Current methods for detecting and assessing HIV-1 antibody resistance.

Antiretroviral therapy is the standard treatment for HIV, but it requires daily use and can cause side effects. Despite being available for decades, there are still 1.5 million new infections and 700,000 deaths each year, highlighting the need for better therapies.

Incorporating temporal dynamics of mutations to enhance the prediction capability of antiretroviral therapy's outcome for HIV-1.

Motivation: In predicting HIV therapy outcomes, a critical clinical question is whether using historical information can enhance predictive capabilities compared with current or latest available data analysis. This study analyses whether historical knowledge, which includes viral mutations detected in all genotypic tests before therapy, their temporal occurrence, and concomitant viral load measurements, can bring improvements. We introduce a method to weigh mutations, considering the previously enumerated factors and the reference mutation-drug Stanford resistance tables.

Torque Teno Virus Load Is Associated With Centers for Disease Control and Prevention Stage and CD4+ Cell Count in People Living With Human Immunodeficiency Virus but Seems Unrelated to AIDS-Defining Events and Human Pegivirus Load.

Background: Torque teno virus (TTV) is part of the human virome. TTV load was related to the immune status in patients after organ transplantation. We hypothesize that TTV load could be an additional marker for immune function in people living with HIV (PLWH).

Cohort Profile: A European Multidisciplinary Network for the Fight against HIV Drug Resistance (EuResist Network).

The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement.

Analysis of mutational history of multidrug-resistant genotypes with a mutagenetic tree model.

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug resistance, however, is a rare event in modern HIV treatment, but can be life-threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time.

Respiratory viruses dynamics and interactions: ten years of surveillance in central Europe.

Background: Lower respiratory tract infections are among the main causes of death. Although there are many respiratory viruses, diagnostic efforts are focused mainly on influenza. The Respiratory Viruses Network (RespVir) collects infection data, primarily from German university hospitals, for a high diversity of infections by respiratory pathogens.

Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR.

Background: Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects.

Results: Here, we present a two-step computational framework MAGAR ( https://bioconductor.

Rhinovirus prevalence as indicator for efficacy of measures against SARS-CoV-2.

Background: Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses.

Methods: We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany.

Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz.

DNA methylation profiling offers unique insights into human development and diseases. Often the analysis of complex tissues and cell mixtures is the only feasible option to study methylation changes across large patient cohorts. Since DNA methylomes are highly cell type specific, deconvolution methods can be used to recover cell type-specific information in the form of latent methylation components (LMCs) from such 'bulk' samples.

Quantitative comparison of within-sample heterogeneity scores for DNA methylation data.

DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed.

Clinical use, efficacy, and durability of maraviroc for antiretroviral therapy in routine care: A European survey.

Objectives: The study aimed to survey maraviroc use and assess effectiveness and durability of maraviroc-containing antiretroviral treatment (ART) in routine practice across Europe.

Methods: Data were retrieved from 26 cohorts in 8 countries comprising adults who started maraviroc in 2005-2016 and had ≥1 follow-up visit. Available V3 sequences were re-analysed centrally for tropism determination by geno2pheno[coreceptor].

Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data.

Chromatin accessibility maps are important for the functional interpretation of the genome. Here, we systematically analysed assay specific differences between DNase I-seq, ATAC-seq and NOMe-seq in a side by side experimental and bioinformatic setup. We observe that most prominent nucleosome depleted regions (NDRs, e.

Soluble immune markers in the different phases of chronic hepatitis B virus infection.

Chronic hepatitis B virus (HBV) infection may follow four different consecutive phases, which are defined by virology as well as biochemical markers and differ in terms of prognosis and need for antiviral treatment. Currently, host responses reflected by immune markers are not considered in this definition. We aimed to study soluble immune markers and their distribution in different phases of chronic HBV infection.

Near-Neighbor Interactions in the NS3-4A Protease of HCV Impact Replicative Fitness of Drug-Resistant Viral Variants.

A variety of amino acid substitutions in the NS3-4A protease of the hepatitis C virus lead to protease inhibitor (PI) resistance. Many of these significantly impair the replication fitness of the resistant variants in a genotype- and subtype-dependent manner, a critical factor in determining the probability with which resistant variants will persist. However, the underlying molecular mechanisms are unknown.

RnBeads 2.0: comprehensive analysis of DNA methylation data.

DNA methylation is a widely investigated epigenetic mark with important roles in development and disease. High-throughput assays enable genome-scale DNA methylation analysis in large numbers of samples. Here, we describe a new version of our RnBeads software - an R/Bioconductor package that implements start-to-finish analysis workflows for Infinium microarrays and various types of bisulfite sequencing.

Relative Principal Components Analysis: Application to Analyzing Biomolecular Conformational Changes.

A new method termed "Relative Principal Components Analysis" (RPCA) is introduced that extracts optimal relevant principal components to describe the change between two data samples representing two macroscopic states. The method is widely applicable in data-driven science. Calculating the components is based on a physical framework that introduces the objective function (the Kullback-Leibler divergence) appropriate for quantifying the change of the macroscopic state affected by the changes in the microscopic features.

Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.

Background: Bidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology.

A comprehensive analysis of 195 DNA methylomes reveals shared and cell-specific features of partially methylated domains.

Background: Partially methylated domains are extended regions in the genome exhibiting a reduced average DNA methylation level. They cover gene-poor and transcriptionally inactive regions and tend to be heterochromatic. We present a comprehensive comparative analysis of partially methylated domains in human and mouse cells, to identify structural and functional features associated with them.

From hype to reality: data science enabling personalized medicine.

Background: Personalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media).

geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data.

Identifying resistance to antiretroviral drugs is crucial for ensuring the successful treatment of patients infected with viruses such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). In contrast to Sanger sequencing, next-generation sequencing (NGS) can detect resistance mutations in minority populations. Thus, genotypic resistance testing based on NGS data can offer novel, treatment-relevant insights.