Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis.
Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and ...assess their stability after 12 to 18 months. A further aim was to evaluate clusters’ robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma.
In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis β-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma.
Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values < .05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments.
Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.
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, molecules that inhibit immune cell activity following binding to glycosylated cell-surface antigens, are emerging as attractive targets for cancer immunotherapy. Defining biologically relevant ...ligands that bind and activate such receptors, however, has historically been a significant challenge. Here, we present a CRISPRi genomic screening strategy that allowed unbiased identification of the key genes required for cell-surface presentation of glycan ligands on leukemia cells that bind the glyco-immune checkpoint receptors Siglec-7 and Siglec-9. This approach revealed a selective interaction between Siglec-7 and the mucin-type glycoprotein CD43. Further work identified a specific N-terminal glycopeptide region of CD43 containing clusters of disialylated O-glycan tetrasaccharides that form specific Siglec-7 binding motifs. Knockout or blockade of CD43 in leukemia cells relieves Siglec-7-mediated inhibition of immune killing activity. This work identifies a potential target for immune checkpoint blockade therapy and represents a generalizable approach to dissection of glycan-receptor interactions in living cells.
Abstract
We report the discovery of six ultra-faint Milky Way satellites identified through matched-filter searches conducted using Dark Energy Camera (DECam) data processed as part of the second ...data release of the DECam Local Volume Exploration (DELVE) survey. Leveraging deep Gemini/GMOS-N imaging (for four candidates) as well as follow-up DECam imaging (for two candidates), we characterize the morphologies and stellar populations of these systems. We find that these candidates all share faint absolute magnitudes (
M
V
≥ −3.2 mag) and old, metal-poor stellar populations (
τ
> 10 Gyr, Fe/H < −1.4 dex). Three of these systems are more extended (
r
1/2
> 15 pc), while the other three are compact (
r
1/2
< 10 pc). From these properties, we infer that the former three systems (Boötes V, Leo Minor I, and Virgo II) are consistent with ultra-faint dwarf galaxy classifications, whereas the latter three (DELVE 3, DELVE 4, and DELVE 5) are likely ultra-faint star clusters. Using data from the Gaia satellite, we confidently measure the proper motion of Boötes V, Leo Minor I, and DELVE 4, and tentatively detect a proper-motion signal from DELVE 3 and DELVE 5; no signal is detected for Virgo II. We use these measurements to explore possible associations between the newly discovered systems and the Sagittarius dwarf spheroidal, the Magellanic Clouds, and the Vast Polar Structure, finding several plausible associations. Our results offer a preview of the numerous ultra-faint stellar systems that will soon be discovered by the Vera C. Rubin Observatory and highlight the challenges of classifying the faintest stellar systems.
Abstract
We report the discovery of Pegasus IV, an ultra-faint dwarf galaxy found in archival data from the Dark Energy Camera processed by the DECam Local Volume Exploration Survey. Pegasus IV is a ...compact, ultra-faint stellar system (
r
1
/
2
=
41
−
6
+
8
pc;
M
V
= −4.25 ± 0.2 mag) located at a heliocentric distance of
90
−
6
+
4
kpc
. Based on spectra of seven nonvariable member stars observed with Magellan/IMACS, we confidently resolve Pegasus IV’s velocity dispersion, measuring
σ
v
=
3.3
−
1.1
+
1.7
km s
−1
(after excluding three velocity outliers); this implies a mass-to-light ratio of
M
1
/
2
/
L
V
,
1
/
2
=
167
−
99
+
224
M
⊙
/
L
⊙
for the system. From the five stars with the highest signal-to-noise spectra, we also measure a systemic metallicity of Fe/H =
−
2.63
−
0.30
+
0.26
dex, making Pegasus IV one of the most metal-poor ultra-faint dwarfs. We tentatively resolve a nonzero metallicity dispersion for the system. These measurements provide strong evidence that Pegasus IV is a dark-matter-dominated dwarf galaxy, rather than a star cluster. We measure Pegasus IV’s proper motion using data from Gaia Early Data Release 3, finding (
μ
α
*
,
μ
δ
) = (0.33 ± 0.07, −0.21 ± 0.08) mas yr
−1
. When combined with our measured systemic velocity, this proper motion suggests that Pegasus IV is on an elliptical, retrograde orbit, and is currently near its orbital apocenter. Lastly, we identify three potential RR Lyrae variable stars within Pegasus IV, including one candidate member located more than 10 half-light radii away from the system’s centroid. The discovery of yet another ultra-faint dwarf galaxy strongly suggests that the census of Milky Way satellites is still incomplete, even within 100 kpc.
A recent genome-wide association study reported association between schizophrenia and the ZNF804A gene on chromosome 2q32.1. We attempted to replicate these findings in our Irish Case-Control Study ...of Schizophrenia (ICCSS) sample (N=1021 cases, 626 controls). Following consultation with the original investigators, we genotyped three of the most promising single-nucleotide polymorphisms (SNPs) from the Cardiff study. We replicate association with rs1344706 (trend test one-tailed P=0.0113 with the previously associated A allele) in ZNF804A. We detect no evidence of association with rs6490121 in NOS1 (one-tailed P=0.21), and only a trend with rs9922369 in RGRIP1L (one-tailed P=0.0515). On the basis of these results, we completed genotyping of 11 additional linkage disequilibrium-tagging SNPs in ZNF804A. Of 12 SNPs genotyped, 11 pass quality control criteria and 4 are nominally associated, with our most significant evidence of association at rs7597593 (P=0.0013) followed by rs1344706. We observe no evidence of differential association in ZNF804A on the basis of family history or sex of case. The associated SNP rs1344706 lies in approximately 30 bp of conserved mammalian sequence, and the associated A allele is predicted to maintain binding sites for the brain-expressed transcription factors MYT1l and POU3F1/OCT-6. In controls, expression is significantly increased from the A allele of rs1344706 compared with the C allele. Expression is increased in schizophrenic cases compared with controls, but this difference does not achieve statistical significance. This study replicates the original reported association of ZNF804A with schizophrenia and suggests that there is a consistent link between the A allele of rs1344706, increased expression of ZNF804A and risk for schizophrenia.
Electronic noses (eNoses) are emerging point-of-care tools that may help in the subphenotyping of chronic respiratory diseases such as asthma.
We aimed to investigate whether eNoses can classify ...atopy in pediatric and adult patients with asthma.
Participants with asthma and/or wheezing from 4 independent cohorts were included; BreathCloud participants (n = 429), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adults (n = 96), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes pediatric participants (n = 100), and Pharmacogenetics of Asthma Medication in Children: Medication with Anti-Inflammatory Effects 2 participants (n = 30). Atopy was defined as a positive skin prick test result (≥3 mm) and/or a positive specific IgE level (≥0.35 kU/L) for common allergens. Exhaled breath profiles were measured by using either an integrated eNose platform or the SpiroNose. Data were divided into 2 training and 2 validation sets according to the technology used. Supervised data analysis involved the use of 3 different machine learning algorithms to classify patients with atopic versus nonatopic asthma with reporting of areas under the receiver operating characteristic curves as a measure of model performance. In addition, an unsupervised approach was performed by using a bayesian network to reveal data-driven relationships between eNose volatile organic compound profiles and asthma characteristics.
Breath profiles of 655 participants (n = 601 adults and school-aged children with asthma and 54 preschool children with wheezing 68.2% of whom were atopic) were included in this study. Machine learning models utilizing volatile organic compound profiles discriminated between atopic and nonatopic participants with areas under the receiver operating characteristic curves of at least 0.84 and 0.72 in the training and validation sets, respectively. The unsupervised approach revealed that breath profiles classifying atopy are not confounded by other patient characteristics.
eNoses accurately detect atopy in individuals with asthma and wheezing in cohorts with different age groups and could be used in asthma phenotyping.
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Recent analysis of the second data release of Gaia has revealed a number of new stellar streams surrounding the Milky Way. It has been suggested that one of these streams, Gjöll, is associated with ...the globular cluster NGC 3201, but thus far the association has only been based on kinematics of the stream stars. In this work we identify five likely stream members in the Gaia data that are bright enough for high-resolution spectroscopic follow-up with the Harlan J. Smith telescope at McDonald Observatory. One star is ruled out as a member based on its radial velocity. Abundance analysis of the remaining four kinematic members reveals a good chemical match to NGC 3201 for two of the stars, driven by their similar Al and -element abundances. Of the remaining two, one shows no chemical similarity to NGC 3201 and is likely an unassociated Milky Way halo field star, while the other exhibits a similar Al abundance but has somewhat lower -element abundances. The chemical tagging of stars in the Gjöll stream to NGC 3201 confirms this association and provides direct proof of the hierarchical formation of the Milky Way.
Abstract
We report the discovery of a new ultra-faint stellar system found near the Magellanic Clouds in the DECam Local Volume Exploration Survey. This new system, DELVE J0155−6815 (DELVE 2), is ...located at a heliocentric distance of
D
⊙
= 71 ± 4 kpc, which places it at a 3D physical separation of 12 ± 3 kpc from the center of the Small Magellanic Cloud and
from the center of the Large Magellanic Cloud (LMC). DELVE 2 is identified as a resolved overdensity of old (
τ
> 13.3 Gyr) and metal-poor (
dex) stars with a projected half-light radius of
and an absolute magnitude of
. The size and luminosity of DELVE 2 are consistent with both the population of recently discovered ultra-faint globular clusters and the smallest ultra-faint dwarf galaxies. However, its photometrically derived age and metallicity would place it among the oldest and most metal-poor globular clusters in the Magellanic system. In the absence of spectroscopic measurements of the system’s metallicity dispersion and internal kinematics, we are unable to conclusively classify this system at this time. DELVE 2 is detected in
Gaia
DR2 with a clear proper-motion signal, with multiple blue horizontal-branch stars near the centroid of the system with proper motions consistent with the systemic mean. We measure the system proper motion to be
=
mas yr
−1
. We compare the spatial position and proper motion of DELVE 2 with simulations of the accreted satellite population of the LMC and find that it is very likely to be associated with the LMC.
The “sphingosin” backbone of sphingolipids was so named by J.L.W. Thudichum in 1884 for its enigmatic (“Sphinx-like”) properties. Although still an elusive class of lipids, research on the ...involvement of sphingolipids in the signal transduction pathways that mediate cell growth, differentiation, multiple cell functions, and cell death has been rapidly expanding our understanding of these compounds. In addition to the newly discovered role of ceramide as an intracellular second messenger for tumor necrosis factor-α, IL-1β, and other cytokines, sphingosine, sphingosine-1-phosphate, and other sphingolipid metabolites have recently been demonstrated to modulate cellular calcium homeostasis and cell proliferation. Perturbation of sphingolipid metabolism using synthetic and naturally occurring inhibitors of key enzymes of the biosynthetic pathways is aiding the characterization of these processes; for examples, inhibition of cerebroside synthase has indicated a role for ceramide in cellular stress responses including heat shock, and inhibition of ceramide synthase (by fumonisins) has revealed the role of disruption of sphingolipid metabolism in several animal diseases. Fumonisins are currently the focus of a FDA long-term tumor study. This review summarizes recent research on (i) the role of sphingolipids as important components of the diet, (ii) the role of sphingoid base metabolites and the ceramide cycle in expression of genes regulating cell growth, differentiation, and apoptosis, (iii) the use of cerebroside synthase inhibitors as tools for understanding the role of sphingolipids as mediators of cell cycle progression, renal disease, and stress responses, and (iv) the involvement of disrupted sphingolipid metabolism in animal disease and cellular deregulation associated with exposure to inhibitors of ceramide synthase and serine palmitoyltransferase, key enzymes inde novosphingolipid biosynthesis. These findings illustrate how an understanding of the function of sphingolipids can help solve questions in toxicology and this is undoubtedly only the beginning of this story.
We propose to combine the benefits of flexible parametric survival modeling and regularization to improve risk prediction modeling in the context of time‐to‐event data. Thereto, we introduce ridge, ...lasso, elastic net, and group lasso penalties for both log hazard and log cumulative hazard models. The log (cumulative) hazard in these models is represented by a flexible function of time that may depend on the covariates (i.e., covariate effects may be time‐varying). We show that the optimization problem for the proposed models can be formulated as a convex optimization problem and provide a user‐friendly R implementation for model fitting and penalty parameter selection based on cross‐validation. Simulation study results show the advantage of regularization in terms of increased out‐of‐sample prediction accuracy and improved calibration and discrimination of predicted survival probabilities, especially when sample size was relatively small with respect to model complexity. An applied example illustrates the proposed methods. In summary, our work provides both a foundation for and an easily accessible implementation of regularized parametric survival modeling and suggests that it improves out‐of‐sample prediction performance.
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