Differential patterns of 27 cord blood immune biomarkers across gestational age

Nana Matoba, Nxian Yu, Karen Mestan, Colleen Pearson, Katherin Ortiz, Nicolas Porta, Poul Thorsen, Kristin Skogstrand, David M. Hougaard, Barry Zuckerman, Xiaobin Wang

Research output: Contribution to journalArticle

Abstract

OBJECTIVES. Inflammation has been associated with preterm delivery and adverse neonatal outcomes such as cerebral palsy and chronic lung disease. However, no study to date has simultaneously examined a wide range of inflammatory mediators and their relationship to gestational age. We sought to describe the distribution of immune biomarkers in cord blood across gestational age and to investigate the association between biomarker level patterns and preterm birth. PATIENTS AND METHODS. As part of a large-scale molecular epidemiological study of preterm birth conducted at Boston Medical Center, this study analyzed both clinical and biomarker data from 927 births. Twenty-seven biomarkers were simultaneously quantified by immunoassay. The associations between the quartiles of 27 biomarkers and 3 gestational groups (≤32, 33-36, and ≥37 weeks) were analyzed. Biomarkers found to be significant were further analyzed for dose-response correlation with preterm birth by logistic regression, adjusted for pertinent demographic and clinical factors. RESULTS. The 27 biomarkers could be classified into 1 of 3 groups: (1) biomarkers increased in preterm birth (interleukin [IL]-2, IL-4, IL-5, IL-8, IL-10, monocyte chemoattractant protein 1, macrophage inflammatory protein [MIP]-1α, MIP-1β, soluble IL-6 receptor α, tumor necrosis factor α, soluble tumor necrosis factor receptor I, and TREM-1 [triggering receptor expressed on myeloid cells 1]); (2) biomarkers decreased in preterm birth (brain-derived neurotrophic factor, IL-1β, IL-18, matrix metalloproteinase 9, and neurotrophin 3); and (3) biomarkers not associated with preterm birth (IL-6, IL-12, IL-17, granulocyte/macrophage colony-stimulating factor, interferon γ, macrophage migration inhibitory factor, neurotrophin 4, RANTES [regulated on activation, normal T-cell expressed and secreted], transforming growth factor β, and tumor necrosis factor β). CONCLUSIONS. Biomarkers have different directions of association with prematurity; for significant biomarkers, the strength of association increases with biomarker concentration. Our results provide important information that could be used to guide additional studies aimed at determining mechanisms that contribute to preterm birth.

Original languageEnglish (US)
Pages (from-to)1320-1328
Number of pages9
JournalPediatrics
Volume123
Issue number5
DOIs
StatePublished - May 2009
Externally publishedYes

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Fetal Blood
Gestational Age
Biomarkers
Premature Birth
Macrophage Inflammatory Proteins
Tumor Necrosis Factor-alpha
Macrophage Migration-Inhibitory Factors
Neurotrophin 3
Interleukin-6 Receptors
Matrix Metalloproteinase 3
Interleukin-18
Interleukin-17
Chemokine CCL2
Tumor Necrosis Factor Receptors
Brain-Derived Neurotrophic Factor
Interleukin-5
Matrix Metalloproteinase 9
Transforming Growth Factors
Myeloid Cells
Cerebral Palsy

Keywords

  • Biomarkers
  • Cord blood
  • Prematurity

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

Cite this

Matoba, N., Yu, N., Mestan, K., Pearson, C., Ortiz, K., Porta, N., ... Wang, X. (2009). Differential patterns of 27 cord blood immune biomarkers across gestational age. Pediatrics, 123(5), 1320-1328. https://doi.org/10.1542/peds.2008-1222

Differential patterns of 27 cord blood immune biomarkers across gestational age. / Matoba, Nana; Yu, Nxian; Mestan, Karen; Pearson, Colleen; Ortiz, Katherin; Porta, Nicolas; Thorsen, Poul; Skogstrand, Kristin; Hougaard, David M.; Zuckerman, Barry; Wang, Xiaobin.

In: Pediatrics, Vol. 123, No. 5, 05.2009, p. 1320-1328.

Research output: Contribution to journalArticle

Matoba, N, Yu, N, Mestan, K, Pearson, C, Ortiz, K, Porta, N, Thorsen, P, Skogstrand, K, Hougaard, DM, Zuckerman, B & Wang, X 2009, 'Differential patterns of 27 cord blood immune biomarkers across gestational age', Pediatrics, vol. 123, no. 5, pp. 1320-1328. https://doi.org/10.1542/peds.2008-1222
Matoba N, Yu N, Mestan K, Pearson C, Ortiz K, Porta N et al. Differential patterns of 27 cord blood immune biomarkers across gestational age. Pediatrics. 2009 May;123(5):1320-1328. https://doi.org/10.1542/peds.2008-1222
Matoba, Nana ; Yu, Nxian ; Mestan, Karen ; Pearson, Colleen ; Ortiz, Katherin ; Porta, Nicolas ; Thorsen, Poul ; Skogstrand, Kristin ; Hougaard, David M. ; Zuckerman, Barry ; Wang, Xiaobin. / Differential patterns of 27 cord blood immune biomarkers across gestational age. In: Pediatrics. 2009 ; Vol. 123, No. 5. pp. 1320-1328.
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AU - Matoba, Nana

AU - Yu, Nxian

AU - Mestan, Karen

AU - Pearson, Colleen

AU - Ortiz, Katherin

AU - Porta, Nicolas

AU - Thorsen, Poul

AU - Skogstrand, Kristin

AU - Hougaard, David M.

AU - Zuckerman, Barry

AU - Wang, Xiaobin

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N2 - OBJECTIVES. Inflammation has been associated with preterm delivery and adverse neonatal outcomes such as cerebral palsy and chronic lung disease. However, no study to date has simultaneously examined a wide range of inflammatory mediators and their relationship to gestational age. We sought to describe the distribution of immune biomarkers in cord blood across gestational age and to investigate the association between biomarker level patterns and preterm birth. PATIENTS AND METHODS. As part of a large-scale molecular epidemiological study of preterm birth conducted at Boston Medical Center, this study analyzed both clinical and biomarker data from 927 births. Twenty-seven biomarkers were simultaneously quantified by immunoassay. The associations between the quartiles of 27 biomarkers and 3 gestational groups (≤32, 33-36, and ≥37 weeks) were analyzed. Biomarkers found to be significant were further analyzed for dose-response correlation with preterm birth by logistic regression, adjusted for pertinent demographic and clinical factors. RESULTS. The 27 biomarkers could be classified into 1 of 3 groups: (1) biomarkers increased in preterm birth (interleukin [IL]-2, IL-4, IL-5, IL-8, IL-10, monocyte chemoattractant protein 1, macrophage inflammatory protein [MIP]-1α, MIP-1β, soluble IL-6 receptor α, tumor necrosis factor α, soluble tumor necrosis factor receptor I, and TREM-1 [triggering receptor expressed on myeloid cells 1]); (2) biomarkers decreased in preterm birth (brain-derived neurotrophic factor, IL-1β, IL-18, matrix metalloproteinase 9, and neurotrophin 3); and (3) biomarkers not associated with preterm birth (IL-6, IL-12, IL-17, granulocyte/macrophage colony-stimulating factor, interferon γ, macrophage migration inhibitory factor, neurotrophin 4, RANTES [regulated on activation, normal T-cell expressed and secreted], transforming growth factor β, and tumor necrosis factor β). CONCLUSIONS. Biomarkers have different directions of association with prematurity; for significant biomarkers, the strength of association increases with biomarker concentration. Our results provide important information that could be used to guide additional studies aimed at determining mechanisms that contribute to preterm birth.

AB - OBJECTIVES. Inflammation has been associated with preterm delivery and adverse neonatal outcomes such as cerebral palsy and chronic lung disease. However, no study to date has simultaneously examined a wide range of inflammatory mediators and their relationship to gestational age. We sought to describe the distribution of immune biomarkers in cord blood across gestational age and to investigate the association between biomarker level patterns and preterm birth. PATIENTS AND METHODS. As part of a large-scale molecular epidemiological study of preterm birth conducted at Boston Medical Center, this study analyzed both clinical and biomarker data from 927 births. Twenty-seven biomarkers were simultaneously quantified by immunoassay. The associations between the quartiles of 27 biomarkers and 3 gestational groups (≤32, 33-36, and ≥37 weeks) were analyzed. Biomarkers found to be significant were further analyzed for dose-response correlation with preterm birth by logistic regression, adjusted for pertinent demographic and clinical factors. RESULTS. The 27 biomarkers could be classified into 1 of 3 groups: (1) biomarkers increased in preterm birth (interleukin [IL]-2, IL-4, IL-5, IL-8, IL-10, monocyte chemoattractant protein 1, macrophage inflammatory protein [MIP]-1α, MIP-1β, soluble IL-6 receptor α, tumor necrosis factor α, soluble tumor necrosis factor receptor I, and TREM-1 [triggering receptor expressed on myeloid cells 1]); (2) biomarkers decreased in preterm birth (brain-derived neurotrophic factor, IL-1β, IL-18, matrix metalloproteinase 9, and neurotrophin 3); and (3) biomarkers not associated with preterm birth (IL-6, IL-12, IL-17, granulocyte/macrophage colony-stimulating factor, interferon γ, macrophage migration inhibitory factor, neurotrophin 4, RANTES [regulated on activation, normal T-cell expressed and secreted], transforming growth factor β, and tumor necrosis factor β). CONCLUSIONS. Biomarkers have different directions of association with prematurity; for significant biomarkers, the strength of association increases with biomarker concentration. Our results provide important information that could be used to guide additional studies aimed at determining mechanisms that contribute to preterm birth.

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