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Zeljkovic A, Vekic J, Stefanovic A. Obesity and dyslipidemia in early life: Impact on cardiometabolic risk. Metabolism 2024; 156:155919. [PMID: 38653373 DOI: 10.1016/j.metabol.2024.155919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 04/19/2024] [Accepted: 04/19/2024] [Indexed: 04/25/2024]
Abstract
Childhood obesity with its growing prevalence worldwide presents one of the most important health challenges nowadays. Multiple mechanisms are involved in the development of this condition, as well as in its associations with various cardiometabolic complications, such as insulin resistance, diabetes, metabolic dysfunction-associated steatotic liver disease and cardiovascular diseases. Recent findings suggest that childhood obesity and associated dyslipidemia at least partly originate from epigenetic modifications that take place in the earliest periods of life, namely prenatal and perinatal periods. Hence, alterations of maternal metabolism could be fundamentally responsible for fetal and neonatal metabolic programming and consequently, for metabolic health of offspring in later life. In this paper, we will review recent findings on the associations among intrauterine and early postnatal exposure to undesirable modulators of metabolism, development of childhood obesity and later cardiometabolic complications. Special attention will be given to maternal dyslipidemia as a driven force for undesirable epigenetic modulations in offspring. In addition, newly proposed lipid biomarkers of increased cardiometabolic risk in obese children and adolescents will be analyzed, with respect to their predictive potential and clinical applicability.
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Affiliation(s)
- Aleksandra Zeljkovic
- Department of Medical Biochemistry, University of Belgrade-Faculty of Pharmacy, Belgrade, Serbia
| | - Jelena Vekic
- Department of Medical Biochemistry, University of Belgrade-Faculty of Pharmacy, Belgrade, Serbia.
| | - Aleksandra Stefanovic
- Department of Medical Biochemistry, University of Belgrade-Faculty of Pharmacy, Belgrade, Serbia
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Prince N, Liang D, Tan Y, Alshawabkeh A, Angel EE, Busgang SA, Chu SH, Cordero JF, Curtin P, Dunlop AL, Gilbert-Diamond D, Giulivi C, Hoen AG, Karagas MR, Kirchner D, Litonjua AA, Manjourides J, McRitchie S, Meeker JD, Pathmasiri W, Perng W, Schmidt RJ, Watkins DJ, Weiss ST, Zens MS, Zhu Y, Lasky-Su JA, Kelly RS. Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium. Metabolomics 2024; 20:16. [PMID: 38267770 PMCID: PMC11099615 DOI: 10.1007/s11306-023-02082-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/12/2023] [Indexed: 01/26/2024]
Abstract
INTRODUCTION Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.
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Affiliation(s)
- Nicole Prince
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Donghai Liang
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Youran Tan
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Akram Alshawabkeh
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA
| | - Elizabeth Esther Angel
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, 95616, USA
| | - Stefanie A Busgang
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Su H Chu
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - José F Cordero
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
| | - Paul Curtin
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Anne L Dunlop
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Diane Gilbert-Diamond
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
- Department of Medicine, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
- Department of Pediatrics, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
| | - Cecilia Giulivi
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California Davis, Davis, CA, 95616, USA
| | - Anne G Hoen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, 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
| | - Augusto A Litonjua
- Division of Pediatric Pulmonary Medicine, Golisano Children's Hospital at Strong, University of Rochester Medical Center, Rochester, NY, 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
| | - John D Meeker
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Wimal Pathmasiri
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rebecca J Schmidt
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, 95616, USA
- MIND Institute, School of Medicine, University of California Davis, Davis, CA, 95616, USA
| | - Deborah J Watkins
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael S Zens
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
| | - Yeyi Zhu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
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Blanco Sequeiros E, Tuomaala AK, Tabassum R, Bergman PH, Koivusalo SB, Huvinen E. Early ascending growth is associated with maternal lipoprotein profile during mid and late pregnancy and in cord blood. Int J Obes (Lond) 2023; 47:1081-1087. [PMID: 37592059 PMCID: PMC10599999 DOI: 10.1038/s41366-023-01361-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 07/24/2023] [Accepted: 08/07/2023] [Indexed: 08/19/2023]
Abstract
INTRODUCTION Intrauterine conditions and accelerating early growth are associated with childhood obesity. It is unknown, whether fetal programming affects the early growth and could alterations in the maternal-fetal metabolome be the mediating mechanism. Therefore, we aimed to assess the associations between maternal and cord blood metabolite profile and offspring early growth. METHODS The RADIEL study recruited 724 women at high risk for gestational diabetes mellitus (GDM) BMI ≥ 30 kg/m2 and/or prior GDM) before or in early pregnancy. Blood samples were collected once in each trimester, and from cord. Metabolomics were analyzed by targeted nuclear magnetic resonance (NMR) technique. Following up on offsprings' first 2 years growth, we discovered 3 distinct growth profiles (ascending n = 80, intermediate n = 346, and descending n = 146) by using latent class mixed models (lcmm). RESULTS From the cohort of mother-child dyads with available growth profile data (n = 572), we have metabolomic data from 232 mothers from 1st trimester, 271 from 2nd trimester, 277 from 3rd trimester and 345 from cord blood. We have data on 220 metabolites in each trimester and 70 from cord blood. In each trimester of pregnancy, the mothers of the ascending group showed higher levels of VLDL and LDL particles, and lower levels of HDL particles (p < 0.05). When adjusted for gestational age, birth weight, sex, delivery mode, and maternal smoking, there was an association with ascending profile and 2nd trimester total cholesterol in HDL2, 3rd trimester total cholesterol in HDL2 and in HDL, VLDL size and ratio of triglycerides to phosphoglycerides (TG/PG ratio) in cord blood (p ≤ 0.002). CONCLUSION Ascending early growth was associated with lower maternal total cholesterol in HDL in 2nd and 3rd trimester, and higher VLDL size and more adverse TG/PG ratio in cord blood. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, http://www. CLINICALTRIALS com , NCT01698385.
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Affiliation(s)
- Elina Blanco Sequeiros
- University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Soite Children's Hospital, Kokkola, Finland.
| | - Anna-Kaisa Tuomaala
- Department of Pediatrics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Paula H Bergman
- Biostatistics Consulting, Department of Public Health, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Saila B Koivusalo
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Emilia Huvinen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Xie J, Han Y, Peng L, Zhang J, Gong X, Du Y, Ren X, Zhou L, Li Y, Zeng P, Shao J. BMI growth trajectory from birth to 5 years and its sex-specific association with prepregnant BMI and gestational weight gain. Front Nutr 2023; 10:1101158. [PMID: 36866049 PMCID: PMC9971005 DOI: 10.3389/fnut.2023.1101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/18/2023] [Indexed: 02/16/2023] Open
Abstract
Objective The purpose of the study was to identify the latent body mass index (BMI) z-score trajectories of children from birth to 5 years of age and evaluate their sex-specific association with prepregnant BMI and gestational weight gain (GWG). Methods This was a retrospective longitudinal cohort study performed in China. In total, three distinct BMI-z trajectories from birth to 5 years of age were determined for both genders using the latent class growth modeling. The logistic regression model was used to assess the associations of maternal prepregnant BMI and GWG with childhood BMI-z growth trajectories. Results Excessive GWG increased the risks of children falling into high-BMI-z trajectory relative to adequate GWG (OR = 2.04, 95% CI: 1.29, 3.20) in boys; girls born to mothers with prepregnancy underweight had a higher risk of low-BMI-z trajectory than girls born to mothers with prepregnancy adequate weight (OR = 1.85, 95% CI: 1.22, 2.79). Conclusion BMI-z growth trajectories of children from 0 to 5 years of age have population heterogeneity. Prepregnant BMI and GWG are associated with child BMI-z trajectories. It is necessary to monitor weight status before and during pregnancy to promote maternal and child health.
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Affiliation(s)
- Jinting Xie
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yan Han
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Lei Peng
- Xuzhou Maternal and Child Health Family Planning Service Center, Xuzhou, Jiangsu, China
| | - Jingjing Zhang
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xiangjun Gong
- Xuzhou Maternal and Child Health Family Planning Service Center, Xuzhou, Jiangsu, China
| | - Yan Du
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xiangmei Ren
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Li Zhou
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yuanhong Li
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ping Zeng
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jihong Shao
- School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China,*Correspondence: Jihong Shao,
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Hu Z, Han L, Liu J, Fowke JH, Han JC, Kakhniashvili D, LeWinn KZ, Bush NR, Mason WA, Zhao Q. Prenatal metabolomic profiles mediate the effect of maternal obesity on early childhood growth trajectories and obesity risk: the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study. Am J Clin Nutr 2022; 116:1343-1353. [PMID: 36055779 PMCID: PMC9630879 DOI: 10.1093/ajcn/nqac244] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 07/26/2022] [Accepted: 08/30/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Maternal prepregnancy obesity is an important risk factor for offspring obesity, which may partially operate through prenatal programming mechanisms. OBJECTIVES The study aimed to systematically identify prenatal metabolomic profiles mediating the intergenerational transmission of obesity. METHODS We included 450 African-American mother-child pairs from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study pregnancy cohort. LC-MS was used to conduct metabolomic profiling on maternal plasma samples of the second trimester. The childhood growth outcomes of interest included BMI trajectories from birth to age 4 y (rising-high-, moderate-, and low-BMI trajectories) as well as overweight/obesity (OWO) risk at age 4 y. Mediation analysis was conducted to identify metabolite mediators linking maternal OWO and childhood growth outcomes. The potential causal effects of maternal OWO on metabolite mediators were examined using the Mendelian randomization (MR) method. RESULTS Among the 880 metabolites detected in the maternal plasma during pregnancy, 14 and 11 metabolites significantly mediated the effects of maternal prepregnancy OWO on childhood BMI trajectories and the OWO risk at age 4 y, respectively, and 5 mediated both outcomes. The MR analysis suggested 6 of the 20 prenatal metabolite mediators might be causally influenced by maternal prepregnancy OWO, most of which are from the pathways related to the metabolism of amino acids (hydroxyasparagine, glutamate, and homocitrulline), sterols (campesterol), and nucleotides (N2,N2-dimethylguanosine). CONCLUSIONS Our study provides further evidence that prenatal metabolomic profiles might mediate the effect of maternal OWO on early childhood growth trajectories and OWO risk in offspring. The metabolic pathways, including identified metabolite mediators, might provide novel intervention targets for preventing the intrauterine development of obesity in the offspring of mothers with obesity.
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Affiliation(s)
- Zunsong Hu
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Luhang Han
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jiawang Liu
- Medicinal Chemistry Core, Office of Research, University of Tennessee Health Science Center, Memphis, TN, USA; Department of Pharmaceutical Science, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jay H Fowke
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Joan C Han
- Departments of Pediatrics and Physiology, University of Tennessee Health Science Center, and Children's Foundation Research Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, New York, NY, USA
| | - David Kakhniashvili
- Proteomics and Metabolomics Core, Office of Research, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kaja Z LeWinn
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Nicole R Bush
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - W Alex Mason
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Qi Zhao
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
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