A multi-omic analysis of birthweight in newborn cord blood reveals new underlying mechanisms related to cholesterol metabolism.


Journal

Metabolism: clinical and experimental
ISSN: 1532-8600
Titre abrégé: Metabolism
Pays: United States
ID NLM: 0375267

Informations de publication

Date de publication:
09 2020
Historique:
received: 18 11 2019
revised: 05 06 2020
accepted: 11 06 2020
pubmed: 20 6 2020
medline: 9 10 2020
entrez: 20 6 2020
Statut: ppublish

Résumé

Birthweight reflects in utero exposures and later health evolution. Despite existing studies employing high-dimensional molecular measurements, the understanding of underlying mechanisms of birthweight remains limited. To investigate the systems biology of birthweight, we cross-sectionally integrated the methylome, the transcriptome, the metabolome and a set of inflammatory proteins measured in cord blood samples, collected from four birth-cohorts (n = 489). We focused on two sets of 68 metabolites and 903 CpGs previously related to birthweight and investigated the correlation structures existing between these two sets and all other omic features via bipartite Pearson correlations. This dataset revealed that the set of metabolome and methylome signatures of birthweight have seven signals in common, including three metabolites [PC(34:2), plasmalogen PC(36:4)/PC(O-36:5), and a compound with m/z of 781.0545], two CpGs (on the DHCR24 and SC4MOL gene), and two proteins (periostin and CCL22). CCL22, a macrophage-derived chemokine has not been previously identified in relation to birthweight. Since the results of the omics integration indicated the central role of cholesterol metabolism, we explored the association of cholesterol levels in cord blood with birthweight in the ENVIRONAGE cohort (n = 1097), finding that higher birthweight was associated with increased high-density lipoprotein cholesterol and that high-density lipoprotein cholesterol was lower in small versus large for gestational age newborns. Our data suggests that an integration of different omic-layers in addition to single omics studies is a useful approach to generate new hypotheses regarding biological mechanisms. CCL22 and cholesterol metabolism in cord blood play a mechanistic role in birthweight.

Sections du résumé

BACKGROUND
Birthweight reflects in utero exposures and later health evolution. Despite existing studies employing high-dimensional molecular measurements, the understanding of underlying mechanisms of birthweight remains limited.
METHODS
To investigate the systems biology of birthweight, we cross-sectionally integrated the methylome, the transcriptome, the metabolome and a set of inflammatory proteins measured in cord blood samples, collected from four birth-cohorts (n = 489). We focused on two sets of 68 metabolites and 903 CpGs previously related to birthweight and investigated the correlation structures existing between these two sets and all other omic features via bipartite Pearson correlations.
RESULTS
This dataset revealed that the set of metabolome and methylome signatures of birthweight have seven signals in common, including three metabolites [PC(34:2), plasmalogen PC(36:4)/PC(O-36:5), and a compound with m/z of 781.0545], two CpGs (on the DHCR24 and SC4MOL gene), and two proteins (periostin and CCL22). CCL22, a macrophage-derived chemokine has not been previously identified in relation to birthweight. Since the results of the omics integration indicated the central role of cholesterol metabolism, we explored the association of cholesterol levels in cord blood with birthweight in the ENVIRONAGE cohort (n = 1097), finding that higher birthweight was associated with increased high-density lipoprotein cholesterol and that high-density lipoprotein cholesterol was lower in small versus large for gestational age newborns.
CONCLUSIONS
Our data suggests that an integration of different omic-layers in addition to single omics studies is a useful approach to generate new hypotheses regarding biological mechanisms. CCL22 and cholesterol metabolism in cord blood play a mechanistic role in birthweight.

Identifiants

pubmed: 32553738
pii: S0026-0495(20)30156-6
doi: 10.1016/j.metabol.2020.154292
pmc: PMC7450273
pii:
doi:

Substances chimiques

CCL22 protein, human 0
Chemokine CCL22 0
Cholesterol 97C5T2UQ7J

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

154292

Subventions

Organisme : Medical Research Council
ID : MR/S019669/1
Pays : United Kingdom

Informations de copyright

Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest None.

Références

Diabetologia. 2016 Apr;59(4):799-812
pubmed: 26750116
J Biol Chem. 2012 Jun 8;287(24):20164-75
pubmed: 22528487
Cytokine. 2012 Nov;60(2):377-84
pubmed: 22857868
Int J Epidemiol. 2011 Jun;40(3):647-61
pubmed: 21324938
Am J Psychiatry. 2017 Apr 1;174(4):319-328
pubmed: 27838934
J Clin Diagn Res. 2017 Jan;11(1):SC05-SC07
pubmed: 28274013
Indian J Clin Biochem. 2013 Apr;28(2):152-7
pubmed: 24426201
Epigenetics. 2016 May 3;11(5):354-62
pubmed: 27019159
Am J Epidemiol. 2007 May 15;165(10):1216-8
pubmed: 17344203
Int J Epidemiol. 2017 Oct 1;46(5):1392-1393k
pubmed: 29040580
Endocr Rev. 2007 Apr;28(2):219-51
pubmed: 17322454
Hum Mol Genet. 2014 Jan 15;23(2):534-45
pubmed: 24014485
Metabolism. 2017 Nov;76:11-22
pubmed: 28987236
Int J Epidemiol. 2012 Aug;41(4):930-40
pubmed: 21471022
Nat Commun. 2019 Jun 13;10(1):2581
pubmed: 31197173
Metabolism. 2018 Oct;87:A1-A9
pubmed: 30098323
J Biol Chem. 2015 Nov 27;290(48):28822-33
pubmed: 26463208
Oncotarget. 2017 Jan 31;8(5):7384-7390
pubmed: 27863395
J Pediatr. 2020 May;220:64-72.e2
pubmed: 32093929
Cell Commun Signal. 2017 Jun 21;15(1):23
pubmed: 28637459
Am J Physiol Lung Cell Mol Physiol. 2018 Nov 1;315(5):L870-L881
pubmed: 30113229
Nat Rev Immunol. 2003 Feb;3(2):133-46
pubmed: 12563297
Med Sci Monit. 2014 Oct 30;20:2097-105
pubmed: 25357084
Mol Nutr Food Res. 2019 Jan;63(1):e1700889
pubmed: 29714050
J Clin Endocrinol Metab. 2018 Jan 1;103(1):346-355
pubmed: 29140440
Obes Facts. 2017;10(2):85-100
pubmed: 28376503
Environ Sci Technol. 2018 May 1;52(9):5427-5437
pubmed: 29597345
BMC Pediatr. 2014 Feb 07;14:36
pubmed: 24506846
Environ Health Perspect. 2004 Dec;112(17):1691-6
pubmed: 15579415
Int J Cancer. 2005 Jul 1;115(4):611-7
pubmed: 15700315
Metabolomics. 2007 Sep;3(3):211-221
pubmed: 24039616
Placenta. 2011 Mar;32 Suppl 2:S218-21
pubmed: 21300403
Metabolism. 2020 Mar;104:154141
pubmed: 31923386
Atherosclerosis. 2002 Mar;161(1):215-23
pubmed: 11882335
Hum Mol Genet. 2015 Aug 1;24(15):4464-79
pubmed: 25935004
Clin Epigenetics. 2016 Nov 16;8:118
pubmed: 27891191
J Proteome Res. 2018 Mar 2;17(3):1235-1247
pubmed: 29401400
J Exp Med. 2019 May 6;216(5):1170-1181
pubmed: 30910796
PLoS One. 2012;7(10):e46705
pubmed: 23071618
J Dev Orig Health Dis. 2017 Oct;8(5):513-519
pubmed: 28889823
J Clin Endocrinol Metab. 2019 Oct 1;104(10):4459-4472
pubmed: 31498869
Indian J Med Res. 2016 Aug;144(2):194-199
pubmed: 27934797
J Pediatr Endocrinol Metab. 2017 May 24;30(6):677-681
pubmed: 28489558
Chem Biodivers. 2012 May;9(5):888-99
pubmed: 22589090
Int J Epidemiol. 2017 Oct 1;46(5):1386-1387m
pubmed: 28089960
Circulation. 2005 Sep 6;112(10):1414-8
pubmed: 16129799
Genome Biol. 2016 May 05;17:88
pubmed: 27150361
Nat Commun. 2019 Apr 23;10(1):1893
pubmed: 31015461
PLoS Comput Biol. 2013;9(7):e1003123
pubmed: 23861661
Nucleic Acids Res. 2019 Jan 8;47(D1):D1005-D1012
pubmed: 30445434
Metabolites. 2019 Apr 18;9(4):
pubmed: 31003499
Cell Physiol Biochem. 2018;45(2):614-624
pubmed: 29402770
Clin Epigenetics. 2017 Feb 7;9:15
pubmed: 28194238
Nucleic Acids Res. 2018 Jul 2;46(W1):W486-W494
pubmed: 29762782
Adv Genet. 2016;93:147-90
pubmed: 26915271
J Immunol. 2011 Aug 15;187(4):1778-87
pubmed: 21768398
Exp Hematol. 1997 May;25(5):374-86
pubmed: 9168059
Hum Mol Genet. 2015 Jul 1;24(13):3752-63
pubmed: 25869828
Int J Epidemiol. 2018 Aug 1;47(4):1195-1206
pubmed: 29788280
Pac Symp Biocomput. 2015;:231-42
pubmed: 25592584
Int J Hyg Environ Health. 2017 Mar;220(2 Pt A):142-151
pubmed: 27576363
PLoS One. 2011;6(10):e26905
pubmed: 22046403
J Dev Orig Health Dis. 2016 Dec;7(6):672-677
pubmed: 27572697
Am J Epidemiol. 2014 Apr 1;179(7):834-42
pubmed: 24561991

Auteurs

Rossella Alfano (R)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom; Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, United Kingdom; Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.

Marc Chadeau-Hyam (M)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom; Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, United Kingdom; Institute for Risk Assessment Sciences (IRAS), Division of Environmental Epidemiology, Utrecht University, Utrecht, the Netherlands.

Akram Ghantous (A)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Pekka Keski-Rahkonen (P)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Leda Chatzi (L)

Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90007, United States; Department of Social Medicine, University of Crete, Heraklion, Crete, Greece.

Almudena Espin Perez (AE)

Department of Biomedical Informatics Research, Stanford University, CA, United States.

Zdenko Herceg (Z)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Manolis Kogevinas (M)

Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain; ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain.

Theo M de Kok (TM)

Department of Toxicogenomics, Maastricht University, Maastricht, the Netherlands.

Tim S Nawrot (TS)

Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium; Environment & Health Unit, Leuven University, Leuven, Belgium.

Alexei Novoloaca (A)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Chirag J Patel (CJ)

Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.

Costanza Pizzi (C)

Department of Medical Sciences, University of Turin and CPO-Piemonte, Torino, Italy.

Nivonirina Robinot (N)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Franca Rusconi (F)

Unit of Epidemiology, Anna Meyer Children's University Hospital, Florence, Italy.

Augustin Scalbert (A)

International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008 Lyon, France.

Jordi Sunyer (J)

ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain.

Roel Vermeulen (R)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom; Institute for Risk Assessment Sciences (IRAS), Division of Environmental Epidemiology, Utrecht University, Utrecht, the Netherlands.

Martine Vrijheid (M)

Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain; ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain.

Paolo Vineis (P)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom; Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, United Kingdom; Human Genetic Foundation (HuGeF), Turin, Italy.

Oliver Robinson (O)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom.

Michelle Plusquin (M)

Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom; Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, United Kingdom; Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium. Electronic address: michelle.plusquin@uhasselt.be.

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