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Ortega, Victor E.

https://orcid.org/0000-0001-6361-7372

Mayo Clinic

Mayo Clinic

Citations 21

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.
Multi-trait polygenic scores for COPD and COPD exacerbations implicate druggable proteins
Zhang, Chengyue , He, Yixuan, Zhang, Jingzhou, Feldman, William B. , Ding, Yi , Pasaniuc, Bogdan, Chang, Diana, Chen, Qingwen , Lasky-Su, Jessica, Hecker, Julian, Tobin, Martin D., Chen, Jing , Kalra, S. , Pratte, Katherine A., Im, Hae Kyung, Wan, Emily S., Manichaikul, Ani, Silverman, Edwin K., Bowler, Russell P., Lange, Leslie A., Ortega, Victor E., Cho, Michael H., Moll, Matthew R., Konigsberg, Iain R. , Zhang, Jingzhou , Chikowore, Tinashe , Hu, Xiaowei , Paşaniuc, Bogdan , Lasky‐Su, Jessica , Tobin, Martin D. , Pratte, Katherine , Wan, Emily S. , Manichaikul, Ani , Silverman, Edwin K. , Bowler, Russell P. , Lange, Leslie A., Ortega, Victor E. , Martin, Alicia R. , Cho, Michael H. , Moll, Matt

JCI Insight | February 19, 2026 | Volume: 11 | Issue: 7 | Pages: No page available

10.1172/jci.insight.199951 Get It

BACKGROUND We constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting. METHODS PRSmix + , a multi-trait PRS framework, is used to train a composite PRS (PRS multi ) in COPDGene non-Hispanic White participants ( n = 6,647). Associations of PRS multi with COPD status (GOLD 2–4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American ( n = 2,466), ECLIPSE ( n = 1,858), Mass General Brigham Biobank ( n = 15,152), and All of Us ( n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRS multi and were validated with proteomic data in COPDGene ( n = 5,173) and UK Biobank ( n = 5,012). RESULTS PRSmix + selected 7 traits for PRS multi . In multivariable models, PRS multi was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28–1.94]) and exacerbation frequency (meta-analysis RE β 0.21 [95% CI: 0.11–0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRS multi outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION COPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.
Reply to Abushanab et al. : Longitudinal Outcomes of Pi*MZ versus Pi*MM Subjects Stratified by Former and Current Smoking Status
Barjaktarević, Igor , Zhang, Zian , Buhr, Russell G. , Hixson, Roxana, Ortega, Victor E. , Buhr, Russell G , Ortega, Victor, Barjaktarevic, Igor , Tashkin, Donald P.

Annals of the American Thoracic Society | December 1, 2025 | Volume: 22 | Issue: 12 | Pages: 1969-1970

10.1513/annalsats.202508-882le Get It

Matrix metalloproteinases and disease severity among PI*MZ and PI*ZZ individuals in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) cohort
Tejwani, Vickram , Pratte, Katherine , Ortega, Victor E. , Kaminski, Naftali , Kaminski, Naftali , Bowler, Russell P. , Serban, Karina A. , Stoller, James K. , Strange, Charlie

BMJ Open Respiratory Research | November 18, 2025 | Volume: 12 | Issue: 1 | Pages: e003585

10.1136/bmjresp-2025-003585 Get It

Introduction There is an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygotes for the alpha-1 antitrypsin (AAT) Z allele (PI*MZ), but there is significant variation in outcomes. Matrix metalloproteinases (MMPs) contribute to worse airway disease and emphysema. Given that the AAT protein is an antiprotease, we hypothesised that MMPs play a modifying role among AAT-deficient individuals. Methods We studied PI*MZ (n=39) and PI*ZZ (n=27) individuals from the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis Study cohort. MMP (MMP3, MMP9, MMP10, MMP12 and MMP15) gene expression was assessed in bronchoalveolar lavage cells and peripheral blood mononuclear cells. Plasma protein MMP (MMP3, MMP9, MMP10 and MMP12) expression was assessed using SomaScan and BAL MMP15 protein using ELISA. MMP values were log-transformed, and linear regression analyses were used to assess lung function, patient-reported outcomes and CT emphysema adjusted for age, body mass index, sex and duration of smoking. Results Alveolar MMP3 and MMP15 were uniquely associated with worse lung function, patient-reported outcomes and emphysema among PI*MZ individuals. MMP10 was associated with less disease severity among PI*MZ individuals. Discussion Our study shows that alveolar MMP3 and MMP15 may uniquely contribute to disease among PI*MZ individuals, raising the possibility that they could serve as biomarkers or therapeutic targets in this highly prevalent COPD phenotype. Furthermore, we show that MMP10 may serve a protective effect. In aggregate, these data support further studies of the MMP pathway among lung-affected PI*MZ individuals, as they may serve as biomarkers or pharmacological targets in future studies.
SPIROMICS HF: Rationale, Design, and Reproducibility of Measures
Barr, R. Graham , Lima, João A.C. , Prince, Martin R. , Abraham, Theodore P. , Agarwal, Prachi , Arora, Garima , Balasubramanian, Aparna , Barjaktarević, Igor , Bello, Natalie A. , Carr, James C. , Cooper, Christopher B. , Finn, J. Paul , Freed, Benjamin H. , Hansel, Nadia N. , Hsu, Jeffrey J. , Kitzman, Dalane W. , LaBounty, Troy , Lee, Yoo Jin , Liu, Jing , Lloyd, Steven G. , Markl, Michael , Ortega, Victor E. , Paine, Robert , Peters, Stephen P. , Schroeder, Joyce , Shepshelovich, Daniel , Sun, Yifei , Wells, J. Michael , Wieben, Oliver , Woodruff, Prescott G. , Ambale-Venkatesh, Bharath , Agarwal, Prachi P , Arora, Garima , Balasubramanian, Aparna , Barjaktarevic, Igor , Bello, Natalie A , Bluemke, David A , Budoff, Matthew , Carr, James C , Chaudhuri, Dipayan , Cooper, Christopher B , Couper, David , Finn, J Paul , Freed, Benjamin H , Han, MeiLan King , Hansel, Nadia N , Hsu, Jeffrey J , Kitzman, Dalane W , Krishnan, Jerry A , LaBounty, Troy M , Lee, Yoo Jin , Liu, Jing , Lloyd, Steven G , Mukherjee, Monica , Beussink-Nelson, Lauren , Ohar, Jill , Paine, Robert , Schroeder, Joyce D , Shen, Wei , Sun, Yifei , Vogel-Claussen, Jens , Watson, Karol E. , Wells, J Michael , Wieben, Oliver , Woodruff, Prescott G , Shah, Sanjiv J , Markl, Michael , Barr, R. Graham , Bluemke, David A. , Budoff, Matthew J. , Couper, David , Mukherjee, Monica , Vogel‐Claussen, Jens

Circulation: Heart Failure | November 5, 2025 | Volume: 18 | Issue: 12 | Pages: No page available

10.1161/circheartfailure.125.012833 Get It

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.
Neutrophil-to-Lymphocyte Ratio as a Biomarker in Clinically Stable Chronic Obstructive Pulmonary Disease: SPIROMICS Cohort
HOESTEREY, DANIEL , Markovic, Daniela , Buhr, Russell G. , Tashkin, Donald P., Barr, R. Graham, Belperio, John A. , Bowler, Russell P. , Bleecker, Eugene R., Couper, David J., Cooper, Christopher B. , Han, MeiLan K., Hansel, Nadia N. , Hastie, Annette T. , Hoffman, Eric A. , Kanner, Richard E. , O’Neal, Wanda K. , Ortega, Victor E. , Paine, Robert, Shrivastav, Abhishek K., Wells, J. Michael , Woodruff, Prescott G. , Hoesterey, Daniel T , Buhr, Russell G , Bowler, Russell P , Doerschuk, Claire M , Drummond, M Bradley , Hastie, Annette T , Hoffman, Eric A , Huang, Yvonne J , Krishnan, Jerry A , Wells, J Michael , Curtis, Jeffrey L , O'Neal, Wanda K , Dang, Hong , Barr, R. Graham, Couper, David J., Criner, Gerard J. , Doerschuk, Claire M. , Dransfield, Mark T. , Drummond, Michael , Fawzy, Ashraf , Freeman, Christine M. , Han, MeiLan King , Kaner, Robert J. , Kim, Victor, Martínez, Fernando J. , Shrivastav, Abhishek K., Curtis, Jeffrey L. , Barjaktarević, Igor

Annals of the American Thoracic Society | September 8, 2025 | Volume: 22 | Issue: 12 | Pages: 1881-1890

10.1513/annalsats.202412-1265oc Get It

Abstract Rationale Inflammation is central to chronic obstructive pulmonary disease (COPD) pathogenesis but incompletely represented in COPD prognostic models. The neutrophil-to-lymphocyte ratio (NLR) is a readily available inflammatory biomarker. Objectives To explore the associations of NLR with smoking status, clinical features of COPD, and future adverse outcomes. Methods We analyzed NLR calculated from the complete blood count of participants who currently or formerly smoked (n = 2,624) and tobacco-naive control subjects (n = 187) in the SPIROMICS multicenter observational cohort study. We assessed the stability of NLR at 6 weeks and 1 year, the association with select blood biomarkers, and the impact of smoking on NLR and cell counts. We stratified participants by NLR quartiles to compare cross-sectional clinical features at enrollment, prospectively observed exacerbations at 1 year, and mortality during longitudinal follow up. Results Higher NLR quartiles were broadly associated with more severe clinical features of COPD. NLR values were repeatable at 6 weeks (intraclass correlation coefficient, 0.74) and 1 year (intraclass correlation coefficient, 0.62). The impact of smoking on NLR varied with the severity of airflow limitation, mediated by an interaction between smoking, forced expiratory volume in 1 second percent predicted, and neutrophil counts but not lymphocyte counts. The highest NLR quartile (>3.11) was associated with an increased risk of exacerbation over 1 year (adjusted odds ratio, 1.51; 95% confidence interval, 1.18, 1.92) and increased risk of mortality (adjusted hazard ratio, 1.41; 95% confidence interval, 1.20, 1.66) compared with quartiles 1–3. Conclusions Elevated NLR in stable COPD is a widely available biomarker associated with increased risk for exacerbation and death. The impact of cigarette smoking on NLR varies with disease severity.
Serum IgA isotypes are associated with percent emphysema, wall thickness and lung function decline
Pottinger, Tess D. , Buschur, Kristina L., Ortega, Victor E. , Bleecker, Eugene R., Meyers, Deborah A., Hoffman, Eric A. , Smith, Benjamin M. , Kiryluk, Krzysztof , Barr, R. Graham , Pottinger, Tess , Kiryluk, Krzysztof , Hoffman, Eric A , Liu, Zhonghua , Liu, Lili , Curtis, Jeffrey L. , Manichaikul, Ani , Rich, Stephen S. , Meyers, Deborah A. , Novák, Jan

Thorax | August 22, 2025 | Volume: 80 | Issue: 11 | Pages: 829-837

10.1136/thorax-2025-222990 Get It

Rationale Immunoglobulin A (IgA) deficiency, a rare, highly heritable trait, is associated with frequent pulmonary infections, emphysema, airway changes and low lung function; however, it is unclear if reduced IgA levels may affect lung structure and function. Methods Serum IgA, IgA1 and galactose-deficient IgA1 (Gd-IgA1) levels were measured in the population-based Multi-Ethnic Study on Atherosclerosis (MESA). The MESA Lung Study measured percent emphysema on cardiac CT and airway dimensions on chest CT, and performed spirometry. Regression models were evaluated after adjustment for demographic and CT factors. Mendelian randomisation (MR) analyses were conducted using genetic variants from the Trans-Omics for Precision Medicine (TOPMed) programme. A replication analysis was performed in the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS). Measurements and main results Among 5497 participants, lower log-normalised serum IgA levels were associated with greater percent emphysema (β=−0.084; 95% CI −0.14 to –0.026; p=0.005), which was confirmed on MR (β=−0.79; 95% CI −1.4 to –0.18; p=0.011). Greater log-normalised serum Gd-IgA1 levels were associated with airway wall thickness (β=0.0079; 95% CI 0.0017 to 0.014; p=0.012; n=2580) and decline in the forced expiratory volume in one second (FEV1) (β=−0.012; 95% CI −0.021 to –0.0036; p=0.0055; n=2778) and FEV1/forced vital capacity (FVC) ratio (β=−0.0028; 95% CI −0.0048 to –0.00084; p=0.0054; n=2778). Conclusion Lower serum IgA levels were associated with greater percent emphysema. Additionally, higher Gd-IgA1 levels were associated with airway wall thickness and lung function decline. These findings support a protective role of IgA in emphysema pathogenesis and possible deleterious role of Gd-IgA1 in airway diseases.
Differences in Airway Epithelial Gene Expression in Resilient vs Non-resilient Smokers
Oh, Anna , Niederhuber, Matthew J. , Jones, Corbin D. , Brennan, Tara A., Currin, Kevin W., Kennedy, Sarah , Christenson, S., Bon, Jessica , Comellas, Alejandro P. , Cooper, C.B., Hansel, N.N., Kaner, R.J. , Marchetti, Nathaniel , Onofrei, C.D., Ortega, Victor E. , Paine, Robert , Woodruff, P., Investigators, SPIROMICS, Christenson, Stephanie A. , Comellas, Alejandro P , Christenson, Stephanie A , Oh, A., Liu, Heng , Kennedy, S., Couper, David , Barjaktarević, Igor , Barr, R. Graham , Bowler, Russell P. , Cooper, C.B. , Han, Mingyuan , Krishnan, Jerry A , Martínez, Fernando J. , Wells, J. Michael

American Journal of Respiratory and Critical Care Medicine | May 11, 2025 | Volume: 211 | Issue: Supplement_1 | Pages: A7375-A7375

10.1164/ajrccm.2025.211.abstracts.a7375 Get It

Abstract Introduction Resilient smokers, who maintain respiratory health despite smoking, remain poorly characterized. Airway epithelial cell gene expression in resilient smokers can provide insight into mechanisms and pathways that may protect smokers from developing smoking-related lung disease. The objective of this study is to identify genes and potential pathways associated with lung-related resilience. Methods Resilient smokers were defined based on a previously published multi-dimensional definition which includes the absence of: 1) spirometric airflow limitation, 2) symptoms (cough/sputum, dyspnea), 3) radiographic (HRCT) abnormalities, 4) exacerbations, and 5) an accelerated FEV1 decline. “Non-resilient” smokers had preserved spirometry but showed abnormalities in at least one domain of resilience. We analyzed airway epithelial brush samples from 21 resilient and 34 non-resilient smokers from SPIROMICS. Differential gene expression was performed using DESeq2 package in R, which estimates differential expression using generalized linear models. We adjusted for sequencing batch, age (continuous), race, gender, and current smoking status. While controlling for these covariates we evaluated differential gene expression between resilient and non-resilient smokers, the interaction between resilience and smoking status, and in each sub-category of resilient (absence of symptoms, radiographic abnormalities, exacerbations, and accelerated decline in FEV1). Results We identified 98 genes that were differentially expressed (FDR ≤0.1) when comparing resilient to non-resilient smokers, 20 of those genes were up regulated in resilient smokers (Figure 1). Notable genes included cadherin-12 (CDH12), aspartate beta-hydroxylase (ASPH), and protein kinase AMP-activated alpha 2 (PRKAA2). CDH12 is involved in cell adhesion and epithelial integrity. ASPH influences cell adhesion and signaling. PRKAA2 plays role in cellular homeostasis and stress response, which may be altered in non-resilient smokers, affecting cellular metabolism and inflammation. BPI folding containing family A member (BPIFA1) was significantly associated with smoking status in the interaction analysis, suggesting its role in modulating the impact of smoking on resilience. BPIFA1 has anti-microbial properties, regulates immune responses, and contributes mucosal surface protection. Sub-category analysis identified 17 genes associated with resilience to symptoms and 2 genes related to physiologic resilience (FEV1 decline), though no significant genes were associated with radiographic or exacerbation resilience. Conclusion Differential gene expression of airway epithelial cells identified distinct expression patterns between resilient and non-resilient smokers. Specifically, genes associated with epithelial cell adhesion, signaling, and cellular homeostasis were up regulated in resilient smokers. These findings suggest that resilient smokers may have transcriptomic profiles and potential mechanisms that mitigate the effects of cigarette smoke.
Epigenomic and Transcriptomic Regulation of the MUC5B/MUC5AC Locus in Bronchial Airway Epithelium and Association With Early Small Airways Disease in Spiromics
Ortega, Victor E. , Chen, Xinyi , Shrivastav, A.K. , Zein, Joe , Howard, Timothy D. , Hawkins, Gregory A., Bowler, R.P., Comellas, Alejandro P. , Cooper, C.B. , Galbán, Craig J. , Hansel, Nadia N. , Hastie, Annette T. , Kanner, Richard E. , Martinez, F.J., Paine, Robert , Hoffman, E.A., Meyers, Deborah A. , Woodruff, P., Curtis, J.L., Bleecker, E.R., Christenson, S., C, NHLBI Subpopulations and Intermediate Outcomes Measures in, Christenson, Stephanie A. , Comellas, Alejandro P , Christenson, Stephanie A , Shrivastav, A.K., Barjaktarević, Igor , Barr, R. Graham , Couper, David , Han, MeiLan King , Kaner, Robert J. , Martinez, F.J., O’Neal, Wanda K. , Hoffman, E.A., Curtis, J.L., Huang, Yvonne J

American Journal of Respiratory and Critical Care Medicine | May 11, 2025 | Volume: 211 | Issue: Supplement_1 | Pages: A5245-A5245

10.1164/ajrccm.2025.211.abstracts.a5245 Get It

Abstract Rationale: MUC5B and MUC5AC are neighboring genes on chromosome 11p15 that encode the two predominant mucins secreted in the respiratory airways. Increased airway mucin concentrations and an imbalance between these two mucins drive COPD symptoms and the development of airflow obstruction or COPD, but the epigenomic regulation of this loci has not been characterized in the airways. Methods: We isolated DNA from bronchial airway brushings of 72 participants with >20 pack-years smoking history from the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS). 36 participants had GOLD-based moderate-to-severe COPD (FEV1/FVC<0.70, FEV1<80%) and 36 were without or with mild COPD. We used the Illumina Infinium Methylation EPIC BeadChip Array to assess proportion of DNA methylation (β) spanning 689,937 CpG sites. We evaluated proportional DNA methylation (β) at 96 CpG loci within a 103kB region using matrixQTL for cis-expression quantitative trait methylation (eQTM: 10kB flanks relative to MUC5AC/MUC5B) integrating bulk RNA-seq data and mQTL models integrating gene sequencing data to identify DNA variation associated with proportion eQTM methylation. Models included age, sex, BMI, clinical site, current smoking vs past smoking, total pack-years, three ancestral components of ancestry, chipset, and position. Results: We identified a top eQTM, cg00524486, marginally associated with MUC5B expression (coefficient estimate=8.75, punadjusted=0.0014, pFDR=0.065, Figure 1B). This eQTM was associated with CT scan parametric response mapping-based functional small airways disease (PRM-fSAD, beta coefficient[β]=3.64, p=0.011). We tested for DNA variation associated with methylation of this top eQTM which identified two methylation quantitative trait loci (mQTL: rs885454 [β=0.044, minor allele frequency[MAF]=0.09, pFDR=0.01], rs868902 [β=0.020, MAF=0.43, pFDR=0.08, Figure 1A) associated with cg00524486 methylation, of which the more frequent mQTL, rs868902, was marginally associated with PRM-fSAD (p=0.07) in the larger SPIROMICS cohort with MUC5B DNA sequencing data. Conclusions: This preliminary multi-omic study of the lower airway epithelium demonstrates that the expression of MUC5B is epigenetically regulated by neighboring CpG probe methylation (eQTM) represented by DNA variation (mQTL). These studies require further confirmation in a larger dataset of airway samples and support a role for epigenetic variation as a biologic contributor and biomarker of early COPD pathogenesis.
Proteomics of CT Emphysema Subtypes in the General Population. The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Guzman, Daniel E., Sun, Yifei , Bertoni, Alan, Johnson, W. Craig , Watson, Karol E., Hoffman, E.A., Dubin, Robert , Oelsner, Elizabeth C. , Laine, Andrew F. , Ortega, Victor E. , Oelsner, Elizabeth C , Pottinger, Tess D. , Post, Wendy S. , Allen, Norrina B. , Pankow, James S. , Manichaikul, Ani , Dubin, R., Deo, Rajat , Angelini, Elsa D. , Bowler, Russell P. , Ganz, Peter , Barr, R. Graham

American Journal of Respiratory and Critical Care Medicine | May 11, 2025 | Volume: 211 | Issue: Supplement_1 | Pages: A5009-A5009

10.1164/ajrccm.2025.211.abstracts.a5009 Get It

Abstract Chronic obstructive pulmonary disease (COPD) and pulmonary emphysema were the third-leading cause of death globally in 2019. Besides alpha-1 antitrypsin deficiency, emphysema lacks disease-modifying medications due to its heterogeneity and there remains a need to further investigate emphysema subtypes to advance its diagnosis and treatment. Recent unsupervised machine learning of the texture and anatomical location of emphysema on computed tomography (CT) images of the lung defined six quantitative CT emphysema subtypes uniquely associated with specific gene variants, environmental exposures, symptoms, physiology and clinical events. We aim to identify associations of plasma proteins with each CT emphysema subtype cross-sectionally in a multi-ethnic general population sample. MESA is a prospective cohort study that recruited 6,814 participants from six communities who self-identified as White, Black, Hispanic, or Asian race/ethnicity, ages 45-84 years old and free of clinical cardiovascular disease in 2000-02. The MESA Lung Study performed CT scans among 3,137 participants in 2010-12, which were labeled with previously described (PMID: 37268414) CT emphysema subtypes. Proteomics was assessed using SomaScan version 4.1 assay (7,596 plasma proteins). Linear regression models were adjusted for age, height, weight, sex, race, educational attainment, smoking status, pack years, urine cotinine level, body-mass index (BMI), estimated glomerular filtration rate (eGFR), CT scanner manufacturer and other CT emphysema subtypes. Results were adjusted to reflect a False Discovery Rate (FDR) p-value of less than 5% using the Benjamini-Hochberg method. Among 2,343 participants with both CT and proteomic data (mean age 69.5 years, 52.3% women, 23.7% with COPD), we identified statistically significant associations of proteins with the vanishing lung subtype (42 proteins; top hit Natural cytotoxicity triggering receptor 3 ligand 1, q = 2.9[asterisk]10-9), restrictive combined pulmonary fibrosis/emphysema (CPFE) subtype (11 proteins; top hit Integrin alpha-2/b1, q=1.0[asterisk]10-5), the combined bronchitis-apical emphysema subtype (9 proteins; top hit Desmoglein-2, q=8.8[asterisk]10-13), and the diffuse emphysema subtype (4 proteins; top hit Pulmonary surfactant-associated protein D, q=5.7[asterisk]10-3). No significant proteins were associated with the obstructive CPFE or senile subtypes after FDR correction. Most proteins were uniquely associated with one CT emphysema subtype, while a few proteins were associated with more than one subtype. This study identified specific proteins for different CT emphysema subtypes, many of which have been related less specifically to emphysema, including pulmonary surfactant production, anti-inflammatory pathways, and mitochondrial deregulation, amongst others. Validation of these proteomic associations can provide insight into further pathway assessment, clinical biomarker discovery, and targeted prevention of emphysema in the general population.