Thymocyte regulatory variant alters transcription factor binding and protects from type 1 diabetes in infants

We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes (T1D) diagnosed below the age of 7 years between the PTPRK and thymocyte-selection-associated (THEMIS) genes. As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind this association using thymocyte genomic data. In four thymocyte populations, we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. In a parallel approach to identifying variants that alter transcription factor binding motifs, the same variant disrupted a predicted motif for Rfx7, which is abundantly expressed in the thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while expression quantitative trait locus and chromatin conformation data associate the insertion with lower THEMIS expression. Extending the analysis to other T1D loci further highlighted rs66733041 affecting the GATA3 transcription factor binding in the AFF3 locus. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development of early-onset T1D.Peer reviewe

Enhanced normalisation of CD4/CD8 ratio with early antiretroviral therapy in primary HIV infection

INTRODUCTION: Despite normalization of total CD4 counts, ongoing immune dysfunction is noted amongst those on antiretroviral therapy (ART). Low CD4/CD8 ratio is associated with a high risk of AIDS and non-AIDS events and may act as a marker of immune senescence [1]. This ratio is improved by ART although normalization is uncommon (~7%) [2]. The probability of normalization of CD4 count is improved with immediate ART initiation in primary HIV infection (PHI) [3]. We examined whether CD4/CD8 ratio similarly normalized in immediate vs. deferred ART at PHI. MATERIAL AND METHODS: Using data from the SPARTAC trial and the UK Register of HIV Seroconverters, we examined the effect of ART with time (continuous) from HIV seroconversion (SC) on CD4/CD8 ratio (≥1) adjusted for sex, risk group, ethnicity, enrolment from an African site and both CD4 count and age at ART initiation. We also examined that effect by dichotomizing HIV duration at ART initiation (ART started within six months of SC: early ART; ART initiated>six months after SC: deferred). We also considered time to CD4 count normalization (≥900 cells/mm(3)). RESULTS: In total, 353 initiated ART with median (IQR) 97.9 (60.5, 384.5) days from estimated seroconversion; 253/353 early ART, 100 deferred ART. At one year after starting ART, 114/253 (45%) early ART had normalized CD4/8 ratio, compared with 11/99 (11%) in the deferred group, whilst 83/253 (33%) of early ART had normalized CD4 counts, compared with 3/99 (3%) in the deferred group. Individuals initiating within six months of PHI were significantly more likely to reach normal ratio than those initiating later (HR, 95% CI 2.96, 1.75 - 5.01, p<0.001). The longer after SC ART was initiated, the reduced likelihood of achieving normalization of CD4/CD8 ratio (HR 0.98, 95% CI 0.96 - 0.99 for each 30-day increase). CD4 count at ART initiation was also associated with normalization, as expected (HR 1.002, 95% CI 1.001 - 1.002, p<0.001). There was an association between normal CD4/CD8 ratio and being virally suppressed (<400 copies HIV RNA/ml) p<0.001. CD4 count normalization was also significantly more likely for those initiating early (HR 5.00, 95% CI 1.52 - 16.41, p=0.008). CONCLUSIONS: The likelihood of achieving normalization of CD4/CD8 ratios was increased if ART was initiated within six months of PHI. Higher CD4/CD8 ratio may reflect a more 'normal' immune phenotype conferring enhanced prognosis and predict post-treatment control

Enhanced normalisation of CD4/CD8 ratio with early antiretroviral therapy in primary HIV infection

Introduction: Despite normalization of total CD4 counts, ongoing immune dysfunction is noted amongst those on antiretroviral therapy (ART). Low CD4/CD8 ratio is associated with a high risk of AIDS and non-AIDS events and may act as a marker of immune senescence [1]. This ratio is improved by ART although normalization is uncommon (7%) [2]. The probability of normalization of CD4 count is improved with immediate ART initiation in primary HIV infection (PHI) [3]. We examined whether CD4/CD8 ratio similarly normalized in immediate vs. deferred ART at PHI. Methods: Using data from the SPARTAC trial and the UK Register of HIV Seroconverters, we examined the effect of ART with time (continuous) from HIV seroconversion (SC) on CD4/CD8 ratio (]1) adjusted for sex, risk group, ethnicity, enrolment from an African site and both CD4 count and age at ART initiation. We also examined that effect by dichotomizing HIV duration at ART initiation (ART started within six months of SC: early ART; ART initiatedsix months after SC: deferred). We also considered time to CD4 count normalization (]900 cells/mm3 ). Results: In total, 353 initiated ART with median (IQR) 97.9 (60.5, 384.5) days from estimated seroconversion; 253/353 early ART, 100 deferred ART. At one year after starting ART, 114/253 (45%) early ART had normalized CD4/8 ratio, compared with 11/99 (11%) in the deferred group, whilst 83/253 (33%) of early ART had normalized CD4 counts, compared with 3/99 (3%) in the deferred group. Individuals initiating within six months of PHI were significantly more likely to reach normal ratio than those initiating later (HR, 95% CI 2.96, 1.755.01, pB0.001). The longer after SC ART was initiated, the reduced likelihood of achieving normalization of CD4/CD8 ratio (HR 0.98, 95% CI 0.960.99 for each 30-day increase). CD4 count at ART initiation was also associated with normalization, as expected (HR 1.002, 95% CI 1.0011.002, pB0.001). There was an association between normal CD4/CD8 ratio and being virally suppressed (B400 copies HIV RNA/ml) pB0.001. CD4 count normalization was also significantly more likely for those initiating early (HR 5.00, 95% CI 1.5216.41, p0.008). Conclusions: The likelihood of achieving normalization of CD4/CD8 ratios was increased if ART was initiated within six months of PHI. Higher CD4/CD8 ratio may reflect a more ‘‘normal’’ immune phenotype conferring enhanced prognosis and predict posttreatment control. Refe

Anti-inflammatory therapy with nebulised dornase alfa in patients with severe COVID-19 pneumonia A Randomised Clinical Trial

SARS-CoV2 infection causes severe, life-threatening pneumonia. Hyper-inflammation, coagulopathy and lymphopenia are associated with pathology and poor outcomes in these patients. Cell-free (cf) DNA is prominent in COVID-19 patients, amplifies inflammation and promotes coagulopathy and immune dysfunction. We hypothesized that cf-DNA clearance by nebulised dornase alfa may reduce inflammation and improve disease outcomes. Here, we evaluated the efficacy of nebulized dornase alfa in patients hospitalised with severe COVID-19 pneumonia. In this randomised controlled single-centre phase 2 proof-of-concept trial, we recruited adult patients admitted to hospital that exhibited stable oxygen saturation (≥94%) on supplementary oxygen and a C-reactive protein (CRP) level ≥30mg/L post dexamethasone treatment. Participants were randomized at a 3:1 ratio to receive twice-daily nebulised dornase alfa in addition to best available care (BAC) or BAC alone for seven days or until hospital discharge. A 2:1 ratio of historical controls to treated individuals (HC, 2:1) were included as the primary endpoint comparators. The primary outcome was a reduction in systemic inflammation measured by blood CRP levels over 7 days post-randomisation, or to discharge if sooner. Secondary and exploratory outcomes included time to discharge, time on oxygen, D-dimer levels, lymphocyte counts and levels of circulating cf-DNA. We screened 75 patients and enrolled 39 participants out of which 30 in dornase alfa arm, and 9 in BAC group. We also matched the recruited patients in the treated group (N=30) to historical controls in the BAC group (N=60). For the the primary outcome, 30 patients in the dornase alfa were compared to 69 patients in the BAC group. Dornase alfa treatment reduced CRP by 33% compared to the BAC group at 7-days (P=0.01). The dornase alfa group least squares mean CRP was 23.23 mg/L (95% CI 17.71 to 30.46) and the BAC group 34.82 mg/L (95% CI 28.55 to 42.47). A significant difference was also observed when only randomised participants were compared. Furthermore, compared to the BAC group, the chance of live discharge was increased by 63% in the dornase alfa group (HR 1.63, 95% CI 1.01 to 2.61, P=0.03), lymphocyte counts were improved (least-square mean: 1.08 vs 0.87, P=0.02) and markers of coagulopathy such as D-dimer were diminished (least-square mean: 570.78 vs 1656.96μg/mL, P=0.004). Moreover, the dornase alfa group exhibited lower circulating cf-DNA levels that correlated with CRP changes over the course of treatment. No differences were recorded in the rates and length of stay in the ICU or the time on oxygen between the groups. Dornase alfa was well-tolerated with no serious adverse events reported. In this proof-of-concept study in patients with severe COVID-19 pneumonia, treatment with nebulised dornase alfa resulted in a significant reduction in inflammation, markers of immune pathology and time to discharge. The effectiveness of dornase alfa in patients with acute respiratory infection and inflammation should be investigated further in larger trials

The Impact of HCV Infection Duration on HIV Disease Progression and Response to cART amongst HIV Seroconverters in the UK

The effect of HCV infection on HIV disease progression remains unclear; the effect of HCV infection duration on HIV disease progression is unknown

A global-local approach for detecting hotspots in multiple-response regression

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, i.e., predictors associated with several responses. Such a task is critical in statistical genetics, as hotspot genetic variants shape the architecture of the genome by controlling the expression of many genes and may initiate decisive functional mechanisms underlying disease endpoints. Existing hierarchical regression approaches designed to model hotspots suffer from two limitations: their discrimination of hotspots is sensitive to the choice of top-level scale parameters for the propensity of predictors to be hotspots, and they do not scale to large predictor and response vectors, e.g., of dimensions $10^3-10^5$ in genetic applications. We address these shortcomings by introducing a flexible hierarchical regression framework that is tailored to the detection of hotspots and scalable to the above dimensions. Our proposal implements a fully Bayesian model for hotspots based on the horseshoe shrinkage prior. Its global-local formulation shrinks noise globally and hence accommodates the highly sparse nature of genetic analyses, while being robust to individual signals, thus leaving the effects of hotspots unshrunk. Inference is carried out using a fast variational algorithm coupled with a novel simulated annealing procedure that allows efficient exploration of multimodal distributions

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, as hotspot genetic variants shape the architecture of the genome by controlling the expression of many genes and may initiate decisive functional mechanisms underlying disease endpoints. Existing hierarchical regression approaches designed to model hotspots suffer from two limitations: their discrimination of hotspots is sensitive to the choice of top-level scale parameters for the propensity of predictors to be hotspots, and they do not scale to large predictor and response vectors, for example, of dimensions 10(3)-10(5) in genetic applications. We address these shortcomings by introducing a flexible hierarchical regression framework that is tailored to the detection of hotspots and scalable to the above dimensions. Our proposal implements a fully Bayesian model for hotspots based on the horseshoe shrinkage prior. Its global-local formulation shrinks noise globally and, hence, accommodates the highly sparse nature of genetic analyses while being robust to individual signals, thus leaving the effects of hotspots unshrunk. Inference is carried out using a fast variational algorithm coupled with a novel simulated annealing procedure that allows efficient exploration of multimodal distributions

A global-local approach for detecting hotspots in multiple-response regression

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, i.e., predictors associated with several responses. Such a task is critical in statistical genetics, as hotspot genetic variants shape the architecture of the genome by controlling the expression of many genes and may initiate decisive functional mechanisms underlying disease endpoints. Existing hierarchical regression approaches designed to model hotspots suffer from two limitations: their discrimination of hotspots is sensitive to the choice of top-level scale parameters for the propensity of predictors to be hotspots, and they do not scale to large predictor and response vectors, e.g., of dimensions $10^3-10^5$ in genetic applications. We address these shortcomings by introducing a flexible hierarchical regression framework that is tailored to the detection of hotspots and scalable to the above dimensions. Our proposal implements a fully Bayesian model for hotspots based on the horseshoe shrinkage prior. Its global-local formulation shrinks noise globally and hence accommodates the highly sparse nature of genetic analyses, while being robust to individual signals, thus leaving the effects of hotspots unshrunk. Inference is carried out using a fast variational algorithm coupled with a novel simulated annealing procedure that allows efficient exploration of multimodal distributions

cd4_data_primary_dryad

Dataset containing all CD4 data from those individuals included in the primary analysis investigating time from HIV seroconversion to HIV disease progression