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Deborah A Meyers

Publications and source records attributed to Deborah A Meyers.

6 recordsLinked to original sources
PubMed2026

Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning.

Type 2 (T2) immune cells dominate the airways of patients with mild-moderate asthma (MMA) with a more complex type 1 (T1)-T2 mixed immune response evident in treatment-refractory severe asthma (SA). We hypothesized that comparing the transcriptomes of the airway epithelium of patients with SA and MMA would reveal molecular signatures associated with more severe disease in the context of a complex immune response. Using our interpretable machine learning tool, SLIDE, meaningful latent factors (context-specific gene co-expression networks) were revealed that distinguished SA from MMA. Unexpectedly, an aberrant high expression of normally host-protective, membrane-tethered, and IFN-inducible mucins, MUC1 and MUC4, was identified in SA. Gene networks in the significant latent factors discriminating SA from MMA corresponded to enrichment of a keratinization program in SA airways. Keratinization was marked by increased expression of the stress keratin KRT16, signifying squamous metaplasia suggesting adaptive reprogramming of the airway epithelium in response to chronic stress. These mucins and KRT16 were inversely associated with lung function in 2 separate asthma cohorts. Imaging of endobronchial biopsies revealed significantly higher KRT16 protein expression in SA compared with MMA that strongly correlated with MUC1 protein expression. Our study identifies dysregulated host-protective and maladaptive repair responses in SA distinguishing from MMA.

Humans↗
PubMed2025

Genetic architecture and analysis practices of circulating metabolites in the NHLBI Trans-Omics for Precision Medicine Program.

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

Humans↗
PubMed2025

α1-Antitrypsin Gene Variation Associates With Asthma Exacerbations and Related Health Care Utilization.

BACKGROUND: α1-Antitrypsin deficiency is caused by rare pathogenic variants in SERPINA1, the strongest genetic risk factor for chronic obstructive pulmonary disease. Few studies have evaluated the effects of SERPINA1 variation on asthma severity accounting for critical gene-by-environment interactions with smoking. OBJECTIVE: To characterize the influence of SERPINA1 variation on asthma severity. METHODS: DNA samples from 847 non-Hispanic White and 446 African American participants from the Severe Asthma Research Program underwent SERPINA1 resequencing to identify rare variants. An independent population of 1955 individuals with asthma and α1-antitrypsin concentrations from a Cleveland Clinic Health System (CCHS) database were evaluated for severity measures. RESULTS: In White participants, a history of minimum smoking significantly interacted with SERPINA1 low-to-rare frequency variation to determine risk for asthma-related health care utilization. This was attributed to protease inhibitor type Z heterozygotes (MZ, N = 11), who had a higher frequency of emergency department (ED) visits (6 [54.5%] MZ heterozygotes, odds ratio [OR] = 7.60, 95% confidence interval [CI] = 1.71-39.7, P = .010), hospitalization (5 [45.5%], OR = 16.1, 95% CI = 2.64-150.4, P = .0050) in the past year, and lifetime intensive care unit (ICU) admissions (6 [54.5%], OR = 12.5, 95% CI = 2.44-75.6, P = .0032) compared with 146 individuals without SERPINA1 variants (30 [20.5%] reporting ED visits, 17 [11.6%] hospitalization, and 15 [10.3%] ICU admission). SERPINA1 variant-by-ever smoking interactions in African American participants for ED visits (P = .069) were related to 4 of 6 compound heterozygotes reporting an ED visit. In CCHS, α1-antitrypsin concentrations were inversely associated with moderate-to-severe asthma risk (OR = 0.97 per 10 mg/dL increase in α1-antitrypsin, 95% CI = 0.94-0.99, P = .010) and exacerbations (OR = 0.84 per 10 mg/dL, 95% CI = 0.76-0.94, P = .002). CONCLUSIONS: SERPINA1 variation and α1-antitrypsin concentrations impact asthma severity through gene-environment interactions with minimum smoking.

Adult↗
PubMed2024

Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas.

Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

Humans↗
PubMed2024

Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

BACKGROUND: The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. OBJECTIVES: Accordingly, with National Heart, Lung and Blood Institute support, we initiated the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. METHODS/DISCUSSION: SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global initiative for chronic Obstructive Lung Disease (GOLD) groups 0-2 or with preserved ratio-impaired spirometry; and an additional n=40 never-smoker controls. Participants undergo baseline and 3-year follow-up visits, each including high-resolution computed tomography, respiratory oscillometry and spirometry (pre- and postbronchodilator administration), exhaled breath condensate (baseline only), and extensive biospecimen collection, including sputum induction. Symptoms, interim health care utilization, and exacerbations are captured every 6 months via follow-up phone calls. An embedded bronchoscopy substudy involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. CONCLUSION: SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

SPIROMICS↗
PubMed2023

A blood and bronchoalveolar lavage protein signature of rapid FEV1 decline in smoking-associated COPD.

Accelerated progression of chronic obstructive pulmonary disease (COPD) is associated with increased risks of hospitalization and death. Prognostic insights into mechanisms and markers of progression could facilitate development of disease-modifying therapies. Although individual biomarkers exhibit some predictive value, performance is modest and their univariate nature limits network-level insights. To overcome these limitations and gain insights into early pathways associated with rapid progression, we measured 1305 peripheral blood and 48 bronchoalveolar lavage proteins in individuals with COPD [n = 45, mean initial forced expiratory volume in one second (FEV1) 75.6 ± 17.4% predicted]. We applied a data-driven analysis pipeline, which enabled identification of protein signatures that predicted individuals at-risk for accelerated lung function decline (FEV1 decline ≥ 70 mL/year) ~ 6 years later, with high accuracy. Progression signatures suggested that early dysregulation in elements of the complement cascade is associated with accelerated decline. Our results propose potential biomarkers and early aberrant signaling mechanisms driving rapid progression in COPD.

Humans↗