Similar but different: Integrated phylogenetic analysis of Austrian and Swiss HIV-1 sequences reveal differences in transmission patterns of the local HIV-1 epidemics.

OBJECTIVES Phylogenetic analyses of two or more countries allow to detect differences in transmission dynamics of local HIV-1 epidemics beyond differences in demographic characteristics. METHODS A maximum-likelihood phylogenetic tree was built using pol-sequences of the Swiss HIV Cohort Study (SHCS) and the Austrian HIV Cohort Study (AHIVCOS), with international background sequences. Three types of phylogenetic cherries (clusters of size 2) were analyzed further: 1) Domestic cherries, 2) International cherries and 3) SHCS/AHIVCOS-cherries. Transmission group and ethnicities observed within the cherries were compared to the respective distribution expected from a random distribution of patients on the phylogeny. RESULTS The demographic characteristics of the AHIVCOS (included patients: 3'141) and the SHCS (included patients: 12'902) are very similar. In the AHIVCOS, 36.5% of the patients were in domestic cherries, 8.3% in international cherries, and 7.0% in SHCS/AHIVCOS cherries. Similarly, in the SHCS, 43.0% of the patients were in domestic cherries, 8.2% in international cherries, and 1.7% in SHCS/AHIVCOS cherries. While international cherries in the SHCS were dominated by heterosexuals (HET) with MSM being underrepresented, the opposite was the case for the AHIVCOS. In both cohorts, cherries with one patient belonging to the transmission group intravenous drug user (IDU) and the other one non-IDU were underrepresented. CONCLUSION In both cohorts, international HIV transmission plays a major role in the local epidemics, mostly driven by MSM in the AHIVOS, and by HET in the SHCS, highlighting the importance of international collaborations to understand global HIV transmission links on the way to eliminate HIV

Integrase Strand Transfer Inhibitor Use and Cancer Incidence in a Large Cohort Setting

Background: Limited data exist examining the association between incident cancer and cumulative integrase inhibitor (INSTI) exposure. Methods: Participants were followed from baseline (latest of local cohort enrollment or January 1, 2012) until the earliest of first cancer, final follow-up, or December 31, 2019. Negative binomial regression was used to assess associations between cancer incidence and time-updated cumulative INSTI exposure, lagged by 6 months. Results: Of 29 340 individuals, 74% were male, 24% were antiretroviral treatment (ART)-naive, and median baseline age was 44 years (interquartile range [IQR], 36-51). Overall, 13 950 (48%) individuals started an INSTI during follow-up. During 160 657 person-years of follow-up ([PYFU] median 6.2; IQR, 3.9-7.5), there were 1078 cancers (incidence rate [IR] 6.7/1000 PYFU; 95% confidence interval [CI], 6.3-7.1). The commonest cancers were non-Hodgkin lymphoma (n=113), lung cancer (112), Kaposi's sarcoma (106), and anal cancer (103). After adjusting for potential confounders, there was no association between cancer risk and INSTI exposure (≤6 months vs no exposure IR ratio: 1.15 [95% CI, 0.89-1.49], >6-12 months; 0.97 [95% CI, 0.71-1.32], >12-24 months; 0.84 [95% CI, 0.64-1.11], >24-36 months; 1.10 [95% CI, 0.82-1.47], >36 months; 0.90 [95% CI, 0.65-1.26] [P=.60]). In ART-naive participants, cancer incidence decreased with increasing INSTI exposure, mainly driven by a decreasing incidence of acquired immune deficiency syndrome cancers; however, there was no association between INSTI exposure and cancer for those ART-experienced (interaction P<.0001). Conclusions: Cancer incidence in each INSTI exposure group was similar, despite relatively wide CIs, providing reassuring early findings that increasing INSTI exposure is unlikely to be associated with an increased cancer risk, although longer follow-up is needed to confirm this finding

Contemporary antiretrovirals and body-mass index: a prospective study of the RESPOND cohort consortium

BACKGROUND: Weight gain effects of individual antiretroviral drugs are not fully understood. We investigated associations between a prespecified clinically significant increase (>7%) in body-mass index (BMI) and contemporary antiretroviral use. METHODS: The International Cohort Consortium of Infectious Diseases (RESPOND) is a prospective, multicohort collaboration, including data from 17 well established cohorts and over 29 000 people living with HIV. People with HIV under prospective follow-up from Jan 1, 2012, and older than 18 years were eligible for inclusion. Each cohort contributed a predefined minimum number of participants related to the size of the specific cohort (with a minimum of 1000 participants). Participants were required to have CD4 cell counts and HIV viral load measurement in the 12 months before or within 3 months after baseline. For all antiretroviral drugs received at or after RESPOND entry, changes from pre-antiretroviral BMI levels (baseline) were considered at each BMI measurement during antiretroviral treatment. We used logistic regression to identify individual antiretrovirals that were associated with first occurrence of a more than 7% increase in BMI from pre-antiretroviral BMI. We adjusted analyses for time on antiretrovirals, pre-antiretroviral BMI, demographics, geographical region, CD4 cell count, viral load, smoking status, and AIDS at baseline. RESULTS: 14 703 people were included in this study, of whom 7863 (53·5%) had a more than 7% increase in BMI. Compared with lamivudine, use of dolutegravir (odds ratio [OR] 1·27, 95% CI 1·17-1·38), raltegravir (1·37, 1·20-1·56), and tenofovir alafenamide (1·38, 1·22-1·35) was significantly associated with a more than 7% BMI increase, as was low pre-antiretroviral BMI (2·10, 1·91-2·31 for underweight vs healthy weight) and Black ethnicity (1·61, 1·47-1·76 vs White ethnicity). Higher CD4 count was associated with a reduced risk of BMI increase (0·97, 0·96-0·98 per 100 cells per μL increase). Relative to lamivudine, dolutegravir without tenofovir alafenamide (OR 1·21, 95% CI 1·19-1·32) and tenofovir alafenamide without dolutegravir (1·33, 1·15-1·53) remained independently associated with a more than 7% increase in BMI; the associations were higher when dolutegravir and tenofovir alafenamide were used concomitantly (1·79, 1·52-2·11, and 1·70, 1·44-2·01, respectively). INTERPRETATION: Clinicians and people with HIV should be aware of associations between weight gain and use of dolutegravir, tenofovir alafenamide, and raltegravir, particularly given the potential consequences of weight gain, such as insulin resistance, dyslipidaemia, and hypertension. FUNDING: The CHU St Pierre Brussels HIV Cohort, The Austrian HIV Cohort Study, The Australian HIV Observational Database, The AIDS Therapy Evaluation in the Netherlands national observational HIV cohort, The EuroSIDA cohort, The Frankfurt HIV Cohort Study, The Georgian National AIDS Health Information System, The Nice HIV Cohort, The ICONA Foundation, The Modena HIV Cohort, The PISCIS Cohort Study, The Swiss HIV Cohort Study, The Swedish InfCare HIV Cohort, The Royal Free HIV Cohort Study, The San Raffaele Scientific Institute, The University Hospital Bonn HIV Cohort and The University of Cologne HIV Cohorts, ViiV Healthcare, and Gilead Sciences

Single-cell analysis identifies cellular markers of the HIV permissive cell.

Cellular permissiveness to HIV infection is highly heterogeneous across individuals. Heterogeneity is also found across CD4+ T cells from the same individual, where only a fraction of cells gets infected. To explore the basis of permissiveness, we performed single-cell RNA-seq analysis of non-infected CD4+ T cells from high and low permissive individuals. Transcriptional heterogeneity translated in a continuum of cell states, driven by T-cell receptor-mediated cell activation and was strongly linked to permissiveness. Proteins expressed at the cell surface and displaying the highest correlation with T cell activation were tested as biomarkers of cellular permissiveness to HIV. FACS sorting using antibodies against several biomarkers of permissiveness led to an increase of HIV cellular infection rates. Top candidate biomarkers included CD25, a canonical activation marker. The combination of CD25 high expression with other candidate biomarkers led to the identification of CD298, CD63 and CD317 as the best biomarkers for permissiveness. CD25highCD298highCD63highCD317high cell population showed an enrichment of HIV-infection of up to 28 fold as compared to the unsorted cell population. The purified hyper-permissive cell subpopulation was characterized by a downregulation of interferon-induced genes and several known restriction factors. Single-cell RNA-seq analysis coupled with functional characterization of cell biomarkers provides signatures of the "HIV-permissive cell"

New cellular tools reveal complex epithelial–mesenchymal interactions in hepatocarcinogenesis

To enable detailed analyses of cell interactions in tumour development, new epithelial and mesenchymal cell lines were established from human hepatocellular carcinoma by spontaneous outgrowth in culture. We obtained several hepatocarcinoma (HCC)-, B-lymphoblastoid (BLC)-, and myofibroblastoid (MF)-lines from seven cases. In-depth characterisation included cell kinetics, genotype, tumourigenicity, expression of cell-type specific markers, and proteome patterns. Many functions of the cells of origin were found to be preserved. We studied the impact of the mesenchymal lines on hepatocarcinogenesis by in vitro assays. BLC- and MF-supernatants strongly increased the DNA replication of premalignant hepatocytes. The stimulation by MF-lines was mainly attributed to HGF secretion. In HCC-cells, MF-supernatant had only minor effects on cell growth but enhanced migration. MF-lines also stimulated neoangiogenesis through vEGF release. BLC-supernatant dramatically induced death of HCC-cells, which could be largely abrogated by preincubating the supernatant with TNFβ-antiserum. Thus, the new cell lines reveal stage-specific stimulatory and inhibitory interactions between mesenchymal and epithelial tumour cells. In conclusion, the new cell lines provide unique tools to analyse essential components of the complex interplay between the microenvironment and the developing liver cancer, and to identify factors affecting proliferation, migration and death of tumour cells, neoangiogenesis, and outgrowth of additional malignancy

Class-modeling analysis reveals T-cell homeostasis disturbances involved in loss of immune control in elite controllers

Despite long-lasting HIV replication control, a significant proportion of elite controller (EC) patients may experience CD4 T-cell loss. Discovering perturbations in immunological parameters could help our understanding of the mechanisms that may be operating in those patients experiencing loss of immunological control. Methods A case–control study was performed to evaluate if alterations in different T-cell homeostatic parameters can predict CD4 T-cell loss in ECs by comparing data from EC patients showing significant CD4 decline (cases) and EC patients showing stable CD4 counts (controls). The partial least-squares–class modeling (PLS-CM) statistical methodology was employed to discriminate between the two groups of patients, and as a predictive model. Results Herein, we show that among T-cell homeostatic alterations, lower levels of naïve and recent thymic emigrant subsets of CD8 cells and higher levels of effector and senescent subsets of CD8 cells as well as higher levels of exhaustion of CD4 cells, measured prior to CD4 T-cell loss, predict the loss of immunological control. Conclusions These data indicate that the parameters of T-cell homeostasis may identify those EC patients with a higher proclivity to CD4 T-cell loss. Our results may open new avenues for understanding the mechanisms underlying immunological progression despite HIV replication control, and eventually, for finding a functional cure through immune-based clinical trials.projects RD12/0017/0031, RD16/0025/ 0013, and SAF2015-66193-R as part of the Health Research and Development Strategy, State Plan for Scientific and Technical Research and Innovation (2008– 2011 and 2013–2016) and cofinanced by the Institute of Health Carlos III (ISCIII), Sub-Directorate General for Research Assessment and Promotion and European Regional Development Fund. NR is a Miguel Servet investigator from the ISCIII (CP14/00198), Madrid, Spain. C Restrepo was funded by project RD12/0017/ 0031 and is currently funded by project RD16/0025/0013. M García is a predoctoral student co-funded by grant CP14/00198 and an Intramural Research Scholarship from Instituto de Investigación Sanitaria-Fundación Jiménez Díaz (IIS-FJD)