open access

Vol 88, No 8 (2017)
Research paper
Published online: 2017-08-31
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Comparison of whole genome expression profile between preterm and full-term newborns

Przemko Kwinta1, Renata Bokiniec2, Mirosław Bik-Multanowski3, Clara-Cecilie Gunther4, Agnieszka Grabowska3, Teofila Książek3, Anna Madetko-Talowska3, Katarzyna Szewczyk3, Monika Szwarc-Duma2, Maria K. Borszewska-Kornacka2, Lars O. Baumbusch5, Cecilie Revhaug5, Ola D. Saugstad5, Jacek J. Pietrzyk1
·
Pubmed: 28930370
·
Ginekol Pol 2017;88(8):434-441.
Affiliations
  1. Department of Pediatrics, Chair of Pediatrics, Jagiellonian Univeristy Medical College, Krakow, Poland
  2. Klinika Neonatologii i Intensywnej Terapii Noworodka, Warszawski Uniwersytet Medyczny, Karowa 2, 00315 Warszawa, Poland
  3. Katedra Pediatrii, Zakład Genetyki Medycznej, Uniwersytet Jagielloński, Collegium Medicum, Wielicka 265, 30663 Kraków, Poland
  4. Oslo Computing Center, Gaustadalleen 23a, 0373 Oslo, Norway
  5. Department of Pediatric Research, Oslo University Hospital and University of Oslo, Sognsvannsveien 20, 0372 Oslo, Norway

open access

Vol 88, No 8 (2017)
ORIGINAL PAPERS Obstetrics
Published online: 2017-08-31

Abstract

Objectives: Evaluate the time dependent expression of genes in preterm neonates and verify the influence of ontogenic maturation and the environmental factors on the gene expression after birth. Material and methods: The study was carried out on 20 full-term newborns and 62 preterm newborns (mean birth weight = 1002 [g] (SD: 247), mean gestational age = 27.2 weeks (SD: 1.9)). Blood samples were drawn from all the study participants at birth and at the 36th week postmenstrual age from the preterm group to assess whole genome expression in umbilical cord blood and in peripheral blood leukocytes, respectively. (SurePrint G3 Human Gene Expression v3, 8x60K Microarrays (Agilent)).

Results: A substantial number of genes was found to be expressed differentially at the time of birth and at 36 PMA in comparison to the term babies with more genes being down-regulated than up-regulated. However, the fold change in the majority of cases was < 2.0. Extremely preterm and very preterm infants were characterized by significantly down-regulated cytokine and chemokine related pathways. The number of down-regulated genes decreased and number of up-regulated genes increased at 36 PMA vs. cord blood. There were no specific gene expression pathway profiles found within the groups of different gestational ages.

Conclusions: Preterm delivery is associated with a different gene expression profile in comparison to term delivery. The gene expression profile changes with the maturity of a newborn measured by the gestational age.

Abstract

Objectives: Evaluate the time dependent expression of genes in preterm neonates and verify the influence of ontogenic maturation and the environmental factors on the gene expression after birth. Material and methods: The study was carried out on 20 full-term newborns and 62 preterm newborns (mean birth weight = 1002 [g] (SD: 247), mean gestational age = 27.2 weeks (SD: 1.9)). Blood samples were drawn from all the study participants at birth and at the 36th week postmenstrual age from the preterm group to assess whole genome expression in umbilical cord blood and in peripheral blood leukocytes, respectively. (SurePrint G3 Human Gene Expression v3, 8x60K Microarrays (Agilent)).

Results: A substantial number of genes was found to be expressed differentially at the time of birth and at 36 PMA in comparison to the term babies with more genes being down-regulated than up-regulated. However, the fold change in the majority of cases was < 2.0. Extremely preterm and very preterm infants were characterized by significantly down-regulated cytokine and chemokine related pathways. The number of down-regulated genes decreased and number of up-regulated genes increased at 36 PMA vs. cord blood. There were no specific gene expression pathway profiles found within the groups of different gestational ages.

Conclusions: Preterm delivery is associated with a different gene expression profile in comparison to term delivery. The gene expression profile changes with the maturity of a newborn measured by the gestational age.

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Keywords

transcriptome, very low birth weight, cord blood

About this article
Title

Comparison of whole genome expression profile between preterm and full-term newborns

Journal

Ginekologia Polska

Issue

Vol 88, No 8 (2017)

Article type

Research paper

Pages

434-441

Published online

2017-08-31

Page views

1946

Article views/downloads

1460

DOI

10.5603/GP.a2017.0080

Pubmed

28930370

Bibliographic record

Ginekol Pol 2017;88(8):434-441.

Keywords

transcriptome
very low birth weight
cord blood

Authors

Przemko Kwinta
Renata Bokiniec
Mirosław Bik-Multanowski
Clara-Cecilie Gunther
Agnieszka Grabowska
Teofila Książek
Anna Madetko-Talowska
Katarzyna Szewczyk
Monika Szwarc-Duma
Maria K. Borszewska-Kornacka
Lars O. Baumbusch
Cecilie Revhaug
Ola D. Saugstad
Jacek J. Pietrzyk

References (17)
  1. Stoll BJ, Hansen NI, Bell EF, et al. Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. Trends in Care Practices, Morbidity, and Mortality of Extremely Preterm Neonates, 1993-2012. JAMA. 2015; 314(10): 1039–1051.
  2. Kusuda S, Fujimura M, Uchiyama A, et al. Neonatal Research Network, Japan. Trends in morbidity and mortality among very-low-birth-weight infants from 2003 to 2008 in Japan. Pediatr Res. 2012; 72(5): 531–538.
  3. Beligere N, Perumalswamy V, Tandon M, et al. Retinopathy of prematurity and neurodevelopmental disabilities in premature infants. Semin Fetal Neonatal Med. 2015; 20(5): 346–353.
  4. Jarjour IT. Neurodevelopmental outcome after extreme prematurity: a review of the literature. Pediatr Neurol. 2015; 52(2): 143–152.
  5. Strueby L, Thébaud B. Advances in bronchopulmonary dysplasia. Expert Rev Respir Med. 2014; 8(3): 327–338.
  6. Bhandari V, Bizzarro MJ, Shetty A, et al. Neonatal Genetics Study Group. Familial and genetic susceptibility to major neonatal morbidities in preterm twins. Pediatrics. 2006; 117(6): 1901–1906.
  7. Saugstad O. Oxygen and oxidative stress in bronchopulmonary dysplasia. J Perinat Med. 2010; 38(6): 571–577.
  8. Karna P, Muttineni J, Angell L, et al. Retinopathy of prematurity and risk factors: a prospective cohort study. BMC Pediatr. 2005; 5(1): 18.
  9. Kim K, Zakharkin SO, Allison DB. Expectations, validity, and reality in gene expression profiling. J Clin Epidemiol. 2010; 63(9): 950–959.
  10. Slonim DK, Yanai I. Getting started in gene expression microarray analysis. PLoS Comput Biol. 2009; 5(10): e1000543.
  11. Ritchie ME, Phipson B, Wu Di, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015; 43(7): e47.
  12. Huang DaW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009; 4(1): 44–57.
  13. Huang DaW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009; 37(1): 1–13.
  14. Hamilton SA, Tower CL, Jones RL. Identification of chemokines associated with the recruitment of decidual leukocytes in human labour: potential novel targets for preterm labour. PLoS One. 2013; 8(2): e56946.
  15. Oros D, Strunk M, Breton P, et al. Altered gene expression in human placenta after suspected preterm labour. Placenta. 2017; 55: 21–28.
  16. Ibrahim SA, Ackerman WE, Summerfield TL, et al. Inflammatory gene networks in term human decidual cells define a potential signature for cytokine-mediated parturition. Am J Obstet Gynecol. 2016; 214(2): 284.e1–284.e47.
  17. Haddad R, Tromp G, Kuivaniemi H, et al. Human spontaneous labor without histologic chorioamnionitis is characterized by an acute inflammation gene expression signature. Am J Obstet Gynecol. 2006; 195(2): 394.e1–394.24.

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