Disease extent and anti-tubercular treatment response correlates with -specific CD4 T-cell phenotype regardless of HIV-1 status.

Objectives: The development of non-sputum-based assays for tuberculosis (TB) diagnosis and treatment monitoring is a key priority. Recent data indicate that whole blood-based assays to assess the phenotype of (Mtb)-specific CD4 T cells hold promise for this purpose and require further investigation in well-characterised TB cohorts. In this study, we investigated the relationship between the phenotypic signature of Mtb-specific CD4 responses, TB disease extent and treatment response.

Genome-wide heritability analysis of severe malaria resistance reveals evidence of polygenic inheritance.

Background: Estimating single nucleotide polymorphism (SNP)-heritability (h2g) of severe malaria resistance and its distribution across the genome might shed new light in to the underlying biology.

Method: We investigated h2g of severe malaria resistance from a genome-wide association study (GWAS) dataset (sample size = 11 657). We estimated the h2g and partitioned in to chromosomes, allele frequencies and annotations using the genetic relationship-matrix restricted maximum likelihood approach.

Incidence of Tuberculosis Among HIV-Positive Individuals Initiating Antiretroviral Treatment at Higher CD4 Counts in the HPTN 071 (PopART) Trial in South Africa.

Introduction: Antiretroviral treatment (ART) guidelines recommend life-long ART for all HIV-positive individuals. This study evaluated tuberculosis (TB) incidence on ART in a cohort of HIV-positive individuals starting ART regardless of CD4 count in a programmatic setting at 3 clinics included in the HPTN 071 (PopART) trial in South Africa.

Methods: A retrospective cohort analysis of HIV-positive individuals aged ≥18 years starting ART, between January 2014 and November 2015, was conducted.

Robust inference of positive selection from recombining coding sequences.

Motivation: Accurate detection of positive Darwinian selection can provide important insights to researchers investigating the evolution of pathogens. However, many pathogens (particularly viruses) undergo frequent recombination and the phylogenetic methods commonly applied to detect positive selection have been shown to give misleading results when applied to recombining sequences. We propose a method that makes maximum likelihood inference of positive selection robust to the presence of recombination.