Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models.

The mechanisms triggering the human immunodeficiency virus type I (HIV-1) to switch the coreceptor usage from CCR5 to CXCR4 during the course of infection are not entirely understood. While low CD4+ T cell counts are associated with CXCR4 usage, a predominance of CXCR4 usage with still high CD4+ T cell counts remains puzzling. Here, we explore the hypothesis that viral adaptation to the human leukocyte antigen (HLA) complex, especially to the HLA class II alleles, contributes to the coreceptor switch. To this end, we sequence the viral gag and env protein with corresponding HLA class I and II alleles of a new cohort of 312 treatment-naive, subtype C, chronically-infected HIV-1 patients from South Africa. To estimate HLA adaptation, we develop a novel computational approach using Bayesian generalized linear mixed models (GLMMs). Our model allows to consider the entire HLA repertoire without restricting the model to pre-learned HLA-polymorphisms. In addition, we correct for phylogenetic relatedness of the viruses within the model itself to account for founder effects. Using our model, we observe that CXCR4-using variants are more adapted than CCR5-using variants (p-value = 1.34e-2). Additionally, adapted CCR5-using variants have a significantly lower predicted false positive rate (FPR) by the geno2pheno[coreceptor] tool compared to the non-adapted CCR5-using variants (p-value = 2.21e-2), where a low FPR is associated with CXCR4 usage. Consequently, estimating HLA adaptation can be an asset in predicting not only coreceptor usage, but also an approaching coreceptor switch in CCR5-using variants. We propose the usage of Bayesian GLMMs for modeling virus-host adaptation in general.

Changes in real-world walking speed following 60-day bed-rest.

The aim of this work was to explore whether real-world walking speed (RWS) would change as a consequence of 60-day bed-rest. The main hypothesis was that daily RWS would decrease after the bed-rest, with a subsequent recovery during the first days of re-ambulation. Moreover, an exploratory analysis was done in order to understand whether there is an agreement between the loss in RWS after bed-rest and the loss in the maximum oxygen uptake capacity (VO2max), or the loss in maximal vertical jump power (JUMP) respectively. Twenty-four subjects were randomly assigned to one of three groups: a continuous artificial gravity group, an intermittent artificial gravity group, or a control group. The fitted linear mixed effects model showed a significant decrease (p < 0.001) of RWS after the 60-day bed-rest and a subsequent increase (p < 0.001) of RWS during the 14-day recovery period in the study facility. No or little agreement was found between the loss in RWS and the loss in VO2max capacity or the loss in maximal vertical jumping power (RWS vs. VO2max: p = 0.81, RWS vs. JUMP: p = 0.173). Decreased RWS after bed-rest, with a follow-up recovery was observed for all three groups, regardless of the training intervention. This suggests that RWS, also in these settings, was able to reflect a de-conditioning and follow-up recovery process.