Network Analysis Reveals Protein Modules Associated with Childhood Respiratory Diseases.

Background: The first year of life is a period of rapid immune development that can impact health trajectories and the risk of developing respiratory-related diseases, such as asthma, recurrent infections, and eczema. However, the biology underlying subsequent disease development remains unknown. Methods: Using weighted gene correlation network analysis (WGCNA), we derived modules of highly correlated immune-related proteins in plasma samples from children at age 1 year (N=294) from the Vitamin D Antenatal Asthma Reduction Trial (VDAART). We applied regression analyses to assess relationships between protein modules and development of childhood respiratory diseases up to age 6 years. We then characterized genomic, environmental, and metabolomic factors associated with modules. Results: WGCNA identified four protein modules at age 1 year associated with incidence of childhood asthma and/or recurrent wheeze (Padj range: 0.02-0.03), respiratory infections (Padj range: 6.3×10-9-2.9×10-6), and eczema (Padj=0.01) by age 6 years; three modules were associated with at least one environmental exposure (Padj range: 2.8×10-10-0.03) and disrupted metabolomic pathway(s) (Padj range: 2.8×10-6-0.04). No genome-wide SNPs were identified as significant genetic risk factors for any protein module. Relationships between protein modules with clinical, environmental, and 'omic factors were temporally sensitive and could not be recapitulated in protein profiles at age 6 years. Conclusion: These findings suggested protein profiles as early as age 1 year predicted development of respiratory-related diseases through age 6 and were associated with changes in pathways related to amino acid and energy metabolism. These may inform new strategies to identify vulnerable individuals based on immune protein profiling.

Metabolomics of IgE-Mediated Food Allergy and Oral Immunotherapy Outcomes based on Metabolomic Profiling.

Background: The immunometabolic mechanisms underlying variable responses to oral immunotherapy (OIT) in patients with IgE-mediated food allergy are unknown. Objective: To identify novel pathways associated with tolerance in food allergy, we used metabolomic profiling to find pathways important for food allergy in multi-ethnic cohorts and responses to OIT. Methods: Untargeted plasma metabolomics data were generated from the VDAART healthy infant cohort (N=384), a Costa Rican cohort of children with asthma (N=1040), and a peanut OIT trial (N=20) evaluating sustained unresponsiveness (SU, protection that lasts after therapy) versus transient desensitization (TD, protection that ends immediately afterwards). Generalized linear regression modeling and pathway enrichment analysis identified metabolites associated with food allergy and OIT outcomes. Results: Compared with unaffected children, those with food allergy were more likely to have metabolomic profiles with altered histidines and increased bile acids. Eicosanoids (e.g., arachidonic acid derivatives) (q=2.4×10 -20 ) and linoleic acid derivatives (q=3.8×10 -5 ) pathways decreased over time on OIT. Comparing SU versus TD revealed differing concentrations of bile acids (q=4.1×10 -8 ), eicosanoids (q=7.9×10 -7 ), and histidine pathways (q=0.015). In particular, the bile acid lithocholate (4.97[1.93,16.14], p=0.0027), the eicosanoid leukotriene B4 (3.21[1.38,8.38], p=0.01), and the histidine metabolite urocanic acid (22.13[3.98,194.67], p=0.0015) were higher in SU. Conclusions: We observed distinct profiles of bile acids, histidines, and eicosanoids that vary among patients with food allergy, over time on OIT and between SU and TD. Participants with SU had higher levels of metabolites such as lithocholate and urocanic acid, which have immunomodulatory roles in key T-cell subsets, suggesting potential mechanisms of tolerance in immunotherapy. Key Messages: - Compared with unaffected controls, children with food allergy demonstrated higher levels of bile acids and distinct histidine/urocanic acid profiles, suggesting a potential role of these metabolites in food allergy. - In participants receiving oral immunotherapy for food allergy, those who were able to maintain tolerance-even after stopping therapyhad lower overall levels of bile acid and histidine metabolites, with the exception of lithocholic acid and urocanic acid, two metabolites that have roles in T cell differentiation that may increase the likelihood of remission in immunotherapy. Capsule summary: This is the first study of plasma metabolomic profiles of responses to OIT in individuals with IgE-mediated food allergy. Identification of immunomodulatory metabolites in allergic tolerance may help identify mechanisms of tolerance and guide future therapeutic development.

Urinary eicosanoid levels in early life and risk of atopic disease in childhood.

BACKGROUND: Eicosanoids are lipid mediators including thromboxanes (TXs), prostaglandins (PGs), and leukotrienes with a pathophysiological role in established atopic disease. However, their role in the inception of disease is unclear. This study aimed to investigate the association between urinary eicosanoids in early life and development of atopic disease. METHODS: This study quantified the levels of 21 eicosanoids in urine from children from the COPSAC2010 (Copenhagen Prospective Studies on Asthma in Childhood 2010) (age 1 year, n = 450) and VDAART (Vitamin D Antenatal Asthma Reduction Trial) (age 3 years, n = 575) mother-child cohorts and analyzed the associations with development of wheeze/asthma, atopic dermatitis, and biomarkers of type-2 inflammation, applying false discovery rate of 5% (FDR5%) multiple testing correction. RESULTS: In both cohorts, analyses adjusted for environmental determinants showed that higher TXA2 eicosanoids in early life were associated with increased risk of developing atopic dermatitis (P < FDR5%) and type-2 inflammation (P < .05). In VDAART, lower PGE2 and PGI2 eicosanoids and higher isoprostanes were also associated with increased risk of atopic dermatitis (P < FDR5%). For wheeze/asthma, analyses in COPSAC2010 showed that lower isoprostanes and PGF2 eicosanoids and higher PGD2 eicosanoids at age 1 year associated with an increased risk at age 1-10 years (P < .05), whereas analyses in VDAART showed that lower PGE2 and higher TXA2 eicosanoids at age 3 years associated with an increased risk at 6 years (P < FDR5%). CONCLUSIONS: This study suggests that early life perturbations in the eicosanoid metabolism are present before the onset of atopic disease in childhood, which provides pathophysiological insight in the inception of atopic diseases.

Family history as the strongest predictor of aortic and peripheral aneurysms in patients with intracranial aneurysms.

OBJECTIVE: Intracranial aneurysms (IA) and aortic aneurysms (AA) are both abnormal dilations of arteries with familial predisposition and have been proposed to share co-prevalence and pathophysiology. Associations of IA and non-aortic peripheral aneurysms are less well-studied. The goal of the study was to understand the patterns of aortic and peripheral (extracranial) aneurysms in patients with IA, and risk factors associated with the development of these aneurysms. METHODS: 4701 patients were included in our retrospective analysis of all patients with intracranial aneurysms at our institution over the past 26 years. Patient demographics, comorbidities, and aneurysmal locations were analyzed. Univariate and multivariate analyses were performed to study associations with and without extracranial aneurysms. RESULTS: A total of 3.4% of patients (161 of 4701) with IA had at least one extracranial aneurysm. 2.8% had thoracic or abdominal aortic aneurysms. Age, male sex, hypertension, coronary artery disease, history of ischemic cerebral infarction, connective tissues disease, and family history of extracranial aneurysms in a 1st degree relative were associated with the presence of extracranial aneurysms and a higher number of extracranial aneurysms. In addition, family history of extracranial aneurysms in a second degree relative is associated with the presence of extracranial aneurysms and atrial fibrillation is associated with a higher number of extracranial aneurysms. CONCLUSION: Significant comorbidities are associated with extracranial aneurysms in patients with IA. Family history of extracranial aneurysms has the strongest association and suggests that IA patients with a family history of extracranial aneurysms may benefit from screening.

Consistent Multi-Omic Relationships Uncover Molecular Basis of Pediatric Asthma IgE Regulation.

Serum total immunoglobulin E levels (total IgE) capture the state of the immune system in relation to allergic sensitization. High levels are associated with airway obstruction and poor clinical outcomes in pediatric asthma. Inconsistent patient response to anti-IgE therapies motivates discovery of molecular mechanisms underlying serum IgE level differences in children with asthma. To uncover these mechanisms using complementary metabolomic and transcriptomic data, abundance levels of 529 named metabolites and expression levels of 22,772 genes were measured among children with asthma in the Childhood Asthma Management Program (CAMP, N=564) and the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS, N=309) via the TOPMed initiative. Gene-metabolite associations dependent on IgE were identified within each cohort using multivariate linear models and were interpreted in a biochemical context using network topology, pathway and chemical enrichment, and representation within reactions. A total of 1,617 total IgE-dependent gene-metabolite associations from GACRS and 29,885 from CAMP met significance cutoffs. Of these, glycine and guanidinoacetic acid (GAA) were associated with the most genes in both cohorts, and the associations represented reactions central to glycine, serine, and threonine metabolism and arginine and proline metabolism. Pathway and chemical enrichment analysis further highlighted additional related pathways of interest. The results of this study suggest that GAA may modulate total IgE levels in two independent pediatric asthma cohorts with different characteristics, supporting the use of L-Arginine as a potential therapeutic for asthma exacerbation. Other potentially new targetable pathways are also uncovered.

The Asthma Risk Gene, GSDMB, Promotes Mitochondrial DNA-induced ISGs Expression.

Released mitochondrial DNA (mtDNA) in cells activates cGAS-STING pathway, which induces expression of interferon-stimulated genes (ISGs) and thereby promotes inflammation, as frequently seen in asthmatic airways. However, whether the genetic determinant, Gasdermin B (GSDMB), the most replicated asthma risk gene, regulates this pathway remains unknown. We set out to determine whether and how GSDMB regulates mtDNA-activated cGAS-STING pathway and subsequent ISGs induction in human airway epithelial cells. Using qPCR, ELISA, native polyacrylamide gel electrophoresis, co-immunoprecipitation and immunofluorescence assays, we evaluated the regulation of GSDMB on cGAS-STING pathway in both BEAS-2B cells and primary normal human bronchial epithelial cells (nHBEs). mtDNA was extracted in plasma samples from human asthmatics and the correlation between mtDNA levels and eosinophil counts was analyzed. GSDMB is significantly associated with RANTES expression in asthmatic nasal epithelial brushing samples from the Genes-environments and Admixture in Latino Americans (GALA) II study. Over-expression of GSDMB promotes DNA-induced IFN and ISGs expression in bronchial epithelial BEAS-2B cells and nHBEs. Conversely, knockout of GSDMB led to weakened induction of interferon (IFNs) and ISGs in BEAS-2B cells. Mechanistically, GSDMB interacts with the C-terminus of STING, promoting the translocation of STING to Golgi, leading to the phosphorylation of IRF3 and induction of IFNs and ISGs. mtDNA copy number in serum from asthmatics was significantly correlated with blood eosinophil counts especially in male subjects. GSDMB promotes the activation of mtDNA and poly (dA:dT)-induced activation of cGAS-STING pathway in airway epithelial cells, leading to enhanced induction of ISGs.

Vitamin D constrains inflammation by modulating the expression of key genes on Chr17q12-21.1.

Vitamin D possesses immunomodulatory functions and vitamin D deficiency has been associated with the rise in chronic inflammatory diseases, including asthma (Litonjua and Weiss, 2007). Vitamin D supplementation studies do not provide insight into the molecular genetic mechanisms of vitamin D-mediated immunoregulation. Here, we provide evidence for vitamin D regulation of two human chromosomal loci, Chr17q12-21.1 and Chr17q21.2, reliably associated with autoimmune and chronic inflammatory diseases. We demonstrate increased vitamin D receptor (Vdr) expression in mouse lung CD4+ Th2 cells, differential expression of Chr17q12-21.1 and Chr17q21.2 genes in Th2 cells based on vitamin D status and identify the IL-2/Stat5 pathway as a target of vitamin D signaling. Vitamin D deficiency caused severe lung inflammation after allergen challenge in mice that was prevented by long-term prenatal vitamin D supplementation. Mechanistically, vitamin D induced the expression of the Ikzf3-encoded protein Aiolos to suppress IL-2 signaling and ameliorate cytokine production in Th2 cells. These translational findings demonstrate mechanisms for the immune protective effect of vitamin D in allergic lung inflammation with a strong molecular genetic link to the regulation of both Chr17q12-21.1 and Chr17q21.2 genes and suggest further functional studies and interventional strategies for long-term prevention of asthma and other autoimmune disorders.

Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning.

INTRODUCTION: Spirometry is the gold standard for COPD diagnosis and severity determination, but is technique-dependent, nonspecific, and requires administration by a trained healthcare professional. There is a need for a fast, reliable, and precise alternative diagnostic test. This study's aim was to use interpretable machine learning to diagnose COPD and assess severity using 75-second carbon dioxide (CO2) breath records captured with TidalSense's N-TidalTM capnometer. METHOD: For COPD diagnosis, machine learning algorithms were trained and evaluated on 294 COPD (including GOLD stages 1-4) and 705 non-COPD participants. A logistic regression model was also trained to distinguish GOLD 1 from GOLD 4 COPD with the output probability used as an index of severity. RESULTS: The best diagnostic model achieved an AUROC of 0.890, sensitivity of 0.771, specificity of 0.850 and positive predictive value (PPV) of 0.834. Evaluating performance on all test capnograms that were confidently ruled in or out yielded PPV of 0.930 and NPV of 0.890. The severity determination model yielded an AUROC of 0.980, sensitivity of 0.958, specificity of 0.961 and PPV of 0.958 in distinguishing GOLD 1 from GOLD 4. Output probabilities from the severity determination model produced a correlation of 0.71 with percentage predicted FEV1. CONCLUSION: The N-TidalTM device could be used alongside interpretable machine learning as an accurate, point-of-care diagnostic test for COPD, particularly in primary care as a rapid rule-in or rule-out test. N-TidalTM also could be effective in monitoring disease progression, providing a possible alternative to spirometry for disease monitoring.

Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma.

BACKGROUND: Lung function trajectories (LFTs) have been shown to be an important measure of long-term health in asthma. While there is a growing body of metabolomic studies on asthma status and other phenotypes, there are no prospective studies of the relationship between metabolomics and LFTs or their genomic determinants. METHODS: We utilized ordinal logistic regression to identify plasma metabolite principal components associated with four previously-published LFTs in children from the Childhood Asthma Management Program (CAMP) (n = 660). The top significant metabolite principal component (PCLF) was evaluated in an independent cross-sectional child cohort, the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n = 1151) and evaluated for association with spirometric measures. Using meta-analysis of CAMP and GACRS, we identified associations between PCLF and microRNA, and SNPs in their target genes. Statistical significance was determined using an false discovery rate-adjusted Q-value. FINDINGS: The top metabolite principal component, PCLF, was significantly associated with better LFTs after multiple-testing correction (Q-value = 0.03). PCLF is composed of the urea cycle, caffeine, corticosteroid, carnitine, and potential microbial (secondary bile acid, tryptophan, linoleate, histidine metabolism) metabolites. Higher levels of PCLF were also associated with increases in lung function measures and decreased circulating neutrophil percentage in both CAMP and GACRS. PCLF was also significantly associated with microRNA miR-143-3p, and SNPs in three miR-143-3p target genes; CCZ1 (P-value = 2.6 × 10-5), SLC8A1 (P-value = 3.9 × 10-5); and TENM4 (P-value = 4.9 × 10-5). INTERPRETATION: This study reveals associations between metabolites, miR-143-3p and LFTs in children with asthma, offering insights into asthma physiology and possible interventions to enhance lung function and long-term health. FUNDING: Molecular data for CAMP and GACRS via the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI).

Gasdermin B, an asthma-susceptibility gene, promotes MAVS-TBK1 signalling and airway inflammation.

RATIONALE: Respiratory virus-induced inflammation is the leading cause of asthma exacerbation, frequently accompanied by induction of interferon-stimulated genes (ISGs). How asthma-susceptibility genes modulate cellular response upon viral infection by fine-tuning ISG induction and subsequent airway inflammation in genetically susceptible asthma patients remains largely unknown. OBJECTIVES: To decipher the functions of gasdermin B (encoded by GSDMB) in respiratory virus-induced lung inflammation. METHODS: In two independent cohorts, we analysed expression correlation between GSDMB and ISG s. In human bronchial epithelial cell line or primary bronchial epithelial cells, we generated GSDMB-overexpressing and GSDMB-deficient cells. A series of quantitative PCR, ELISA and co-immunoprecipitation assays were performed to determine the function and mechanism of GSDMB for ISG induction. We also generated a novel transgenic mouse line with inducible expression of human unique GSDMB gene in airway epithelial cells and infected the mice with respiratory syncytial virus to determine the role of GSDMB in respiratory syncytial virus-induced lung inflammation in vivo. RESULTS: GSDMB is one of the most significant asthma-susceptibility genes at 17q21 and acts as a novel RNA sensor, promoting mitochondrial antiviral-signalling protein (MAVS)-TANK binding kinase 1 (TBK1) signalling and subsequent inflammation. In airway epithelium, GSDMB is induced by respiratory viral infections. Expression of GSDMB and ISGs significantly correlated in respiratory epithelium from two independent asthma cohorts. Notably, inducible expression of human GSDMB in mouse airway epithelium led to enhanced ISGs induction and increased airway inflammation with mucus hypersecretion upon respiratory syncytial virus infection. CONCLUSIONS: GSDMB promotes ISGs expression and airway inflammation upon respiratory virus infection, thereby conferring asthma risk in risk allele carriers.

Machine Learning Prediction of Treatment Response to Inhaled Corticosteroids in Asthma.

BACKGROUND: Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma. METHODS: The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest. RESULTS: The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independent test cohort, and the random forest model achieved an AUC of 0.74 (95% CI 0.70-0.78; sensitivity: 0.70; specificity: 0.68). The genes contributing to the prediction of ICS response included those associated with ICS responses in asthma (TPSAB1, FBXL16), asthma symptoms and severity (ABCA7, CNN2, PTRN3, and BSG/CD147), airway remodeling (ELANE, FSTL3), mucin production (GAL3ST), leukotriene synthesis (GPX4), allergic asthma (ZFPM1, SBNO2), and others. CONCLUSIONS: An accurate risk prediction of ICS response can be obtained using machine learning methods, with the potential to inform personalized treatment decisions. Further studies are needed to examine if the integration of richer phenotype data could improve risk prediction.

Circulating miRNAs associate with historical childhood asthma hospitalization in different serum vitamin D groups.

BACKGROUND: Vitamin D may help to alleviate asthma exacerbation because of its anti-inflammation effect, but the evidence is inconsistent in childhood asthma. MiRNAs are important mediators in asthma pathogenesis and also excellent non-invasive biomarkers. We hypothesized that circulating miRNAs are associated with asthma exacerbation and modified by vitamin D levels. METHODS: We sequenced baseline serum miRNAs from 461 participants in the Childhood Asthma Management Program (CAMP). Logistic regression was used to associate miRNA expression with asthma exacerbation through interaction analysis first and then stratified by vitamin D insufficient and sufficient groups. Microarray from lymphoblastoid B-cells (LCLs) treated by vitamin D or sham of 43 subjects in CAMP were used for validation in vitro. The function of miRNAs was associated with gene modules by weighted gene co-expression network analysis (WGCNA). RESULTS: We identified eleven miRNAs associated with asthma exacerbation with vitamin D effect modification. Of which, five were significant in vitamin D insufficient group and nine were significant in vitamin D sufficient group. Six miRNAs, including hsa-miR-143-3p, hsa-miR-192-5p, hsa-miR-151a-5p, hsa-miR-24-3p, hsa-miR-22-3p and hsa-miR-451a were significantly associated with gene modules of immune-related functions, implying miRNAs may mediate vitamin D effect on asthma exacerbation through immune pathways. In addition, hsa-miR-143-3p and hsa-miR-451a are potential predictors of childhood asthma exacerbation at different vitamin D levels. CONCLUSIONS: miRNAs are potential mediators of asthma exacerbation and their effects are directly impacted by vitamin D levels.

Fast computation of the eigensystem of genomic similarity matrices.

The computation of a similarity measure for genomic data is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases due to confounding by population stratification, for instance in linear regressions. However, the calculation of both a similarity matrix and its singular value decomposition (SVD) are computationally intensive. The contribution of this article is threefold. First, we demonstrate that the calculation of three matrices (called the covariance matrix, the weighted Jaccard matrix, and the genomic relationship matrix) can be reformulated in a unified way which allows for the application of a randomized SVD algorithm, which is faster than the traditional computation. The fast SVD algorithm we present is adapted from an existing randomized SVD algorithm and ensures that all computations are carried out in sparse matrix algebra. The algorithm only assumes that row-wise and column-wise subtraction and multiplication of a vector with a sparse matrix is available, an operation that is efficiently implemented in common sparse matrix packages. An exception is the so-called Jaccard matrix, which does not have a structure applicable for the fast SVD algorithm. Second, an approximate Jaccard matrix is introduced to which the fast SVD computation is applicable. Third, we establish guaranteed theoretical bounds on the accuracy (in [Formula: see text] norm and angle) between the principal components of the Jaccard matrix and the ones of our proposed approximation, thus putting the proposed Jaccard approximation on a solid mathematical foundation, and derive the theoretical runtime of our algorithm. We illustrate that the approximation error is low in practice and empirically verify the theoretical runtime scalings on both simulated data and data of the 1000 Genome Project.

Preschool impulse oscillometry predicts active asthma and impaired lung function at school age.

BACKGROUND: Asthmatic symptoms often start during early childhood. Impulse oscillometry (IOS) is feasible in preschool children who may be unable to reliably perform spirometry measurements. OBJECTIVE: We sought to evaluate the use of IOS in a multicenter, multiethnic high-risk asthma cohort titled the Vitamin D Antenatal Asthma Reduction Trial. METHODS: The trial recruited pregnant women whose children were followed from birth to age 8 years. Lung function was assessed with IOS at ages 4, 5, and 6 years and spirometry at ages 5, 6, 7, and 8 years. Asthma status, respiratory symptoms, and medication use were assessed with repeated questionnaires from birth to age 8 years. RESULTS: In total, 220 children were included in this secondary analysis. Recent respiratory symptoms and short-acting ß2-agonist use were associated with increased respiratory resistance at 5 Hz at age 4 years (ß = 2.6; 95% CI, 1.0 to 4.4; P = .002 and ß = 3.4; 95% CI, 0.7 to 6.2; P = .015, respectively). Increased respiratory resistance at 5 Hz at age 4 years was also associated with decreased lung function from ages 5 to 8 years (ß = -0.3; 95% CI, -0.5 to -0.1; P < .001 for FEV1 at 8 years) and active asthma at age 8 years (ß = 2.0; 95% CI, 0.2 to 3.8; P = .029). CONCLUSIONS: Increased respiratory resistance in preschool IOS is associated with frequent respiratory symptoms as well as school-age asthma and lung function impairment. Our findings suggest that IOS may serve as a potential objective measure for early identification of children who are at high risk of respiratory morbidity.

Joint clinical and molecular subtyping of COPD with variational autoencoders.

Chronic Obstructive Pulmonary Disease (COPD) is a complex, heterogeneous disease. Traditional subtyping methods generally focus on either the clinical manifestations or the molecular endotypes of the disease, resulting in classifications that do not fully capture the disease's complexity. Here, we bridge this gap by introducing a subtyping pipeline that integrates clinical and gene expression data with variational autoencoders. We apply this methodology to the COPDGene study, a large study of current and former smoking individuals with and without COPD. Our approach generates a set of vector embeddings, called Personalized Integrated Profiles (PIPs), that recapitulate the joint clinical and molecular state of the subjects in the study. Prediction experiments show that the PIPs have a predictive accuracy comparable to or better than other embedding approaches. Using trajectory learning approaches, we analyze the main trajectories of variation in the PIP space and identify five well-separated subtypes with distinct clinical phenotypes, expression signatures, and disease outcomes. Notably, these subtypes are more robust to data resampling compared to those identified using traditional clustering approaches. Overall, our findings provide new avenues to establish fine-grained associations between the clinical characteristics, molecular processes, and disease outcomes of COPD.

Lung function trajectories in a cohort of patients with moderate-to-severe asthma on mepolizumab, omalizumab, or dupilumab.

BACKGROUND: Lung function is an independent predictor of mortality. We evaluated the lung function trajectories of a cohort of patients with asthma receiving biologic therapy. METHODS: We identified 229 monoclonal antibody-naïve adult patients with moderate-to-severe asthma who initiated omalizumab, mepolizumab, or dupilumab between 2010 and 2022 in a large healthcare system in Boston, MA. Generalized additive mixed models were used to estimate the lung function trajectories during the 156 weeks following biologic initiation. Response was defined as an improvement in FEV1 or a decrease of ≤0.5% per year. The Kaplan-Meier estimator was used to assess time to no additional improvement in FEV1 in responders. All models were adjusted for age, sex, body mass index, smoking status, baseline exacerbation rate, and baseline blood eosinophil count. RESULTS: Eighty-eight patients initiated mepolizumab, 76 omalizumab, and 65 dupilumab. Baseline eosinophil count was highest in the mepolizumab group (405 cells/mcL) and lowest for omalizumab (250 cells/mcL). Both FEV1 and FVC improved in the mepolizumab group (FEV1 + 20 mL/year; FVC +43 mL/year). For omalizumab, there was an initial improvement in the first year followed by decline with an overall FEV1 loss of -44 mL/year and FVC -32 mL/year. For dupilumab, both FEV1 (+61 mL/year) and FVC (+74 mL/year) improved over time. Fifty percent of the mepolizumab group, 58% omalizumab, and 72% of dupilumab were responders. The median time to no additional FEV1 improvement in responders was 24 weeks for omalizumab, 48 weeks for mepolizumab, and 57 weeks for dupilumab. CONCLUSION: In this clinical cohort, mepolizumab, omalizumab, and dupilumab had beneficial effects on FEV1 and FVC with distinct post-initiation trajectories.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments.

Since dietary intake is challenging to directly measure in large-scale cohort studies, we often rely on self-reported instruments (e.g., food frequency questionnaires, 24-hour recalls, and diet records) developed in nutritional epidemiology. Those self-reported instruments are prone to measurement errors, which can lead to inaccuracies in the calculation of nutrient profiles. Currently, few computational methods exist to address this problem. In the present study, we introduce a deep-learning approach --- Microbiome-based nutrient profile corrector (METRIC), which leverages gut microbial compositions to correct random errors in self-reported dietary assessments using 24-hour recalls or diet records. We demonstrate the excellent performance of METRIC in minimizing the simulated random errors, particularly for nutrients metabolized by gut bacteria in both synthetic and three real-world datasets. Further research is warranted to examine the utility of METRIC to correct actual measurement errors in self-reported dietary assessment instruments.

Association of Prenatal Maternal and Infant Vitamin D Supplementation with Offspring Asthma.

Rationale: The role and timing of vitamin D supplementation in the prevention of asthma has not been fully elucidated. Objective: To describe the association between prenatal and postnatal vitamin D with offspring asthma outcomes in participants of the Vitamin D Antenatal Asthma Reduction Trial. Methods: We classified 748 mother-offspring pairs into four groups based on the mother's randomization to receive high-dose versus low-dose (4,400 IU vs. 400 IU) vitamin D supplementation during pregnancy and the offspring parent-reported high-dose versus low-dose (⩾400 IU vs. <400 IU) vitamin D supplementation as estimated by intake of vitamin D drops or infant formula. We used logistic regression to test the association of the four vitamin D exposure groups-"mother-low/infant-low (reference)," "mother-high/infant-high," "mother-high/infant-low," and "mother-low/infant-high"-with offspring asthma and/or recurrent wheeze at age 3 years, active asthma at age 6 years, and atopic asthma at age 6 years. Results: The risk of asthma and/or recurrent wheeze at 3 years was lowest in the mother-high/infant-low group (adjusted odds ratio vs. mother-low/infant-low, 0.39; 95% confidence interval, 0.16-0.88, P = 0.03). When stratifying by history of exclusive breastfeeding until age 4 months, the protective effect in the mother-high/infant-low group was seen only among exclusively breastfed infants (odds ratio vs. mother-low/infant-low, 0.19; 95% confidence interval, 0.04-0.68; P = 0.02). We did not observe any significant associations with active or atopic asthma at age 6 years. Conclusions: We observe that high-dose prenatal and low-dose postnatal vitamin D supplementation may be associated with reduced offspring asthma or recurrent wheeze by age 3 years, but this association may be confounded by the protective effect of breastfeeding.

A novel piwi-interacting RNA associates with type 2-high asthma phenotypes.

BACKGROUND: Piwi-interacting RNAs (piRNAs), comprising the largest noncoding RNA group, regulate transcriptional processes. Whether piRNAs are associated with type 2 (T2)-high asthma is unknown. OBJECTIVE: We sought to investigate the association between piRNAs and T2-high asthma in childhood asthma. METHODS: We sequenced plasma samples from 462 subjects in the Childhood Asthma Management Program (CAMP) as the discovery cohort and 1165 subjects in the Genetics of Asthma in Costa Rica Study (GACRS) as a replication cohort. Sequencing reads were filtered first, and piRNA reads were annotated and normalized. Linear regression was used for the association analysis of piRNAs and peripheral blood eosinophil count, total serum IgE level, and long-term asthma exacerbation in children with asthma. Mediation analysis was performed to investigate the effect direction. We then ascertained if the circulating piRNAs were present in asthmatic airway epithelial cells in a Gene Expression Omnibus (GEO; www.ncbi.nlm.nih.gov/geo) public data set. RESULTS: Fifteen piRNAs were significantly associated with eosinophil count in CAMP (P ≤ .05), and 3 were successfully replicated in GACRS. Eleven piRNAs were associated with total IgE in CAMP, and one of these was replicated in GACRS. All 22 significant piRNAs were identified in epithelial cells in vitro, and 6 of these were differentially expressed between subjects with asthma and healthy controls. Fourteen piRNAs were associated with long-term asthma exacerbation, and effect of piRNAs on long-term asthma exacerbation are mediated through eosinophil count and serum IgE level. CONCLUSION: piRNAs are associated with peripheral blood eosinophils and total serum IgE in childhood asthma and may play important roles in T2-high asthma.