Clinical trial NCT01142947
Conditions: Asthma
Keywords: Inhaled corticosteroids Asthma Pharmacogenomics Genome wide association study Admixture mapping Continental population groups
Sponsor: Henry Ford Health System
Start date: 2007-10-01; Completion date: 2019-03-11
Enrollment: 362 participants; Allocation: NA; Intervention model: SINGLE_GROUP

Brief summary:
Inhaled corticosteroids (ICS) are considered first-line treatment for persistent asthma, yet little is known about the genetic factors that influence response to this therapy. This study seeks to quantify response to ICS therapy in African American and white patients, as well as look for genetic markers that predict treatment response.

Detailed description:
Inhaled corticosteroids (ICS) are considered first-line therapy for the management and control of patients with persistent asthma. Use of inhaled steroids has been associated with improved lung function, diminished symptoms, and fewer exacerbations. However studies show considerable inter-subject variability in ICS response. It has also been estimated that corticosteroid resistance accounts for half of all asthma-related health care costs. Therefore, identifying factors associated with ICS response is both clinical and economically important. African-American patients have been understudied with respect to genetic predictors of asthma controller medication response, and to date there have been no sufficiently powered genome-wide association studies of ICS treatment response among African American individuals with asthma. This issue is of particular importance, since African-American individuals are disproportionately affected by asthma-related complications. In this proposal, we seek to identify novel genetic loci associated with ICS treatment responsiveness (defined by the change in Asthma Control Test score) among African American individuals treated with beclomethasone dipropionate (BD) for 6 weeks. We will attempt to validate loci identified in the discovery set by 1) reassessing these variants for their interaction with ICS treatment on asthma exacerbations in a separate group of African American individuals with asthma, and 2) by reexamining the genetic association with change in asthma control among similarly treated (i.e., treatment with 6 weeks of BD) European Americans with asthma.

Arms: arm 1: Patients who meet eligibility criteria will be treated with 6 weeks of beclomethasone dipropionate to assess change in pulmonary function and asthma control. These change will be used as phenotypes in a genetic association study. There is no placebo group.
Interventions: intervention 1: beclomethasone dipropionate
Intervention descriptions: intervention 1: 160 mcg twice a day (320 mcg per day total)

Protocol documents:
Prot_SAP_000.pdf: 
Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE)   
 
Clinicaltrials.gov number: NCT01142947 
 
Updated: September 19, 2016 
 
 
 
 
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
PROTOCOL 
Study population 
All SAPPHIRE individuals were recruited from Henry Ford Health System, whose Institutional 
Review Board approved this study.  Informed written consent was obtained prior to the 
collection of any data.  If the participant was a minor (age <18 years), informed written consent 
was obtained from a legal guardian and written assent was obtained from the participant.  
Individuals were eligible to participate as asthma cases if they were 12-56 years of age, had a 
documented physician diagnosis of asthma, and no prior diagnosis of congestive heart failure or 
chronic obstructive pulmonary disease.   
At the time of enrollment, participants underwent a research evaluation.  Lung function 
testing was performed using a pneumotachometer in accordance with 2005 ATS/ERS guideline 
recommendations.  Reversible airway obstruction was assessed by administering 360µg (4 puffs) 
of albuterol sulfate from a standard metered dose inhaler (MDI).  Spirometry was obtained 
before and 15 minutes after bronchodilator administration.  For individuals with ≤12% 
improvement in their forced expiratory volume at 1 second (FEV1), a second dose of albuterol 
(360µg for individuals ≥18 years and 180µg for individuals <18 years) was administered 
followed by lung function reassessment 15 minutes after the second dose.  Individuals were 
considered to have reversible airway obstruction if their FEV1 improved by >12% after 
bronchodilator administration.   
 
Discovery Group 
Study participants who met the following criteria were invited to undergo a 6-week 
course of inhaled beclomethasone dipropionate hydrofluoroalkane (beclomethasone HFA): no 
use of inhaled or systemic corticosteroids in the 4 weeks preceding the evaluation, a pre-
bronchodilator FEV1 that was 40-90% of predicted, reversible airway obstruction (i.e., >12% 
change in FEV1 with albuterol administration), no smoking in the year prior to the evaluation and 
<10 pack-year smoking history in total, and not pregnant at the time of evaluation.  Individuals 
who met these criteria and consented to undergo treatment were instructed to use 320µg (i.e., 2 
puffs twice a day) of beclomethasone HFA daily via MDI (QVAR, Teva Respiratory LLC, 
Horsham, PA) with the use of a spacer device (AeroChamber Plus Flow-Vu spacer, Monaghan 
Medical Corp., Plattsburgh, NY).  Treatment adherence was monitored using a DOSER-CT 
device (Meditrack, Easton, MA).  This adherence monitoring device was fitted to each ICS MDI 
to count the total number of actuations.  The group of individuals who completed the 6-week 
course of ICS treatment and had genome wide genotype data (described below) comprised the 
biomarker discovery group.  Genome-wide genotyping was performed in African American 
individuals (self-reported race-ethnicity), who collectively comprised the largest population 
group in the SAPPHIRE cohort.  As a result, the discovery sample consisted of 244 African 
American individuals who had both completed 6 weeks of study administered ICS treatment and 
genome-wide genotype data.   
Genome-wide genotyping was performed using DNA isolated from whole blood and the 
Axiom AFR array (Affymetrix Inc., Santa Clara, CA).  Quality control of the array results 
included a dish quality control measure ≥0.82, an overall call rate ≥97%, and no discordance 
between patient-reported sex and the measured X-heterozygosity.  Genotyped single nucleotide 
polymorphisms with an overall SNP call rate <95%, a minor allele frequency (MAF) <5%, or 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
exact Hardy-Weinberg equilibrium p-value <10-4 were removed from the analysis.  Only 
autosomal SNPs were analyzed.   
 
Validation Groups 
Validation was carried out in 2 additional groups from the SAPPHIRE cohort.  The primary 
validation set consisted of African American SAPPHIRE participants (n=803) who met the 
following criteria: available prospective clinical data on asthma exacerbations from available 
electronic health records, measures of ICS exposure through pharmacy claims records, existing 
genome-wide genotype data meeting QC standards, and African American race-ethnicity by 
participant self-report.  Health records were used to identify severe asthma exacerbations and 
generate measures of ICS exposure over time.  Severe asthma exacerbation were defined as those 
requiring burst oral corticosteroids, an emergency department visit, or a hospitalization.   
We standardized each available ICS preparation on the U.S. market by multiplying the 
number of actuations per container by the milligram dose released per actuation and dividing by 
the milligram strength of the lowest recommended dose for that preparation as specified in 
National Asthma Education and Prevention Program. Expert Panel Report 3 (ERP-3) guidelines.  
Applying our standardization method to participant health data, we assigned each prescription 
fill the value assigned for each preparation and divided by the total number of days between fills 
(i.e., days until the next fill) to approximate the amount of ICS used each day.  We summed each 
daily value for 6 months and and divided by 180 to create a measure that could be interpreted as 
a 6-month average of the daily number of ICS doses (in units of what ERP-3 guidelines defined 
as a “low” dose for that preparation).  This process was repeated for each day of each 
individual’s follow-up to create a moving window of ICS exposure for participant in the primary 
validation set.  We also created a dichotomous indicator variable for each day of follow-up to 
denote when a patient had used a long-acting beta-agonist (LABA) in the preceding 180 days.  
As time-updated proxy measures of asthma severity, we created separate exposure variables for 
short-acting beta-agonist (SABA) MDI and nebulizer use.  The SABA measures were calculated 
by summing the doses filled over a 90 day moving window.  Therefore, the SABA measures 
represented the average number of SABA doses used per day in the preceding 3-months.  We 
also created a baseline asthma severity measure based on asthma rescue medication use in the 
preceding year as described by Allen-Ramey et al. (J Manag Care Pharm 2006; 12:310-21). 
The second validation group comprised European American individuals from the 
SAPPHIRE cohort (n=98) who met the same selection criteria and underwent the same 6-week 
ICS treatment protocol as the discovery set.  Because this group of European American 
SAPPHIRE participants had the same treatment regimen and follow-up duration as the discovery 
set, change in ACT composite score was used as the outcome variable.  Participants in this 
second validation group were genotyped for the rs3827907 SNP using a TaqMan SNP 
Genotyping Assay (Applied Biosystems). 
 
Statistical Analysis 
In the discovery analysis, we used an additive genetic model and linear regression to assess the 
relationship between genotype and change in ACT score over 6 weeks of ICS treatment.  To 
capture both an independent genetic effect and a modifying effect on ICS treatment response, we 
included both the main effect of each SNP and an interaction term between the SNP and ICS 
exposure.  The full model also included individual variables for patient age, sex, ACT score at 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
baseline (i.e., the time of enrollment into the study), smoking status (coded as never, past, and 
present), the first three principal components (derived using the program EIGENSOFT and 
representing underlying population substructure), and ICS exposure (continuous measure based 
on adherence).  To jointly test the effect of the SNP and the SNP x ICS interaction, we compared 
the full model containing all of the aforementioned variables with a reduced model (i.e., all of 
the variables in the full model except for the SNP and interaction term) using an F-test.   
 
SNP associations with P<5.0x10-7 (strict Bonferroni correction P<0.05/574,370=8.71x10-
8) from the discovery were reassessed in the validation groups.  The primary validation analysis 
was performed in African American SAPPHIRE participants who were not involved in the 6 
weeks of study-administered ICS treatment but did have longitudinal clinical information on 
asthma exacerbations (n=803).  Proportional hazards regression was used to evaluate the 
association between both the SNP term and the SNP x ICS interaction term with time-to-severe 
asthma exacerbation.  These models also accounted for patient age, sex, BMI, smoking status, 
ACT score at baseline (i.e., enrollment), baseline asthma severity score, LABA use (an indicator 
variable denoting use of an ICS-LABA combination inhaler), time-updated measures of SABA 
MDI and nebulizer use, the first 3 principal components, and the time-updated ICS exposure 
measure.  A 2-degree of freedom likelihood ratio test was used to evaluate the significance of the 
difference in model fit for all variables as compared with a reduced model without the SNP and 
the SNP x ICS interaction terms. 
 
 
We also assessed for replication in the 98 European American SAPPHIRE participants 
who completed 6-weeks of ICS treatment.  The linear regression analysis was the same as used 
in the discovery set with the exception that only the top variant, rs3827907, was assessed, and 
the regression model did not include principal components to account for underlying population 
structure. 
  
Analyses were performed using R statistical software.  
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
FIGURE LEGENDS 
 
Figure E1.  Quantile-quantile (Q-Q) plot of expected vs. observed genome-wide joint association 
test results before (A) and after (B) applying genomic control.  Each joint test estimated the 
combined effect of a single nucleotide polymorphism (SNP) and its interaction with inhaled 
corticosteroid (ICS) use on changes in asthma control occurring over 6 weeks of ICS treatment.  
Asthma control was measured using the composite Asthma Control Test (ACT) score.  The 
models also adjusted for patient age, sex, ACT score at baseline (i.e., the time of study 
enrollment), smoking status, the first three principal components, and ICS adherence.  The Q-Q 
plot before applying genomic control (plot A) showed mild inflation (l=1.09); this was corrected 
via genomic control (plot B).  
 
Figure E2.  LocusZoom plot of rs3827907 on chromosome 14.  Single nucleotide 
polymorphisms located within a 200 kilobase window upstream and downstream of rs3827907 
are shown.  P-values were generated using the joint (SNP and SNP*ICS combined) test of 
association with changes in asthma control occurring over 6 weeks of ICS treatment.  The SNP 
color represents the level of correlation between each SNP and rs3827907.  Genes located in the 
region are shown beneath the plotted SNPs. 
 
Figure E3.  Relationship between rs3827907 genotype and absolute change in Asthma Control 
Test (ACT) composite score among African American participants in the Study of Asthma 
Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) following 6 
weeks of observed inhaled corticosteroid (ICS) treatment.  Results are restricted to the 129 
individuals whose asthma was not controlled at baseline (ACT score ≤19) and are stratified by 
levels of patient ICS use (£75% adherence was considered low use and >75% adherence was 
considered high use). Black lines connect the means for each group.  
 
Figure E4.  Relationship between rs3827907 genotype and absolute change in Asthma Control 
Test (ACT) composite score among African American participants in the SAPPHIRE cohort 
following 6 weeks of observed inhaled corticosteroid (ICS) treatment (n=244).  The rs3827907 
genotype is categorized in TT homozygotes and C-allele carriers (denoted C- and representing 
individuals with either the CT or CC genotypes).  Results are stratified by levels of patient ICS 
use (≤75% adherence was considered low use and >75% adherence was considered high use).  
Black lines connect the means for each group. 
 
Figure E5.  Relationship between rs3827907 genotype and absolute change in Asthma Control 
Test (ACT) composite score among European American participants in the Study of Asthma 
Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) cohort following 
6 weeks of observed inhaled corticosteroid (ICS) treatment (n=98).  Results are stratified by 
levels of patient ICS use (£75% adherence was considered low use and >75% adherence was 
considered high use).  Black lines connect the means for each group.            
 
Figure E6.  Correlation of expression between protein-coding genes located within 1 megabase 
upstream and downstream of rs3827907 on chromosome 14.  Gene expression is based on read 
counts from RNA-seq data obtained from 158 African American participants from the Study of 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE).  Read 
counts were normalized using the program DESeq2 
(https://bioconductor.org/packages/release/bioc/html/DESeq2.html).  Gene expression of 
EDDM3B in whole blood was low and did not meet our criterion for evaluation (≥50% of 
individuals with read counts >0); therefore, it is not listed among the 32 genes evaluated for this 
region.   
 
Figure E7.  Effect of baseline measures of eosinophil-derived neurotoxin (EDN) on the 
relationship between rs3827907 C-allele carrier status and absolute change in Asthma Control 
Test (ACT) composite score among European American participants in the SAPPHIRE cohort 
following 6 weeks of observed inhaled corticosteroid (ICS) treatment (n=96).  Results are 
stratified by levels of patient ICS use (≤75% adherence was considered low use and >75% 
adherence was considered high use) and pre-treatment serum levels of EDN.  Low and high EDN 
levels were defined as those ≤2.34 ng/mL and >2.34 ng/mL, respectively.  Black lines connect 
the means for each group.     
 
Figure E8.  Effect of baseline blood eosinophil counts on relationship between rs3827907 C-
allele carrier status and absolute change in Asthma Control Test (ACT) composite score among 
European American participants in the SAPPHIRE cohort following 6 weeks of observed inhaled 
corticosteroid (ICS) treatment (n=94).  Results are stratified by levels of patient ICS use (≤75% 
adherence was considered low use and >75% adherence was considered high use) and blood 
eosinophil counts measured before ICS treatment.  Low and high eosinophil counts were defined 
as those ≤222 cells/µL and >222 cells/ µL, respectively.  Black lines connect the means for each 
group.     
 
Figure E9.  LocusZoom plot of rs3827907 on chromosome 14 including imputed variants.  
Single nucleotide polymorphisms located within a 200 kilobase window upstream and 
downstream of rs3827907 are shown.  P-values were generated using the joint (SNP and 
SNP*ICS combined) test of association with changes in asthma control occurring over 6 weeks 
of ICS treatment.  The SNP color represents the level of correlation between each SNP and 
rs3827907.  After res3827907, the next most significant variant, imputed SNP rs12891518, is 
also labeled. Genes located in the region are shown beneath the plotted SNPs. 
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
SUPPLEMENTAL REFERENCES 
 
1. 
Miller MR, Crapo R, Hankinson J, Brusasco V, Burgos F, Casaburi R, et al. General 
considerations for lung function testing. Eur Respir J 2005; 26:153-61. 
2. 
Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. 
Standardisation of spirometry. Eur Respir J 2005; 26:319-38. 
3. 
Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of 
the general U.S. population. Am J Respir Crit Care Med 1999; 159:179-87. 
4. 
Bender B, Wamboldt FS, O'Connor SL, Rand C, Szefler S, Milgrom H, et al. 
Measurement of children's asthma medication adherence by self report, mother report, 
canister weight, and Doser CT. Ann Allergy Asthma Immunol 2000; 85:416-21. 
5. 
O'Connor SL, Bender BG, Gavin-Devitt LA, Wamboldt MZ, Milgrom H, Szefler S, et al. 
Measuring adherence with the Doser CT in children with asthma. J Asthma 2004; 
41:663-70. 
6. 
Ewels P, Magnusson M, Lundin S, Kaller M. MultiQC: summarize analysis results for 
multiple tools and samples in a single report. Bioinformatics 2016; 32:3047-8. 
7. 
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast 
universal RNA-seq aligner. Bioinformatics 2013; 29:15-21. 
8. 
Wang L, Wang S, Li W. RSeQC: quality control of RNA-seq experiments. 
Bioinformatics 2012; 28:2184-5. 
9. 
Ramirez F, Dundar F, Diehl S, Gruning BA, Manke T. deepTools: a flexible platform for 
exploring deep-sequencing data. Nucleic Acids Res 2014; 42:W187-91. 
10. 
Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or 
without a reference genome. BMC Bioinformatics 2011; 12:323. 
11. 
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for 
RNA-seq data with DESeq2. Genome Biol 2014; 15:550. 
12. 
Reddel HK, Taylor DR, Bateman ED, Boulet LP, Boushey HA, Busse WW, et al. An 
official American Thoracic Society/European Respiratory Society statement: asthma 
control and exacerbations: standardizing endpoints for clinical asthma trials and clinical 
practice. Am J Respir Crit Care Med 2009; 180:59-99. 
13. 
Williams LK, Peterson EL, Wells K, Ahmedani BK, Kumar R, Burchard EG, et al. 
Quantifying the proportion of severe asthma exacerbations attributable to inhaled 
corticosteroid nonadherence. J Allergy Clin Immunol 2011; 128:1185-91. 
14. 
Wells KE, Peterson EL, Ahmedani BK, Severson RK, Gleason-Comstock J, Williams 
LK. The relationship between combination inhaled corticosteroid and long-acting beta-
agonist use and severe asthma exacerbations in a diverse population. J Allergy Clin 
Immunol 2012; 129:1274-9. 
15. 
Williams LK, Joseph CL, Peterson EL, Wells K, Wang M, Chowdhry VK, et al. Patients 
with asthma who do not fill their inhaled corticosteroids: a study of primary 
nonadherence. J Allergy Clin Immunol 2007; 120:1153-9. 
16. 
Expert Panel Report 3 (EPR-3): Guidelines for the Diagnosis and Management of 
Asthma-Summary Report 2007. J Allergy Clin Immunol 2007; 120:S94-138. 
17. 
Paris J, Peterson EL, Wells K, Pladevall M, Burchard EG, Choudhry S, et al. 
Relationship between recent short-acting beta-agonist use and subsequent asthma 
exacerbations. Ann Allergy Asthma Immunol 2008; 101:482-7. 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
18. 
Allen-Ramey FC, Bukstein D, Luskin A, Sajjan SG, Markson LE. Administrative claims 
analysis of asthma-related health care utilization for patients who received inhaled 
corticosteroids with either montelukast or salmeterol as combination therapy. J Manag 
Care Pharm 2006; 12:310-21. 
19. 
Nishimura KK, Galanter JM, Roth LA, Oh SS, Thakur N, Nguyen EA, et al. Early-life air 
pollution and asthma risk in minority children. The GALA II and SAGE II studies. Am J 
Respir Crit Care Med 2013; 188:309-18. 
20. 
Neophytou AM, White MJ, Oh SS, Thakur N, Galanter JM, Nishimura KK, et al. Air 
Pollution and Lung Function in Minority Youth with Asthma in the GALA II (Genes-
Environments and Admixture in Latino Americans) and SAGE II (Study of African 
Americans, Asthma, Genes, and Environments) Studies. Am J Respir Crit Care Med 
2016; 193:1271-80. 
21. 
Pino-Yanes M, Gignoux CR, Galanter JM, Levin AM, Campbell CD, Eng C, et al. 
Genome-wide association study and admixture mapping reveal new loci associated with 
total IgE levels in Latinos. J Allergy Clin Immunol 2015; 135:1502-10. 
22. 
White MJ, Risse-Adams O, Goddard P, Contreras MG, Adams J, Hu D, et al. Novel 
genetic risk factors for asthma in African American children: Precision Medicine and the 
SAGE II Study. Immunogenetics 2016; 68:391-400. 
23. 
Yang JJ, Li J, Buu A, Williams LK. Efficient inference of local ancestry. Bioinformatics 
2013; 29:2750-6. 
24. 
Choudhry S, Coyle NE, Tang H, Salari K, Lind D, Clark SL, et al. Population 
stratification confounds genetic association studies among Latinos. Hum Genet 2006; 
118:652-64. 
25. 
Yaeger R, Avila-Bront A, Abdul K, Nolan PC, Grann VR, Birchette MG, et al. 
Comparing genetic ancestry and self-described race in african americans born in the 
United States and in Africa. Cancer Epidemiol Biomarkers Prev 2008; 17:1329-38. 
26. 
Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal 
components analysis corrects for stratification in genome-wide association studies. Nat 
Genet 2006; 38:904-9. 
27. 
Price AL, Zaitlen NA, Reich D, Patterson N. New approaches to population stratification 
in genome-wide association studies. Nat Rev Genet 2010; 11:459-63. 
28. 
consortium Tgp. A map of human genome variation from population-scale sequencing. 
Nature 2010; 467:1061-73. 
29. 
Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in 
unrelated individuals. Genome Res 2009; 19:1655-64. 
30. 
Pino-Yanes M, Thakur N, Gignoux CR, Galanter JM, Roth LA, Eng C, et al. Genetic 
ancestry influences asthma susceptibility and lung function among Latinos. J Allergy 
Clin Immunol 2015; 135:228-35. 
31. 
Consortium TIH. A second generation human haplotype map of over 3.1 million SNPs. 
Nature 2007:851-61. 
32. 
Kraft P, Yen YC, Stram DO, Morrison J, Gauderman WJ. Exploiting gene-environment 
interaction to detect genetic associations. Hum Hered 2007; 63:111-9. 
33. 
Fagny M, Paulson JN, Kuijjer ML, Sonawane AR, Chen CY, Lopes-Ramos CM, et al. 
Exploring regulation in tissues with eQTL networks. Proc Natl Acad Sci U S A 2017; 
114:E7841-E50. 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
34. 
Yao C, Joehanes R, Johnson AD, Huan T, Liu C, Freedman JE, et al. Dynamic Role of 
trans Regulation of Gene Expression in Relation to Complex Traits. Am J Hum Genet 
2017; 100:571-80. 
35. 
Stegle O, Parts L, Piipari M, Winn J, Durbin R. Using probabilistic estimation of 
expression residuals (PEER) to obtain increased power and interpretability of gene 
expression analyses. Nat Protoc 2012; 7:500-7. 
36. 
R Core Team. R: A language and environment for statistical computing. Vienna, Austria: 
R Foundation for Statistical Computing, 2014. 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
Table E1.  Interactions between previously reported pharmacogenetic variants and inhaled corticosteroid use on changes in 
asthma control among individuals in the discovery set (n=244)* 
SNP 
Chr 
Position 
Imputation 
Quality† 
Allele‡ 
MAF‡ 
Gene 
Parameter 
estimate for 
SNP§ 
P-value for 
SNP term║ 
Parameter 
estimate for 
SNP x ICS 
interaction§ 
P-value for 
interaction 
term║ 
P-value for 
joint test¶ 
rs10044254 
5 
15,783,596 
0.96 
G/A 
0.35 
FBXL7 
2.49 
0.060 
-3.08 
0.063 
0.167 
rs2395672 
6 
37,428,577 
0.75 
A/G 
0.03 
CMTR1 
2.38 
0.583 
-1.72 
0.750 
0.566 
rs6924808 
6 
98,358,575 
0.95 
G/A 
0.39 
0.41 
0.733 
-0.70 
0.651 
0.861 
rs6456042 
6 
166,534,742 
0.96 
A/C 
0.35 
T 
1.18 
0.369 
-1.33 
0.413 
0.657 
rs3127412 
6 
166,535,561 
0.96 
C/T 
0.35 
T 
1.18 
0.369 
-1.33 
0.413 
0.657 
rs37972 
7 
8,007,509 
0.92 
T/C 
0.18 
GLCCI1 
-0.20 
0.910 
0.44 
0.840 
0.918 
rs2691529 
7 
77,803,275 
0.89 
C/T 
0.24 
MAGI2 
-0.86 
0.564 
0.77 
0.685 
0.713 
rs6467778 
7 
138,178,222 
0.95 
A/G 
0.17 
TRIM24 
-1.43 
0.354 
1.36 
0.481 
0.521 
rs10481450 
8 
9,798,246 
0.80 
A/T 
0.13 
2.88 
0.092 
-2.63 
0.248 
0.061 
rs3793371 
8 
144,664,299 
0.97 
A/G 
0.04 
EEF1D 
(NAPRT1) 
2.03 
0.761 
-2.32 
0.760 
0.954 
rs4271056 
9 
38,232,043 
1.00 
C/T 
0.23 
-2.10 
0.106 
2.86 
0.087 
0.230 
rs7850103 
9 
118,137,835 
0.99 
A/C 
0.15 
DEC1 (TNC) 
2.14 
0.263 
-3.57 
0.132 
0.126 
rs1353649 
11 
20,253,599 
0.99 
A/G 
0.40 
-1.45 
0.203 
2.31 
0.113 
0.194 
rs4980524 
11 
63,959,259 
0.99 
C/A 
0.29 
STIP1 
0.38 
0.736 
-0.82 
0.563 
0.655 
rs6591838 
11 
63,959,356 
0.99 
G/A 
0.21 
STIP1 
0.43 
0.736 
-0.53 
0.744 
0.944 
rs2236647 
11 
63,964,605 
0.99 
C/T 
0.28 
STIP1 
-1.03 
0.452 
1.15 
0.494 
0.740 
rs1144764 
11 
77,870,486 
0.94 
T/C 
0.39 
KCTD21-AS1 
(ALG8) 
-1.75 
0.191 
2.38 
0.161 
0.367 
rs12891009 
14 
74,083,846 
0.93 
T/C 
0.26 
ACOT6/HEAT
R4 (ACOT4) 
-0.18 
0.884 
-0.24 
0.877 
0.580 
rs2230155 
15 
59,510,189 
0.90 
A/G 
0.41 
MYO1E 
0.84 
0.448 
-1.38 
0.341 
0.550 
rs12438740 
15 
59,515,767 
1.00 
A/G 
0.41 
MYO1E 
0.58 
0.601 
-0.97 
0.507 
0.744 
rs242941 
17 
43,892,520 
1.00 
C/A 
0.37 
CRHR1 
0.16 
0.883 
0.00 
0.999 
0.880 
rs242939 
17 
43,895,579 
1.00 
C/T 
0.32 
CRHR1 
2.19 
0.081 
-2.82 
0.085 
0.215 
rs1876828 
17 
43,911,525 
0.99 
T/C 
0.03 
CRHR1 
5.29 
0.459 
-5.67 
0.497 
0.701 
rs2240017 
17 
45,810,919 
0.38 
G/C 
0.01 
TBX21 
4.87 
0.916 
-3.57 
0.963 
0.560 
rs1380657 
17 
48,598,785 
1.00 
G/A 
0.12 
MYCBPAP 
(SPATA20) 
2.95 
0.113 
-4.70 
0.052 
0.081 
rs6504666 
17 
48,601,328 
1.00 
G/A 
0.16 
MYCBPAP 
(SPATA20) 
0.99 
0.544 
-1.21 
0.565 
0.831 
rs9303988 
18 
6,667,583 
0.67 
T/C 
0.44 
1.10 
0.348 
-1.29 
0.397 
0.631 
rs279728 
20 
45,080,421 
1.00 
T/C 
0.23 
0.75 
0.551 
-0.98 
0.538 
0.826 
rs2037925 
21 
40,699,931 
0.95 
C/T 
0.33 
(BRWD1) 
-2.27 
0.098 
2.38 
0.155 
0.192 
rs2836987 
21 
40,706,594 
0.94 
C/T 
0.31 
(BRWD1) 
-1.53 
0.272 
1.65 
0.334 
0.503 
rs138335 
22 
41,227,086 
0.83 
C/G 
0.07 
ST13 
1.30 
0.652 
-2.64 
0.456 
0.350 
rs138337 
22 
41,231,053 
0.94 
G/A 
0.42 
ST13 
0.79 
0.504 
-1.09 
0.465 
0.759 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
SNP denotes single nucleotide polymorphism; Chr, chromosome; MAF, minor allele frequency; and ICS, inhaled corticosteroid.   
*SNPs were selected from variants previously reported to be associated with ICS response.  The outcome phenotype was the change 
in asthma control test (ACT) score from before to immediately following 6 weeks of inhaled corticosteroid (ICS) treatment.  
†The imputation quality score is the MACH-based imputation r2 value, which ranges from zero to one. Values closer to one indicate 
higher imputation quality. 
‡The “effect” allele is shown first, and the referent allele follows.  The allele frequency of the “effect” allele is provided, and in the 
current table, this estimate is based on the observed frequency in the discovery set. 
§The parameter estimates demonstrate the direction and magnitude for a change in the ACT score over the course of 6 weeks of ICS 
treatment.  A positive parameter estimate indicates that the variable was associated with an improvement in asthma control over the 
course of treatment.  The parameter estimate for the SNP can be interpreted as the effect on asthma control for each additional “effect” 
allele (i.e., none [=0], one [=1], or two alleles [=2]).  The parameter estimate for the interaction term can be interpreted as the 
combined effect of increasing ICS use (i.e., going from zero to complete adherence to the prescribed dose [a continuous variable 
ranging from 0 to 1]) and the number of “effect” alleles on the change in asthma control over 6 weeks of ICS treatment.     
║The P-values for the SNP and SNP x ICS interaction variables are shown for the model simultaneously including these variables, as 
well as adjusting for patient age, sex, ACT score at baseline enrollment into the study, smoking status (coded as never, past, and 
present), the first three principal components, and ICS adherence. 
¶The F-test assessed the significance of the difference in model fit between the full model (i.e., all of the aforementioned variables 
included) and the reduced model (i.e., the full model minus both the SNP and SNP x ICS interaction terms).  In other words, a joint 
test was used to simultaneously assess the combined significance of the SNP and SNP x ICS interaction terms. 
 
 
 
 
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
Table E2.  Interactions between previously reported pharmacogenetic variants and inhaled corticosteroid use on severe 
asthma exacerbations among African American SAPPHIRE participants in the validation set (n=803)* 
SNP 
Chr 
Position 
Imputation 
Quality† 
Allele‡ 
MAF‡ 
Gene 
Parameter 
estimate for 
SNP§ 
P-value 
for SNP 
term║ 
Parameter 
estimate for 
SNP x ICS 
interaction§ 
P-value for 
interaction 
term║ 
P-value 
for joint 
test¶ 
rs10044254 
5 
15,783,596 
0.96 
G/A 
0.34 
FBXL7 
-0.18 
0.115 
0.13 
0.433 
0.282 
rs2395672 
6 
37,428,577 
0.75 
A/G 
0.04 
CMTR1 
0.28 
0.326 
-0.88 
0.036 
0.020 
rs6924808 
6 
98,358,575 
0.95 
G/A 
0.42 
0.00 
0.981 
-0.18 
0.212 
0.331 
rs6456042 
6 
166,534,742 
0.96 
A/C 
0.36 
T 
0.10 
0.367 
0.09 
0.524 
0.294 
rs3127412 
6 
166,535,561 
0.96 
C/T 
0.36 
T 
0.10 
0.367 
0.09 
0.524 
0.294 
rs37972 
7 
8,007,509 
0.92 
T/C 
0.21 
GLCCI1 
0.20 
0.104 
-0.22 
0.188 
0.233 
rs2691529 
7 
77,803,275 
0.89 
C/T 
0.26 
MAGI2 
0.16 
0.154 
-0.04 
0.742 
0.336 
rs6467778 
7 
138,178,222 
0.95 
A/G 
0.16 
TRIM24 
-0.40 
0.017 
0.21 
0.304 
0.039 
rs10481450 
8 
9,798,246 
0.80 
A/T 
0.13 
0.13 
0.437 
0.07 
0.717 
0.508 
rs3793371 
8 
144,664,299 
0.97 
A/G 
0.04 
EEF1D 
(NAPRT1) 
-0.71 
0.016 
-0.29 
0.361 
3.27x10-4 
rs4271056 
9 
38,232,043 
1.00 
C/T 
0.22 
0.07 
0.587 
0.16 
0.319 
0.316 
rs7850103 
9 
118,137,835 
0.99 
A/C 
0.11 
DEC1 (TNC) 
0.77 
6.38x10-7 
-0.46 
0.030 
1.87x10-5 
rs1353649 
11 
20,253,599 
0.99 
A/G 
0.42 
-0.03 
0.762 
0.19 
0.106 
0.215 
rs4980524 
11 
63,959,259 
0.99 
C/A 
0.32 
STIP1 
0.15 
0.189 
-0.21 
0.109 
0.218 
rs6591838 
11 
63,959,356 
0.99 
G/A 
0.21 
STIP1 
0.13 
0.336 
-0.27 
0.117 
0.271 
rs2236647 
11 
63,964,,605 
0.99 
C/T 
0.29 
STIP1 
-0.02 
0.856 
0.03 
0.837 
0.975 
rs1144764 
11 
77,870,486 
0.94 
T/C 
0.39 
KCTD21-
AS1 (ALG8) 
0.13 
0.218 
-0.03 
0.839 
0.415 
rs12891009 
14 
74,083,846 
0.93 
T/C 
0.27 
ACOT6/HEA
TR4 
(ACOT4) 
0.31 
0.012 
-0.36 
0.029 
0.026 
rs2230155 
15 
59,510,189 
0.90 
A/G 
0.38 
MYO1E 
0.29 
0.014 
-0.06 
0.750 
0.028 
rs12438740 
15 
59,515,767 
1.00 
A/G 
0.38 
MYO1E 
0.30 
0.012 
-0.07 
0.699 
0.024 
rs242941 
17 
43,892,520 
1.00 
C/A 
0.42 
CRHR1 
-0.02 
0.829 
0.15 
0.183 
0.367 
rs242939 
17 
43,895,579 
1.00 
C/T 
0.31 
CRHR1 
0.04 
0.734 
0.13 
0.368 
0.433 
rs1876828 
17 
43,911,525 
0.99 
T/C 
0.06 
CRHR1 
-0.69 
0.007 
0.45 
0.026 
0.010 
rs2240017 
17 
45,810,919 
0.38 
G/C 
0.01 
TBX21 
-0.60 
0.334 
3.55 
2.52x10-6 
0.010 
rs1380657 
17 
48,598,785 
1.00 
G/A 
0.13 
MYCBPAP 
(SPATA20) 
-0.16 
0.348 
-0.13 
0.504 
0.262 
rs6504666 
17 
48,601,328 
1.00 
G/A 
0.16 
MYCBPAP 
(SPATA20) 
0.08 
0.572 
-0.06 
0.663 
0.840 
rs9303988 
18 
6,667,583 
0.67 
T/C 
0.39 
0.01 
0.948 
-0.10 
0.438 
0.672 
rs279728 
20 
45,080,421 
1.00 
T/C 
0.21 
0.48 
3.36x10-4 
0.23 
0.191 
1.43x10-5 
rs2037925 
21 
40,699,931 
0.95 
C/T 
0.37 
(BRWD1) 
-0.34 
0.003 
-0.07 
0.538 
0.001 
rs2836987 
21 
40,706,594 
0.94 
C/T 
0.34 
(BRWD1) 
-0.19 
0.103 
-0.08 
0.457 
0.047 
rs138335 
22 
41,227,086 
0.83 
C/G 
0.08 
ST13 
0.19 
0.298 
-0.22 
0.470 
0.575 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
rs138337 
22 
41,231,053 
0.94 
G/A 
0.41 
ST13 
0.11 
0.305 
0.00 
0.985 
0.471 
SAPPHIRE denotes Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity; SNP, single nucleotide 
polymorphism; Chr, chromosome; MAF, minor allele frequency; and ICS, inhaled corticosteroid.   
*SNPs were selected from variants previously reported to be associated with ICS response.  Cox proportional hazards models were 
used to assess associations with time-to-severe asthma exacerbation (i.e., burst oral corticosteroid use, asthma-related emergency 
department visits, and hospitalizations for asthma).   
†The imputation quality score is the MACH-based imputation r2 value, which ranges from zero to one. Values closer to one indicate 
higher imputation quality. 
‡The “effect” allele is shown first, and the referent allele follows.  The allele frequency of the “effect” allele is provided, and in the 
current table, this estimate is based on the observed frequency in the validation set. 
§The parameter estimates represent the risk (i.e., hazard) of having a severe asthma exacerbation following the initial (baseline) 
assessment at study entry.  A negative parameter estimate indicates that the variable was associated with a lower risk of experiencing a 
severe asthma exacerbation.  The parameter estimate for the SNP can be interpreted as the effect on exacerbation risk for each 
additional “effect” allele (i.e., none [=0], one [=1], or two alleles [=2]).  The parameter estimate for the interaction term can be 
interpreted as the combined effect of increasing ICS use (i.e., average number of ICS doses taken per day – see Methods Section and 
Supplemental Methods Section for more details on how longitudinal ICS exposure measures were created) and the number of “effect” 
alleles on the risk of a severe asthma exacerbation.     
║The P-values for the SNP and SNP x ICS interaction variables are shown for the model simultaneously including these variables, as 
well as adjusting for patient age, sex, BMI, smoking status, ACT score at baseline (i.e., time of study enrollment), baseline asthma 
severity score, LABA use (an indicator variable denoting use of an ICS-LABA combination inhaler), time-updated measures of SABA 
MDI and nebulizer use, the first 3 principal components, and the time-updated ICS exposure measure.     
¶The likelihood ratio test assessed the significance of the difference in model fit between the full model (i.e., all of the aforementioned 
variables included) and the reduced model (i.e., the full model minus both the SNP and SNP x ICS interaction terms).  In other words, 
a joint test was used to simultaneously assess the combined significance of the SNP and SNP x ICS interaction terms. 
 
 
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
Table E3. Relationship between rs3827907 genotype and inhaled corticosteroid use on change in asthma control stratified by 
pre-treatment eosinophilia African American individuals in the SAPPHIRE cohort* 
Sample  
 
Sample size 
 
rs3827907 C-allele status 
ICS use 
SNP*ICS interaction 
Parameter  
estimate† 
P-value 
Parameter  
estimate† 
P-value 
Parameter  
estimate† 
P-value 
All 
243 
-2.569 
5.38x10-4 
0.097 
0.851 
4.405 
1.52x10-5 
 High EDN‡ 
121 
-3.838 
9.87x10-5 
-0.014 
0.984 
5.485 
1.35x10-4 
 Low EDN‡ 
122 
-1.154 
0.314 
0.365 
0.658 
3.319 
0.029 
 High Eosinophils§ 
56 
-2.720 
0.238 
-0.777 
0.567 
7.050 
0.041 
 Low Eosinophils§ 
57 
-2.365 
0.154 
-0.753 
0.533 
3.722 
0.075 
 
 
 
 
 
 
 
 
C-allele carrier 
61 
-- 
-- 
4.304 
4.61x10-5 
-- 
-- 
 High EDN‡ 
28 
-- 
-- 
5.986 
0.002 
-- 
-- 
 Low EDN‡ 
33 
-- 
-- 
4.247 
0.003 
-- 
-- 
 High Eosinophils§ 
-- 
-- 
10.234 
0.516 
-- 
-- 
 Low Eosinophils§ 
 
-- 
-- 
2.765 
0.116 
-- 
-- 
 
 
 
 
 
 
 
 
TT homozygotes 
182 
-- 
-- 
0.14 
0.782 
-- 
-- 
 High EDN‡ 
93 
-- 
-- 
0.131 
0.830 
-- 
-- 
 Low EDN‡ 
89 
-- 
-- 
0.327 
0.713 
-- 
-- 
 High Eosinophils§ 
45 
-- 
-- 
-0.627 
0.621 
-- 
-- 
 Low Eosinophils§ 
39 
-- 
-- 
-1.079 
0.415 
-- 
-- 
SAPPHIRE denotes Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity; ICS, inhaled corticosteroid; 
SNP, single nucleotide polymorphism; and EDN, eosinophil-derived neurotoxin.   
*The analysis was restricted to SAPPHIRE participants from the discovery set with available data and who underwent 6 weeks of 
observed ICS treatment.  Change is asthma control was taken as the change in Asthma Control Test composite score from before to 
after ICS treatment.  
†Parameter estimates represent the effect of a one-unit increase in the variable listed.  The rs3827907 genotype was collapsed into C-
allele carriers (=1) and TT homozyogotes (=0).  Inhaled corticosteroid use was dichotomously categorized into those whose adherence 
was ≤75% (low use) and >75% (high use) over course of the 6-week treatment regimen.  The interaction term represents the combined 
effect of rs3827907 C-allele carrier status and level of ICS use.  The models used to create the parameter estimates simultaneously 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
included all of the variables shown, as well as variables to adjust for patient age, sex, BMI, smoking status, ACT score at baseline, and 
first 3 principal components.  Positive parameter estimates suggest that the variable was associated with an improvement in asthma 
control over the 6-week ICS treatment trial.   
‡The study population was stratified based on the median EDN serum level for the entire group with these data (n=243) prior to 
initiating ICS treatment.  A baseline EDN value ≤2.34 ng/mL was considered low and a value >2.34 ng/mL was considered high.   
§The study population was also stratified based on the median blood eosinophil for the entire group with these data (n=133) prior to 
initiating ICS treatment.  A baseline blood eosinophil count ≤222 cells/µL was considered low and a count >222 cells/µL was 
considered high.   
 
 


Title: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity 
(SAPPHIRE) - NCT01142947 
Last updated: 02/19/2019 
 
Table E4. Relationship between both rs3827907 and rs12891519 genotype and RNASE2 
gene expression in peripheral blood among African American participants with and 
without asthma from the SAPPHIRE cohort.  
Groups 
rs3827907 variant 
rs12891518 variant 
Parameter 
estimate* 
P-value 
Parameter 
estimate* 
P-value 
All participants (n=597) 
-0.237 
0.004 
-0.235 
0.008 
Asthma cases (n=408) 
-0.243 
0.018 
-0.220 
0.047 
Controls (n=189) 
-0.224 
0.103 
-0.267 
0.069 
SAPPHIRE denotes the Study of Asthma Phenotypes and Pharmacogenomic Interactions by 
Race-ethnicity. 
*Linear regression was used to examine the relationship between both rs3827907 genotype 
(coded as TT=0, CT=1, CC=2) and rs12891518 genotype (code AA=0, AT=1, and TT=2) and 
gene expression (dependent variable).  The model adjusted for patient age, sex, BMI, the 
absolute cell counts for each of the 5 white blood cell types measured (i.e., neutrophils, 
monocytes, lymphocytes, eosinophils, and basophils from complete blood counts obtained at the 
time that the RNA was collected), sequence batch, and the first 30 probabilistic estimation of 
expression residuals (PEERs).  The parameter estimates are the adjusted genotype main effect 
estimates for rs3827907 and rs12891518.  A negative parameter estimate suggests that the minor 
allele (i.e., the C-allele for rs3827907 and the T-allele for rs12891518) was associated with 
decreased RNASE2 gene expression.