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Shrivastav, A

Mayo Clinic

Mayo Clinic in Arizona

Citations 4

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.
C101-06 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
B29-14 Genetic Insights Into Asthma Exacerbations: A Gwas in the Mayo Clinic Tapestry Cohort
Agogo-Mawuli, P S, Bleecker, E R, Fernandez, G, Grilli, C, Chiarella, S E, Shrivastav, A, Upjohn, D, Egan, J, Cardet, J C, Castro, M, Denlinger, L C, Vierkant, R, Luehrs, T, Sicotte, H, Lazaridis, K, Fahy, J V, Israel, E, Jarjour, N N, Mauger, D T, Moore, W C, Levy, B D, Woodruff, P G, Wenzel, S E, Meyers, D A, Zein, J G, Ortega, V E, Agogo-Mawuli, Percy S. , Cardet, Juan Carlos , Denlinger, Loren C. , Vierkant, Robert A. , Luehrs, Tony, Sicotte, Hugues , Kn, Lazaridis, Fahy, John V. , Israel, Elliot , Levy, Bruce David , Wenzel, Sally E. , 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/aamag162.432 Get It

Abstract Rationale Asthma contributes substantially to healthcare burden and morbidity through frequent exacerbations. Emerging evidence suggests that genetic factors play a crucial role in modulating susceptibility to asthma exacerbations. To better understand the genetic architecture of exacerbations, we conducted a genome-wide association study (GWAS) in the Tapestry cohort. Methods The Tapestry Study, a large-scale, decentralized and clinical grade genomic sequencing study, conducted Exome+® sequencing at Helix, Inc. on 98,075 Mayo Clinic participants. After excluding patients with ≥10 pack-years of smoking and/or emphysema, we performed a GWAS of asthma exacerbations in 3,960 adults with asthma based on ICD codes. Cases (n = 1,059) were defined as individuals who experienced at least two exacerbations between 2020 and 2025; the remaining 2,901 individuals served as controls. Asthma exacerbations were defined by oral or systemic corticosteroid prescriptions with durations ranging from 3 days up to 28 days. Logistic regression models adjusted for age, sex, BMI, and the first six principal components of ancestry. Replication was performed in 1,273 asthma patients (439 African Americans and 834 non-Hispanic Whites) from the NHLBI-sponsored Severe Asthma Research Program (SARP 1-3), with adjustments for age, sex, BMI, and the first 10 principal components of ancestry. Results Based on a minor allele frequency (MAF) threshold of > 0.05, we analyzed 5,256,135 genome-wide variants. Genome-wide significant associations for asthma exacerbations (p < 5.0 × 10⁻8) included loci at a pseudogene in SMPD4P1 (rs680548, MAF = 0.39, OR = 1.37, p = 9.10 × 10⁻9). Additional variants showing suggestive associations included loci within ENDOD1 (rs638776, OR = 0.69, p = 1.20 × 10⁻6), PCSK2 (rs2206454, OR = 1.32, p = 3.53 × 10⁻6), RBFOX1 (rs17667084, OR = 0.60, p = 5.11 × 10⁻6), and CDC42EP3 (rs721660, OR = 1.29, p = 5.68 × 10⁻6). Subthreshold associations in Tapestry including loci at CDC42EP3 (rs4670213, OR = 1.27, p = 1.41x10-5, MAF = 0.36), and SDR39U1 (rs12587663,OR = 0.83, p = 5.86x10-4, MAF = 0.46) were replicated in the SARP longitudinal visit 5 with p-values of 8.523x10-3 (rs4670213, OR = 1.78), and 2.88x10-4 (rs12587663,OR=0.43), respectively. Conclusion Our GWAS for asthma exacerbations in the Tapestry cohort identified variant loci relevant to mitophagy mechanisms (CDC42EP3, PMID: 40783597), immune signaling and RNA splicing regulation (RBFOX1, PMID: 31301374), and neuromodulatory pathways (PCSK2, PMID: 32794589), all previously implicated in asthma pathophysiology. Collectively, these findings highlight potential novel genetic contributors to asthma exacerbations and provide a foundation for improving risk stratification and therapeutic targeting in asthma management. This abstract is funded by: This abstract is funded by: Mayo Clinic Funding: X01 from the NHLBI for TOPMed whole-genome sequencing and NIH grants R01 HL142992, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086, U10 HL109046.
B22-01 Local Ancestral Loci Associated With Lung Function in African American Asthma Populations
Shrivastav, A, Slack, S, Zein, J G, Chiarella, S E, Althoff, M D, Daya, M, Cardet, J C, Hastie, A T, Hawkins, G A, Moore, W C, Barnes, K, Busse, W W, Castro, M, Denlinger, L C, Erzurum, S C, Jackson, D J, Jarjour, N N, Levy, I, Mauger, D, Szefler, S J, Israel, E, Wenzel, S E, Wechsler, M E, Bleecker, E R, Meyers, D A, Johnson, R K, Ortega, V E, Zein, Joe , Althoff, Meghan D. , Daya, Michelle , Cardet, Juan Carlos , Hastie, Annette T. , Denlinger, Loren C. , Szefler, SJ, Israel, Elliot , Wenzel, Sally E. , Wechsler, Michael E , Meyers, Deborah A. , Johnson, Rachel K.

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

10.1093/ajrccm/aamag162.393 Get It

Abstract Rationale Higher African genetic ancestry has been associated with lower lung function, among individuals from specific racial-ethnic groups. The influence and interactions of genetic variation and ancestry in lung function is poorly understood. This study investigates ancestry-associated loci influencing lung function via admixture mapping and fine-scale allelic association. Methods 512 African American patients with asthma (≥12 years) from the Severe Asthma Research Program and Collaborative Study on the Genetics of Asthma (SARP/CSGA) cohorts were genotyped on the OmniExpress and HumanHap1M arrays or had whole-genome sequencing (WGS). For admixture mapping, global ancestry was inferred using ADMIXTURE and local ancestry estimated using RFMix v1.5.4 with CEU (N = 99) and YRI (N = 108) references across 15,095 local ancestry segments. Peak regions and contiguous segments (p < 10-3) were fine mapped in SARP using local ancestry estimated from WGS with MAF ≥0.03. The Local Ancestry Adjusted Allelic Association (LAAA) model was used to fine map local genetic effect, local ancestry effect, and the interaction between the two, adjusted for age, sex, height, BMI, cohort, and percentage global African ancestry. SNPs with local genetic or interaction p < 10⁻³ were tested for replication in 282 adolescent/adult participants from the Best African Response to Asthma Drugs (BARD) cohort genotyped with the MEGA array imputed to TOPMed (MAF ≥0.03). Results Mean African genetic ancestry was 81.3% in SARP and 80.1% in BARD. In SARP, African genetic ancestry was inversely associated with lung function (FEV₁:β = −7.9, p = 0.005; FVC:β = −9.0, p = 0.004), with stronger effects in females (FEV₁: β = −9.3, p = 0.003; FVC: β = −11.4, p = 0.001) than males (FEV₁:β = −6.4, p = 0.237; FVC:β = −5.7, p = 0.340). Similar total and sex-specific associations were identified in BARD. Admixture mapping in SARP/CSGA identified significant peaks for maximum FVC (p < 1.87 × 10⁻4) on chromosomes 8 and 17 near RP1 and RBFOX3, and near-significant peaks on chromosome 5 near IQGAP2, SNRPCP2, SV2C and for the maximum FEV₁/FVC ratio on chromosome 10 near PCDH15. Fine mapping identified the top SNP on chromosome 8 (rs73587686; p-allele-dose=9.0x10-5; RGS20; q11.23), with 62 additional SNPs overlapping RGS20. SNP rs7825816 was also identified in SARP (β = 2.35, p-allele-dose =1.03 × 10⁻4) and replicated in BARD (β = 1.15, p-allele-dose =0.03). In BARD, LAAA also identified eight additional SNPs (p ≤ 0.05) in the same LD block (chr8:53914976-53918297) overlapping with RGS20, ATP6V1H, and TCEA1. Conclusions We identified multiple chromosomal regions associated with lung function in asthma patients of predominantly African genetic ancestry. Lung function associations were strongest at genetic variation near a key that was replicated in an independent asthma cohort. This abstract is funded by: R01 K08 HL118128, R01 HL142992, R01 NR013700, R01 HL69167, R01 HL161674, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086-04, U10 HL098115, HL098102, HL098096, HL098075, HL098090, HL098177, HL098098, HL098107, HL098112, HL098103, and K12 HL89992