Expression Analysis Of Asthma Candidate Genes During Human And Murine Lung Development

Article (PDF Available)inRespiratory research 12(1):86 · June 2011with31 Reads
DOI: 10.1186/1465-9921-12-86 · Source: PubMed
Abstract
Little is known about the role of most asthma susceptibility genes during human lung development. Genetic determinants for normal lung development are not only important early in life, but also for later lung function. To investigate the role of expression patterns of well-defined asthma susceptibility genes during human and murine lung development. We hypothesized that genes influencing normal airways development would be over-represented by genes associated with asthma. Asthma genes were first identified via comprehensive search of the current literature. Next, we analyzed their expression patterns in the developing human lung during the pseudoglandular (gestational age, 7-16 weeks) and canalicular (17-26 weeks) stages of development, and in the complete developing lung time series of 3 mouse strains: A/J, SW, C57BL6. In total, 96 genes with association to asthma in at least two human populations were identified in the literature. Overall, there was no significant over-representation of the asthma genes among genes differentially expressed during lung development, although trends were seen in the human (Odds ratio, OR 1.22, confidence interval, CI 0.90-1.62) and C57BL6 mouse (OR 1.41, CI 0.92-2.11) data. However, differential expression of some asthma genes was consistent in both developing human and murine lung, e.g. NOD1, EDN1, CCL5, RORA and HLA-G. Among the asthma genes identified in genome wide association studies, ROBO1, RORA, HLA-DQB1, IL2RB and PDE10A were differentially expressed during human lung development. Our data provide insight about the role of asthma susceptibility genes during lung development and suggest common mechanisms underlying lung morphogenesis and pathogenesis of respiratory diseases.
RESEARC H Open Access
Expression analysis of asthma candidate genes
during human and murine lung development
Erik Melén
1,2,3*
, Alvin T Kho
4
, Sunita Sharma
1,5
, Roger Gaedigk
6
, J Steven Leeder
6
, Thomas J Mariani
7
,
Vincent J Carey
1
, Scott T Weiss
1,5,8
and Kelan G Tantisira
1,5,8
Abstract
Background: Little is known about the role of most asthma susceptibility genes during human lung development.
Genetic determinants for normal lung development are not only important early in life, but also for later lung
function.
Objective: To investigate the role of expression patterns of well-defined asthma susceptibility genes during human
and murine lung development. We hypothesized that genes influencing normal airways development would be
over-represented by genes associated with asthma.
Methods: Asthma genes were first identified via comprehensive search of the current literature. Next, we analyzed
their expression patterns in the developing human lung during the pseudoglandular (gestational age, 7-16 weeks)
and canalicular (17-26 weeks) stages of development, and in the complete developing lung time series of 3 mouse
strains: A/J, SW, C57BL6.
Results: In total, 96 genes with association to asthma in at least two human populations were identified in the
literature. Overall, there was no significant over-representation of the asthma genes among genes differentially
expressed during lung development, although trends were seen in the human (Odds ratio, OR 1.22, confidence
interval, CI 0.90-1.62) and C57BL6 mouse (OR 1.41, CI 0.9 2-2.11) data. However, differential expression of some
asthma genes was consistent in both developing human and murine lung, e.g. NOD1, EDN1, CCL5, RORA and HLA-
G. Among the asthma genes identified in genome wide association studies, ROBO1, RORA, HLA-DQB1, IL2RB and
PDE10A were differentia lly expressed during human lung development.
Conclusions: Our data provide insight about the role of asthma susceptibility genes during lung development and
suggest common mechanisms underlying lung morphogenesis and pathogenesis of respiratory disea ses.
Keywords: Asthma, Development, Expression, Genetics, Lung
Introduction
There is good evidence that genetic factors strongly
influence the risk of asthma, and associations between
numerous genes and asthma have been evaluated in the
past decades [1,2]. Recent genome wide a ssociation
studies (GWAS) of asthma have identified several
additional asthma susceptibility genes [3-10]. Little is
knownabouttheroleofmostasthmasusceptibility
genes during human lung development.
The development al origins hypothesis [11] proposes
that specific in utero events at critical periods during
organogenesis and maturation result in long-term
physiological or metabolic changes, ultimately contribut-
ing to disease in later life [12,13]. Our group previously
showed that Wnt signal ing genes that were differentially
expressed during fetal lung development were associated
with impaired lung function in two cohorts of school-
aged asthmatic children [14]. These results suggest the
importance of early life events in determining lung
function. They also highlight the benefit of integrating
gene expression and genetic association data to connect
transcriptomic events in the early developing lung to
genetic associations of lung function in later life.
* Correspondence: erik.melen@ki.se
1
Channing Laboratory, Brigham and Womens Hospital and Harvard Medical
School, Boston, MA, USA
Full list of author information is available at the end of the article
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© 2011 Melén et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribu tion License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and repro duction in
any medium, provided the original work is properly cited.
Asthma is a disease characte rized by both airway
inflammation and smooth muscle contraction, leading
to airway obstruction. Dendritic cells, mast cells, and
T-lymphocytes, as well as airway smooth muscle cells,
all begin to appear within the lung parenchyma during
the pseudoglandular stage of lung development. We
therefore hypothesized that genes influencing normal
airways development, especially during the branching
morphogenesis stage of human lung development,
would be over-represented by genes associated with
asthma. To test this hypothe sis, we investigated the role
of a well-defined set of asthma susceptibility genes
during human and murine lung development. 96 asthma
genes were first identified via comprehensive search of
the current literature. Next, we analyzed their expres-
sion patterns in the developing human lung during the
pseudoglandular (gestational age, 7-16 weeks) and cana-
licular (1 7-27 weeks) stages of development, and in the
complete developing lung time series of 3 mouse strains:
A/J, SW and C57BL6.
We show that overall, there was no over-representa-
tion of the asthma genes among genes differentially
expressed during lung development, which may reflect
the diverse ontological contexts of the asthma genes.
However, some genes showed a consistent pattern of
differential expression in all developing lun g data sets,
e.g. NOD1, EDN1, RORA, CCL5 and HLA- G, which sug-
gests that these genes play a fundamental role in normal
lung development.
Methods
Tissue samples
The human fetal lung tissues were obtained from
National Institu te of Child Health and Human Develop-
ment supported tissue databases and microarray profiled
as previously described [14,15]. Creation of the tissue
repository was approved by the University of Missouri-
Kansas City Pediatric Institutional Review Board. 38
RNA samples from 38 subjects (estimated gestational
age 7-22 weeks or 53-154 days post conception) were
included in the analysis (Table 1). The murine data have
previously been described and their micr oarray data are
available at NCBI Gene Expression Omnibus (GEO,
http://www.ncbi.nlm.nih.gov/ge o); A/J [16], n = 24 sam-
ples; SW [17], n = 11; and C57BL6 mice [18], n = 5,
Table 1.
Microarray analysis
The developing human lung ti me series data is available
at NCBI Gene Expression Omnibus (GEO, http://www.
ncbi.nlm.nih.gov/geo), GSE14334 (Affymetrix Human
Genome GeneCh ip U133 Plus 2.0 microarray platform) .
Expression values were extracted and normalized from .
CEL files using the Affy package and the Robust
Multi-array Average (RMA) method in R/BioConductor
(http://www.bioconductor.org) which returns the mea-
sured expression signal of each micrroarray gene probe
in logarithmic base 2 scale. Validation of the human
microarray analysis by qPCR for gene s differentially
expressed during lung develo pment has been performed
earlier and this demonstrated that 83% of individual
gene expression trajectories could be replicated [15].
The developing whole mouse lung transcriptome data
from three different mouse strains were extracted and
normalized, separately, using RMA in R/BioConductor;
24 samples from A/J (Affymetrix Mu74Av2 platform);
11 samples from SW (Affymetrix Mu11K A and B plat-
forms); and 5 samples from C57BL6 (Affymetrix Mouse
430 Plus 2.0 platform).
Literature search
A PubMed (http://www.ncbi.nlm.nih.gov/pubmed)
search was performed on March 8, 2010 using the
terms 1) asthma together with 2) genetic association
or case control in order to cover all published papers
between July 1, 2008 and December 31, 2009. We
applied the following inclusion criteria for an asthma
gene: 1) significant association with asthma affection
status in at least two populations and 2) at least one sig-
nificant association study with no fewer than 150 cases
Table 1 Summary characteristics of included human and murine lung data sets
Data sets Developmental period N
samples
Platform Probes
represented
on chip
Genes
represented
on chip
Number
of asthma
genes*
Number
of asthma
probes
Ref
Human lungs 7-22 weeks prenatal 38 Affy U133 Plus
2.0
54,675 19,501 96 220 [15]
Mouse A/J lungs 14 days prenatal - 4 weeks
postnatal
24 Affy Mu74Av2 12,488 9,060 66 89 [16]
Mouse SW lungs 12 days prenatal - 4 weeks
postnatal
11 Affy Mu11K A
and B
13,179 7,660 60 86 [17]
Mouse C57BL6
lungs
11.5 days prenatal - 5 days
postnatal
5 Affy Mouse 430
2.0
45,101 21,141 88 142 [18]
* CCL26, GSDMB, HLA-DQB1, PTPRD, TLR10 and WDR36 do not have a mouse orthologue gene.
Melén et al. Respiratory Research 2011, 12:86
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and 150 controls or 150 trios. Genes identified through
three earlier literature searches based on papers pub-
lished before July 1, 2008 were also included if they met
our two predefined criteria [1,19,20]. In addition, all
GWAS of asthma published through September 2010,
were also evaluated and asthma genes were i ncluded if
our criteria were met. Please see Supplemental data for
details about the asthma genes included in our analyses.
Mouse orthologues of human genes were identified
using NCBIs HomoloGene database (http://www.ncbi.
nlm.nih.gov/homologene).
Statistical analysis
Differential gene expression analysis relative to gesta-
tional age was performed using a linear regression
model (lmFit) as implemented in the Limma package in
R/BioConductor. Each microarray gene probes logarith-
mic base 2 expression signal was regressed against the
gestational age as a continuous v ariable representing
days of the developing lung. We adjusted f or multiple
testing using the Benjamini and Hochberg method,
which controls the false discovery rate (i.e. the ex pected
proportion of false discoveries amongst the rejected
hypotheses), and the adjusted p-values were used to
declare a significant gene expression pattern over age
[21]. Differentially expressed refers to an adjusted p-
value of <0.05 in the linear regression model. Fishers
exact test was next performed in Stata Statistical Soft-
ware (Collage Station, Tx) to test whether microrarray
probes representing predefined asthma genes were ove r-
represented among differentially expressed probes rela-
tive to probes representing non-asthma genes .This
analysis was restricted to microarray probes that were
gene annotated because the asthma gene probes were all
annotated. The same analysis steps were performed i n
human and murine data sets. Gene ontology (GO)
enrichment analysis was performed using DAVID (The
Database for Annotation, Visualization and Integrate d
Discovery) [22,23].
Results
In total, 96 asthma susceptibility genes were identified in
the literature (Additional file 1, Table E1 [1,3-10,24-96]).
All genes show significant associa tion with asthma in at
least two human populations, one of which has no fewer
than 150 cases and 150 controls or 150 trios. The 96
genes were represented by 220 probes on the human
microarray (Table 1). Not all human genes have a
mouse orthologue and the mouse microarray data sets
have slightly lower numbers of asthma genes and their
corresponding microarray probes.
We found that 28% of all microarray probes in the
human data set were differentially expressed during the
analyzed lung development period (human estimated
gestational age 7-22 weeks), Table 2. A similar figure
was seen in the A/J mouse and somewhat lower figures
in the SW and C57BL6 mouse strains. Gene ontol ogy
(GO) enrichment analysis using DAVID of the human
list of differentially expressed genes returned 879 signifi-
cant GO terms, of which 6 terms pertain directly to th e
lung development. Among the asthma gene prob es, 32%
were differentially expressed during early human lung
development. While there was a trend towards over-
representation (Odds ratio, OR 1.22, CI 0.90-1.62) this
was not statistically significant in comparison to the
non-asthma gene probes (28%). In agreement with the
human data, no over-representation of asthma gene
probes was found among probes differentially expres sed
during lung development in mice strains, although there
was a trend in the C57BL6 strain (OR 1.41, CI 0.92-
2.11), Table 2.
Although asthma genes as a group was not differen-
tially expressed more than non-asthma genes during
early lung development, some genes were consistently
Table 2 Proportion of the asthma gene probes among probes differentially expressed during lung development in
human and mouse data sets
Human lungs Mouse A/J lungs Mouse SW lungs Mouse C57BL6 lungs
Asthma probes Asthma probes Asthma probes Asthma probes
Differentially expressed Yes No Total* Yes No Total* Yes No Total* Yes No Total*
Yes 71 11373 11444 25 3285 3310 15 2052 2067 32 6637 6669
No 149 29017 29166 64 8511 8575 71 9189 9260 110 32161 32271
Total 220 40390 40610 89 11796 11885 86 11241 11327 142 38798 38940
% differentially expressed probes 32 28 28 28 28 28 17 18 18 23 17 17
p-value 0.18 1.0 1.0 0.09
OR (95% CI) 1.22 (0.90-1.63) 1.01 (0.61-1.63) 0.95 (0.50-1.67) 1.41 (0.92-2.11)
* Analyses restricted to probes represented by annotated genes.
Fishers exact test.
Differentially expressed refers to an adjusted p-value of <0.05 in the linear regression model.
OR = Odds ratio. CI = Confidence interval.
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different ial expressed, as listed in Table 3 (see full list in
Additional file 1, Table E2). Expression of NOD1, E DN1
and IL4R were positively correlated with gestational age
in the human data, whereas ROBO1 and PLAUR were
negatively correlated (i.e. lower expression levels the
higher gestational age). Among the asthma genes identi-
fied in GWAS, ROBO1, RORA, HLA-DQB1, IL2RB and
PDE10A showed most significantevidenceofinvolve-
ment in lung development (all adjusted p < 0.001 for
differential e xpression). Analyses were also done com-
paring gene expression patte rns between the pseudo-
glandular (primary branching morphogenesis stage) and
canalicular stages (with 112 days post conception as the
dividing time point between the 2 stages). The list of
top genes differentially expressed between these two
stages (Additional file 1, Table E3 and Figure E1) corre-
sponds well with the list of top genes using time as a
continuous variable (Table 3).
Next, we evaluated all differentially expressed asthma
gene s in the human data set to see which genes showed
a consistent expression pattern across human and mur-
ine data sets. Table 4 shows all genes with at least one
significant probe per gene in the human data and at
leastonesignificantprobeinamousedataset(n=19
with adjusted p-value <0.05). Eight genes had one or
more significant probes in all dat a sets, with NOD1,
EDN1, CCL5, RORA and HLA-G showing the most con-
sistent expression patterns across human and mouse
(see detailed EDN1/Edn1 expression over time in
human and mouse lung tissue; Figure 1 and 2). In terms
of bio-ontolo gic enrichment, the 19 asthma genes con-
sistently differentially expressed in human and mouse
lung development were enriched for ontological attri-
butes Regulation of cytokine production (IRAK3,
CD86 , NOD1, TNF, IL18, SCGB1A1)andRegulation of
cell activation (STAT6, CD86, IL18, IL 4R, RORA,
SCGB1A1) (Additional file 1, Table E4.) In terms of
gene product characteristics, Disulfide bond ,
Se creted and Signal peptide are attributes of a
majority of the genes. 15 of the 19 genes in Table 4
have been extensively studied in human and murine
experiments that s upport their involvement in asthma
pathogenesis (Additional file 1, Table E5).
In orde r to disentangle pre- and postnatal expression
patterns in the murine data sets, separate pre- and post-
natal analyses were a ttempted. However, this subgroup
analysis was not meaningful for the SW and C56BL6
data sets because of substantially reduced sample size.
The A/J data contains two prenatal time points (day 11
and17),eachwith4uniquesamplesandTableE6
shows overlapping results for human and prenatal A/J
data. Eight of the previously identified 19 genes with
consistent expression pattern across human and murine
data sets (Table 4) were also identified when prenatal
A/J data was used (including Edn1).
Discussion
Little is known about the role of most asthma suscept-
ibility genes during human lung development. Here we
present a thorough evaluation of gene expression
patterns of current published asthma genes in the devel-
oping human and murine lung. While there was no gen-
eral over-representation of asthma genes among
differentially expressed genes, some asthma genes were
consistently differentia lly expressed in mu ltiple develop-
inglungtranscriptomes,e.g.NO D1, EDN1, CCL5,
RORA and HLA-G suggesting key functional roles in
lung development.
Determinants for a normal lung development are criti-
cal not only early in life, but also for later lung function.
Longitudinal studies have shown that infants wit h
reduced lung function have an increased risk of develop-
ing asthma and respiratory illness later in life [97,98].
Shared genetic factors for reduced lung function in chil-
dren with asthma and adults who smoke (e.g. MMP12
variants) emphasize t he role of genetics on long term
lung function [99]. Wnt signaling genes (e.g. Wif1,
Wisp1) were not identified as asthma genes in our
literature search, and were thus not included in our ana-
lyses. In our previous article by Sharma et al, Wif1 and
Wisp1 were differentially expressed during fetal lung
development and polymorphisms in these genes also
Table 3 Gene expression analysis of specific asthma
genes and evidence for differential expression during
human lung development (adjusted p < 0.001 cut off)
Human
gene
symbol
Probe id Average
expression
Adjusted p-value
for differential
expression
Beta
coefficient
NOD1 221073_s_at 7.6 7.0E-8 0.012
EDN1 222802_at 9.3 1.6E-6 0.026
EDN1 218995_s_at 8.6 4.4E-6 0.019
ROBO1 213194_at 10.2 1.5E-5 -0.009
IL4R 203233_at 7.3 3.3E-5 0.010
RORA 226682_at 8.2 3.5E-5 0.022
RORA 236266_at 5.2 5.2E-5 0.011
HPCAL1 212552_at 9.4 5.4E-5 0.012
HLA-
DQB1
212998_x_at 4.8 1.5E-4 0.012
PLAUR 210845_s_at 5.9 2.0E-4 -0.008
IL2RB 205291_at 6.5 2.5E-4 0.007
CCL5 204655_at 4.7 2.6E-4 0.008
HPCAL1 205462_s_at 7.3 4.6E-4 0.013
TLR10 223751_x_at 4.1 4.9E-4 0.005
PDE10A 205501_at 6.4 6.3E-4 -0.011
CCL5 1405_i_at 4.1 9.9E-4 0.008
* Adjusted p-value (B-H method) for differential expression over time.
The beta coefficient corresponds to the mean change in gene expression
per day during the studied period (7-22 weeks of gestational age).
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Table 4 Genes with at least one significant probe per gene in the human data and at least in one mouse data set
(adjusted p-value <0.05)
Human gene
symbol
Mouse gene
symbol
Beta coef.*
human
Beta
coef.* A/
J
Beta
coef.*
SW
Beta coef.*
C57BL6
p-value
human data*
p-value
A/J
p-value
SW
p-value
C57BL6
Combined
p-value
NOD1 Nod1 0.012 --0.133 7.0E-8 --2.1E-2 4.7E-9
EDN1 Edn1 0.026 0.018 0.054 0.138 1.6E-6 7.4E-3 1.4E-3 2.4E-2 3.9E-11
ROBO1 Robo1 -0.009 -0.014 - -0.055 1.5E-5 3.8E-2 - 9.4E-2 6.9E-7
IL4R Il4ra 0.01 0.033 0.032 0.1 3.4E-5 3.0E-5 2.3E-2 5.5E-2 5.8E-11
RORA Rora 0.022 0.01 0.025 0.107 3.5E-5 1.3E-2 9.2E-3 2.1E-2 5.5E-9
PLAUR Plaur -0.008 0.013 0.015 0.106 2.0E-4 2.3E-2 5.2E-2 2.1E-2 9.8E-1
CCL5 Ccl5 0.008 0.022 0.027 0.079 2.6E-4 1.6E-7 1.9E-3 2.0E-2 5.5E-13
IRAK3 Irak3 -0.011 --0.073 1.3E-3 --4.5E-2 2.0E-2
IL18 Il18 0.004 0.01 0.018 0.139 1.6E-3 4.4E-4 2.4E-2 2.7E-1 1.3E-7
STAT6 Stat6 0.007 0.021 0.002 0.106 1.8E-3 1.6E-2 6.0E-1 4.7E-2 2.5E-5
CHIA Chia 0.009 0.077 0.039 0.288 1.8E-3 5.7E-3 3.4E-1 3.3E-2 4.0E-6
HLA-G H2-M3 0.01 0.021 0.032 0.103 2.6E-3 2.9E-5 9.2E-4 1.7E-2 3.7E-10
CD86 Cd86 0.003 0.001 0.008 0.097 5.6E-3 9.3E-1 1.3E-1 3.1E-2 1.9E-3
PRNP Prnp -0.003 0.02 0.031 0.106 8.9E-3 8.8E-3 1.1E-1 7.2E-2 5.0E-1
PCDH1 Pcdh1 0.006 --0.232 1.0E-2 --3.1E-2 1.6E-3
SERPINE1 Serpine1 0.021 0.018 0.02 0.129 1.6E-2 4.5E-5 9.6E-3 1.7E-2 3.3E-8
TNF Tnf 0.004 -0.003 0.007 0.051 2.3E-2 3.7E-1 2.6E-1 4.9E-2 4.5E-2
TLE4 Tle4 -0.004 -0.009 0.006 -0.07 2.3E-2 1.0E-3 3.1E-1 3.0E-1 1.0E-3
SCGB1A1 Scgb1a1 0.017 0.163 0.09 0.736 3.8E-2 1.2E-3 5.1E-2 1.8E-2 4.6E-6
* The beta coefficient corresponds to the mean change in gene expression per day during the studied period.
Adjusted p-value (B-H method). Combined p-value for all data sets (human and murine) using the weighted z-score method.
Empty boxes (-) indicate that the gene was not represented on the chip. Bolded rows indicate genes with at least one significant probe per gene in all tested
data sets (adjusted p-value <0.0 5).
Figure 1 Expression of EDN1 over time in human lung tissue in
relation to time (days post conception), p = 1.6E-6 for
differential expression. The fitted line through the data represents
the beta coefficient from linear regression analysis.
Figure 2 Expression of Edn1 over t ime in mouse whole l ung
tissue in relation to time (days post conception). Solid circles
represent the A/J data (p = 0.007 for differential expression), open
squares represent the C57BL6 data (p = 0.02) and solid triangles
represent the SW data (p = 0.001). The fitted line through each data
set represents the beta coefficient from linear regression analysis.
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showed association with lun g function measured as
FEV1 and FVC, but association to asthma per se was
not tested [14].
The transcriptional control of lung morphogenesis is
key for normal development f rom primordium to a
fully differentiated, functioning organ [100,101].
Human lung growth has historically been categorised
into five stages based on histological and anatomical
characteristics: embryonic (26 days to 5 weeks), pseu-
doglandular (5-16 weeks), canalicular (16-26 weeks),
saccular (26 weeks to birth), an d alveolar (birth to 6
months) [100]. Additional molecular phases wit hin
the pseudoglandular stage have been observed, which
extends our knowledge of lung development beyond
traditional embryology [15].
GWAS have co ntributed to important knowledge
about underlying functional genetics i n many complex
diseases [102]. The majority of trait associated SNPs
show weak to moderate effect sizes, which supports ear-
lier evidence that complex diseases result from several
genetic and, often, environmental factors. Evid ence of a
functional role is also lacking for most identified genes.
In order to increase our understanding of the mechan-
ism and potential function of asthma susceptibility
genes identified in published GWAS and classic
asthma candidate gen es, we evaluated their gene expres-
sion patterns in the developing human lung. Compara-
tive analyses also showed that many of the differential ly
expressed genes in the human data set were also differ-
entially expressed during murine lung development.
Among the GWAS asthma genes, ROBO1, RORA, HLA-
DQB1, IL2RB and PDE10A were differentially expressed
in the human data. These genes represent a wide range
of structural and ontological families with different
assumed functions, but their potential involvement in
lung development has previously not been thoroughly
evaluated. Regulation of cytokine production and cell
activation were the most significant bio-ontologic attri-
butes to genes differentialy expressed during lung
development.
Using the murine data sets for comparative analyses,
RORA, which encodes for a nuclear hormone receptor,
showed the most consistent expression pattern (expres-
sion positively correlated with gestational age in all data
sets). ROBO1 expression was on the other hand nega-
tively correlated with gestational age in all tested data
sets (albeit significant in only 2/3 sets), which indic ates
an important effect early in the developing lung and
then a diminishing effect over time. The ROBO1 protein
is involved in axon guidance and neuronal precursor cell
migration. PTGDR, WDR36, PRNP, DENND1B, PDE4D,
TLE4 and TSLP also showed weak evidence of differen-
tial expression in the human data using adjusted p <
0.05 as cut off (Additional file 1, Table E2), but none
showed consistent gene expression patterns in the mur-
ine data sets.
NOD1 showed the strongest evidence for differential
expression in the human data and this pattern was con-
sistent in the C57BL6 strain. However, Nod1 was not
represented on the platforms used for analyses on the
A/J and SW strains and could thus not b e evaluated in
these data sets (also true for another asthma gene with
consistent expression patterns, PCDH1 [52]). NOD1
encodes for a cytosolic protein which contains an N-
term inal caspase recruitment domain (CARD) and plays
an important role for recognition of bacterial com-
pounds and initiation of the innate immune response
[103]. Little i s known about the role of NOD1 during
lung development and our findings indicate that NOD1
could have important contribution.
EDN1 was the second most differentially expressed
asthma gene in the human data set and very consistent
expression patterns were found in all murine data sets.
Also for the embryonic stage analyses (pseudoglandular
vs canalicular), EDN1 was among the most highly differ-
entially expressed genes. In general, embryonic stage
results were very similar to the results using time as a
continuous variable. EDN1 belong to a family of
secreted peptides pro duced by vascular endothelial cells
with multiple effects on cardiovascular, neural, pulmon-
ary and renal physiology [104,105]. EDN1 shows invol-
vement in pulmonary hypertension, fibrosis, obstr uctive
diseases and acute lung injury, a nd is also required for
the normal development of several tissues. Mice lacking
the Edn1 gene die of respiratory failure at birth and
show severe craniofacial abnormalities, as well as cardio-
vascular defects [106,1 07]. Transgenic m ice with lung-
specific over-expression of the human EDN1 gene
develop, on the other hand, chronic lung inflammati on
and fibrosis [108]. Edn1 heterozygous knockout mice
also show increased bronchial responsiveness and these
result link EDN1 functionally to asthma and obstructive
diseases [72]. To date, three studies report significant
association between EDN1 and asthma [41,109,110].
Our data, as well as previous studies, point to an impor-
tant role for EDN1 in normal lung development, which
warrants further studies.
Our study has several limitations. Our 38 human lung
tissue samples were restricted to the pseudo glandular
and canalicular stages. Information about key exposures
that could influence gene expression patterns, such as
maternal smoking, residential area, and parental allergy
is not available. Thirty-eight samples are a relatively
small sample size for expression analys es due to human
biological variation and fe tal lung tissue during the later
stages of gestation was not available. It is possible that
some asthma genes are important for human lung devel-
opment during the later stages of gestation, but we were
Melén et al. Respiratory Research 2011, 12:86
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Page 6 of 10
notabletoevaluatethiswithourcurrentdataset.To
complement the human data, we analysed expression
patterns from early gestational to postnatal stages of
lung development in three different murine strains. We
used this murine data to replicate, in silico, the human
results in the early stages and to infer human gene
expression pattern in the later stages of the developing
lung. Also, the m icroarray platforms used in the
included data sets do not entirely co ver the human (and
murine) t ranscriptome and important genes may have
been missed (e.g. GPRA/NPSR1 [111] is not represented
on the U133 Plus 2.0 microarray chip and could not be
evaluated). Protein analyses could provide a better view
to understand specific gene functions and the post-tran-
scriptional regulation level, but such data was not avail-
able in our study. Our asthma gene list represents genes
that met our predefined criteria for asthma association,
and some genes genes may have been missed (e.g. those
only captured by the search terms family based study
AND asthma ). Given the rapid rate at whi ch novel
asthma susceptibility loci are being discovered, some of
the most recent asthma genes may have been missed.
These may introduce a potential null bias in the
analysis.
Conclusions
We have evaluated gene expression p atterns of asthma
susceptibility genes identified via a comprehensive litera-
ture search of candidate gene studies and GWAS pub-
lished to date. We found strong and consistent evidence of
differential expression of several asthma genes in the
developing human and murine lung. Among genes identi-
fied in asthma GWAS, ROBO1, RORA, HLA-DQB1, IL2RB
and PDE10A showed most consistent expression patterns
and from asthma candidate genes, e.g. NOD1, EDN1,
CCL5 and HLA-G were identified. Our analyses prov ide
functional insight about asthma susceptibility genes during
normal lung development, which improves our under-
standing about normal and pathological processes related
to respiratory diseases in children and adults.
Additional material
Additional file 1: Supplementary Tables and Figure. Expression
analysis of asthma candidate genes during human and murine lung
development.
List of abbreviations
CI: Confidence interval; DAVID: Database for Annotation, Visualization and
Integrated Discovery; GEO: Gene Expression Omnibus; GO: Gene ontology;
GWAS: Genome wide association studies; NCBI: National Center for
Biotechnology Information; OR: Odds ratio; qPCR: Quantitative real time
polymerase chain reaction.
Acknowledgements
The authors wish to thank Dr. Weiliang Qiu, Channing Laboratory, Brigham
and Womens Hospital and Harvard Medical School, for a valuable statistical
review. Financial support: Supported by National Institutes of Health grants
K25 HL91124, R01 HL88028, and P50 NS40828 (ATK.); R01 ES10855 (JSL); R01
HL097144 (STW), U01 HL65899 (STW and KGT); EM is supported by post doc
grants from the Swedish Heart Lung Foundation, the Swedish Fulbright
Commission, Centre for Allergy Research, Karolinska Institutet and
Riksbankens Jubileumsfond, Erik Rönnbergs scholarship for research on early
childhood diseases.
Author details
1
Channing Laboratory, Brigham and Womens Hospital and Harvard Medical
School, Boston, MA, USA.
2
Institute of Environmental Medicine, Karolinska
Institutet, Stockholm, Sweden.
3
Astrid Lindgren Childrens Hospital, Karolinska
University Hospital, Stockholm, Sweden.
4
Childrens Hospital Informatics
Program, Boston, MA, USA.
5
Division of Pulmonary and Critical Care
Medicine, Brigham and Womens Hospital, Boston, MA, USA.
6
Division of
Clinical Pharmacology and Medical Toxicology, Department of Pediatrics,
Childrens Mercy Hospitals and Clinics, Kansas City, MO, USA.
7
Division of
Neonatology and Center for Pediatric Biomedical Research, University of
Rochester, Rochester NY, USA.
8
Partners Center for Personalized Genetic
Medicine, Boston, MA, USA.
Authors contributions
EM carried out the literature search and the statistical analyses together with
ATK, SS and VJC. EM, RG, JSL, TJM, STW and KGT participated in the design
and planning of the study. EM, ATK and KGT drafted the manuscript. All
authors read and approved the final manuscript.
Competing interests
All authors declare no competing interests and no support from any
organisation for the submitted work; no financial relationships with any
organisations that might have an interest in the submitted work in the
previous 3 years; no other relationships or activities that could appear to
have influenced the submitted work.
Received: 15 March 2011 Accepted: 23 June 2011
Published: 23 June 2011
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doi:10.1186/1465-9921-12-86
Cite this article as: Melén et al.: Expression analysis of asthma candidate
genes during human and murine lung development. Respiratory Research
2011 12:86.
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Melén et al. Respiratory Research 2011, 12:86
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    • "ILC2s are defined based on their ability to produce an array of type 2 cytokines, including IL-4, IL-5, IL-9, and IL-13, as well the cytokine, amphiregulin, and are implicated in helminth clearance and allergic inflammation [88]. Several single nucleotide polymorphisms (SNPs) within the RORA gene are associated with increased susceptibility to asthma899091, and RORí µí»¼ null mice and ILC2-deficient mice generated by RORí µí»¼deficient bone marrow transplants have reduced type 2 cytokine production and partial protection from airway hyper-reactivity [87, 92]. RORí µí»¼ expression was significantly upregulated in patients with therapy-resistant asthma [93]. "
    [Show abstract] [Hide abstract] ABSTRACT: In this overview, we provide an update on recent progress made in understanding the mechanisms of action, physiological functions, and roles in disease of retinoic acid related orphan receptors (RORs). We are particularly focusing on their roles in the regulation of adaptive and innate immunity, brain function, retinal development, cancer, glucose and lipid metabolism, circadian rhythm, metabolic and inflammatory diseases and neuropsychiatric disorders. We also summarize the current status of ROR agonists and inverse agonists, including their regulation of ROR activity and their therapeutic potential for management of various diseases in which RORs have been implicated.
    Full-text · Article · Feb 2016
    • "SMAD3 (SMAD protein family member 3) is a (later) downstream transcription factor of TGFβ and is important for metabolic pathways of regulatory T cells and TH17 [31] cells. It is related to the metabolic pathway of regulatory T cells which forms part of the common [32] process of negative regulation of TH1 and TH2 [33]. SCG3 (secretogranin 3) encodes a protein member of the neuroendocrine secretory protein family, chromogranin/ secretogranin, which are ubiquitous protein regulators of protein secretion [34]. "
    [Show abstract] [Hide abstract] ABSTRACT: Asthma is a chronic disease of the airways and, despite the advances in the knowledge of associated genetic regions in recent years, their mechanisms have yet to be explored. Several genome-wide association studies have been carried out in recent years, but none of these have involved Latin American populations with a high level of miscegenation, as is seen in the Brazilian population. 1246 children were recruited from a longitudinal cohort study in Salvador, Brazil. Asthma symptoms were identified in accordance with an International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. Following quality control, 1 877 526 autosomal SNPs were tested for association with childhood asthma symptoms by logistic regression using an additive genetic model. We complemented the analysis with an estimate of the phenotypic variance explained by common genetic variants. Replications were investigated in independent Mexican and US Latino samples. Two chromosomal regions reached genome-wide significance level for childhood asthma symptoms: the 14q11 region flanking the DAD1 and OXA1L genes (rs1999071, MAF 0.32, OR 1.78, 95 % CI 1.45–2.18, p-value 2.83 × 10 −8 ) and 15q22 region flanking the FOXB1 gene (rs10519031, MAF 0.04, OR 3.0, 95 % CI 2.02–4.49, p-value 6.68 × 10 −8 and rs8029377, MAF 0.03, OR 2.49, 95 % CI 1.76–3.53, p-value 2.45 × 10 −7 ). eQTL analysis suggests that rs1999071 regulates the expression of OXA1L gene. However, the original findings were not replicated in the Mexican or US Latino samples. We conclude that the 14q11 and 15q22 regions may be associated with asthma symptoms in childhood.
    Full-text · Article · Dec 2015
    • "Enrichment analysis consisted of mapping Entrez Gene IDs of differentially expressed genes in culture and in brain onto IDs in entities of built-in functional ontologies represented in MetaCore by process networks and diseases to identify biological processes that were over-represented. Principal component analysis (PCA) was used to characterize the directions of maximal transcriptomic variance in the whole dataset192021 . PCA was performed on an RMA-normalized, ranked, and standardized matrix (mean zero and variance one) of 42 samples (45,101 probes represented on the array). "
    [Show abstract] [Hide abstract] ABSTRACT: Fragile X syndrome (FXS) is a neurodevelopmental disorder whose biochemical manifestations involve dysregulation of mGluR5-dependent pathways, which are widely modeled using cultured neurons. In vitro phenotypes in cultured neurons using standard morphological, functional, and chemical approaches have demonstrated considerable variability. Here, we study transcriptomes obtained in situ in the intact brain tissues of a murine model of FXS to see how they reflect the in vitro state. Methods We used genome-wide mRNA expression profiling as a robust characterization tool for studying differentially expressed pathways in fragile X mental retardation 1 (Fmr1) knockout (KO) and wild-type (WT) murine primary neuronal cultures and in embryonic hippocampal and cortical murine tissue. To study the developmental trajectory and to relate mouse model data to human data, we used an expression map of human development to plot murine differentially expressed genes in KO/WT cultures and brain. Results We found that transcriptomes from cell cultures showed a stronger signature of Fmr1KO than whole tissue transcriptomes. We observed an over-representation of immunological signaling pathways in embryonic Fmr1KO cortical and hippocampal tissues and over-represented mGluR5-downstream signaling pathways in Fmr1KO cortical and hippocampal primary cultures. Genes whose expression was up-regulated in Fmr1KO murine cultures tended to peak early in human development, whereas differentially expressed genes in embryonic cortical and hippocampal tissues clustered with genes expressed later in human development. Conclusions The transcriptional profile in brain tissues primarily centered on immunological mechanisms, whereas the profiles from cell cultures showed defects in neuronal activity. We speculate that the isolation and culturing of neurons caused a shift in neurological transcriptome towards a “juvenile” or “de-differentiated” state. Moreover, cultured neurons lack the close coupling with glia that might be responsible for the immunological phenotype in the intact brain. Our results suggest that cultured cells may recapitulate an early phase of the disease, which is also less obscured with a consequent “immunological” phenotype and in vivo compensatory mechanisms observed in the embryonic brain. Together, these results suggest that the transcriptome of cultured primary neuronal cells, in comparison to whole brain tissue, more robustly demonstrated the difference between Fmr1KO and WT mice and might reveal a molecular phenotype, which is typically hidden by compensatory mechanisms present in vivo. Moreover, cultures might be useful for investigating the perturbed pathways in early human brain development and genes previously implicated in autism.
    Full-text · Article · Dec 2015
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