1. Immunology and Inflammation
  2. Medicine

Perinatal granulopoiesis and risk of pediatric asthma

  1. Benjamin A Turturice  Is a corresponding author
  2. Juliana Theorell
  3. Mary Dawn Koenig
  4. Lisa Tussing-Humphreys
  5. Diane R Gold
  6. Augusto A Litonjua
  7. Emily Oken
  8. Sheryl L Rifas-Shiman
  9. David L Perkins  Is a corresponding author
  10. Patricia W Finn  Is a corresponding author
  1. Department of Microbiology and Immunology, University of Illinois, United States
  2. Department of Medicine, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois, United States
  3. Department of Women, Children and Family Health Science, College of Nursing, University of Illinois, United States
  4. Department of Medicine and Cancer Center, University of Illinois, United States
  5. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, United States
  6. Department of Environmental Health, Harvard T.H. Chan School of Public Health, United States
  7. Division of Pulmonary Medicine, Department of Pediatrics, University of Rochester, United States
  8. Division of Chronic Disease Research Across the Life Course, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, United States
  9. Department of Medicine, Division of Nephrology, University of Illinois, United States
  10. Department of Bioengineering, University of Illinois, United States
https://doi.org/10.7554/eLife.63745
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Cite this article
  1. Benjamin A Turturice
  2. Juliana Theorell
  3. Mary Dawn Koenig
  4. Lisa Tussing-Humphreys
  5. Diane R Gold
  6. Augusto A Litonjua
  7. Emily Oken
  8. Sheryl L Rifas-Shiman
  9. David L Perkins
  10. Patricia W Finn
(2021)
Perinatal granulopoiesis and risk of pediatric asthma
eLife 10:e63745.
https://doi.org/10.7554/eLife.63745
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5 figures, 5 tables and 8 additional files

Figures

Figure 1
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Overview of analytic approach used to identify biological risk for pediatric asthma.

(A) Previously described perinatal risk factors for development of pediatric asthma: preterm birth, low birthweight, male, and maternal obesity. (B) Flow diagram of search, inclusion, exclusion, and univariate testing for transcriptomic analysis. (C) Cohorts, types of biosamples, and outcomes used for validation.

Figure 2 with 1 supplement
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Pooled meta-analysis z-scores identify gene expression signatures related to asthma risk.

Significant (FDR < 1%) genes and gene sets are colored by their association with either higher (red) or lower (blue) risk. (A) Volcano plots of gene expression for univariate analyses. Top 10 most significant genes labeled. (B) Word clouds of GO terms significantly enriched (FDR < 1%) using the pooled z-score as pre-ranked list for GSEA. (C) Protein coding transcripts per million reads (pTPM) in peripheral blood cells (Human Protein Atlas and Monaco et al (Uhlen et al., 2010; Monaco et al., 2019) relative to pooled z-score. Each line represents one cell type; neutrophils highlighted in orange. (D) Spearman’s correlation between pooled z-statistic and individual analyses (diamonds). Average Spearman’s correlations between individual analyses and combination of all other analyses (circle), SD indicated by error bars.

Figure 2—figure supplement 1
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Association between differentially methylated genes and gene expression changes with gestational age.

Comparison of effect size associated with gestational age for genes that were reported as differentially methylated by Bohlin et al., 2016. Gene with increased methylation associated with gestational age demonstrate reduced expression with increasing gestational age.

Figure 3 with 2 supplements
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Validation cohort identifies gene signature associated with pediatric asthma risk factors.

Color labeling indicating association with either higher (red) or lower (blue) risk of pediatric asthma development. (A) Dot-plot demonstrating validation between meta-analysis pooled z-score and UIH cohort mRNAseq z-score. Colored and labeled dots indicate those with non-parametric replication score greater than 3 and 4, respectively. (B,C) Association between number of risk factors or individual risk factors and eigenvalue of gene signature (validation score > 3), UIH cohort.

Figure 3—figure supplement 1
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Replication score enriches for genes associated with multiple risk factors.

Splines (colored according to analysis) of median p-values (left y-axis) for genes with replication scores greater than corresponding cut-off (x-axis). Percentage of genes with replication score greater than corresponding cut-off. Vertical dashed lines two cutoffs: RS > 0 and RS > 3.

Figure 3—figure supplement 2
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Protein–protein Interaction network of candidate genes.

(A) Protein–protein interaction network of candidate genes inferred from STRING (Szklarczyk et al., 2019). Nodes are labeled by risk association: low (blue) and high (red) risk candidate genes. Nodes are colored (purple) if they are associated with GO cellular component term enrichment. (B) Word clouds of GO terms significantly enriched in candidate genes.

Figure 4 with 1 supplement
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Cellular and proteomic differences associated with pediatric asthma risk factors.

(A–C) Re-analysis of publicly available data from Olin et al., 2018. (A) Percentage of neutrophils in cord blood (transformed using centered log-ratios, CLR) correlated with number of risk factors. Pearson’s correlation (R) and Bonferroni adjusted p-value reported. (B) Pearson’s correlation coefficients (R) for plasma-protein concentration and number of risk factors distributed based on risk association of proteins as per Figure 3. Corresponding mRNA from CBMCs were identified for low-risk associated proteins (blue) and no risk associated proteins (dark gray). Most significant negative protein correlations with neutrophil-enriched mRNA (Human Protein Atlas [Uhlen et al., 2010]) are notated. Proteins identified in previous analysis without corresponding mRNA shown light gray. (C) Heatmap of Pearson’s correlations between neutrophils and neutrophil-derived proteins identified in (B). (D) Association between PGLYRP-1 umbilical cord serum concentration, PGLYRP-1 CBMC mRNA, and number of risk factors in UIH cohort.

Figure 4—figure supplement 1
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Association between PGLYRP-1 and sIL6Rα in UIH and Project Viva cohorts.

Scatter plot displaying association between PGLYRP-1 and sIL6Rα in UIH (blue) and Project Viva (yellow) cohorts. Univariate regression lines are shown for both cohorts. Distributions for PGLYRP-1 and sIL6Rα are shown in the margins for each cohort.

Figure 5 with 3 supplements
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Increased umbilical cord blood serum PGLYRP-1 is associated with increased FEV1/FVC and reduced odds of pediatric asthma.

Samples and data derived from a subset of Project Viva (n=358). Odds ratio and coefficient estimates are based on 1 SD increase in serum proteins (PGLYRP-1, sIL6Rα). Error bars indicate 95% CI. Adjusted model co-variates: gestational age, birthweight adjusted for gestational age and sex, mode of delivery, child’s sex, child's race/ethnicity, maternal pre-pregnancy BMI, maternal level of education, maternal atopy, antibiotic exposure during pregnancy, and early-life smoke exposure. (A) PGLYRP-1 and sIL6Rα concentrations in umbilical cord blood serum association with current asthma at mid-childhood and early-teenage time points (determined by questionnaire responses). (B) PGLYRP-1 and sIL6Rα concentrations in umbilical cord blood serum association with FEV1/FVCx100 at mid-childhood and early-teenage follow ups. ***p<0.001, **p<0.01, *p<0.05, #p<0.1.

Figure 5—figure supplement 1
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Cord blood serum proteins in relationship to outcomes.

(A) PGLYRP-1 concentration in umbilical cord blood serum in relationship to current asthma determined by questionnaire response and (B) FEV1/FVCx100 at mid-childhood and early-teenage follow ups. (C) sIL6Rα concentration in umbilical cord blood serum in relationship to current asthma determined by questionnaire response and (D) FEV1/FVCx100 at mid-childhood and early-teenage follow ups.

Figure 5—figure supplement 2
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Relative importance of predictors for pediatric asthma and FEV1/FVC.

Relative importance, displayed as percent of variance explained, for variables used in regressions (Table 3, model 3) for current asthma at mid-childhood and FEV1/FVC in early-teen years. Variance estimated for logistic regression as Mcfadden’s pseudo-R (Jaakkola et al., 2006).

Figure 5—figure supplement 3
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Subset analysis for all covariates used in regression models.

Funnel plot demonstrating relationship effect size estimates and measurement error for subset analyses for (A) current mid-childhood asthma and (B) FEV1/FVCx100 in early-teen years. 95% CI (botted lines) and 99% CI (dashed lines) displayed.

Tables

Table 1
GSE data sets used for meta-analyses.
GSEGPLNNewborn sexGestational ageBirthweightMaternal pre-pregnancy BMITitle
GSE21342GPL694737+Maternal influences on the transmission of leukocyte gene expression profiles in population samples
GSE25504GPL57020+Whole blood mRNA expression profiling of host molecular networks in neonatal sepsis
GSE27272GPL688364+++Comprehensive study of tobacco smoke-related transcriptome alterations in maternal and fetal cells
GSE30032GPL688347+++Deregulation of gene expression induced by environmental tobacco smoke exposure in pregnancy
GSE36828GPL694748++Genome-wide analysis of gene expression levels in placenta and cord blood samples from newborns babies
GSE37100GPL1455038+++Transcriptome changes affecting hedgehog and cytokine signaling in the umbilical cord in late pregnancy: implications for disease risk
GSE48354GPL1668638+++Prenatal arsenic exposure and the epigenome: altered gene expression profiles in newborn cord blood
GSE53473GPL13667128++Standard of hygiene and immune adaptation in newborn infants
GSE60403GPL57016++The obese fetal transcriptome
GSE73685GPL624423+Unique inflammatory transcriptome profiles at the maternal fetal interface and onset of human preterm and term birth
GSE83393GPL17077146+Newborn sex-specific transcriptome signatures and gestational exposure to fine particles: findings from the ENVIRONAGE Birth Cohort
N605386386235164
Table 2
Univariate associations between demographics and serum proteins.
UIH (n = 29)Project viva (n = 358)
β (95% CI)p-valueβ (95% CI)p-value
PGLYRP-1 Z-score*
Number of risk factors†−0.54 (–0.88, –0.19)0.005−0.22 (–0.36, –0.07)0.003
Maternal race: White (ref)0 (ref)0 (ref)
Maternal race: Black0.01 (–0.83, 0.86)0.970.15 (–0.16, 0.46)0.34
Maternal race: Hispanic1.03 (0.05, 2.01)0.040.40 (–0.07, 0.86)0.10
Maternal race: Other1.54 (–0.46, 3.54)0.120.10 (–0.25, 0.46)0.57
Maternal atopy−0.14 (–0.92, 0.64)0.720.06 (–0.16, 0.28)0.58
Maternal pre-pregnancy BMI−0.03 (–0.09, 0.02)0.250.01 (–0.01, 0.03)0.56
Maternal smoking: never (ref)0 (ref)0 (ref)
Maternal smoking: former0.09 (–0.92, 1.12)0.84−0.16 (–0.44, 0.11)0.25
Maternal smoking: during pregnancy––−0.12 (–0.47, 0.22)0.48
Maternal college graduate0.07 (–0.80, 0.93)0.87−0.12 (–0.34, 0.10)0.27
Any antibiotic use during pregnancy––0.20 (-0.02, 0.43)0.08
Gestational age weeks0.25 (–0.01, 0.51)0.060.12 (0.06, 0.19)0.0003
Birthweight adj GA and Sex (Z-score)0.33 (–1.07, 1.74)0.630.03 (–0.09, 0.14)0.66
Female0.39 (–0.37, 1.15)0.300.31 (0.11, 0.52)0.003
C-section−0.08 (–0.89, 0.74)0.85−0.29 (–0.55, –0.02)0.03
Child’s race: White (ref)––0 (ref)
Child’s race: Black––0.16 (–0.14, 0.46)0.31
Child’s race: Hispanic––0.18 (–0.31, 0.68)0.46
Child’s race: Other––0.06 (-0.27, 0.38)0.73
sIL6Rα Z-score*
Number of risk factors†−0.14 (–0.54, –0.25)0.480.02 (–0.13, 0.16)0.81
Maternal race: White (ref)0 (ref)0 (ref)
Maternal race: Black−1.04 (–1.90, –0.19)0.02−0.29 (–0.60, 0.02)0.07
Maternal race: Hispanic−0.36 (–1.34, 0.62)0.450.34 (-0.12, 0.80)0.15
Maternal race: Other0.4 (–1.61, 2.42)0.68−0.03 (–0.39, 0.32)0.85
Maternal atopy−0.23 (–1.01, 0.54)0.55−0.08 (–0.30, 0.14)0.47
Maternal pre-pregnancy BMI−0.04 (–0.10, 0.01)0.120.00 (–0.02, 0.02)0.72
Maternal smoking: never (ref)0 (ref)0 (ref)
Maternal smoking: former−0.90 (–1.86, 0.06)0.07−0.23 (–0.50, 0.05)0.10
Maternal smoking: during pregnancy––−0.12 (–0.46, 0.22)0.48
Maternal college graduate0.44 (–0.41, 1.29)0.29−0.02 (–0.24, 0.19)0.84
Any antibiotic use during pregnancy––0.04 (–0.19, 0.26)0.76
Gestational age weeks−0.11 (–0.39, 0.17)0.43−0.04 (–0.10, 0.03)0.29
Birthweight adj GA and sex (Z-score)−0.15 (–1.57, 1.26)0.82−0.07 (–0.18, 0.04)0.23
Female0.48 (–0.28, 1.23)0.210.05 (–0.16, 0.26)0.63
C-section−0.60 (–1.38, 0.18)0.12−0.14 (–0.41, 0.12)0.29
Child’s race: White (ref)––0 (ref)
Child’s race: Black––−0.24 (–0.54, 0.05)0.11
Child’s race: Hispanic––0.27 (–0.22, 0.76)0.28
Child’s race: Other––0.02 (–0.30, 0.34)0.90

  1. *Serum protein concentrations for UIH and Project Viva were log10 transformed and converted into an internal Z-score.

    †Number of risk factors determined by preterm birth, maternal BMI > 29.9, male, birthweight (z-score) < −1.

Table 3
Association between serum protein concentration and asthma outcomes.
Mid-childhoodEarly-teen
Current asthma, OR (95% CI)Ever asthma, OR (95% CI)Current asthma, OR (95% CI)Ever asthma, OR (95% CI)
PGLYRP-1 Z-score*
Univariate0.52 (0.35, 0.75)0.52 (0.36, 0.74)0.65 (0.39, 1.10)0.64 (0.45, 0.89)
Model 1†0.57 (0.37, 0.85)0.54 (0.36, 0.79)0.86 (0.48, 1.54)0.72 (0.50, 1.03)
Model 2‡0.57 (0.26, 0.65)0.41 (0.26, 0.61)0.62 (0.35, 1.09)0.61 (0.42, 0.87)
Model 3#0.50 (0.31, 0.77)0.48 (0.31, 0.77)0.88 (0.45, 1.72)0.74 (0.51, 1.07)
sIL6Rα Z-score*
Univariate0.87 (0.61, 1.23)0.93 (0.67, 1.29)0.75 (0.42, 1.28)0.93 (0.66, 1.29)
Model 1†0.83 (0.56, 1.23)0.89 (0.63, 1.30)0.68 (0.37, 1.21)0.90 (0.63, 1.27)
Model 2‡0.83 (0.57, 1.24)0.90 (0.63, 1.28)0.67 (0.33, 1.27)0.93 (0.65, 1.31)
Model 3#0.83 (0.55, 1.25)0.90 (0.62, 1.30)0.60 (0.27, 1.19)0.88 (0.61, 1.27)

  1. *Serum protein concentrations were log10 transformed and converted into an internal Z-score.

    †Serum protein concentrations were log10 transformed and conver gestational age, birthweight adjusted for gestational age, mode of delivery, child’s sex, child’s race/ethnicity.

  2. ‡(Mother’s demographics): adjusted for maternal pre-pregnancy BMI, maternal race/ethnicity, maternal level of education, maternal atopy, antibiotic exposure during pregnancy, smoking during pregnancy, 6 months or 1 year.

    #Model 3 (all demographics and birth characteristics): adjusted for all demographics and characteristics in models 1 and 2 except maternal race/ethnicity. This reported value in manuscript.

Table 4
Association between serum protein concentration and pulmonary function.
Mid-childhoodEarly-teen
FEV1/FVCx100 β (95% CI)BDR β (95% CI)FEV1/FVCx100 β (95% CI)BDR β (95% CI)
PGLYRP-1 Z-score*
Univariate1.38 (0.15, 2.61)0.10 (−1.83, 2.03)1.45 (0.49, 2.42)−0.68 (−1.54, 0.17)
Model 1†1.12 (−0.18, 2.41)0.53 (−1.44, 2.51)1.05 (0.11, 1.98)−0.49 (−1.40, 0.41)
Model 2‡1.38 (0.08, 2.69)0.61 (−1.40, 2.63)1.53 (0.54, 2.53)−0.58 (−1.49, 0.34)
Model 3#1.19 (−0.19, 2.56)1.00 (−1.04, 3.04)1.15 (0.20, 2.10)−0.35 (−1.29, 0.59)
sIL6Rα Z-score*
Univariate0.95 (−0.31, 2.20)−0.38 (−2.45, 1.69)0.11 (−0.86, 1.09)0.65 (−0.24, 1.54)
Model 1†0.96 (−0.30, 2.21)−0.37 (-2.41, 1.67)0.02 (−0.87, 0.92)0.71 (−0.19, 1.61)
Model 2‡0.88 (−0.40, 2.16)−0.62 (−2.62, 1.39)−0.02 (−1.00, 0.97)0.75 (−0.17, 1.66)
Model 3#0.92 (−0.36, 2.20)−0.11 (−0.96, 0.70)−0.05 (−0.94, 0.85)0.79 (−0.12, 1.69)

  1. *Serum protein concentrations were log10 transformed and converted into an internal Z-score.

    †Serum protein concentrations were log10 transformed and converted into an internal Z-scoreupplemental Data\\Table 4_Association pulmonary outcomes.xlsx’ "Shed's race/ethnicity.

  2. ‡(Mother's demographics): adjusted for maternal pre-pregnancy BMI, maternal race/ethnicity, maternal level of education, maternal atopy, antibiotic exposure during pregnancy, smoking during pregnancy, 6 months or 1 year.

    #Model 3 (all demographics and birth characteristics): adjusted for all demographics and characteristics in models 1 and 2 except maternal race/ethnicity. This the reported value in manuscript.

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Gene (Homo sapiens)Homo sapiens Genome AssemblyEnsemblGRCh38.12
Biological sample (Homo sapiens)Primary Cord Blood Mononuclear CellsVolunteersUIH CohortDemographics reported in Supplementary file 5
Biological sample (Homo sapiens)Cord Blood SerumVolunteersUIH Cohort
Project Viva		Demographics reported in Supplementary files 5 and 7
Commercial assay or kitHuman PGLYRP1/PGRP-S DuoSet ELISAR and D SystemsDY2590
Commercial assay or kitHuman IL6Ra DuoSet ELISAR and D SystemsDY227
Commercial assay or kitRNeasy Mini KitQiagen74104
Commercial assay or kitRNA 6000 Nano KitAgilent5067–1511
Commercial assay or kitQubit RNA HS Assay KitThermo Fisher ScientificQ32852
Commercial assay or kitTruSeq Stranded mRNA Library Prep KitIllumina20020594
Commercial assay or kitHiSeq × Ten Reagent Kit v2.5IlluminaFC-501–2501
Software, algorithmRRVersion 3.6.3
Software, algorithmgeoqueryBioconductorVersion: 2.36.0
Software, algorithmGeneMetaBioconductorVersion: 1.54.0
Software, algorithmtximportBioconductorVersion: 1.10.1
Software, algorithmDESeq2BioconductorVersion: 1.22.2
Software, algorithmrelaimpoCRANVersion: 2.2–3
Software, algorithmsalmonGithubVersion 0.12.00
Software, algorithmGSEAgsea-msigdb.orgVersion 4.0

Additional files

Supplementary file 1

Meta-analysis of CBMC gene expression associated with newborn sex.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp1-v2.xlsx
Supplementary file 2

Meta-analysis of CBMC gene expression associated with gestational age.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp2-v2.xlsx
Supplementary file 3

Meta-analysis of CBMC gene expression associated with birthweight.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp3-v2.xlsx
Supplementary file 4

Meta-analysis of CBMC gene expression associated with maternal pre-pregnancy BMI.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp4-v2.xlsx
Supplementary file 5

UIH cohort demographics.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp5-v2.xlsx
Supplementary file 6

UIH cohort CBMC gene expression DESeq2 results.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp6-v2.xlsx
Supplementary file 7

Project viva demographics.

https://cdn.elifesciences.org/articles/63745/elife-63745-supp7-v2.xlsx
Transparent reporting form
https://cdn.elifesciences.org/articles/63745/elife-63745-transrepform-v2.pdf

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  1. Benjamin A Turturice
  2. Juliana Theorell
  3. Mary Dawn Koenig
  4. Lisa Tussing-Humphreys
  5. Diane R Gold
  6. Augusto A Litonjua
  7. Emily Oken
  8. Sheryl L Rifas-Shiman
  9. David L Perkins
  10. Patricia W Finn
(2021)
Perinatal granulopoiesis and risk of pediatric asthma
eLife 10:e63745.
https://doi.org/10.7554/eLife.63745