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Meyers, Deborah A.

https://orcid.org/0000-0001-5399-8423

Mayo Clinic

Cleveland Clinic

Citations 53

Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Blackwell, Thomas W., Kachuri, Linda , Castaldi, Peter J. , Cho, Michael H. , Christenson, Stephanie A. , Durda, Peter , Gabriel, Stacey , Hersh, Craig P. , Huntsman, Scott , Hwang, S.-J., Joehanes, Roby, Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching‐Ti , Liu, Yongmei , Mak, Angel C. Y. , Manichaikul, Ani , Paik, David T. , Saferali, Aabida , Smith, Joshua D. , Taylor, Kent D. , Wang, Jiongming , Weinstock, Joshua S. , Weiss, Jeffrey, Wheeler, Heather E. , Zhou, Ying , Zoellner, Sebastian, Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R.G. , Ortega, Victor E. , Johnson, Craig , Gan, Weiniu , Abecasis, Gonçalo , Nickerson, Deborah A. , Ardlie, Kristin G., Woodruff, Prescott G. , Bowler, Russell P. , Meyers, Deborah A. , Reiner, Alex, Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S. , Silverman, Edwin K. , Rich, Stephen S., Heard‐Costa, Nancy L. , Tang, Hua, Rotter, Jerome I. , Smith, Albert V. , Aguet, François, Scott, Laura J. , Raffield, Laura M. , Parker, Stephen C.J. , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. Charles, Guan, Yue, Hall, Michael, Han, Yi, Harris, Daniel, Heavner, Ben, Herrington, David, Hobbs, Brian, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Jackson, Rebecca, Jain, Deepti, Johnsen, Jill, Johnston, Rich, Jones, Kimberly, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Kramer, Holly, Lange, Christoph, Lange, Ethan, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Sandra, Lee, Wen-Jane, Levine, David, Lewis, Joshua, Li, Yun, Lin, Xihong, Liu, Simin, Liu, Yu, Make, Barry, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGoldrick, Daniel, McHugh, Caitlin, Mei, Hao, Meigs, James, Menon, Vipin, Min, Nancy, Moll, Matt, Momin, Zeineen, Montasser, May, Mychaleckyj, Josyf C, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nkechinyere, Osuji, O'Connell, Jeff, O’Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pankow, James, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Phillips, Lawrence S, Pollin, Toni, Becker, Julia Powers, Boorgula, Meher Preethi, Psaty, Bruce, Qiao, Dandi, Rafaels, Nicholas, Rajendran, Mahitha, Rasmussen-Torvik, Laura, Ratan, Aakrosh, Reed, Robert, Regan, Elizabeth, Reupena, Muagututi‘a Sefuiva, Robillard, Rebecca, Roselli, Carolina, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ryan, Kathleen, Sabino, Ester Cerdeira, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Santibanez, Jireh, Schwander, Karen, Sciurba, Frank, Sériès, Frédéric, Shetty, Amol, Shetty, Aniket, Silver, Brian, Skomro, Robert, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taub, Margaret, Taylor, Simeon, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tong, Catherine, Tsai, Michael, Vaidya, Dhananjay, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Watson, Karol, Watt, Jennifer, Weng, Lu-Chen, Wessel, Jennifer, Williams, Kayleen, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Zekavat, Seyedeh Maryam, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Rich, Stephen S. , Pankow, James S. , Reiner, Alex P. , Aguet, François , Johnson, W. Craig , Ardlie, Kristin , Orchard, Peter , Kachuri, Linda , Castaldi, Peter J , Cho, Michael H , Christenson, Stephanie A , Durda, Peter , Hersh, Craig P , Huntsman, Scott , Hwang, Seungyong , Joehanes, Roby , Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching-Ti , Liu, Yongmei , Mak, Angel C Y , Manichaikul, Ani W , Paik, David T , Smith, Joshua D , Taylor, Kent D , Tracy, Russell P , Wang, Jiongming , Wang, Mingqiang , Weinstock, Joshua S , Weiss, Jeffrey , Wheeler, Heather E , Zhou, Ying , Zöllner, Sebastian , Wu, Joseph C , Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R G , Ortega, Victor E , Johnson, W Craig , Gan, Weiniu , Gupta, Namrata , Ardlie, Kristin , Woodruff, Prescott G , Bowler, Russell P , Reiner, Alexander P , Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S , Silverman, Edwin K , Rich, Stephen S , Heard-Costa, Nancy , Tang, Hua , Rotter, Jerome I , Smith, Albert V , Levy, Daniel , Aguet, François , Scott, Laura J , Raffield, Laura M , Parker, Stephen C J , Pankow, James S , Tracy, Russell P. , Wu, Joseph C. , Larson, Martin G. , Cupples, L. Adrienne , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan , Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. Charles, Guan, Yue, Hall, Michael, Han, Yi, Harris, Daniel, Heavner, Ben, Herrington, David, Hobbs, Brian, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Jackson, Rebecca, Jain, Deepti, Johnsen, Jill, Johnston, Rich, Jones, Kimberly, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Kramer, Holly, Lange, Christoph, Lange, Ethan, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Sandra, Lee, Wen-Jane, Levine, David, Lewis, Joshua, Li, Yun, Lin, Xihong, Liu, Simin, Liu, Yu, Make, Barry, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGoldrick, Daniel, McHugh, Caitlin, Mei, Hao, Meigs, James, Menon, Vipin, Min, Nancy, Moll, Matt, Momin, Zeineen, Montasser, May, Mychaleckyj, Josyf C, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nkechinyere, Osuji, O'Connell, Jeff, O’Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Phillips, Lawrence S, Pollin, Toni, Becker, Julia Powers, Boorgula, Meher Preethi, Psaty, Bruce, Qiao, Dandi, Rafaels, Nicholas, Rajendran, Mahitha, Rasmussen-Torvik, Laura, Ratan, Aakrosh, Reed, Robert, Regan, Elizabeth, Reupena, Muagututi‘a Sefuiva, Robillard, Rebecca, Roselli, Carolina, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ryan, Kathleen, Sabino, Ester Cerdeira, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Santibanez, Jireh, Schwander, Karen, Sciurba, Frank, Sériès, Frédéric , Shetty, Amol, Shetty, Aniket, Silver, Brian, Skomro, Robert, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taub, Margaret, Taylor, Simeon, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tong, Catherine, Tsai, Michael, Vaidya, Dhananjay, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Watson, Karol, Watt, Jennifer, Weng, Lu-Chen, Wessel, Jennifer, Williams, Kayleen, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Zekavat, Seyedeh Maryam, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng

Science | July 16, 2026 | Volume: 393 | Issue: 6808 | Pages: No page available

10.1126/science.adx2989 Get It

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.
C101-09 Lower Airway-to-lung Ratio Links to Neutrophil/macrophage Inflammation and Impaired Mucociliary Clearance in Current Smokers in SPIROMICS
Kelly, M E, Woodruff, P G, Curtis, J L, Paine, R, Barjaktarevic, I, Hoffman, E A, Bleecker, E R, Meyers, D A, Bowler, R P, Barr, R G, Cooper, C B, Couper, D, Han, M K, Putcha, N, Kaner, R J, Hansel, N N, O’Neal, W K, Martinez, F J, Ortega, V E, Smith, B M, Christenson, S A, Investigators, SPIROMICS, Curtis, Jeffrey L. , Hoffman, Eric A. , Meyers, Deborah A. , Barr, R. Graham , Han, MeiLan King , Kaner, R.J. , Hansel, Nadia N. , O’Neal, Wanda K. , Christenson, S A

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.2028 Get It

Abstract Rationale Mismatch of airway to lung size has been implicated in chronic obstructive pulmonary disease (COPD) pathophysiology, whether arising from disproportioned growth or from acquired pathologies over the life course. Lower airway-to-lung ratio (ALR), assessed reproducibly via computed tomography (CT) as the mean airway lumen diameters (trachea-to-subsegments) divided by the cubed root of lung volume, is associated with COPD risk and mortality (all-cause, respiratory, cardiovascular, lung cancer). We sought to characterize the airway biology associated with lower ALR by profiling bronchial gene expression across current and former smokers. Methods We leveraged clinical, radiologic, and bronchial epithelial RNA sequencing data from the SPIROMICS (SubPopulations and Intermediate Outcomes Measures in COPD Study) Phase 1 Bronchoscopy Sub-study (n = 161). To analyze transcriptional differential expression (DE) between participants based on CT-assessed ALR, we utilized DESeq2 and then identified impacted pathways by Ingenuity Pathway Analysis (IPA). Generating cell-type transcriptional signatures from lung and blood single cell sequencing atlases, we also assessed association of ALR with differences in airway cellular composition. Results Across all ever-smokers, after adjustment for age, sex, height, COPD status, smoking status, and pack-years, n = 1,324 genes from airway epithelial samples exhibited DE at a false discovery rate (FDR) <0.2. Per IPA, enriched pathways associated with lower ALR included neutrophilic degranulation and macrophage activity. In cell type analysis, lower ALR was associated with higher signatures of macrophages, neutrophils, dendritic cells, and B cells, and lower ciliated and club cell signatures. When we repeated DE analysis using the same covariate adjustments plus an interaction term for ALR and smoking, n = 713 DE genes were identified at FDR <0.2; the association of DE with lower ALR was overwhelmingly in current rather than former smokers (3699 vs. 2 genes). By pathway and cell type analyses, the association between lower ALR and heightened inflammation (greater macrophage and neutrophil signaling) and epithelial dysregulation (downregulated ciliated and club cell function) was primarily restricted to current smokers. Conclusions In adult ever-smokers, lower ALR is associated with transcriptomic evidence of heightened neutrophil- and macrophage-driven airway inflammation and reduced ciliated and club cell expression, associations that were most evident among current smokers. Whether these cross-sectional patterns, which suggest impaired mucociliary defense and a diminished capacity to clear inhaled particulates, are the result of pre-existing reduced ALR, its cause, or both, will require further investigation. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.
C101-10 Epigenetic Signatures of Sputum Eosinophils in COPD
Cao, S, Bleecker, E R, Meyers, D A, Zein, J G, Shrivastav, A, Chen, X, Hawkins, G A, Barjaktarevic, I, Bowes, R, Barr, R G, Comellas, A P, Cooper, C B, Couper, D, Han, M K, Hansel, N N, Hastie, A T, Kaner, R J, Kanner, R E, Martinez, F J, O’Neal, W K, Paine, R, Woodruff, P G, Christenson, S A, Curtis, J L, Huang, Y J , Ortega, V E, Comellas, Alejandro P. , Comellas, Alejandro P , Meyers, Deborah A. , Zein, Joe , Barr, R. Graham , Han, MeiLan King , Hansel, Nadia N. , Hastie, Annette T. , Kaner, R.J. , Kanner, R.E., O’Neal, Wanda K. , Curtis, Jeffrey L.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.2029 Get It

Abstract Rationale Eosinophilic airway inflammation in COPD is associated with more frequent exacerbations,lower lung function,and corticosteroid responsiveness.DNA methylation captures information about genetic factors and environmental exposures, but is under-studied in eosinophilic COPD.We hypothesized that sputum cell methylation patterns reflect genomic regulation of inflammatory endotypes in COPD by DNA sequence variation. Methods We analyzed DNA previously extracted from induced sputum cells for a prior study(PMID38261629) for which sufficient quantity DNA remained for methylation arrays.For this analysis,we focused on n = 132 SPIROMICS participants with ≥20 pack-years smoking history.Samples were stratified into tertiles based on sputum eosinophil proportions,previously determined from sputum cell differential analysis by the centralized sputum analysis core for SPIROMICS(Univ of North Carolina).We assessed proportion of DNA methylation (β values) spanning 936,866 CpG sites using the Illumina Infinium Methylation EPICv2.0 BeadChip Array,which we transformed into M values(meffil R package). To identify differentially methylated regions (DMRs)(FDR<0.05 in minimum of 2 CpG sites per gene region),we contrasted CpG β values between the high-eosinophil and low-eosinophil tertiles(N = 44 each),using the DMRcate package.We tested for enrichment of genes overlapping with significant DMRs using Enrichr (GWAS Catalog 2025 gene set library).To identify genetic variants associated with DNA methylation levels,we performed Methylation Quantitative Trait Loci (meQTL) analysis using TensorQTL.For each CpG site,we tested associations with SNPs within a ± 500 kb window (cis-meQTL).The linear regression model included age,sex,BMI,smoking status,smoking pack-years,study site,inhaled corticosteroid use, the first two genetic principal components, cell-type proportions (macrophages/monocytes, neutrophils, squamous epithelial cells, lymphocytes), and eosinophil tertile . Significant meQTLs were identified at an FDR<0.05 using Benjamini-Hochberg correction. Results A total of 532 eosinophil-associated DMRs (FDR < 0.05) were identified between the high- and low-eosinophil groups,encompassing 446 unique genes.The top enriched pathways related to counts of eosinophils (adjusted p = 0. 00002464), lymphocytes (adjusted p = 0.0001860), and the sum of eosinophils-plus-basophils (adjusted p = 0.0001860).We identified 18,432 significant SNP-CpG/meQTL pairs (FDR < 0.05),suggesting extensive genetic influence on airway DNA methylation patterns.Among the n = 521 eosinophil-associated CpGs that overlapped with meQTLs,rs55687040 (TENT2,a gene involved in mRNA and miRNA processing) is a GWAS locus for FEV1/FVC ratio (PMID: 26634245), suggesting possible genetic control of airway eosinophilic methylation signatures. Conclusions Our findings disclose distinct DNA methylation signatures associated with sputum eosinophil proportion in COPD.A subset of these CpGs are regulated by genetic variants,suggesting an integrated genetic-epigenetic mechanism underlying airway eosinophilic inflammation with the potential to influence COPD risk and severity. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C), grants from the NIH/NHLBI (U01 HL137880, U24 HL141762, R01 HL182622, and R01 HL144718), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; and Theravance Biopharma and Mylan/Viatris.
C101-08 Discordant Airway Gene Expression of TSLP and Its Specific Receptor Subunit, CRLF2, Links CRLF2 to Mixed Granulocytic Inflammation and Lung Function Decline in SPIROMICS
Kelly, M E, Komori, K, Barjaktarevic, I, Curtis, J L, Bleecker, E R, Bowler, R P, Barr, R G, Comellas, A P, Cooper, C B, Couper, D, Han, M K, Hansel, N N, Hoffman, E A, Kaner, R J, Martinez, F J, Meyers, D A, O’Neal, W K, Ortega, V E, Paine, R, Smith, B M, Woodruff, P G, Christenson, S A, Investigators, SPIROMICS, Comellas, Alejandro P. , Comellas, Alejandro P , Curtis, Jeffrey L. , Barr, R. Graham , Han, MeiLan King , Hansel, Nadia N. , Hoffman, Eric A. , Kaner, R.J. , Meyers, Deborah A. , O’Neal, Wanda K. , Christenson, S A

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.2027 Get It

Abstract Rationale Thymic stromal lymphopoietin (TSLP) is an epithelial alarmin chiefly implicated in T2 airway inflammation, though it may also participate in broader (non-T2) inflammatory processes. The utility of airway epithelial gene expression of TSLP and its specific receptor subunit, cytokine receptor-like factor 2 (CRLF2), as biomarkers of downstream inflammation and clinical outcomes remains unclear. Methods We analyzed RNA sequencing data from bronchial airway brushing obtained in phase 1 of the SPIROMICS bronchoscopy sub-study (N = 161: 23 never-smokers, 67 ever-smokers with COPD, 71 ever-smokers without COPD). We related airway TSLP and CRLF2 expression to clinical, hematologic/sputum measures, and gene-expression signatures of T2/eosinophilic and neutrophilic inflammation, including to our published T2 signature and to eosinophil and neutrophil signatures derived from single-cell atlas data. Associations used Spearman correlations and linear models adjusted for age, sex, race/ethnicity, COPD status, smoking status, and pack-years. Results CRLF2 expression correlated with gene-expression evidence of both T2/eosinophilic and neutrophilic inflammation: T2 signature (ρ = 0.26, p < 0.001), eosinophil signature (ρ = 0.44, p < 0.001), and neutrophil signature (ρ = 0.39, p < 0.001). CRLF2 was positively associated with log sputum neutrophil count (ρ = 0.24, p = 0.024) and blood neutrophil count (ρ = 0.036, p < 0.001), but not with sputum or blood eosinophil counts. Higher CRLF2 related to worse baseline lung function, particularly among current smokers, (lower post-bronchodilator FEV1: ρ = −0.21, p = 0.008), as well as greater 5-year FEV1 decline across current and former smokers (ρ = −0.22, p = 0.007). Significant findings persisted after covariate adjustment. In contrast, TSLP expression, although strongly correlated with expression of the epithelial alarmin IL33 (ρ = 0.53, p < 0.001), was negatively correlated with CRLF2 (ρ = −0.24, p = 0.002) and with eosinophil and neutrophil gene-expression signatures (ρ = −0.26 and −0.33, both p < 0.001). TSLP expression showed no association with sputum or blood cell counts. Conclusions In bronchial epithelium from SPIROMICS, gene expression of CRLF2, but not of TSLP, tracked with downstream alarmin-relevant inflammatory programs, consistent with a regulatory role in TSLP signaling through TSLPR, as well as with clinically meaningful outcomes. CRLF2 expression was associated with evidence of both T2/eosinophilic and neutrophilic inflammation, and with lower baseline FEV1 and accelerated FEV1 decline, suggesting engagement of a broader, clinically relevant inflammatory milieu. By contrast, epithelial TSLP transcript levels mirrored IL33 gene expression but were not associated with cellular or transcriptomic inflammation. These findings position CRLF2, rather than TSLP expression itself, as a potential airway biomarker of TSLP-axis activity and disease impact with potential implications for patient stratification as well as strategic approaches for TSLP-pathway-targeted therapies. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.
C101-06 Interactions of Leukotriene-B4 and Interleukin-8 Gene Variants and Protein Levels With PI*MZ Heterozygosity Among the COPDGene and SPIROMICS Cohorts
Tejwani, V, Bazeley, P, Barjaktarevic, I, Barnard, J, Bleecker, E R, Cho, M H, Curtis, J L, Moll, M, Meyers, D A, Ruvuna, L, Shrivastav, A, Siddharthan, T, Silverman, E K, Stoller, J K, Zhang, J, Bowler, R P, Zein, J G, Hersh, C P, Ortega, V E, Bazeley, Peter , Cho, Michael H. , Curtis, Jeffrey L. , Meyers, Deborah A. , Ruvuna, L. , Stoller, James K. , Zein, Joe , Hersh, Craig P.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.2025 Get It

Abstract Rationale Deficiency of alpha-1 antitrypsin (AAT), the protein encoded by SERPINA1, remains the strongest genetic risk factor for COPD. Individuals heterozygote for the type Z variant, termed the PI*MZ genotype (estimated global prevalence n = 35,000,000), experience varying respiratory morbidity beyond expected from tobacco smoking alone. AAT is a pleiotropic protein which inhibits not only neutrophil elastase but also neutrophil chemotaxis mediated by leukotriene B4 (LTB4) [by antagonizing the LTB4 receptor (LTB4R)] and interleukin-8 (IL-8). Although LTB-4 and IL-8 gene variants and protein levels have independently been implicated in COPD, their potential role in PI*MZ is unknown. Methods COPDGene and SPIROMICS are observational tobacco-smoke and COPD-enriched cohort studies. Participants were phenotyped by spirometry and CT imaging, with whole genome sequencing data available via TOPMed. We analyzed participants with PI*MM (COPDGene n = 9,732; SPIROMICS n = 2,105) and PI*MZ (COPDGene n = 300; SPIROMICS n = 83). LTB-4 (ALOX5AP, LTA4H, LTB4R) and IL-8 (CXCL8, CXCR1, CXCR2) associated gene variants (exonic and intronic) with a minor allele frequency of ≥ 0.05 were extracted. We assessed statistical interactions between MZ status and chest CT outcomes or FEV1% predicted using the SPAGxECCT package with adjustment for relatedness (genetic related matrix) and ancestry (top ten PCs). Baseline protein LTB4R (SPIROMICS only) and IL-8 (both cohorts) protein levels were measured via SomaScan, and statistical interactions between MZ status and AAT concentration were explored. Models were adjusted for age, sex, BMI, smoking status, and pack-years. Given the candidate gene discovery approach, significance was defined as nominal p-value<0.05 Results We identified the following number of variants in genes of the LTB-4 or IL-8 pathways: 87 shared between cohorts; 133 unique to COPDGene; 1 unique to SPIROMICS. LTB-4-related polymorphisms were associated (p < 0.05) with any radiographic outcomes in 22 variants (COPDGene) vs. 23 variants (SPIROMICS), with a single overlap (rs17074984 in ALOX5AP). Two LTB-4-pathway variants were associated with FEV1% predicted in SPIROMICS (both in ALOX5AP), but none in COPDGene. AAT plasma concentrations displayed a statistically significant interaction with FEV1% predicted (p = 0.046) and PRMemphysema (p = 0.013) for LTBR4, but not for IL-8. There was not an interaction by MM/MZ status and protein levels. Conclusions Predominantly LTB-4, and not IL-8, pathway-related genetic variants and protein levels may contribute to disease heterogeneity among PI*MZ individuals. The association of circulating LTB4R protein with reduced lung function, particularly among those with low AAT levels, further suggest interactions between AAT and the leukotriene pathway in PI*MZ individuals. Thus, PI*MZ individuals may uniquely derive benefit from leukotriene-targeting pharmacotherapy. This abstract is funded by: NIH NHLBI K23HL173570
D21-17 Dysregulation of Prostaglandin E2 Pathways Correlate With Asthma Severity
Steffan, B N, Lee, K E, Townsend, E A, Jarjour, N N, Bleecker, E R, Castro, M, Christenson, S A, Erzurum, S C, Fahy, J V, Levy, B D, Israel, E, Mauger, D T, Meyers, D A, Phillips, B R, Moore, W C, Wenzel, S E, Woodruff, P, Zein, J G, Jackson, N D, Seibold, M A, Denlinger, L C, Steffan, Breanne N. , Fahy, John V. , Levy, Bruce David , Israel, Elliot , Meyers, Deborah A. , Wenzel, Sally E. , Woodruff, P., Zein, Joe , Jackson, Nathan D. , Denlinger, Loren C.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.661 Get It

Abstract Background Prostaglandin E2 (PGE2) exerts paradoxical effects in asthma, acting as both a protective mediator and a contributor to pathology depending on context. Its role is shaped by type 2 (T2)-status, eosinophilia, and exacerbation frequency. In epithelial cell cultures from asthmatic and healthy individuals, interleukin (IL)-13 suppresses PGE2 synthesis genes (PTGS2 and PGES) while upregulating HPGD, which encodes for the PGE2 catabolic enzyme 15-prostaglandin dehydrogenase (15-PGDH) (PMID:16751012), suggesting diminished PGE2 availability during T2 inflammation. Similarly, in aspirin-exacerbated respiratory disease (AERD), impaired cyclooxygenase disrupts PGE2 biosynthesis, fueling unchecked leukotriene production and eosinophilic inflammation (PMID: 30516547), underscoring PGE2’s protective role in limiting disease progression. Conversely, in nasal polyps, tuft cells are activated by IL-13 to produce PGE2 (PMID: 35608904), highlighting PGE2’s potential pathogenicity. Objective To assess associations between PGE2-pathway gene expression in bronchial brushings and asthma severity, and to determine how nasal polyp history modifies these relationships. Methods We analyzed bronchial epithelial brushings from 109 adults with asthma (mean age 42.4±12.1, 64% female, 52% severe asthma, 18% nasal polyps) using normalized and batch-corrected RNA-seq data from the baseline visit in the Severe Asthma Research Program (SARP)3 (PMID: 36796454). Age-adjusted and nasal polyp-adjusted relationships were calculated between ratios of PGE2 synthesis and metabolism genes and clinical outcomes (ASSESS score, FEV1 %predicted). The composite PGE2 score (PMID: 35608904), derived from nasal polyp analysis, was calculated from the average scaled log-normalized expression of six PGE2-responsive genes. All data were analyzed using a linear regression mixed model with a random effect for site. Results Ratios of PGE2 synthesis genes (PTGS1/2, PTGES2) to HPGD were significantly associated with greater disease severity (change in ASSESS Score) (Fig.1A, solid lines) and lower lung function (change in FEV1 %predicted) (Fig.1B, solid lines). These relationships persisted after adjusting for nasal polyps (Fig.1, dashed lines). The composite PGE2 score was also related to disease severity (Fig.1A, black solid line) but attenuated when nasal polyps were accounted for (Fig.1A, black dashed lines). Interestingly, lower lung function remained associated with the PGE2 score even after nasal polyp adjustment (Fig.1B, dashed black lines). Conclusions Our analysis demonstrates that the balance between PGE2 synthesis and degradation in the bronchial epithelium is closely linked to asthma severity and lung function, independent of nasal polyp status. Future work will integrate transcriptomic and clinical data longitudinally to establish whether PGE2 could serve as a biomarker for asthma trajectory. This abstract is funded by: HL115118 (LCD), U10HL109152 (S.E.W.), U10HL109172 (to E.I. and B.D.L), U10HL109168 (N.N.J.), U10HL109250 (S.C.E), U10HL109164 (W.C.M), U10HL109257 (M.C), and U10HL109146 (to P.G.W. and S.A.C.)
D21-16 Muc1, Muc4 and Ceacam5 Expression Are Elevated in Severe Asthma and Correlate With the Degree of Obstruction and Prospective Exacerbations
Gauthier, M C, Kale, S L, Vincent, A M, Ross, M A, Mehta, I, Calderon, M, Ramonell, R P, Christenson, S A, Woodruff, P G, Castro, M, Jarjour, N N, Sumino, K, Denlinger, L C, Gaston, B, Bleecker, E R, Meyers, D A, Moore, W C, Israel, E, Levy, B D, Mauger, D T, Erzurum, S C, Nee, T J, Ray, P, Croix, C M St, Wenzel, S E, Das, J, Ray, A, Vincent, Augusta, Ross, M, Calderon, Michael Joseph , Ramonell, Richard Paul , Sumino, K., Denlinger, Loren C. , Meyers, Deborah A. , Israel, Elliot , Levy, Bruce David , Nee, Taylor J., Croix, Claudette M. St. , Wenzel, Sally E.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.660 Get It

Abstract Rationale Type-1 inflammation in asthma leads to significant airway level changes independent of Type-2 inflammation and may underlie the severity seen in combined Type1/2 high disease. As IFNs can cause airway epithelial injury and impaired repair, we applied a novel interpretable machine learning algorithm, SLIDE, to analyze the transcriptome of airway epithelial brushings of mild-moderate (MMA) and severe asthma (SA) participants in the Immune Mechanisms in Severe Asthma (IMSA) cohort to identify latent/hidden factors of disease that associate with disease severity. Methods The expression of genes identified by SLIDE as part of a co-expression program was assessed in the full IMSA cohort by severity and in an independent cohort of the NHLBI Severe Asthma Research Program (SARP). We also examined associations of these genes with clinical asthma outcomes in both cohorts. Results SLIDE identified aberrant increased expression of membrane-tethered mucin genes, MUC1 and MUC4. MUC1 appeared in each of 5 significant latent factors associated with greater severity and MUC4 in 2/5. Standard DGE analysis also identified the gene CEACAM5 as a predictor of severity. Pathway analysis of latent factor genes revealed airway keratinization which may contribute to airway remodeling and worsening obstruction over time. Expression of MUC1, MUC4, and CEACAM5 were increased in SA compared to HC in both the full IMSA and separate SARP cohorts (p < 0.001 for all genes in both cohorts). Expression in MMA was consistently lower than in SA in both cohorts, reaching significance in IMSA (p < 0.01) but not consistently in SARP (MUC1 p = 0.04, MUC4 p = 0.27, CEACAM5 p = 0.27). Protein analysis of endobronchial biopsies by immunofluorescence staining showed a trend towards increased MUC1 protein content with evidence of secretion. MUC1, MUC4 and CEACAM5 were negatively correlated with FEV1 % predicted in both cohorts (IMSA: MUC1 r=-0.47, p < 0.01, MUC4 r=-0.47, p < 0.01, CEACAM5 r=-0.62, p < 0.01; SARP: MUC1 r=-0.19, p = 0.05, MUC4 r=-0.29, p < 0.01, CEACAM5 r=-0.51, p < 0.01). All three genes positively correlated with prospective exacerbations in both cohorts (IMSA: MUC1 r = 0.345, p = 0.01, MUC4 r = 0.216, p = 0.08, CEACAM5 r = 0.368, p < 0.01; SARP: MUC1 r = 0.22, p = 0.02, MUC4 r = 0.32, p < 0.01, CEACAM5 r = 0.38, p < 0.01). Conclusions The expression of MUC1, MUC4 and CEACAM5 increased with asthma severity in the airway epithelium and correlated with both prospective exacerbations and obstruction. As pathway analysis of genes in the significant latent factors were associated with airway keratinization aberrant expression of these mucins (with known signaling functions) may contribute to maladaptive repair and airway remodeling that drives obstruction over time, contributing to worse asthma outcomes. This abstract is funded by: NIH
C34-28 Secretor Status Does Not Affect Airway Mucus Plugging or Exacerbation Rates in Asthma
Khanna, K, Charbit, A R, Bleecker, E R, Meyers, D A, Seibold, M A, Castro, M, Comhair, S A, Denlinger, L C, Erzurum, S C, Johansson, M W, Israel, E, Levy, B D, Mauger, D T, Sumino, K, Wenzel, S E, Woodruff, P G, Fahy, J V, Khanna, Kritika , Meyers, Deborah A. , Denlinger, Loren C. , Johansson, Mats W. , Israel, Elliot , Levy, Bruce David , Sumino, K., Wenzel, Sally E. , Fahy, John V.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.613 Get It

Abstract Rationale The activity of fucosyltransferase 2 (FUT2) determines if mucin glycan structures in epithelial mucus include histo-blood group antigens (HBGAs). People with active FUT2 express HBGAs in epithelial mucus secretions and are terms “secretors”, while non-secretors lack HBGAs in their secretions because they have a FUT2 genotype that inactivates the glycosyl transferase. Prior research suggests that secretors who are blood type O (type O secretors) are susceptible to asthma exacerbations1 and that FUT2 knockout mice (functional non-secretors) are protected from mucus plugging in allergen challenge models2,3. We set out here to determine if secretor status influences mucus plug prevalence in asthma and to confirm if type O secretors are susceptible to asthma exacerbations. Methods We determined secretor status in asthma participants from the Severe Asthma Research Program-3 (SARP-3) cohort (N = 507) in two ways, a specific fucose lectin binding assay in sputum and FUT2 genotyping. Blood group type was determined using ABO genotyping. We analyzed mucus plug segment scores, asthma exacerbations rates and other clinical and biological features in patients stratified by secretor status and blood type (non-secretors, type O secretors, and non-type O secretors). Results Secretor status determined by lectin binding in sputum was strongly concordant with genotypic analysis. Within the SARP-3 cohort, 26.2% were non-secretors, 32.3% type were O secretors, and 41.4% were non-type O secretors. Mucus plug segment scores, annualized asthma exacerbation rates, and other measures of asthma severity were similar in non-secretors, type O secretors, and non-type O secretors (Table). Although type O secretors had increased values for fractional exhaled nitric oxide (FeNO) and higher expression of type 2 gene network genes in their sputum cells, measures of sputum eosinophil inflammation were not higher in this subgroup (Table). Conclusion Secretor status does not influence the prevalence of mucus plugging in asthma patients, and we did not confirm a prior report that type O secretors have an increased risk of asthma exacerbation. Although type O secretors have modestly increased FeNO levels and increased expression of type 2 immune genes in their sputum, it is not clear if this is a biologically important signal. 1. Innes et al. AJRCCM; 2011. 2. Saku et al. JACI; 2019. 3. Hara et al. AJRCMB; 2025 This abstract is funded by: The study was supported by the National Institutes of Health grants R01 HL080414 (JVF), P01 HL107202 (JVF), R01 HL164787 (JVF), U10 HL109172 (EI), U10 HL109152 (SEW), U10 HL109257 (MC), U10 HL109250 (SCE), U10 HL109146 (JVF), U10 HL109164 (ERB), U01 HL146002 (BDL), U10 HL109086 (DTM) and Sandler Asthma Basic Research Center at UCSF (JVF). The following companies provided financial support for study activities at the Coordinating and Clinical Centers beyond the third year of patient follow-up: AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi–Genzyme Regeneron, and Teva. These companies had no role in study design or data analysis, and the only restriction on the funds was that they be used to support the SARP initiative.
C34-10 Inflammatory Genes Are Downregulated in Induced Sputum of Corticosteroid Responders but Unchanged in Non-Responders
Zein, J G, Nixon, L, Kyriakidou, M, Hu, B, Castro, M, Denlinger, L C, Erzurum, S C, Fahy, J V, Gaston, B, Israel, E, Jarjour, N N, Levy, B D, Mauger, D, Moore, W C, Ortega, V E, Phipatanakul, W, Woodruff, P G, Wenzel, S E, Meyers, D A, Bleecker, E R, Zein, Joe , Denlinger, Loren C. , Fahy, John V. , Israel, Elliot , Levy, Bruce David , Phipatanakul, Wanda , Wenzel, Sally E. , Meyers, Deborah A.

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.595 Get It

Abstract Rationale We hypothesize that corticosteroid resistance causes uncontrolled inflammation and severe asthma. The genetic and molecular mechanisms underlying steroid responsiveness in asthma remain poorly understood (PMID28493293). This study aims to characterize transcriptomic profiles distinguishing steroid responders from steroid resistant asthma. Methods Longitudinal bulk RNA-seq of SARP3 sputum samples was analyzed before and after an “induced phenotype” with 40 mg triamcinolone acetonide (TCA) injection (PMID 27967215). Participants were classified as responders or non-responders based on whether their FEV₁ change after TCA exceeded the median. Paired differential gene expression analyses were performed separately for each group using limma and voom, with participant as a factor and adjustment for sputum cell count differentials. Z-scores were calculated to compare gene expression changes after TCA injection between responders and non-responders, and pathway enrichment was assessed using the fgsea package. Results Baseline demographics and clinical characteristics of 696 SARP3 asthma participants receiving TCA are shown in Table 1. The median [IQR] FEV1 change post-TCA was 1.81% [-2.16, 7.17]. Responders had higher baseline FEV1%, FEV1/FVC ratio, blood eosinophil counts, and sputum eosinophil percentages, but lower serum CRP levels. Steroid responsiveness was associated with asthma severity (Table 1). Among 154 participants with paired sputum RNA-seq data, 70 (45%) exhibited >1.81% improvement in FEV₁ and were classified as responders. Following TCA treatment, non-responders showed no significant changes in gene expression. In responders, 18 genes were upregulated and 203 downregulated. Downregulated genes were associated with Th2 immunity (IL13, IL1RL1, CCL17, SIGLEC8), IgE signaling (FCER1A, FCER2), epithelial barrier function and mucus production (MUC2, MUC7, ALOX15, TFF3), tissue remodeling and fibrosis (MMP10, TIMP3), ciliary function (DNAH5, CFAP43, FOXJ1), and airway hyperreactivity (HRH4, RAMP1). Key genes notably downregulated in responders compared to non-responders included IL13, CCL5, PTGDR2, FCER2, and CLEC10A. Pathway analysis revealed enhanced IL-10-mediated anti-inflammatory signaling, suppression of pro-inflammatory pathways (NF-κB, IL-1, Th1/Th2, asthma, arachidonic acid metabolism, chemokine, NOTCH4), and regulation of mitochondrial oxidative phosphorylation. Conclusions Steroid resistance impairs glucocorticoid-mediated suppression of pro-inflammatory pathways, including NF-κB, IL-1, and Th1/Th2 signaling. This persistent airway inflammation limits improvements in lung function and contributes to worse clinical outcomes, including increased airflow obstruction, and symptom burden. Glucocorticoid resistance in asthma may be driven by receptor dysfunction, airway inflammation, epigenetic changes, and environmental exposures resulting in persistent airway inflammation and remodeling. Elucidating the molecular mechanisms underlying steroid resistance is critical for developing personalized targeted therapies in asthma. This abstract is funded by: NIH-NHLBI - R01 HL161674 (PI: Joe Zein)
C34-11 Sex May Modulate the Association Between Dnah11 Primary Ciliary Dyskinesia Risk Variants and Asthma
Kyriakidou, M, Marozkina, N, Nixon, L, Hu, B, Silveyra, P, Ortega, V E, Bleecker, E R, Meyers, D A, Gaston, B, Zein, J G, Marozkina, Nadzeya , Meyers, Deborah A. , Zein, Joe

American Journal of Respiratory and Critical Care Medicine | May 18, 2026 | Volume: 212 | Issue: Supplement_1 | Pages: No page available

10.1093/ajrccm/aamag162.596 Get It

Abstract Rationale Primary ciliary dyskinesia (PCD) pathogenic gene variants disrupt motile cilia, leading to both PCD and asthma through epithelial dysfunction. Asthma shows sex differences, and progesterone regulates ciliary beat frequency, indicating that genetic defects in ciliary proteins may exert sex-dependent effects. Therefore, we hypothesize that rare, pathogenic variants in PCD genes contribute to asthma risk in a sex-specific manner. Methods We performed a rare-variant aggregation analysis of the DNAH11 gene using UK Biobank OQFE exome dosages, with sex-stratified analyses. Within each sex, genotype dosages were coded as individual-level minor allele counts (0-2) and filtered to include variants with a minor allele frequency (MAF) ≤1% and a minor allele count (MAC) ≥5 across the cohort. Asthma phenotypes were defined from a curated dataset (N = 452,927), excluding COPD and other lung diseases. For each sex, logistic null models adjusted for age were fitted, and gene-level associations for binary outcomes were tested using SKAT, Burden, and SKAT-O. To assess variant-specific influences, we performed leave-one-out (LOO) analyses, sequentially omitting each variant and recalculating p-values. The effect size across the cohort was calculated by fitting a Firth logistic regression comparing carriers to non-carriers, adjusted for age by sex. Finally, sex modification was tested using a Firth model including carrier-by-sex interaction term. Results After filtering, DNAH11 included two rare variants; 7:21564185-G>T and 7:21591370-G>A in each sex (MAF≈1-2x10-5). Among females (N = 245,718; 28,649 with asthma), 16 carriers were observed (MAC≈16). Gene-based tests showed a significant association with asthma (Burden_p=0.004; SKAT-O_p=0.005; SKAT_p=0.013). Firth carrier model OR was 4.58 (95% CI 1.62-11.98, p = 0.0055) (Figure 1A). LOO analyses (Figure 1B) showed both variants contributed to the signal; removing 7:21591370-G>A increased SKAT-O p to 0.075 (Δ-log10p≈+1.15), while removing 7:21564185-G>T increased p to 0.014 (Δ-log10p≈+0.41, with the association remaining significant after removing the latter. Among males (N = 207,209; 20,777 with asthma), 10 carriers were observed (MAC≈10) with no significant association (Burden_p=0.926; SKAT-O_p=0.797; SKAT_p=0.668; Firth_p=0.781). The carrier-by-sex interaction term in the combined Firth model was not significant (p = 0.190), suggesting the female-specific signal could not be detected in the males due to limited power. Conclusions This analysis provides primary evidence that these rare, pathogenic variants in the DNAH11 PCD gene may contribute to asthma susceptibility in a sex-specific manner, with a significant association observed only in females. The signal was predominantly driven by 7:21591370-G>A. This suggests that genetic disruption of ciliary function may interact with female-specific hormonal factors (i.e., progesterone) to influence asthma risk. This abstract is funded by: NIH