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1.
bioRxiv ; 2024 Mar 20.
Article in English | MEDLINE | ID: mdl-38562829

ABSTRACT

The secreted mucins MUC5AC and MUC5B play critical defensive roles in airway pathogen entrapment and mucociliary clearance by encoding large glycoproteins with variable number tandem repeats (VNTRs). These polymorphic and degenerate protein coding VNTRs make the loci difficult to investigate with short reads. We characterize the structural diversity of MUC5AC and MUC5B by long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that human MUC5B is largely invariant (5761-5762aa); however, seven haplotypes have expanded VNTRs (6291-7019aa). In contrast, 30 allelic variants of MUC5AC encode 16 distinct proteins (5249-6325aa) with cysteine-rich domain and VNTR copy number variation. We grouped MUC5AC alleles into three phylogenetic clades: H1 (46%, ~5654aa), H2 (33%, ~5742aa), and H3 (7%, ~6325aa). The two most common human MUC5AC variants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium (LD) and Tajima's D analyses reveal that East Asians carry exceptionally large MUC5AC LD blocks with an excess of rare variation (p<0.05). To validate this result, we used Locityper for genotyping MUC5AC haplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observed signatures of positive selection in H1 and H2 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Africans and Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium, consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein coding VNTRs for improved disease associations.

2.
Clin Epigenetics ; 15(1): 156, 2023 10 03.
Article in English | MEDLINE | ID: mdl-37784136

ABSTRACT

BACKGROUND: Albuterol is the first-line asthma medication used in diverse populations. Although DNA methylation (DNAm) is an epigenetic mechanism involved in asthma and bronchodilator drug response (BDR), no study has assessed whether albuterol could induce changes in the airway epithelial methylome. We aimed to characterize albuterol-induced DNAm changes in airway epithelial cells, and assess potential functional consequences and the influence of genetic variation and asthma-related clinical variables. RESULTS: We followed a discovery and validation study design to characterize albuterol-induced DNAm changes in paired airway epithelial cultures stimulated in vitro with albuterol. In the discovery phase, an epigenome-wide association study using paired nasal epithelial cultures from Puerto Rican children (n = 97) identified 22 CpGs genome-wide associated with repeated-use albuterol treatment (p < 9 × 10-8). Albuterol predominantly induced a hypomethylation effect on CpGs captured by the EPIC array across the genome (probability of hypomethylation: 76%, p value = 3.3 × 10-5). DNAm changes on the CpGs cg23032799 (CREB3L1), cg00483640 (MYLK4-LINC01600), and cg05673431 (KSR1) were validated in nasal epithelia from 10 independent donors (false discovery rate [FDR] < 0.05). The effect on the CpG cg23032799 (CREB3L1) was cross-tissue validated in bronchial epithelial cells at nominal level (p = 0.030). DNAm changes in these three CpGs were shown to be influenced by three independent genetic variants (FDR < 0.05). In silico analyses showed these polymorphisms regulated gene expression of nearby genes in lungs and/or fibroblasts including KSR1 and LINC01600 (6.30 × 10-14 ≤ p ≤ 6.60 × 10-5). Additionally, hypomethylation at the CpGs cg10290200 (FLNC) and cg05673431 (KSR1) was associated with increased gene expression of the genes where they are located (FDR < 0.05). Furthermore, while the epigenetic effect of albuterol was independent of the asthma status, severity, and use of medication, BDR was nominally associated with the effect on the CpG cg23032799 (CREB3L1) (p = 0.004). Gene-set enrichment analyses revealed that epigenomic modifications of albuterol could participate in asthma-relevant processes (e.g., IL-2, TNF-α, and NF-κB signaling pathways). Finally, nine differentially methylated regions were associated with albuterol treatment, including CREB3L1, MYLK4, and KSR1 (adjusted p value < 0.05). CONCLUSIONS: This study revealed evidence of epigenetic modifications induced by albuterol in the mucociliary airway epithelium. The epigenomic response induced by albuterol might have potential clinical implications by affecting biological pathways relevant to asthma.


Subject(s)
Asthma , DNA Methylation , Child , Humans , Epigenomics , Asthma/drug therapy , Asthma/genetics , Albuterol/pharmacology , Albuterol/therapeutic use , Epigenesis, Genetic , Bronchodilator Agents/pharmacology , Bronchodilator Agents/therapeutic use , Epithelial Cells , Genome-Wide Association Study
3.
J Allergy Clin Immunol ; 150(2): 302-311, 2022 08.
Article in English | MEDLINE | ID: mdl-35660376

ABSTRACT

BACKGROUND: Whether children and people with asthma and allergic diseases are at increased risk for severe acute respiratory syndrome virus 2 (SARS-CoV-2) infection is unknown. OBJECTIVE: Our aims were to determine the incidence of SARS-CoV-2 infection in households with children and to also determine whether self-reported asthma and/or other allergic diseases are associated with infection and household transmission. METHODS: For 6 months, biweekly nasal swabs and weekly surveys were conducted within 1394 households (N = 4142 participants) to identify incident SARS-CoV-2 infections from May 2020 to February 2021, which was the pandemic period largely before a vaccine and before the emergence of SARS-CoV-2 variants. Participant and household infection and household transmission probabilities were calculated by using time-to-event analyses, and factors associated with infection and transmission risk were determined by using regression analyses. RESULTS: In all, 147 households (261 participants) tested positive for SARS-CoV-2. The household SARS-CoV-2 infection probability was 25.8%; the participant infection probability was similar for children (14.0% [95% CI = 8.0%-19.6%]), teenagers (12.1% [95% CI = 8.2%-15.9%]), and adults (14.0% [95% CI = 9.5%-18.4%]). Infections were symptomatic in 24.5% of children, 41.2% of teenagers, and 62.5% of adults. Self-reported doctor-diagnosed asthma was not a risk factor for infection (adjusted hazard ratio [aHR] = 1.04 [95% CI = 0.73-1.46]), nor was upper respiratory allergy or eczema. Self-reported doctor-diagnosed food allergy was associated with lower infection risk (aHR = 0.50 [95% CI = 0.32-0.81]); higher body mass index was associated with increased infection risk (aHR per 10-point increase = 1.09 [95% CI = 1.03-1.15]). The household secondary attack rate was 57.7%. Asthma was not associated with household transmission, but transmission was lower in households with food allergy (adjusted odds ratio = 0.43 [95% CI = 0.19-0.96]; P = .04). CONCLUSION: Asthma does not increase the risk of SARS-CoV-2 infection. Food allergy is associated with lower infection risk, whereas body mass index is associated with increased infection risk. Understanding how these factors modify infection risk may offer new avenues for preventing infection.


Subject(s)
Asthma , COVID-19 , Hypersensitivity , Adolescent , Adult , Asthma/epidemiology , COVID-19/epidemiology , Child , Humans , Hypersensitivity/epidemiology , Prospective Studies , Risk Factors , SARS-CoV-2
4.
Nat Commun ; 11(1): 5139, 2020 10 12.
Article in English | MEDLINE | ID: mdl-33046696

ABSTRACT

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.


Subject(s)
Betacoronavirus/physiology , Coronavirus Infections/virology , Interferons/metabolism , Interleukin-13/metabolism , Nasal Mucosa/pathology , Peptidyl-Dipeptidase A/genetics , Pneumonia, Viral/virology , Serine Endopeptidases/genetics , Angiotensin-Converting Enzyme 2 , COVID-19 , Child , Coronavirus Infections/metabolism , Coronavirus Infections/pathology , Epithelial Cells/metabolism , Gene Expression Profiling , Gene Expression Regulation , Genetic Variation , Host-Pathogen Interactions , Humans , Inflammation , Middle Aged , Nasal Mucosa/metabolism , Pandemics , Peptidyl-Dipeptidase A/metabolism , Pneumonia, Viral/metabolism , Pneumonia, Viral/pathology , SARS-CoV-2 , Serine Endopeptidases/metabolism , Virus Internalization
5.
bioRxiv ; 2020 Apr 10.
Article in English | MEDLINE | ID: mdl-32511326

ABSTRACT

Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both ACE2 and TMPRSS2, that vary in frequency across world populations. Importantly, we find TMPRSS2 is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates ACE2 expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate IL6 while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

6.
Nat Commun ; 11(1): 2485, 2020 05 19.
Article in English | MEDLINE | ID: mdl-32427931

ABSTRACT

Cigarette smoke first interacts with the lung through the cellularly diverse airway epithelium and goes on to drive development of most chronic lung diseases. Here, through single cell RNA-sequencing analysis of the tracheal epithelium from smokers and non-smokers, we generate a comprehensive atlas of epithelial cell types and states, connect these into lineages, and define cell-specific responses to smoking. Our analysis infers multi-state lineages that develop into surface mucus secretory and ciliated cells and then contrasts these to the unique specification of submucosal gland (SMG) cells. Accompanying knockout studies reveal that tuft-like cells are the likely progenitor of both pulmonary neuroendocrine cells and CFTR-rich ionocytes. Our smoking analysis finds that all cell types, including protected stem and SMG populations, are affected by smoking through both pan-epithelial smoking response networks and hundreds of cell-specific response genes, redefining the penetrance and cellular specificity of smoking effects on the human airway epithelium.


Subject(s)
Epithelial Cells/metabolism , Gene Expression Profiling/methods , Lung/metabolism , Respiratory Mucosa/metabolism , Smoking/genetics , Trachea/metabolism , Animals , Cells, Cultured , Gene Knockout Techniques , Gene Regulatory Networks , Humans , Lung/cytology , Mice , NIH 3T3 Cells , Non-Smokers/statistics & numerical data , Respiratory Mucosa/cytology , Sequence Analysis, RNA/methods , Single-Cell Analysis/methods , Smokers/statistics & numerical data , Trachea/cytology
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