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

Rossella Alfano; Marc Chadeau-Hyam; Akram Ghantous; Pekka Keski-Rahkonen; Leda Chatzi; Almudena Espin Perez; Zdenko Herceg; Manolis Kogevinas; Theo M. de Kok; Tim S. Nawrot; Alexei Novoloaca; Chirag J. Patel; Costanza Pizzi; Nivonirina Robinot; Franca Rusconi; Augustin Scalbert; Jordi Sunyer; Roel Vermeulen; Martine Vrijheid; Paolo Vineis; Oliver Robinson; Michelle Plusquin

doi:10.1016/j.metabol.2020.154292

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

Rossella Alfano, Marc Chadeau-Hyam, Akram Ghantous, Pekka Keski-Rahkonen, Leda Chatzi, Almudena Espin Perez, Zdenko Herceg, Manolis Kogevinas, Theo M. de Kok, Tim S. Nawrot, Alexei Novoloaca, Chirag J. Patel, Costanza Pizzi, Nivonirina Robinot, Franca Rusconi, Augustin Scalbert, Jordi Sunyer, Roel Vermeulen, Martine Vrijheid, Paolo VineisOliver Robinson, Michelle Plusquin^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

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 (Toss-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(0-36:5), 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. Crown Copyright (C) 2020 Published by Elsevier Inc.

Original language	English
Article number	154292
Number of pages	12
Journal	Metabolism-Clinical and Experimental
Volume	110
DOIs	https://doi.org/10.1016/j.metabol.2020.154292
Publication status	Published - Sept 2020

Keywords

Birth weight
Cholesterol
DNA methylation
Gene expression
Metabolome
Proteins
FOR-GESTATIONAL-AGE
EPIGENOME-WIDE ASSOCIATION
DNA METHYLATION
COHORT PROFILE
C-PEPTIDE
METABOLOMICS
EXPRESSION
INSULIN
LIPIDS
ANTHROPOMETRY

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Alfano, R., Chadeau-Hyam, M., Ghantous, A., Keski-Rahkonen, P., Chatzi, L., Perez, A. E., Herceg, Z., Kogevinas, M., de Kok, T. M., Nawrot, T. S., Novoloaca, A., Patel, C. J., Pizzi, C., Robinot, N., Rusconi, F., Scalbert, A., Sunyer, J., Vermeulen, R., Vrijheid, M., ... Plusquin, M. (2020). A multi-omic analysis of birthweight in newborn cord blood reveals new underlying mechanisms related to cholesterol metabolism. Metabolism-Clinical and Experimental, 110, Article 154292. https://doi.org/10.1016/j.metabol.2020.154292

@article{5153e45a47204db4ad9846ebd6cb7493,

title = "A multi-omic analysis of birthweight in newborn cord blood reveals new underlying mechanisms related to cholesterol metabolism",

abstract = "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 (Toss-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(0-36:5), 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. Crown Copyright (C) 2020 Published by Elsevier Inc.",

keywords = "Birth weight, Cholesterol, DNA methylation, Gene expression, Metabolome, Proteins, FOR-GESTATIONAL-AGE, EPIGENOME-WIDE ASSOCIATION, DNA METHYLATION, COHORT PROFILE, C-PEPTIDE, METABOLOMICS, EXPRESSION, INSULIN, LIPIDS, ANTHROPOMETRY",

author = "Rossella Alfano and Marc Chadeau-Hyam and Akram Ghantous and Pekka Keski-Rahkonen and Leda Chatzi and Perez, {Almudena Espin} and Zdenko Herceg and Manolis Kogevinas and {de Kok}, {Theo M.} and Nawrot, {Tim S.} and Alexei Novoloaca and Patel, {Chirag J.} and Costanza Pizzi and Nivonirina Robinot and Franca Rusconi and Augustin Scalbert and Jordi Sunyer and Roel Vermeulen and Martine Vrijheid and Paolo Vineis and Oliver Robinson and Michelle Plusquin",

note = "Funding Information: This work is supported by the Bijzonder Onderzoeksfonds (BOF) Hasselt University through a PhD fellowship [to RA], the “EXPOsOMICS” grant [grant number 308610-FP7 European Commission to PV], and the “STOP” grant [grant number 774548 - European Commission H2020 to PV]. The ENVIRONAGE birth-cohort is supported by the EU Program “Ideas” ( ERC-2012-StG-310898 ) and the FWO ( G082317N ). Piccolipi{\`u} cohort has been funded by the CCM grant 2010 and the Italian Ministry of Health . Funding Information: This work is supported by the Bijzonder Onderzoeksfonds (BOF) Hasselt University through a PhD fellowship [to RA], the ?EXPOsOMICS? grant [grant number 308610-FP7 European Commission to PV], and the ?STOP? grant [grant number 774548-European Commission H2020 to PV]. The ENVIRONAGE birth-cohort is supported by the EU Program ?Ideas? (ERC-2012-StG-310898) and the FWO (G082317N). Piccolipi? cohort has been funded by the CCM grant 2010 and the Italian Ministry of Health. Publisher Copyright: {\textcopyright} 2020",

year = "2020",

month = sep,

doi = "10.1016/j.metabol.2020.154292",

language = "English",

volume = "110",

journal = "Metabolism-Clinical and Experimental",

issn = "0026-0495",

publisher = "W B Saunders Co-Elsevier Inc",

}

Alfano, R, Chadeau-Hyam, M, Ghantous, A, Keski-Rahkonen, P, Chatzi, L, Perez, AE, Herceg, Z, Kogevinas, M, de Kok, TM, Nawrot, TS, Novoloaca, A, Patel, CJ, Pizzi, C, Robinot, N, Rusconi, F, Scalbert, A, Sunyer, J, Vermeulen, R, Vrijheid, M, Vineis, P, Robinson, O & Plusquin, M 2020, 'A multi-omic analysis of birthweight in newborn cord blood reveals new underlying mechanisms related to cholesterol metabolism', Metabolism-Clinical and Experimental, vol. 110, 154292. https://doi.org/10.1016/j.metabol.2020.154292

TY - JOUR

T1 - A multi-omic analysis of birthweight in newborn cord blood reveals new underlying mechanisms related to cholesterol metabolism

AU - Alfano, Rossella

AU - Chadeau-Hyam, Marc

AU - Ghantous, Akram

AU - Keski-Rahkonen, Pekka

AU - Chatzi, Leda

AU - Perez, Almudena Espin

AU - Herceg, Zdenko

AU - Kogevinas, Manolis

AU - de Kok, Theo M.

AU - Nawrot, Tim S.

AU - Novoloaca, Alexei

AU - Patel, Chirag J.

AU - Pizzi, Costanza

AU - Robinot, Nivonirina

AU - Rusconi, Franca

AU - Scalbert, Augustin

AU - Sunyer, Jordi

AU - Vermeulen, Roel

AU - Vrijheid, Martine

AU - Vineis, Paolo

AU - Robinson, Oliver

AU - Plusquin, Michelle

N1 - Funding Information: This work is supported by the Bijzonder Onderzoeksfonds (BOF) Hasselt University through a PhD fellowship [to RA], the “EXPOsOMICS” grant [grant number 308610-FP7 European Commission to PV], and the “STOP” grant [grant number 774548 - European Commission H2020 to PV]. The ENVIRONAGE birth-cohort is supported by the EU Program “Ideas” ( ERC-2012-StG-310898 ) and the FWO ( G082317N ). Piccolipiù cohort has been funded by the CCM grant 2010 and the Italian Ministry of Health . Funding Information: This work is supported by the Bijzonder Onderzoeksfonds (BOF) Hasselt University through a PhD fellowship [to RA], the ?EXPOsOMICS? grant [grant number 308610-FP7 European Commission to PV], and the ?STOP? grant [grant number 774548-European Commission H2020 to PV]. The ENVIRONAGE birth-cohort is supported by the EU Program ?Ideas? (ERC-2012-StG-310898) and the FWO (G082317N). Piccolipi? cohort has been funded by the CCM grant 2010 and the Italian Ministry of Health. Publisher Copyright: © 2020

PY - 2020/9

Y1 - 2020/9

N2 - 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 (Toss-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(0-36:5), 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. Crown Copyright (C) 2020 Published by Elsevier Inc.

AB - 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 (Toss-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(0-36:5), 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. Crown Copyright (C) 2020 Published by Elsevier Inc.

KW - Birth weight

KW - Cholesterol

KW - DNA methylation

KW - Gene expression

KW - Metabolome

KW - Proteins

KW - FOR-GESTATIONAL-AGE

KW - EPIGENOME-WIDE ASSOCIATION

KW - DNA METHYLATION

KW - COHORT PROFILE

KW - C-PEPTIDE

KW - METABOLOMICS

KW - EXPRESSION

KW - INSULIN

KW - LIPIDS

KW - ANTHROPOMETRY

U2 - 10.1016/j.metabol.2020.154292

DO - 10.1016/j.metabol.2020.154292

M3 - Article

C2 - 32553738

SN - 0026-0495

VL - 110

JO - Metabolism-Clinical and Experimental

JF - Metabolism-Clinical and Experimental

M1 - 154292

ER -