Explore the vast range of titles available.

Shamil Sunyaev, Chris Cotsapas and colleagues present a joint likelihood framework for determining the statistical evidence of shared genetic effects of overlapping disease-associated loci and expression quantitative trait loci (eQTLs). They find evidence for shared genetic effects at 25% of eQTL–autoimmune disease locus pairs. Most autoimmune-disease-risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene-regulatory activity. GWAS loci are also enriched in expression quantitative trait loci (eQTLs), thus suggesting that most risk variants alter gene expression 1 , 2 . However, because causal variants are difficult to identify, and cis -eQTLs occur frequently, it remains challenging to identify specific instances of disease-relevant changes to gene regulation. Here, we used a novel joint likelihood framework with higher resolution than that of previous methods to identify loci where autoimmune-disease risk and an eQTL are driven by a single shared genetic effect. Using eQTLs from three major immune subpopulations, we found shared effects in only ∼25% of the loci examined. Thus, we show that a fraction of gene-regulatory changes suggest strong mechanistic hypotheses for disease risk, but we conclude that most risk mechanisms are not likely to involve changes in basal gene expression.

Circadian rhythms are known to regulate immune responses in healthy animals, but it is unclear whether they persist during acute illnesses where clock gene expression is disrupted by systemic inflammation. Here we use a genome-wide approach to investigate circadian gene and metabolite expression in the lungs of endotoxemic mice and find that novel cellular and molecular circadian rhythms are elicited in this setting. The endotoxin-specific circadian programme exhibits unique features, including a divergent group of rhythmic genes and metabolites compared with the basal state and a distinct periodicity and phase distribution. At the cellular level, endotoxin treatment also alters circadian rhythms of leukocyte counts within the lung in a bmal1 -dependent manner, such that granulocytes rather than lymphocytes become the dominant oscillating cell type. Our results show that inflammation produces a complex re-organization of cellular and molecular circadian rhythms that are relevant to early events in lung injury. Whether circadian rhythms occur in settings where clock gene expression is suppressed, such as systemic inflammation, is unclear. Here, the authors examine gene expression and metabolites in the lungs of endotoxemic mice and show that inflammation causes changes in circadian rhythms at the cellular and molecular level.

Abstract Rationale Daily high-dose aspirin therapy benefits many patients with aspirin-exacerbated respiratory disease but provides no benefit for aspirin-tolerant patients with asthma. Type 2 inflammation characterizes aspirin-exacerbated respiratory disease. Objectives To determine whether high-dose aspirin therapy changes biomarkers of type 2 inflammation in aspirin-exacerbated respiratory disease. Methods Forty-two subjects with aspirin-exacerbated respiratory disease underwent an aspirin desensitization and were placed on high-dose aspirin (1,300 mg daily). Fifteen aspirin-tolerant subjects with asthma were also placed on high-dose aspirin. Biologic specimens and clinical parameters were collected at baseline and after 8 weeks on aspirin. Urinary eicosanoids, plasma tryptase and cytokine levels, platelet–leukocyte aggregates, and granulocyte transcripts were assessed. Measurements and Main Results Eight weeks of high-dose aspirin decreased nasal symptoms and urinary prostaglandin E metabolite (P < 0.05) and increased urinary leukotriene E4 (P < 0.01) levels in subjects with aspirin-exacerbated respiratory disease, but not in those with aspirin-tolerant asthma. Urinary prostaglandin D2 and thromboxane metabolites decreased in both groups. Only in subjects with aspirin-exacerbated respiratory disease, exhaled nitric oxide (P < 0.05), plasma tryptase (P < 0.01), and blood eosinophil (P < 0.01) and basophil (P < 0.01) counts increased and plasma tryptase correlated with eosinophil counts (Pearson r = 0.514; P < 0.01) on aspirin. After correction for eosinophil counts, aspirin-induced changes in blood granulocyte transcripts did not differ between groups. Aspirin had no effect on platelet–leukocyte aggregates, platelet activation markers, or plasma cytokines in either group. Conclusions High-dose aspirin therapy for 8 weeks paradoxically increases markers of type 2 inflammation in subjects with aspirin-exacerbated respiratory disease, despite reducing nasal symptoms. This effect of aspirin is unique to aspirin-exacerbated respiratory disease and not observed in subjects with aspirin-tolerant asthma.

The molecular and clinical features of a complex disease can be influenced by other diseases affecting the same individual. Understanding disease-disease interactions is therefore crucial for revealing shared molecular mechanisms among diseases and designing effective treatments. Here we introduce Flow Centrality (FC), a network-based approach to identify the genes mediating the interaction between two diseases in a protein-protein interaction network. We focus on asthma and COPD, two chronic respiratory diseases that have been long hypothesized to share common genetic determinants and mechanisms. We show that FC highlights potential mediator genes between the two diseases, and observe similar outcomes when applying FC to 66 additional pairs of related diseases. Further, we perform in vitro perturbation experiments on a widely replicated asthma gene, GSDMB , showing that FC identifies candidate mediators of the interactions between GSDMB and COPD-associated genes. Our results indicate that FC predicts promising gene candidates for further study of disease-disease interactions. Complex diseases often share genetic determinants and symptoms, but the mechanistic basis of disease interactions remains elusive. Here, the authors propose a network topological measure to identify proteins linking complex diseases in the interactome, and identify mediators between COPD and asthma.

Background Childhood asthma is strongly influenced by genetics and is a risk factor for reduced lung function and chronic obstructive pulmonary disease (COPD) in adults. This study investigates self-reported childhood asthma in adult smokers from the COPDGene Study. We hypothesize that childhood asthma is associated with decreased lung function, increased risk for COPD, and that a genome-wide association study (GWAS) will show association with established asthma variants. Methods We evaluated current and former smokers ages 45–80 of non-Hispanic white (NHW) or African American (AA) race. Childhood asthma was defined by self-report of asthma, diagnosed by a medical professional, with onset at < 16 years or during childhood. Subjects with a history of childhood asthma were compared to those who never had asthma based on lung function, development of COPD, and genetic variation. GWAS was performed in NHW and AA populations, and combined in meta-analysis. Two sets of established asthma SNPs from published literature were examined for association with childhood asthma. Results Among 10,199 adult smokers, 730 (7%) reported childhood asthma and 7493 (73%) reported no history of asthma. Childhood asthmatics had reduced lung function and increased risk for COPD (OR 3.42, 95% CI 2.81–4.18). Genotype data was assessed for 8031 subjects. Among NHWs, 391(7%) had childhood asthma, and GWAS identified one genome-wide significant association in KIAA1958 (rs59289606, p  = 4.82 × 10 − 8 ). Among AAs, 339 (12%) had childhood asthma. No SNPs reached genome-wide significance in the AAs or in the meta-analysis combining NHW and AA subjects; however, potential regions of interest were identified. Established asthma SNPs were examined, seven from the NHGRI-EBI database and five with genome-wide significance in the largest pediatric asthma GWAS. Associations were found in the current childhood asthma GWAS with known asthma loci in IL1RL1 , IL13 , LINC01149 , near GSDMB , and in the C11orf30-LRRC32 region (Bonferroni adjusted p  < 0.05 for all comparisons). Conclusions Childhood asthmatics are at increased risk for COPD. Defining asthma by self-report is valid in populations at risk for COPD, identifying subjects with clinical and genetic characteristics known to associate with childhood asthma. This has potential to improve clinical understanding of asthma-COPD overlap (ACO) and enhance future research into ACO-specific treatment regimens. Trial registration ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008).

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible. We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study. We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations). Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.

Severe viral pneumonia caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by a hyperinflammatory state typified by elevated circulating pro-inflammatory cytokines, frequently leading to potentially lethal vascular complications including thromboembolism, disseminated intracellular coagulopathy and vasculitis. Though endothelial infection and subsequent endothelial damage have been described in patients with fatal COVID-19, the mechanism by which this occurs remains elusive, particularly given that, under naïve conditions, pulmonary endothelial cells demonstrate minimal cell surface expression of the SARS-CoV-2 binding receptor ACE2. Herein we describe SARS-CoV-2 infection of the pulmonary endothelium in postmortem lung samples from individuals who died of COVID-19, demonstrating both heterogeneous ACE2 expression and endothelial damage. In primary endothelial cell cultures, we show that SARS-CoV-2 infection is dependent on the induction of ACE2 protein expression and that this process is facilitated by type 1 interferon-alpha (IFNα) or -beta(β)—two of the main anti-viral cytokines induced in severe SARS-CoV-2 infection—but not significantly by other cytokines (including interleukin 6 and interferon γ/λ). Our findings suggest that the stereotypical anti-viral interferon response may paradoxically facilitate the propagation of COVID-19 from the respiratory epithelium to the vasculature, raising concerns regarding the use of exogenous IFNα/β in the treatment of patients with COVID-19.

Abstract Rationale The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. Objectives We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease. Methods Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes. Measurements and Main Results Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 × 10−6) and hospitalization (P = 0.01), respectively. Conclusions There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma.

Patients with short telomere syndromes and pulmonary fibrosis have increased complications after lung transplant. However, the more general impact of donor and recipient telomere length in lung transplant has not been well characterized. This was an observational cohort study of patients who received lung transplant at a single center between January 1st 2012 and January 31st 2015. Relative donor lymphocyte telomere length was measured and classified into long (third tertile) and short (other tertiles). Relative recipient lung telomere length was measured and classified into short (first tertile) and long (other tertiles). Outcome data included survival, need for modification of immunosuppression, liver or kidney injury, cytomegalovirus reactivation, and acute rejection. Recipient lung tissue telomere lengths were measured for 54 of the 79 patients (68.3%) who underwent transplant during the study period. Donor lymphocyte telomeres were measured for 45 (83.3%) of these recipients. Neither long donor telomere length (hazard ratio [HR] = 0.58, 95% confidence interval [CI], 0.12-2.85, p = 0.50) nor short recipient telomere length (HR = 1.01, 95% CI = 0.50-2.05, p = 0.96) were associated with adjusted survival following lung transplant. Recipients with short telomeres were less likely to have acute cellular rejection (23.5% vs. 58.8%, p = 0.02) but were not more likely to have other organ dysfunction. In this small cohort, neither long donor lymphocyte telomeres nor short recipient lung tissue telomeres were associated with adjusted survival after lung transplantation. Larger studies are needed to confirm these findings.