Efficient and targeted COVID-19 border testing via reinforcement learning.

Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all travellers to restricting entry from select nations on the basis of population-level epidemiological metrics such as cases, deaths or testing positivity rates1,2. Here we report the design and performance of a reinforcement learning system, nicknamed Eva. In the summer of 2020, Eva was deployed across all Greek borders to limit the influx of asymptomatic travellers infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and to inform border policies through real-time estimates of COVID-19 prevalence. In contrast to country-wide protocols, Eva allocated Greece's limited testing resources on the basis of incoming travellers' demographic information and testing results from previous travellers. By comparing Eva's performance against modelled counterfactual scenarios, we show that Eva identified 1.85 times as many asymptomatic, infected travellers as random surveillance testing, with up to 2-4 times as many during peak travel, and 1.25-1.45 times as many asymptomatic, infected travellers as testing policies that utilize only epidemiological metrics. We demonstrate that this latter benefit arises, at least partially, because population-level epidemiological metrics had limited predictive value for the actual prevalence of SARS-CoV-2 among asymptomatic travellers and exhibited strong country-specific idiosyncrasies in the summer of 2020. Our results raise serious concerns on the effectiveness of country-agnostic internationally proposed border control policies3 that are based on population-level epidemiological metrics. Instead, our work represents a successful example of the potential of reinforcement learning and real-time data for safeguarding public health.

Performance of Different Risk Scores for the Detection of Atrial Fibrillation Among Patients With Cryptogenic Stroke.

BACKGROUND: Atrial fibrillation (AF) is a frequent underlying cause of cryptogenic stroke (CS) and its detection can be increased using implantable cardiac monitoring (ICM). We sought to evaluate different risk scores and assess their diagnostic ability in identifying patients with CS with underlying AF on ICM. METHODS: Patients with CS, being admitted to a single tertiary stroke center between 2017 and 2022 and receiving ICM, were prospectively evaluated. The CHA2DS2-VASc, HAVOC, Brown ESUS-AF, and C2HEST scores were calculated at baseline. The primary outcome of interest was the detection of AF, which was defined as at least 1 AF episode on ICM lasting for 2 consecutive minutes or more. The diagnostic accuracy measures and the net reclassification improvement were calculated for the 4 risk scores. Stroke recurrence was evaluated as a secondary outcome. RESULTS: A total of 250 patients with CS were included, and AF was detected by ICM in 20.4% (n=51) during a median monitoring period of 16 months. Patients with CS with AF detection were older compared with the rest (P=0.045). The median HAVOC, Brown ESUS-AF, and C2HEST scores were higher among the patients with AF compared with the patients without AF (all P<0.05), while the median CHA2DS2-VASc score was similar between the 2 groups. The corresponding C statistics for CHA2DS2-VASc, HAVOC, Brown ESUS-AF, and C2HEST for AF prediction were 0.576 (95% CI, 0.482-0.670), 0.612 (95% CI, 0.523-0.700), 0.666 (95% CI, 0.587-0.746), and 0.770 (95% CI, 0.699-0.839). The C2HEST score presented the highest diagnostic performance based on C statistics (P<0.05 after correction for multiple comparisons) and provided significant improvement in net reclassification for AF detection (>70%) compared with the other risk scores. Finally, stroke recurrence was documented in 5.6% of the study population, with no difference regarding the 4 risk scores between patients with and without recurrent stroke. CONCLUSIONS: The C2HEST score was superior to the CHA2DS2-VASc, HAVOC, and Brown ESUS-AF scores for discriminating patients with CS with underlying AF using ICM.

Standardized Cumulative Metrics of Excess Mortality to Monitor Health System Resilience Throughout COVID-19 and Other Respiratory Virus Resurgences.

Monitoring morbidity and mortality in resurgences of respiratory infections poses significant challenges, as shown by coronavirus disease 2019 (COVID-19). For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence on the general population through direct recording of COVID-19 related deaths. To overcome these limitations, more robust, less-biased metrics, such as all-cause deaths, have been proposed for monitoring the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardized single-point and standardized cumulative metrics that allow comparability of excess mortality through space and time. We explain why z score allows for comparison of excess mortality between countries and different periods, while cumulative z score allows assessment of excess mortality over long periods. Our commentary reiterates the importance of standardized statistics of excess mortality for COVID-19 surveillance as we move toward a coexistence with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that will allow drawing conclusions from best practices in different health systems and different periods.

Standardized Cumulative Metrics of Excess Mortality to Monitor Health System Resilience Throughout COVID-19 and Other Respiratory Virus Resurgences.

Monitoring morbidity and mortality in resurgences of respiratory infections poses significant challenges, as shown by coronavirus disease 2019 (COVID-19). For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence on the general population through direct recording of COVID-19 related deaths. To overcome these limitations, more robust, less-biased metrics, such as all-cause deaths, have been proposed for monitoring the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardized single-point and standardized cumulative metrics that allow comparability of excess mortality through space and time. We explain why z score allows for comparison of excess mortality between countries and different periods, while cumulative z score allows assessment of excess mortality over long periods. Our commentary reiterates the importance of standardized statistics of excess mortality for COVID-19 surveillance as we move toward a coexistence with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that will allow drawing conclusions from best practices in different health systems and different periods.

Human endogenous retroviruses in cancer: Oncogenesis mechanisms and clinical implications.

Human Endogenous Retroviruses (HERVs) are viral sequences integrated into the human genome, resulting from the infection of human germ-line cells by ancient exogenous retroviruses. Despite losing their replication and retrotransposition abilities, HERVs appear to have been co-opted in human physiological functions while their aberrant expression is linked to human disease. The role of HERVs in multiple malignancies has been demonstrated, however, the extent to which HERV activation and expression participate in the development of cancer is not yet fully comprehended. In this review article, we discuss the presumed role of HERVs in carcinogenesis and their promising diagnostic and prognostic implications. Additionally, we explore recent data on the HERVs in cancer therapeutics, either through the manipulation of their expression, to induce antitumor innate immunity responses or as cancer immunotherapy targets. Finally, more precise and higher resolution high-throughput sequencing approaches will further elucidate HERV participation in human physiological and pathological processes.

BreakAlign: a Perl program to align chimaeric (split) genomic NGS reads and allow visual confirmation of novel retroviral integrations.

BACKGROUND: Retroviruses replicate by integrating a DNA copy into a host chromosome. Detecting novel retroviral integrations (ones not in the reference genome sequence of the host) from genomic NGS data is bioinformatically challenging and frequently produces many false positives. One common method of confirmation is visual inspection of an alignment of the chimaeric (split) reads that span a putative novel retroviral integration site. We perceived the need for a program that would facilitate this by producing a multiple alignment containing both the viral and host regions that flank an integration. RESULTS: BreakAlign is a Perl program that uses blastn to produce such a multiple alignment. In addition to the NGS dataset and a reference viral sequence, the program requires either (a) the ~ 500nt host genome sequence that spans the putative integration or (b) coordinates of this putative integration in an installed copy of the reference human genome (multiple integrations can be processed automatically). BreakAlign is freely available from https://github.com/marchiem/breakalign and is accompanied by example files allowing a test run. CONCLUSION: BreakAlign will confirm and facilitate characterisation of both (a) germline integrations of endogenous retroviruses and (b) somatic integrations of exogenous retroviruses such as HIV and HTLV. Although developed for use with genomic short-read NGS (second generation) data and retroviruses, it should also be useful for long-read (third generation) data and any mobile element with at least one conserved flanking region.

Development and Analytical Validation of a One-Step Five-Plex RT-ddPCR Assay for the Quantification of SARS-CoV-2 Transcripts in Clinical Samples.

Highly sensitive methodologies for SARS-CoV-2 detection are essential for the control of COVID-19 pandemic. We developed and analytically validated a highly sensitive and specific five-plex one-step RT-ddPCR assay for SARS-CoV-2. We first designed in-silico novel primers and probes for the simultaneous absolute quantification of three different regions of the nucleoprotein (N) gene of SARS-CoV-2 (N1, N2, N3), a synthetic RNA as an external control (RNA-EC), and Beta-2-Microglobulin (B2M) as an endogenous RNA internal control (RNA-IC). The developed assay was analytically validated using synthetic DNA and RNA calibrator standards and then was applied to 100 clinical specimens previously analyzed with a commercially available CE-IVD RT-qPCR assay. The analytical validation of the developed assay resulted in very good performance characteristics in terms of analytical sensitivity, linearity, analytical specificity, and reproducibility and recovery rates even at very low viral concentrations. The simultaneous absolute quantification of the RNA-EC and RNA-IC provides the necessary metrics for quality control assessment. Direct comparison of the developed one-step five-plex RT-ddPCR assay with a CE-IVD RT-qPCR kit revealed a very high concordance and a higher sensitivity [concordance: 99/100 (99.0%, Spearman's correlation coefficient: -0.850, p < 0.001)]. The developed assay is highly sensitive, specific, and reproducible and has a broad linear dynamic range, providing absolute quantification of SARS-COV-2 transcripts. The inclusion of two RNA quality controls, an external and an internal, is highly important for standardization of SARS-COV-2 molecular testing in clinical and wastewater samples.

Estimation of the determinants for HIV late presentation using the traditional definition and molecular clock-inferred dates: Evidence that older age, heterosexual risk group and more recent diagnosis are prognostic factors.

OBJECTIVES: HIV late presentation (LP) has been increasing in recent years in Europe. Our aim was to investigate the characteristics of LP in Greece using in addition to the traditional definition for LP, the time interval between HIV infection and diagnosis. METHODS: Our nationwide sample included HIV-1 sequences generated from 6166 people living with HIV (PLWH) in Greece during the period 1999-2015. Our analysis was based on the molecularly inferred HIV-1 infection dates for PLWH infected within local molecular transmission clusters of subtypes A1 and B. RESULTS: Analysis of the determinants of LP was conducted using either CD4 counts or AIDS-defining condition at diagnosis or the time from infection to diagnosis. Older age, heterosexual transmission risk group and more recent diagnosis were associated with increased risk for LP. In contrast to previous studies, people who inject drugs (PWID) had a shorter median time to diagnosis (0.63 years) compared to men who have sex with men (MSM) (1.72 years) and heterosexuals (2.43 years). Using HIV infection dates that provide an unbiased marker for LP compared to CD4 counts at diagnosis, which are age-dependent, we estimated that the time to diagnosis increased gradually with age. Migrants infected regionally do not differ with respect to LP status compared to native Greeks. CONCLUSIONS: We demonstrate that older people and heterosexuals are among those at higher risk for LP; and given the growing number of older people among newly diagnosed cases, tailored interventions are needed in these populations.

Significance of serum HBV RNA in non-cirrhotic HBeAg-negative chronic hepatitis B patients who discontinue effective antiviral therapy.

HBV RNA is considered as a promising predictor in patients who discontinue nucleos(t)ide analogues (NAs). We determined HBV RNA levels in non-cirrhotic HBeAg-negative patients who discontinued NAs and assessed their predictability for 12-month outcomes. Fifty-seven patients of DARING-B study were included. HBV RNA levels were determined in stored monthly serum samples drawn at 0-3 months after end of therapy (EOT). Other markers previously determined in the same cohort including hepatitis B core-related antigen (HBcrAg) were also assessed. HBV RNA at EOT was detectable in 7% of patients, who developed virological/clinical relapse and required retreatment at month 2; in patients with undetectable EOT HBV RNA, 12-month cumulative rates of virological relapse, clinical relapse and retreatment were 68%, 28% and 21%, respectively (p ≤ 0.008). HBV RNA at month-1 after EOT was detectable in 19% of patients being associated with higher probability only of virological relapse (p = 0.001). HBV RNA levels correlated significantly to HBV DNA, HBcrAg, ALT and interferon-induced protein-10, but not HBsAg levels. Combined EOT HBV RNA and HBcrAg detection and/or HBsAg >1000 IU/ml was associated only with higher probability of retreatment having higher sensitivity and lower specificity than HBV RNA alone. In conclusion, serum HBV RNA is detectable in a minority of non-cirrhotic HBeAg-negative patients under effective long-term NAs therapy offering low sensitivity but 100% specificity for early retreatment due to severe clinical relapses after NA discontinuation. The combinations of EOT HBV RNA with HBcrAg and/or high HBsAg levels increase sensitivity but decrease specificity for prediction of retreatment after NAs withdrawal.

Earlier treatment initiation is associated with a decreased number of HIV-1 subtype A1 transmissions in Greece.

OBJECTIVES: Subtypes A1 and B are the most prevalent HIV-1 clades in Greece. Subtype A1 epidemic is highly monophyletic and corresponds to transmissions that occurred locally. Our aim in this molecular epidemiology analysis was to investigate the role of early treatment in preventing new HIV-1 transmissions. METHODS: Our analysis focused on 791 subtype A1 sequences from treatment-naïve individuals in Greece. Estimation of infection dates was performed by molecular clock calculations using Bayesian methods. We estimated the time interval between (1) the infection and sampling dates (linkage to care window), (2) the sampling dates and antiretroviral therapy (ART) initiation (treatment window), and (3) the infection dates and ART initiation (transmissibility window) for the study population. We also inferred the putative source of HIV infections between individuals of different groups divided according to the length of treatment, linkage to care or transmissibility window. RESULTS: A significant decline was detected for the treatment window during 2014-2015 versus the 2 previous years (p=0.0273), while the linkage to care interval remained unchanged during the study period. Inference of the putative source of HIV infections suggested that individuals with a recent diagnosis or narrow transmissibility window (time period between HIV infection and ART initiation) were not sources of HIV infections to other groups. Contrarily, a significant number of HIV infections originated from individuals with longer transmissibility window interval. CONCLUSIONS: Our findings showed that the treatment window is decreasing over time, presumably due to the updated treatment guidelines. Our study also demonstrates that people treated earlier after infection do not transmit at high rates, thus documenting the benefits of early ART initiation in preventing ongoing HIV-1 transmission.

Human Endogenous Retrovirus-K HML-2 integration within RASGRF2 is associated with intravenous drug abuse and modulates transcription in a cell-line model.

HERV-K HML-2 (HK2) has been proliferating in the germ line of humans at least as recently as 250,000 years ago, with some integrations that remain polymorphic in the modern human population. One of the solitary HK2 LTR polymorphic integrations lies between exons 17 and 18 of RASGRF2, a gene that affects dopaminergic activity and is thus related to addiction. Here we show that this antisense HK2 integration (namely RASGRF2-int) is found more frequently in persons who inject drugs compared with the general population. In a Greek HIV-1-positive population (n = 202), we found RASGRF2-int 2.5 times (14 versus 6%) more frequently in patients infected through i.v. drug use compared with other transmission route controls (P = 0.03). Independently, in a United Kingdom-based hepatitis C virus-positive population (n = 184), we found RASGRF2-int 3.6 times (34 versus 9.5%) more frequently in patients infected during chronic drug abuse compared with controls (P < 0.001). We then tested whether RASGRF2-int could be mechanistically responsible for this association by modulating transcription of RASGRF2 We show that the CRISPR/Cas9-mediated insertion of HK2 in HEK293 cells in the exact RASGRF2 intronic position found in the population resulted in significant transcriptional and phenotypic changes. We also explored mechanistic features of other intronic HK2 integrations and show that HK2 LTRs can be responsible for generation of cis-natural antisense transcripts, which could interfere with the transcription of nearby genes. Our findings suggest that RASGRF2-int is a strong candidate for dopaminergic manipulation, and emphasize the importance of accurate mapping of neglected HERV polymorphisms in human genomic studies.

Molecular epidemiology reveals the role of war in the spread of HIV in Ukraine.

Ukraine has one of the largest HIV epidemics in Europe, historically driven by people who inject drugs (PWID). The epidemic showed signs of stabilization in 2012, but the recent war in eastern Ukraine may be reigniting virus spread. We investigated the movement of HIV-infected people within Ukraine before and during the conflict. We analyzed HIV-1 subtype-A pol nucleotide sequences sampled during 2012-2015 from 427 patients of 24 regional AIDS centers and used phylogeographic analysis to reconstruct virus movement among different locations in Ukraine. We then tested for correlations between reported PWID behaviors and reconstructed patterns of virus spread. Our analyses suggest that Donetsk and Lugansk, two cities not controlled by the Ukrainian government in eastern Ukraine, were significant exporters of the virus to the rest of the country. Additional analyses showed that viral dissemination within the country changed after 2013. Spearman correlation analysis showed that incoming virus flow was correlated with the number of HIV-infected internally displaced people. Additionally, there was a correlation between more intensive virus movement and locations with a higher proportion of PWID practicing risky sexual behaviors. Our findings suggest that effective prevention responses should involve internally displaced people and people who frequently travel to war-affected regions. Scale-up of harm reduction services for PWID will be an important factor in preventing new local HIV outbreaks in Ukraine.

Molecular Analysis of Human Immunodeficiency Virus Type 1 (HIV-1)-Infected Individuals in a Network-Based Intervention (Transmission Reduction Intervention Project): Phylogenetics Identify HIV-1-Infected Individuals With Social Links.

Background: The Transmission Reduction Intervention Project (TRIP) is a network-based intervention that aims at decreasing human immunodeficiency virus type 1 (HIV-1) spread. We herein explore associations between transmission links as estimated by phylogenetic analyses, and social network-based ties among persons who inject drugs (PWID) recruited in TRIP. Methods: Phylogenetic trees were inferred from HIV-1 sequences of TRIP participants. Highly supported phylogenetic clusters (transmission clusters) were those fulfilling 3 different phylogenetic confidence criteria. Social network-based ties (injecting or sexual partners, same venue engagement) were determined based on personal interviews, recruitment links, and field observation. Results: TRIP recruited 356 individuals (90.2% PWID) including HIV-negative controls; recently HIV-infected seeds; long-term HIV-infected seeds; and their social network members. Of the 150 HIV-infected participants, 118 (78.7%) were phylogenetically analyzed. Phylogenetic analyses suggested the existence of 13 transmission clusters with 32 sequences. Seven of these clusters included 14 individuals (14/32 [43.8%]) who also had social ties with at least 1 member of their cluster. This proportion was significantly higher than what was expected by chance. Conclusions: Molecular methods can identify HIV-infected people socially linked with another person in about half of the phylogenetic clusters. This could help public health efforts to locate individuals in networks with high transmission rates.

Nanopore sequencing and full genome de novo assembly of human cytomegalovirus TB40/E reveals clonal diversity and structural variations.

BACKGROUND: Human cytomegalovirus (HCMV) has a double-stranded DNA genome of approximately 235 Kbp that is structurally complex including extended GC-rich repeated regions. Genomic recombination events are frequent in HCMV cultures but have also been observed in vivo. Thus, the assembly of HCMV whole genomes from technologies producing shorter than 500 bp sequences is technically challenging. Here we improved the reconstruction of HCMV full genomes by means of a hybrid, de novo genome-assembly bioinformatics pipeline upon data generated from the recently released MinION MkI B sequencer from Oxford Nanopore Technologies. RESULTS: The MinION run of the HCMV (strain TB40/E) library resulted in ~ 47,000 reads from a single R9 flowcell and in ~ 100× average read depth across the virus genome. We developed a novel, self-correcting bioinformatics algorithm to assemble the pooled HCMV genomes in three stages. In the first stage of the bioinformatics algorithm, long contigs (N50 = 21,892) of lower accuracy were reconstructed. In the second stage, short contigs (N50 = 5686) of higher accuracy were assembled, while in the final stage the high quality contigs served as template for the correction of the longer contigs resulting in a high-accuracy, full genome assembly (N50 = 41,056). We were able to reconstruct a single representative haplotype without employing any scaffolding steps. The majority (98.8%) of the genomic features from the reference strain were accurately annotated on this full genome construct. Our method also allowed the detection of multiple alternative sub-genomic fragments and non-canonical structures suggesting rearrangement events between the unique (UL /US) and the repeated (T/IRL/S) genomic regions. CONCLUSIONS: Third generation high-throughput sequencing technologies can accurately reconstruct full-length HCMV genomes including their low-complexity and highly repetitive regions. Full-length HCMV genomes could prove crucial in understanding the genetic determinants and viral evolution underpinning drug resistance, virulence and pathogenesis.

An Innovative Study Design to Assess the Community Effect of Interventions to Mitigate HIV Epidemics Using Transmission-Chain Phylodynamics.

Given globalization and other social phenomena, controlling the spread of infectious diseases has become an imperative public health priority. A plethora of interventions that in theory can mitigate the spread of pathogens have been proposed and applied. Evaluating the effectiveness of such interventions is costly and in many circumstances unrealistic. Most important, the community effect (i.e., the ability of the intervention to minimize the spread of the pathogen from people who received the intervention to other community members) can rarely be evaluated. Here we propose a study design that can build and evaluate evidence in support of the community effect of an intervention. The approach exploits molecular evolutionary dynamics of pathogens in order to track new infections as having arisen from either a control or an intervention group. It enables us to evaluate whether an intervention reduces the number and length of new transmission chains in comparison with a control condition, and thus lets us estimate the relative decrease in new infections in the community due to the intervention. We provide as an example one working scenario of a way the approach can be applied with a simulation study and associated power calculations.

A novel method for the multiplexed target enrichment of MinION next generation sequencing libraries using PCR-generated baits.

The enrichment of targeted regions within complex next generation sequencing libraries commonly uses biotinylated baits to capture the desired sequences. This method results in high read coverage over the targets and their flanking regions. Oxford Nanopore Technologies recently released an USB3.0-interfaced sequencer, the MinION. To date no particular method for enriching MinION libraries has been standardized. Here, using biotinylated PCR-generated baits in a novel approach, we describe a simple and efficient way for multiplexed enrichment of MinION libraries, overcoming technical limitations related with the chemistry of the sequencing-adapters and the length of the DNA fragments. Using Phage Lambda and Escherichia coli as models we selectively enrich for specific targets, significantly increasing the corresponding read-coverage, eliminating unwanted regions. We show that by capturing genomic fragments, which contain the target sequences, we recover reads extending targeted regions and thus can be used for the determination of potentially unknown flanking sequences. By pooling enriched libraries derived from two distinct E. coli strains and analyzing them in parallel, we demonstrate the efficiency of this method in multiplexed format. Crucially we evaluated the optimal bait size for large fragment libraries and we describe for the first time a standardized method for target enrichment in MinION platform.

Human endogenous retrovirus (HERV) expression is not induced by treatment with the histone deacetylase (HDAC) inhibitors in cellular models of HIV-1 latency.

BACKGROUND: While antiretroviral therapies have improved life expectancy and reduced viral loads in HIV-1-positive individuals, the cessation of treatment results in a rebound of viral replication. This suggests that a reservoir of latently-infected cells remains within these patients, the identity of which is ill-defined and therefore difficult to target therapeutically. Current strategies are aimed at using drugs such as histone deacetylase (HDAC) inhibitors to induce the expression of latent HIV-1 proviruses in order to activate and ultimately eradicate this reservoir of infected cells. One concern with the use of HDAC inhibitors is that they could up-regulate human endogenous retroviruses (HERVs), as well as HIV-1, with potentially pathophysiological consequences. RESULTS: In this study, we analysed the transcription of HERV genes in HIV-1 latency T cell (J-LAT 8.4) and monocyte (U1) models following treatment with the HDAC inhibitors, vorinostat, panobinostat and romidepsin. We examined the expression of HERV-K (HML-2) env and pol, as well as the co-opted genes HERV-W env (syncytin-1), HERV-FRD env (syncytin-2), in these cell lines. Finally, we investigated HERV expression in primary human T cells. CONCLUSIONS: We show that HDAC inhibitors did not substantially increase the transcription of the analysed HERV env or pol genes, suggesting that histone acetylation is not crucial for controlling HERV expression in these experimental models and in ex vivo primary human T cells. Importantly, this indicates that unwanted HERV expression does not appear to be a barrier to the use of HDAC inhibitors in HIV-1 cure strategies.

Transmission of hepatitis C virus infection among younger and older people who inject drugs in Vancouver, Canada.

BACKGROUND & AIMS: Understanding HCV transmission among people who inject drugs (PWID) is important for designing prevention strategies. This study investigated whether HCV infection among younger injectors occurs from few or many transmission events from older injectors to younger injectors among PWID in Vancouver, Canada. METHODS: HCV antibody positive participants at enrolment or follow-up (1996-2012) were tested for HCV RNA and sequenced (Core-E2). Time-stamped phylogenetic trees were inferred using Bayesian Evolutionary Analysis Sampling Trees (BEAST). Association of age with phylogeny was tested using statistics implemented in the software Bayesian Tip Significance (BaTS) testing. Factors associated with clustering (maximum cluster age: five years) were identified using logistic regression. RESULTS: Among 699 participants with HCV subtype 1a, 1b, 2b and 3a infection (26% female, 24% HIV+): 21% were younger (<27years), and 10% had recent HCV seroconversion. When inferred cluster age was limited to <5years, 15% (n=108) were in clusters/pairs. Although a moderate degree of segregation was observed between younger and older participants, there was also transmission between age groups. Younger age (<27 vs. >40, AOR: 3.14; 95% CI: 1.54, 6.39), HIV (AOR: 1.97; 95% CI: 1.22, 3.18) and subtype 3a (AOR: 2.12; 95% CI: 1.33, 3.38) were independently associated with clustering. CONCLUSIONS: In this population of PWID from Vancouver, HCV among young injectors was seeded from many transmission events between HCV-infected older and younger injectors. Phylogenetic clustering was associated with younger age and HIV. These data suggest that HCV transmission among PWID is complex, with transmission occurring between and among older and younger PWID.

Larger mammalian body size leads to lower retroviral activity.

Retroviruses have been infecting mammals for at least 100 million years, leaving descendants in host genomes known as endogenous retroviruses (ERVs). The abundance of ERVs is partly determined by their mode of replication, but it has also been suggested that host life history traits could enhance or suppress their activity. We show that larger bodied species have lower levels of ERV activity by reconstructing the rate of ERV integration across 38 mammalian species. Body size explains 37% of the variance in ERV integration rate over the last 10 million years, controlling for the effect of confounding due to other life history traits. Furthermore, 68% of the variance in the mean age of ERVs per genome can also be explained by body size. These results indicate that body size limits the number of recently replicating ERVs due to their detrimental effects on their host. To comprehend the possible mechanistic links between body size and ERV integration we built a mathematical model, which shows that ERV abundance is favored by lower body size and higher horizontal transmission rates. We argue that because retroviral integration is tumorigenic, the negative correlation between body size and ERV numbers results from the necessity to reduce the risk of cancer, under the assumption that this risk scales positively with body size. Our model also fits the empirical observation that the lifetime risk of cancer is relatively invariant among mammals regardless of their body size, known as Peto's paradox, and indicates that larger bodied mammals may have evolved mechanisms to limit ERV activity.