Literature DB >> 27494297

Cell type specific DNA methylation in cord blood: A 450K-reference data set and cell count-based validation of estimated cell type composition.

Kristina Gervin1, Christian Magnus Page2, Hans Christian D Aass3, Michelle A Jansen4,5,6, Heidi Elisabeth Fjeldstad7, Bettina Kulle Andreassen8, Liesbeth Duijts4,9,10,11, Joyce B van Meurs12, Menno C van Zelm13,14, Vincent W Jaddoe4,5,11, Hedvig Nordeng15,16, Gunn Peggy Knudsen17, Per Magnus17, Wenche Nystad2, Anne Cathrine Staff7,18, Janine F Felix4,5,11, Robert Lyle1,15,16.   

Abstract

Epigenome-wide association studies of prenatal exposure to different environmental factors are becoming increasingly common. These studies are usually performed in umbilical cord blood. Since blood comprises multiple cell types with specific DNA methylation patterns, confounding caused by cellular heterogeneity is a major concern. This can be adjusted for using reference data consisting of DNA methylation signatures in cell types isolated from blood. However, the most commonly used reference data set is based on blood samples from adult males and is not representative of the cell type composition in neonatal cord blood. The aim of this study was to generate a reference data set from cord blood to enable correct adjustment of the cell type composition in samples collected at birth. The purity of the isolated cell types was very high for all samples (>97.1%), and clustering analyses showed distinct grouping of the cell types according to hematopoietic lineage. We explored whether this cord blood and the adult peripheral blood reference data sets impact the estimation of cell type composition in cord blood samples from an independent birth cohort (MoBa, n = 1092). This revealed significant differences for all cell types. Importantly, comparison of the cell type estimates against matched cell counts both in the cord blood reference samples (n = 11) and in another independent birth cohort (Generation R, n = 195), demonstrated moderate to high correlation of the data. This is the first cord blood reference data set with a comprehensive examination of the downstream application of the data through validation of estimated cell types against matched cell counts.

Entities:  

Keywords:  Cellular heterogeneity; DNA methylation; EWAS; cord blood; reference data set

Mesh:

Year:  2016        PMID: 27494297      PMCID: PMC5048717          DOI: 10.1080/15592294.2016.1214782

Source DB:  PubMed          Journal:  Epigenetics        ISSN: 1559-2294            Impact factor:   4.528


  47 in total

1.  Cohort profile: the Norwegian Mother and Child Cohort Study (MoBa).

Authors:  Per Magnus; Lorentz M Irgens; Kjell Haug; Wenche Nystad; Rolv Skjaerven; Camilla Stoltenberg
Journal:  Int J Epidemiol       Date:  2006-08-22       Impact factor: 7.196

2.  Phenotypic differences between cord blood and adult peripheral blood.

Authors:  María C López; Brent E Palmer; David A Lawrence
Journal:  Cytometry B Clin Cytom       Date:  2008-07-18       Impact factor: 3.058

3.  Complete blood count reference values of cord blood in Taiwan and the influence of gender and delivery route on them.

Authors:  Yu-Hsun Chang; Shang-Hsien Yang; Tso-Fu Wang; Teng-Yi Lin; Kuo-Liang Yang; Shu-Huey Chen
Journal:  Pediatr Neonatol       Date:  2011-05-06       Impact factor: 2.083

4.  The Generation R Study: Biobank update 2015.

Authors:  Claudia J Kruithof; Marjolein N Kooijman; Cornelia M van Duijn; Oscar H Franco; Johan C de Jongste; Caroline C W Klaver; Johan P Mackenbach; Henriëtte A Moll; Hein Raat; Edmond H H M Rings; Fernando Rivadeneira; Eric A P Steegers; Henning Tiemeier; Andre G Uitterlinden; Frank C Verhulst; Eppo B Wolvius; Albert Hofman; Vincent W V Jaddoe
Journal:  Eur J Epidemiol       Date:  2014-12-21       Impact factor: 8.082

5.  A comprehensive study of umbilical cord blood cell developmental changes and reference ranges by gestation, gender and mode of delivery.

Authors:  L Glasser; N Sutton; M Schmeling; J T Machan
Journal:  J Perinatol       Date:  2015-01-29       Impact factor: 2.521

6.  The biobank of the Norwegian Mother and Child Cohort Study: a resource for the next 100 years.

Authors:  Kjersti S Rønningen; Liv Paltiel; Helle M Meltzer; Rannveig Nordhagen; Kari K Lie; Ragnhild Hovengen; Margaretha Haugen; Wenche Nystad; Per Magnus; Jane A Hoppin
Journal:  Eur J Epidemiol       Date:  2006-09-20       Impact factor: 8.082

7.  Comprehensive methylome map of lineage commitment from haematopoietic progenitors.

Authors:  Hong Ji; Lauren I R Ehrlich; Jun Seita; Peter Murakami; Akiko Doi; Paul Lindau; Hwajin Lee; Martin J Aryee; Rafael A Irizarry; Kitai Kim; Derrick J Rossi; Matthew A Inlay; Thomas Serwold; Holger Karsunky; Lena Ho; George Q Daley; Irving L Weissman; Andrew P Feinberg
Journal:  Nature       Date:  2010-08-15       Impact factor: 49.962

8.  SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips.

Authors:  Jovana Maksimovic; Lavinia Gordon; Alicia Oshlack
Journal:  Genome Biol       Date:  2012-06-15       Impact factor: 13.583

9.  Characterization of neutrophil subsets in healthy human pregnancies.

Authors:  Aloysius Ssemaganda; Lindsay Kindinger; Philip Bergin; Leslie Nielsen; Juliet Mpendo; Ali Ssetaala; Noah Kiwanuka; Markus Munder; Tiong Ghee Teoh; Pascale Kropf; Ingrid Müller
Journal:  PLoS One       Date:  2014-02-13       Impact factor: 3.240

10.  Longitudinal, genome-scale analysis of DNA methylation in twins from birth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance.

Authors:  David Martino; Yuk Jin Loke; Lavinia Gordon; Miina Ollikainen; Mark N Cruickshank; Richard Saffery; Jeffrey M Craig
Journal:  Genome Biol       Date:  2013-05-22       Impact factor: 13.583

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1.  Maternal swimming pool exposure during pregnancy in relation to birth outcomes and cord blood DNA methylation among private well users.

Authors:  Lucas A Salas; Emily R Baker; Mark J Nieuwenhuijsen; Carmen J Marsit; Brock C Christensen; Margaret R Karagas
Journal:  Environ Int       Date:  2019-01-05       Impact factor: 9.621

2.  Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation.

Authors:  John Dou; Rebecca J Schmidt; Kelly S Benke; Craig Newschaffer; Irva Hertz-Picciotto; Lisa A Croen; Ana-Maria Iosif; Janine M LaSalle; M Daniele Fallin; Kelly M Bakulski
Journal:  Epigenetics       Date:  2018-02-16       Impact factor: 4.528

3.  DNA methylation studies of depression with onset in the peripartum: A critical systematic review.

Authors:  Sarah Ellen Braun; Dana Lapato; Roy E Brown; Eva Lancaster; Timothy P York; Ananda B Amstadter; Patricia A Kinser
Journal:  Neurosci Biobehav Rev       Date:  2019-04-11       Impact factor: 8.989

4.  Associations between infant sex and DNA methylation across umbilical cord blood, artery, and placenta samples.

Authors:  Anne K Bozack; Elena Colicino; Allan C Just; Robert O Wright; Andrea A Baccarelli; Rosalind J Wright; Alison G Lee
Journal:  Epigenetics       Date:  2021-10-22       Impact factor: 4.861

5.  Newborn DNA methylation and asthma acquisition across adolescence and early adulthood.

Authors:  Liang Li; John W Holloway; Susan Ewart; Syed Hasan Arshad; Caroline L Relton; Wilfried Karmaus; Hongmei Zhang
Journal:  Clin Exp Allergy       Date:  2022-01-16       Impact factor: 5.401

6.  Identification of a foetal epigenetic compartment in adult human kidney.

Authors:  John K Wiencke; Ze Zhang; Devin C Koestler; Lucas A Salas; Annette M Molinaro; Brock C Christensen; Karl T Kelsey
Journal:  Epigenetics       Date:  2021-03-30       Impact factor: 4.528

7.  A comparison of epithelial cell content of oral samples estimated using cytology and DNA methylation.

Authors:  Yen Ting Wong; Michael A Tayeb; Timothy C Stone; Laurence B Lovat; Andrew E Teschendorff; Rafal Iwasiow; Jeffrey M Craig
Journal:  Epigenetics       Date:  2021-07-13       Impact factor: 4.861

8.  The epigenetic clock and physical development during childhood and adolescence: longitudinal analysis from a UK birth cohort.

Authors:  Andrew J Simpkin; Laura D Howe; Kate Tilling; Tom R Gaunt; Oliver Lyttleton; Wendy L McArdle; Susan M Ring; Steve Horvath; George Davey Smith; Caroline L Relton
Journal:  Int J Epidemiol       Date:  2017-04-01       Impact factor: 7.196

9.  Prenatal Bisphenol a Exposure, DNA Methylation, and Low Birth Weight: A Pilot Study in Taiwan.

Authors:  Yu-Fang Huang; Chia-Huang Chang; Pei-Jung Chen; I-Hsuan Lin; Yen-An Tsai; Chian-Feng Chen; Yu-Chao Wang; Wei-Yun Huang; Ming-Song Tsai; Mei-Lien Chen
Journal:  Int J Environ Res Public Health       Date:  2021-06-07       Impact factor: 3.390

10.  Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium.

Authors:  Gemma C Sharp; Lucas A Salas; Claire Monnereau; Catherine Allard; Paul Yousefi; Todd M Everson; Jon Bohlin; Zongli Xu; Rae-Chi Huang; Sarah E Reese; Cheng-Jian Xu; Nour Baïz; Cathrine Hoyo; Golareh Agha; Ritu Roy; John W Holloway; Akram Ghantous; Simon K Merid; Kelly M Bakulski; Leanne K Küpers; Hongmei Zhang; Rebecca C Richmond; Christian M Page; Liesbeth Duijts; Rolv T Lie; Phillip E Melton; Judith M Vonk; Ellen A Nohr; ClarLynda Williams-DeVane; Karen Huen; Sheryl L Rifas-Shiman; Carlos Ruiz-Arenas; Semira Gonseth; Faisal I Rezwan; Zdenko Herceg; Sandra Ekström; Lisa Croen; Fahimeh Falahi; Patrice Perron; Margaret R Karagas; Bilal M Quraishi; Matthew Suderman; Maria C Magnus; Vincent W V Jaddoe; Jack A Taylor; Denise Anderson; Shanshan Zhao; Henriette A Smit; Michele J Josey; Asa Bradman; Andrea A Baccarelli; Mariona Bustamante; Siri E Håberg; Göran Pershagen; Irva Hertz-Picciotto; Craig Newschaffer; Eva Corpeleijn; Luigi Bouchard; Debbie A Lawlor; Rachel L Maguire; Lisa F Barcellos; George Davey Smith; Brenda Eskenazi; Wilfried Karmaus; Carmen J Marsit; Marie-France Hivert; Harold Snieder; M Daniele Fallin; Erik Melén; Monica C Munthe-Kaas; Hasan Arshad; Joseph L Wiemels; Isabella Annesi-Maesano; Martine Vrijheid; Emily Oken; Nina Holland; Susan K Murphy; Thorkild I A Sørensen; Gerard H Koppelman; John P Newnham; Allen J Wilcox; Wenche Nystad; Stephanie J London; Janine F Felix; Caroline L Relton
Journal:  Hum Mol Genet       Date:  2017-10-15       Impact factor: 6.150

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