Compositions and Methods of Modulating 15-PGDH Activity

Compounds and methods of modulating 15-PGDH activity, modulating tissue prostaglandin levels, treating disease, diseases disorders, or conditions in which it is desired to modulate 15-PGDH activity and/or prostaglandin levels include 15-PGDH inhibitors and 15-PGDH activators described herein

Mutations in succinate dehydrogenase B (SDHB) enhance neutrophil survival independent of HIF-1α expression.

status: publishe

IL4Rα signaling abrogates hypoxic neutrophil survival and limits acute lung injury responses <i>in vivo</i>

Rationale: Acute respiratory distress syndrome is defined by the presence of systemic hypoxia and consequent on disordered neutrophilic inflammation. Local mechanisms limiting the duration and magnitude of this neutrophilic response remain poorly understood.  Objectives: To test the hypothesis that during acute lung inflammation tissue production of proresolution type 2 cytokines (IL-4 and IL-13) dampens the proinflammatory effects of hypoxia through suppression of HIF-1a (hypoxia-inducible factor-1a)mediated neutrophil adaptation, resulting in resolution of lung injury.  Methods: Neutrophil activation of IL4Ra (IL-4 receptor a) signaling pathways was explored ex vivo in human acute respiratory distress syndrome patient samples, in vitro after the culture of human peripheral blood neutrophils with recombinant IL-4 under conditions of hypoxia, and in vivo through the study of IL4Ra-deficient neutrophils in competitive chimera models and wild-type mice treated with IL-4.  Measurements and Main Results: IL-4 was elevated in human BAL from patients with acute respiratory distress syndrome, and its receptor was identified on patient blood neutrophils. Treatment of human neutrophils with IL-4 suppressed HIF-1a-dependent hypoxic survival and limited proinflammatory transcriptional responses. Increased neutrophil apoptosis in hypoxia, also observed with IL-13, required active STAT signaling, and was dependent on expression of the oxygen-sensing prolyl hydroxylase PHD2. In vivo, IL-4Ra-deficient neutrophils had a survival advantage within a hypoxic inflamed niche; in contrast, inflamed lung treatment with IL-4 accelerated resolution through increased neutrophil apoptosis.  Conclusions: We describe an important interaction whereby IL4Ra-dependent type 2 cytokine signaling can directly inhibit hypoxic neutrophil survival in tissues and promote resolution of neutrophil-mediated acute lung injury

A WFC3 study of globular clusters in NGC 4150 - an early-type minor merger

We combine near-ultraviolet (NUV; 2250 {\AA}) and optical (U, B, V, I) imaging from the Wide Field Camera 3 (WFC3), on board the Hubble Space Telescope (HST), to study the globular cluster (GC) population in NGC 4150, a sub-L* (M_B ~ -18.48 mag) early-type minor-merger remnant in the Coma I cloud. We use broadband NUV-optical photometry from the WFC3 to estimate individual ages, metallicities, masses and line-of-sight extinctions [E_(B-V)] for 63 bright (M_V < -5 mag) GCs in this galaxy. In addition to a small GC population with ages greater than 10 Gyr, we find a dominant population of clusters with ages centred around 6 Gyr, consistent with the expected peak of stellar mass assembly in faint early-types residing in low-density environments. The old and intermediate-age GCs in NGC 4150 are metal-poor, with metallicities less than 0.1 ZSun, and reside in regions of low extinction (E_(B-V) < 0.05 mag). We also find a population of young, metal-rich (Z > 0.3 ZSun) clusters that have formed within the last Gyr and reside in relatively dusty (E_(B-V) > 0.3 mag) regions that are coincident with the part of the galaxy core that hosts significant recent star formation. Cluster disruption models (in which ~80-90% of objects younger than a few 10^8 yr dissolve every dex in time) suggest that the bulk of these young clusters are a transient population.Comment: Submitted to MNRAS Letter

Change in Blood Pressure Variability Among Treated Elderly Hypertensive Patients and Its Association With Mortality

Background: Information is scarce regarding effects of antihypertensive medication on blood pressure variability (BPV) and associated clinical outcomes. We examined whether antihypertensive treatment changes BPV over time and whether such change (decline or increase) has any association with long-term mortality in an elderly hypertensive population. Methods and Results: We used data from a subset of participants in the Second Australian National Blood Pressure study (n=496) aged ≥65 years who had 24-hour ambulatory blood pressure recordings at study entry (baseline) and then after a median of 2 years while on treatment (follow-up). Weighted day-night systolic BPV was calculated for both baseline and follow-up as a weighted mean of daytime and nighttime blood pressure standard deviations. The annual rate of change in BPV over time was calculated from these BPV estimates. Furthermore, we classified both BPV estimates as high and low based on the baseline median BPV value and then classified BPV changes into stable: low BPV, stable: high BPV, decline: high to low, and increase: low to high. We observed an annual decline (mean±SD: −0.37±1.95; 95% CI, −0.54 to −0.19; P<0.001) in weighted day-night systolic BPV between baseline and follow-up. Having constant stable: high BPV was associated with an increase in all-cause mortality (hazard ratio: 3.03; 95% CI, 1.67–5.52) and cardiovascular mortality (hazard ratio: 3.70; 95% CI, 1.62–8.47) in relation to the stable: low BPV group over a median 8.6 years after the follow-up ambulatory blood pressure monitoring. Similarly, higher risk was observed in the decline: high to low group. Conclusions: Our results demonstrate that in elderly hypertensive patients, average BPV declined over 2 years of follow-up after initiation of antihypertensive therapy, and having higher BPV (regardless of any change) was associated with increased long-term mortality

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)