role on HBsAg-secretion. In this light, genotypic-testing can be a valuable tool to optimize the clinical interpretation of HBsAg in genotype-D and to provide information on HBV-pathogenicity and disease-progression.
Specific HBsAg mutations are known to hamper HBsAg recognition by neutralizing antibodies thus challenging HBV-vaccination efficacy. Nevertheless, information on their impact and spreading over time is limited. Here, we characterize the circulation of vaccine-escape mutations from 2005 to 2019 and their correlation with virological parameters in a large cohort of patients infected with HBV genotype-D (N = 947), dominant in Europe. Overall, 17.7% of patients harbours ≥1 vaccine-escape mutation with the highest prevalence in subgenotype-D3. Notably, complex profiles (characterized by ≥2 vaccine-escape mutations) are revealed in 3.1% of patients with a prevalence rising from 0.4% in 2005-2009 to 3.0% in 2010-2014 and 5.1% in 2015-2019 (P = 0.007) (OR[95%CI]:11.04[1.42-85.58], P = 0.02, by multivariable-analysis). The presence of complex profiles correlates with lower HBsAg-levels (median[IQR]:40[0-2905]IU/mL for complex profiles vs 2078[115-6037]IU/ml and 1881[410-7622]IU/mL for single or no vaccine-escape mutation [P < 0.02]). Even more, the presence of complex profiles correlates with HBsAg-negativity despite HBV-DNA positivity (HBsAg-negativity in 34.8% with ≥2 vaccine-escape mutations vs 6.7% and 2.3% with a single or no vaccine-escape mutation, P < 0.007). These in-vivo findings are in keeping with our in-vitro results showing the ability of these mutations in hampering HBsAg secretion or HBsAg recognition by diagnostic antibodies. In conclusion, vaccine-escape mutations, single or in complex profiles, circulate in a not negligible fraction of HBV genotype-D infected patients with an increasing temporal trend, suggesting a progressive enrichment in the circulation of variants able to evade humoral responses. This should be considered for a proper clinical interpretation of HBsAg-results and for the development of novel vaccine formulations for prophylactic and therapeutic purposes.
This study aimed at updating previous data on HIV-1 integrase variability, by using effective bioinformatics methods combining different statistical instruments from simple entropy and mutation rate to more specific approaches such as Hellinger distance. A total of 2133 HIV-1 integrase sequences were analyzed in: i) 1460 samples from drug-naïve [DN] individuals; ii) 386 samples from drug-experienced but INI-naïve [IN] individuals; iii) 287 samples from INI-experienced [IE] individuals. Within the three groups, 76 amino acid positions were highly conserved (≤0.2% variation, Hellinger distance: <0.25%), with 35 fully invariant positions; while, 80 positions were conserved (>0.2% to <1% variation, Hellinger distance: <1%). The H12-H16-C40-C43 and D64-D116-E152 motifs were all well conserved. Some residues were affected by dramatic changes in their mutation distributions, especially between DN and IE samples (Hellinger distance ≥1%). In particular, 15 positions (D6, S24, V31, S39, L74, A91, S119, T122, T124, T125, V126, K160, N222, S230, C280) showed a significant decrease of mutation rate in IN and/or IE samples compared to DN samples. Conversely, 8 positions showed significantly higher mutation rate in samples from treated individuals (IN and/or IE) compared to DN. Some of these positions, such as E92, T97, G140, Y143, Q148 and N155, were already known to be associated with resistance to integrase inhibitors; other positions including S24, M154, V165 and D270 are not yet documented to be associated with resistance. Our study confirms the high conservation of HIV-1 integrase and identified highly invariant positions using robust and innovative methods. The role of novel mutations located in the critical region of HIV-1 integrase deserves further investigation.
Abstract Background Post COVID-19 condition (PCC) affects 10–40% of patients and is characterized by persisting symptoms at ≥ 4 weeks after SARS CoV-2 infection. Symptoms can last 7 or even more months. How long PCC persists and any changes in its clinical phenotypes over time require further investigation. We investigated PCC trajectories and factors associated with PCC persistence. Material and methods We included both hospitalized COVID-19 patients and outpatients from February 2020 to June 2023, who underwent at least one follow-up visit after acute infection at San Paolo Hospital, University of Milan. Follow-up visits were conducted at the post COVID-19 clinic or via telemedicine. During each follow-up examination, patients completed a short version of the WHO CRF for ongoing symptoms, the Hospital Anxiety and Depression Scale (HADS), and a screening tool for Post-Traumatic Stress Disorder (PTSD). Statistical analyses involved Chi-square, Mann-Whitney, Kruskal-Wallis tests, and logistic regression analysis. Results We enrolled 853 patients (median age 62, IQR 52–73; 41% females). 551/853 (64.6%), 152/418 (36.4%) and 21/69 (30.4%) presented PCC at median follow up of 3 (IQR 2–3), 7 (IQR 6–10) and 26 (IQR 20–33) months, respectively (p < 0.001). The main clinical phenotypes were fatigue, respiratory sequelae, brain fog and chronic pain; anosmia/dysgeusia was observed mostly in the first post-acute period. Female sex, acute disease in 2020, a longer hospital stay and no COVID-19 vaccination were associated with persistence or resolution of PCC compared to never having had PCC. Anxiety, depression and PTSD were more common in PCC patients. By fitting a logistic regression analysis, acute infection in 2020 remained independently associated with persistent PCC, adjusting for age, sex, preexisting comorbidities and disease severity (AOR 0.479 for 2021 vs 2020, 95%CI 0.253–0.908, p = 0.024; AOR 0.771 for 2022 vs 2020, 95%CI 0.259–2.297, p = 0.641; AOR 0.086 for 2023 vs 2020, 95%CI 0.086–3.830, p = 0.565). Conclusions There was a reduction in the PCC burden 7 months following the acute phase; still, one third of patients experienced long-lasting symptoms. The main clinical presentations of PCC remain fatigue, respiratory symptoms, brain fog, and chronic pain. Having had SARS CoV-2 infection during the first pandemic phases appears to be associated with persistent PCC.
