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Dong Y, Lau HX, Suaini NHA, Kee MZL, Ooi DSQ, Shek LPC, Lee BW, Godfrey KM, Tham EH, Ong MEH, Liu N, Wong L, Tan KH, Chan JKY, Yap FKP, Chong YS, Eriksson JG, Feng M, Loo EXL. A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development. ENVIRONMENTAL RESEARCH 2024; 250:118523. [PMID: 38382664 DOI: 10.1016/j.envres.2024.118523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/19/2024] [Accepted: 02/18/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome starting already in the preconception phase. METHODS We performed a combined analysis of two multi-ethnic Asian birth cohorts, the Growing Up in Singapore Towards healthy Outcomes (GUSTO) and the Singapore PREconception Study of long Term maternal and child Outcomes (S-PRESTO) cohorts. Interviewer-administered questionnaires were used to collect information on demography, lifestyle and childhood atopic eczema, rhinitis and wheeze development. Data training was performed using XGBoost, genetic algorithm and logistic regression models, and the top variables with the highest importance were identified. Additive explanation values were identified and inputted into a final multiple logistic regression model. Generalised structural equation modelling with maternal and child blood micronutrients, metabolites and cytokines was performed to explain possible mechanisms. RESULTS The final study population included 1151 mother-child pairs. Our findings suggest that these childhood diseases are likely programmed in utero by the preconception and pregnancy exposomes through inflammatory pathways. We identified preconception alcohol consumption and maternal depressive symptoms during pregnancy as key modifiable maternal environmental exposures that increased eczema and rhinitis risk. Our mechanistic model suggested that higher maternal blood neopterin and child blood dimethylglycine protected against early childhood wheeze. After birth, early infection was a key driver of atopic eczema and rhinitis development. CONCLUSION Preconception and antenatal exposomes can programme atopic eczema, rhinitis and wheeze development in utero. Reducing maternal alcohol consumption during preconception and supporting maternal mental health during pregnancy may prevent atopic eczema and rhinitis by promoting an optimal antenatal environment. Our findings suggest a need to include preconception environmental exposures in future research to counter the earliest precursors of disease development in children.
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Affiliation(s)
- Yizhi Dong
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore.
| | - Hui Xing Lau
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
| | - Noor Hidayatul Aini Suaini
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
| | - Michelle Zhi Ling Kee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
| | - Delicia Shu Qin Ooi
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore.
| | - Lynette Pei-Chi Shek
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Bee Wah Lee
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Keith M Godfrey
- School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, United Kingdom; MRC Lifecourse Epidemiology Centre, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
| | - Elizabeth Huiwen Tham
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore; Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
| | - Marcus Eng Hock Ong
- Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore; Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
| | - Nan Liu
- Duke-NUS Medical School, National University of Singapore, Singapore; Health Services Research Centre, Singapore Health Services, Singapore, Singapore; Institute of Data Science, National University of Singapore, Singapore.
| | - Limsoon Wong
- School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore.
| | - Kok Hian Tan
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital (KKH), Singapore.
| | - Jerry Kok Yen Chan
- Duke-NUS Medical School, National University of Singapore, Singapore; Department of Reproductive Medicine, KK Women's and Children's Hospital (KKH), Singapore.
| | - Fabian Kok Peng Yap
- Duke-NUS Medical School, National University of Singapore, Singapore; Department of Paediatrics, KK Women's and Children's Hospital (KKH), Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore.
| | - Johan Gunnar Eriksson
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore; Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore; Folkhälsan Research Center, Helsinki, Finland; Department of General Practice and Primary Health Care, University of Helsinki, Finland.
| | - Mengling Feng
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore.
| | - Evelyn Xiu Ling Loo
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Dean's Office, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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Kyrkou C, Fotakis C, Dimitropoulou A, Tsakoumaki F, Zoumpoulakis P, Menexes G, Biliaderis CG, Athanasiadis AP, Michaelidou AM. Maternal Dietary Protein Patterns and Neonatal Anthropometrics: A Prospective Study with Insights from NMR Metabolomics in Amniotic Fluid. Metabolites 2023; 13:977. [PMID: 37755257 PMCID: PMC10535439 DOI: 10.3390/metabo13090977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/17/2023] [Accepted: 08/21/2023] [Indexed: 09/28/2023] Open
Abstract
This study aimed to characterize dietary protein patterns (DPPs) in a sample pool of 298 well-nourished pregnant women and explore potential associations between DPPs and neonatal anthropometrics. Maternal dietary data were collected using a validated food frequency questionnaire. Neonatal anthropometrics were abstracted from health booklets. A hierarchical cluster analysis identified three DPPs: "Dairy-focused", "Med-fusion", and "Traditional-inspired". The "Dairy-focused" DPP exhibited the highest protein intake (p < 0.001), predominantly animal protein (p < 0.001), while the "Traditional-inspired" DPP presented higher plant protein (p < 0.001) and fiber intakes (p < 0.001), and, therefore, a reduced carbohydrate-to-fiber quotient (p < 0.001). The "Med-fusion" DPP had the lowest protein-to-fat ratio (p < 0.001). Infants of women following the "Dairy-focused" DPP had the highest birth height centiles (p = 0.007) and the lowest ponderal index (p = 0.003). The NMR-metabolomics approach was implemented on a subset of women that provided amniotic fluid (AF) specimens (n = 62) to elucidate distinct metabolic signatures associated with DPPs. PCA and OPLS-DA models verified the adherence to three DPPs, revealing that the levels of several amino acids (AAs) were the highest in "Dairy-focused", reflecting its protein-rich nature. The "Traditional-inspired" DPP showed decreased AAs and glucose levels. This knowledge may contribute to optimizing maternal dietary recommendations. Further research is needed to validate these findings and better understand the relationships between maternal diet, AF metabolic signature, and neonatal anthropometrics.
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Affiliation(s)
- Charikleia Kyrkou
- Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (C.K.); (A.D.); (F.T.); (C.G.B.)
| | - Charalambos Fotakis
- Institute of Chemical Biology, National Hellenic Research Foundation, 116 35 Athens, Greece; (C.F.); (P.Z.)
| | - Aristea Dimitropoulou
- Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (C.K.); (A.D.); (F.T.); (C.G.B.)
| | - Foteini Tsakoumaki
- Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (C.K.); (A.D.); (F.T.); (C.G.B.)
| | - Panagiotis Zoumpoulakis
- Institute of Chemical Biology, National Hellenic Research Foundation, 116 35 Athens, Greece; (C.F.); (P.Z.)
- Department of Food Science and Technology, University of West Attica, Ag. Spyridonos, 122 43 Egaleo, Greece
| | - Georgios Menexes
- Department of Field Crops and Ecology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Costas G. Biliaderis
- Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (C.K.); (A.D.); (F.T.); (C.G.B.)
| | - Apostolos P. Athanasiadis
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Alexandra-Maria Michaelidou
- Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (C.K.); (A.D.); (F.T.); (C.G.B.)
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Gleason B, Kuang A, Bain JR, Muehlbauer MJ, Ilkayeva OR, Scholtens DM, Lowe WL. Association of Maternal Metabolites and Metabolite Networks with Newborn Outcomes in a Multi-Ancestry Cohort. Metabolites 2023; 13:505. [PMID: 37110162 PMCID: PMC10145069 DOI: 10.3390/metabo13040505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/23/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
The in utero environment is important for newborn size at birth, which is associated with childhood adiposity. We examined associations between maternal metabolite levels and newborn birthweight, sum of skinfolds (SSF), and cord C-peptide in a multinational and multi-ancestry cohort of 2337 mother-newborn dyads. Targeted and untargeted metabolomic assays were performed on fasting and 1 h maternal serum samples collected during an oral glucose tolerance test performed at 24-32 week gestation in women participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Anthropometric measurements were obtained on newborns at birth. Following adjustment for maternal BMI and glucose, per-metabolite analyses demonstrated significant associations between maternal metabolite levels and birthweight, SSF, and cord C-peptide. In the fasting state, triglycerides were positively associated and several long-chain acylcarnitines were inversely associated with birthweight and SSF. At 1 h, additional metabolites including branched-chain amino acids, proline, and alanine were positively associated with newborn outcomes. Network analyses demonstrated distinct clusters of inter-connected metabolites significantly associated with newborn phenotypes. In conclusion, numerous maternal metabolites during pregnancy are significantly associated with newborn birthweight, SSF, and cord C-peptide independent of maternal BMI and glucose, suggesting that metabolites in addition to glucose contribute to newborn size at birth and adiposity.
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Affiliation(s)
- Brooke Gleason
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60091, USA
| | - Alan Kuang
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60091, USA
| | - James R. Bain
- Duke Molecular Physiology Institute, Durham, NC 27701, USA
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Michael J. Muehlbauer
- Duke Molecular Physiology Institute, Durham, NC 27701, USA
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Olga R. Ilkayeva
- Duke Molecular Physiology Institute, Durham, NC 27701, USA
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Denise M. Scholtens
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60091, USA
| | - William L. Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60091, USA
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Yeum D, Gilbert-Diamond D, Doherty B, Coker M, Stewart D, Kirchner D, McRitchie S, Sumner S, Karagas MR, Hoen AG. Associations of maternal plasma and umbilical cord plasma metabolomics profiles with birth anthropometric measures. Pediatr Res 2023:10.1038/s41390-022-02449-2. [PMID: 36627359 DOI: 10.1038/s41390-022-02449-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/11/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth might influence fetal growth and birth anthropometry. The objective was to examine how maternal plasma and umbilical cord plasma metabolites are associated with newborn anthropometric measures, a known predictor of future health outcomes. METHODS Pregnant women between 24 and 28 weeks of gestation were recruited as part of a prospective cohort study. Blood samples from 413 women at enrollment and 787 infant cord blood samples were analyzed using the Biocrates AbsoluteIDQ® p180 kit. Multivariable linear regression models were used to examine associations of cord and maternal metabolites with infant anthropometry at birth. RESULTS In cord blood samples from this rural cohort from New Hampshire of largely white residents, 13 metabolites showed negative associations, and 10 metabolites showed positive associations with birth weight Z-score. Acylcarnitine C5 showed negative association, and 4 lysophosphatidylcholines showed positive associations with birth length Z-score. Maternal blood metabolites did not significantly correlate with birth weight and length Z-scores. CONCLUSIONS Consistent findings were observed for several acylcarnitines that play a role in utilization of energy sources, and a lysophosphatidylcholine that is part of oxidative stress and inflammatory response pathways in cord plasma samples. IMPACT The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth may influence fetal growth and birth anthropometry. This study examines the independent effects of maternal gestational and infant cord blood metabolomes across different classes of metabolites on birth anthropometry. Acylcarnitine species were negatively associated and glycerophospholipids species were positively associated with weight and length Z-scores at birth in the cord plasma samples, but not in the maternal plasma samples. This study identifies lipid metabolites in infants that possibly may affect early growth.
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Affiliation(s)
- Dabin Yeum
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Diane Gilbert-Diamond
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Children's Environmental Health and Disease Prevention Center at Dartmouth, Hanover, NH, USA
| | - Brett Doherty
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Modupe Coker
- Department of Oral Biology, Rutgers School of Dental Medicine, Rutgers State University of New Jersey, Newark, NJ, USA
| | - Delisha Stewart
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - David Kirchner
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Susan McRitchie
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Susan Sumner
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Margaret R Karagas
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Children's Environmental Health and Disease Prevention Center at Dartmouth, Hanover, NH, USA
| | - Anne G Hoen
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Department of Biomedical Data Science, Geisel School of Medicine, Lebanon, NH, USA
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Barry CJS, Lawlor DA, Shapland CY, Sanderson E, Borges MC. Using Mendelian Randomisation to Prioritise Candidate Maternal Metabolic Traits Influencing Offspring Birthweight. Metabolites 2022; 12:537. [PMID: 35736469 PMCID: PMC9231269 DOI: 10.3390/metabo12060537] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/27/2022] Open
Abstract
Marked physiological changes in pregnancy are essential to support foetal growth; however, evidence on the role of specific maternal metabolic traits from human studies is limited. We integrated Mendelian randomisation (MR) and metabolomics data to probe the effect of 46 maternal metabolic traits on offspring birthweight (N = 210,267). We implemented univariable two-sample MR (UVMR) to identify candidate metabolic traits affecting offspring birthweight. We then applied two-sample multivariable MR (MVMR) to jointly estimate the potential direct causal effect for each candidate maternal metabolic trait. In the main analyses, UVMR indicated that higher maternal glucose was related to higher offspring birthweight (0.328 SD difference in mean birthweight per 1 SD difference in glucose (95% CI: 0.104, 0.414)), as were maternal glutamine (0.089 (95% CI: 0.033, 0.144)) and alanine (0.137 (95% CI: 0.036, 0.239)). In additional analyses, UVMR estimates were broadly consistent when selecting instruments from an independent data source, albeit imprecise for glutamine and alanine, and were attenuated for alanine when using other UVMR methods. MVMR results supported independent effects of these metabolites, with effect estimates consistent with those seen with the UVMR results. Among the remaining 43 metabolic traits, UVMR estimates indicated a null effect for most lipid-related traits and a high degree of uncertainty for other amino acids and ketone bodies. Our findings suggest that maternal gestational glucose and glutamine are causally related to offspring birthweight.
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Affiliation(s)
- Ciarrah-Jane Shannon Barry
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Deborah A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
- NIHR Bristol Biomedical Research Centre, Bristol BS8 2BN, UK
| | - Chin Yang Shapland
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
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Voerman E, Jaddoe VWV, Shokry E, Ruijter GJG, Felix JF, Koletzko B, Gaillard R. Associations of maternal and infant metabolite profiles with foetal growth and the odds of adverse birth outcomes. Pediatr Obes 2022; 17:e12844. [PMID: 34384140 PMCID: PMC9285592 DOI: 10.1111/ijpo.12844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 07/18/2021] [Accepted: 07/26/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Adaptations in maternal and foetal metabolic pathways may predispose to altered foetal growth and adverse birth outcomes. OBJECTIVE To assess the associations of maternal early-pregnancy metabolite profiles and infant metabolite profiles at birth with foetal growth from first trimester onwards and the odds of adverse birth outcomes. METHODS In a prospective population-based cohort among 976 Dutch pregnant women and their children, serum concentrations of amino acids, non-esterified fatty acids (NEFA), phospholipids (PL) and carnitines in maternal early-pregnancy blood and in cord blood were obtained by liquid-chromatography tandem mass spectrometry. Information on foetal growth was available from first trimester onwards. RESULTS After false discovery rate correction for multiple testing, higher infant total and individual NEFA concentrations were associated with a lower weight, length, and head circumference at birth. Higher infant total and individual acyl-lysophosphatidylcholine (lyso.PC.a) and alkyl-lysophosphatidylcholine concentrations were associated with higher weight and head circumference (lyso.PC.a only) at birth, higher odds of LGA and lower odds of SGA. Few individual maternal metabolites were associated with foetal growth measures in third trimester and at birth, but not with the odds of adverse birth outcomes. CONCLUSIONS Our results suggest that infant metabolite profiles, particularly total and individual lyso.PC.a and NEFA concentrations, were strongly related to growth measures at birth and the odds of adverse birth outcomes. Few individual maternal early-pregnancy metabolites, but not total metabolite concentrations, are associated with foetal growth measures in third trimester and at birth.
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Affiliation(s)
- Ellis Voerman
- The Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands,Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands,Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Engy Shokry
- Division of Metabolic and Nutritional Medicine, Department of Paediatrics, Dr. von Hauner Children's HospitalLMU ‐ Ludwig‐Maximilians Universität MünchenMunichGermany
| | - George J. G. Ruijter
- Department of Clinical Genetics, Center for Lysosomal and Metabolic Disease, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands,Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Department of Paediatrics, Dr. von Hauner Children's HospitalLMU ‐ Ludwig‐Maximilians Universität MünchenMunichGermany
| | - Romy Gaillard
- The Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands,Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
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