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Elhakeem A, Frysz M, Goncalves Soares A, Bell JA, Cole TJ, Heron J, Howe LD, Sebert S, Tilling K, Timpson NJ, Lawlor DA. Evaluation and comparison of nine growth and development-based measures of pubertal timing. COMMUNICATIONS MEDICINE 2024; 4:159. [PMID: 39112679 PMCID: PMC11306255 DOI: 10.1038/s43856-024-00580-1] [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: 07/04/2023] [Accepted: 07/25/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Pubertal timing is heritable, varies between individuals, and has implications for life-course health. There are many different indicators of pubertal timing, and how they relate to each other is unclear. Our aim was to quantitatively compare nine indicators of pubertal timing. METHODS We used data from questionnaires and height, weight, and bone measurements from ages 7-17 y in a population-based cohort of 4267 females and 4251 males to compare nine growth and development-based indicators of pubertal timing. We summarise age of each indicator, their phenotypic and genetic correlations, and how they relate to established genetic risk score (GRS) for puberty timing, and phenotypic childhood body composition measures. RESULTS We show that pubic hair in males (mean: 12.6 y) and breasts in females (11.5 y) are early indicators of puberty, and voice breaking (14.2 y) and menarche (12.7 y) are late indicators however, there is substantial variation between individuals in pubertal age. All indicators show evidence of positive phenotypic intercorrelations (e.g., r = 0.49: male genitalia and pubic hair ages), and positive genetic intercorrelations. An age at menarche GRS positively associates with all other pubertal age indicators (e.g., difference in female age at peak height velocity per SD higher GRS: 0.24 y, 95%CI: 0.21 to 0.26), as does an age at voice breaking GRS (e.g., difference in age at male axillary hair: 0.11 y, 0.07 to 0.15). Higher childhood fat mass and lean mass associated with earlier puberty timing. CONCLUSIONS Our findings provide insights into the measurements of the timing of pubertal growth and development and illustrate value of various pubertal timing indicators in life-course research.
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Affiliation(s)
- Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Monika Frysz
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ana Goncalves Soares
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tim J Cole
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Jon Heron
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sylvain Sebert
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
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Hernáez Á, Elhakeem A, Barros H, Vrijkotte TGM, Fraser A, Lawlor DA, Magnus MC. Parental infertility and offspring cardiometabolic trajectories: a pooled analysis of three European cohorts. Fertil Steril 2024; 121:853-863. [PMID: 38237653 DOI: 10.1016/j.fertnstert.2024.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/01/2024] [Accepted: 01/08/2024] [Indexed: 02/12/2024]
Abstract
OBJECTIVE To assess whether parental infertility is associated with differences in cardiometabolic trajectories in offspring. DESIGN Pooled observational analysis in three prospective cohorts. SETTING Three nationwide pregnancy cohorts. PATIENTS A total of 14,609 singletons from the UK Avon Longitudinal Study of Parents and Children, the Portuguese Geraçao 21, and the Amsterdam Born Children and Their Development study. Each cohort contributed data up to ages 26, 12, and 13 years, respectively. INTERVENTION Parental infertility is defined as time-to-pregnancy of ≥12 months (n = 1,392, 9.5%). MAIN OUTCOME MEASURES Trajectories of body mass index (BMI), waist circumference, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol (LDL-C) level, high-density lipoprotein cholesterol (HDL-C) level, triglycerides level, and glucose level were compared in the offspring of couples with and without infertility. Trajectories were modeled using mixed-effects models with natural cubic splines adjusting for cohort, sex of the offspring, and maternal factors (age, BMI, smoking, educational level, parity, and ethnicity). Predicted levels of cardiometabolic traits up to 25 years of age were compared with parental infertility. RESULTS Offspring of couples with infertility had increasingly higher BMI (difference in mean predicted levels by age 25 years: 1.09 kg/m2, 95% confidence interval [0.68-1.50]) and suggestively higher diastolic blood pressure at age 25 years (1.21 mmHg [-0.003 to 2.43]). Their LDL-C tended to be higher, and their HDL-C values tended to be lower over time (age: 25 years, LDL-C: 4.07% [-0.79 to 8.93]; HDL-C: -2.78% [-6.99 to 1.43]). At age 17 years, offspring of couples with infertility had higher waist circumference (1.05 cm [0.11-1.99]) and systolic blood pressure (age: 17 years; 0.93 mmHg [0.044-1.81]), but these differences attenuated at later ages. No intergroup differences in triglyceride and glucose level trajectories were observed. Further adjustment for paternal age, BMI, smoking, and educational level, and both parents' histories of diabetes and hypertension in the cohort with this information available (Avon Longitudinal Study of Parents and Children) did not attenuate intergroup differences. CONCLUSION Offspring of couples with infertility relative to those of fertile couples have increasingly higher BMI over the years, suggestively higher blood pressure levels, and tend to have greater values of LDL-C and lower values of HDL-C with age.
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Affiliation(s)
- Álvaro Hernáez
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain.
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Henrique Barros
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional, Porto, Portugal
| | - Tanja G M Vrijkotte
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam Reproduction and Development Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; National Institute for Health Research Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
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Lawton M, Ben-Shlomo Y, Gkatzionis A, Hu MT, Grosset D, Tilling K. Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression. Eur J Epidemiol 2024; 39:521-533. [PMID: 38281297 PMCID: PMC11219432 DOI: 10.1007/s10654-023-01093-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 12/21/2023] [Indexed: 01/30/2024]
Abstract
Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR). We consider a multivariate approach to 2SMR using a multilevel model for disease progression to estimate the causal effect an exposure has on the intercept and slope. We carry out a simulation study comparing a naïve univariate 2SMR approach to a multivariate 2SMR approach with one exposure that effects both the intercept and slope of an outcome that changes linearly with time since diagnosis. The simulation study results, across six different scenarios, for both approaches were similar with no evidence against a non-zero bias and appropriate coverage of the 95% confidence intervals (for intercept 93.4-96.2% and the slope 94.5-96.0%). The multivariate approach gives a better joint coverage of both the intercept and slope effects. We also apply our method to two Parkinson's cohorts to examine the effect body mass index has on disease progression. There was no strong evidence that BMI affects disease progression, however the confidence intervals for both intercept and slope were wide.
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Affiliation(s)
- Michael Lawton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Apostolos Gkatzionis
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, Oxford University and Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Donald Grosset
- School of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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4
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Kukla A, Sahi SS, Navratil P, Benzo RP, Smith BH, Duffy D, Park WD, Shah M, Shah P, Clark MM, Fipps DC, Denic A, Schinstock CA, Dean PG, Stegall MD, Kudva YC, Diwan TS. Weight Loss Surgery Increases Kidney Transplant Rates in Patients With Renal Failure and Obesity. Mayo Clin Proc 2024; 99:705-715. [PMID: 38702124 DOI: 10.1016/j.mayocp.2024.01.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/23/2023] [Accepted: 01/25/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE To describe the outcomes of kidney transplant (KT) candidates with obesity undergoing sleeve gastrectomy (SG) to meet the criteria for KT. METHODS Retrospective analysis was conducted of electronic medical records of KT candidates with obesity (body mass index >35 kg/m2) who underwent SG in our institution. Weight loss, adverse health events, and the listing and transplant rates were abstracted and compared with the nonsurgical cohort. RESULTS The SG was performed in 54 patients; 50 patients did not have surgery. Baseline demographic characteristics were comparable at the time of evaluation. Mean body mass index ± SD of the SG group was 41.7±3.6 kg/m2 at baseline (vs 41.5±4.3 kg/m2 for nonsurgical controls); at 2 and 12 months after SG, it was 36.4±4.1 kg/m2 and 32.6±4.0 kg/m2 (P<.01 for both). In the median follow-up time of 15.5 months (interquartile range, 6.4 to 23.9 months), SG was followed by active listing (37/54 people), and 20 of 54 received KT during a median follow-up time of 20.9 months (interquartile range, 14.7 to 28.3 months) after SG. In contrast, 14 of 50 patients in the nonsurgical cohort were listed, and 5 received a KT (P<.01). Three patients (5.6%) experienced surgical complications. There was no difference in overall hospitalization rates and adverse health outcomes, but the SG cohort experienced a higher risk of clinically significant functional decline. CONCLUSION In KT candidates with obesity, SG appears to be effective, with 37% of patients undergoing KT during the next 18 months (P<.01). Further research is needed to confirm and to improve the safety and efficacy of SG for patients with obesity seeking a KT.
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Affiliation(s)
- Aleksandra Kukla
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Von Liebig Transplant Center, Mayo Clinic, Rochester, MN.
| | - Sukhdeep S Sahi
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Pavel Navratil
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Department of Urology, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic; Faculty of Medicine in Hradec Kralove, Charles University, Hradec Kralove, Czech Republic
| | - Roberto P Benzo
- Department of Pulmonary Medicine, Mayo Clinic, Rochester, MN
| | - Byron H Smith
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Dustin Duffy
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Walter D Park
- Department of Cardiovascular Surgery Research, Mayo Clinic, Rochester, MN
| | - Meera Shah
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Pankaj Shah
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Matthew M Clark
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - David C Fipps
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Carrie A Schinstock
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Von Liebig Transplant Center, Mayo Clinic, Rochester, MN
| | - Patrick G Dean
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
| | - Yogish C Kudva
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Tayyab S Diwan
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
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Burdeau JA, Stephenson BJK, Aris IM, Preston EV, Hivert MF, Oken E, Mahalingaiah S, Chavarro JE, Calafat AM, Rifas-Shiman SL, Zota AR, James-Todd T. First trimester plasma PER- AND Polyfluoroalkyl Substances (PFAS) and blood pressure trajectories across the second and third trimesters of pregnancy. ENVIRONMENT INTERNATIONAL 2024; 186:108628. [PMID: 38583297 PMCID: PMC11196104 DOI: 10.1016/j.envint.2024.108628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/31/2024] [Accepted: 04/02/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND Evidence suggests that exposure to per- and polyfluoroalkyl substances (PFAS) increases risk of high blood pressure (BP) during pregnancy. Prior studies did not examine associations with BP trajectory parameters (i.e., overall magnitude and velocity) during pregnancy, which is linked to adverse pregnancy outcomes. OBJECTIVES To estimate associations of multiple plasma PFAS in early pregnancy with BP trajectory parameters across the second and third trimesters. To assess potential effect modification by maternal age and parity. METHODS In 1297 individuals, we quantified six PFAS in plasma collected during early pregnancy (median gestational age: 9.4 weeks). We abstracted from medical records systolic BP (SBP) and diastolic BP (DBP) measurements, recorded from 12 weeks gestation until delivery. BP trajectory parameters were estimated via Super Imposition by Translation and Rotation modeling. Subsequently, Bayesian Kernel Machine Regression (BKMR) was employed to estimate individual and joint associations of PFAS concentrations with trajectory parameters - adjusting for maternal age, race/ethnicity, pre-pregnancy body mass index, income, parity, smoking status, and seafood intake. We evaluated effect modification by age at enrollment and parity. RESULTS We collected a median of 13 BP measurements per participant. In BKMR, higher concentration of perfluorooctane sulfonate (PFOS) was independently associated with higher magnitude of overall SBP and DBP trajectories (i.e., upward shift of trajectories) and faster SBP trajectory velocity, holding all other PFAS at their medians. In stratified BKMR analyses, participants with ≥ 1 live birth had more pronounced positive associations between PFOS and SBP velocity, DBP magnitude, and DBP velocity - compared to nulliparous participants. We did not observe significant associations between concentrations of the overall PFAS mixture and either magnitude or velocity of the BP trajectories. CONCLUSION Early pregnancy plasma PFOS concentrations were associated with altered BP trajectory in pregnancy, which may impact future cardiovascular health of the mother.
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Affiliation(s)
- Jordan A Burdeau
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Briana J K Stephenson
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Emma V Preston
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Shruthi Mahalingaiah
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, Massachusetts General Hospital, Boston, MA, USA.
| | - Jorge E Chavarro
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Ami R Zota
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
| | - Tamarra James-Todd
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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6
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Golding J, Iles-Caven Y, Northstone K, Fraser A, Heron J. Measures of puberty in the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring cohort. Wellcome Open Res 2024; 8:453. [PMID: 38716046 PMCID: PMC11075130 DOI: 10.12688/wellcomeopenres.19793.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2024] [Indexed: 05/20/2024] Open
Abstract
Background When studying the development of children through the preteen years into adolescence, it is often important to link features of their physical and mental health to the stage of puberty at the time. This is complex since individuals vary substantially in the ages at which they reach different pubertal milestones. Methods The Avon Longitudinal Study of Parents and Children (ALSPAC) is an ongoing longitudinal cohort study based in southwest England that recruited over 14000 women in pregnancy, with expected dates of delivery between April 1991 and December 1992. From 1999, information on puberty was collected using a number of different methods : (a) A series of annual questionnaires were administered when the index children were aged between eight and 17 years; these were mainly concerned with the physical changes associated with puberty; (b) identification of the age at peak height growth using the SITAR methodology; and (c) retrospective information from the girls on their age at onset of menstruation (menarche). Results The advantages and disadvantages of each method are discussed. Conclusions The data are available for analysis by interested researchers.
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Affiliation(s)
- Jean Golding
- Bristol Medical School, University of Bristol, Bristol, Bristol, BS8 2BN, UK
| | - Yasmin Iles-Caven
- Bristol Medical School, University of Bristol, Bristol, Bristol, BS8 2BN, UK
| | - Kate Northstone
- Bristol Medical School, University of Bristol, Bristol, Bristol, BS8 2BN, UK
| | - Abigail Fraser
- Bristol Medical School, University of Bristol, Bristol, Bristol, BS8 2BN, UK
| | - Jon Heron
- Bristol Medical School, University of Bristol, Bristol, Bristol, BS8 2BN, UK
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7
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Gonçalves Soares A, Santos S, Seyve E, Nedelec R, Puhakka S, Eloranta AM, Mikkonen S, Yuan WL, Lawlor DA, Heron J, Vrijheid M, Lepeule J, Nieuwenhuijsen M, Fossati S, Jaddoe VW, Lakka T, Sebert S, Heude B, Felix JF, Elhakeem A, Timpson NJ. Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood. JACC. ADVANCES 2024; 3:100808. [PMID: 38939392 PMCID: PMC11198279 DOI: 10.1016/j.jacadv.2023.100808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 09/25/2023] [Accepted: 10/23/2023] [Indexed: 06/29/2024]
Abstract
Background Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.
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Affiliation(s)
- Ana Gonçalves Soares
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Susana Santos
- The Generation R Study Group, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
- Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Universidade do Porto, Porto, Portugal
| | - Emie Seyve
- Inserm, CNRS, Institute for Advanced Biosciences, Grenoble Alpes University, Grenoble, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
| | - Rozenn Nedelec
- Faculty of Medicine, Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Soile Puhakka
- Faculty of Medicine, Research Unit of Population Health, University of Oulu, Oulu, Finland
- Department of Sports and Exercise Medicine, Oulu Deaconess Institute, Oulu, Finland
| | - Aino-Maija Eloranta
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Santtu Mikkonen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland
| | - Wen Lun Yuan
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research (A∗STAR), Singapore, Singapore
| | - Deborah A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jon Heron
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Johanna Lepeule
- Inserm, CNRS, Institute for Advanced Biosciences, Grenoble Alpes University, Grenoble, France
| | - Mark Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Serena Fossati
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Vincent W.V. Jaddoe
- The Generation R Study Group, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Timo Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Sylvain Sebert
- Faculty of Medicine, Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Barbara Heude
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
| | - Janine F. Felix
- The Generation R Study Group, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Lyons-Reid J, Derraik JGB, Kenealy T, Albert BB, Ramos Nieves JM, Monnard CR, Titcombe P, Nield H, Barton SJ, El-Heis S, Tham E, Godfrey KM, Chan SY, Cutfield WS. Impact of preconception and antenatal supplementation with myo-inositol, probiotics, and micronutrients on offspring BMI and weight gain over the first 2 years. BMC Med 2024; 22:39. [PMID: 38287349 PMCID: PMC10826220 DOI: 10.1186/s12916-024-03246-w] [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: 03/01/2023] [Accepted: 01/02/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND Nutritional intervention preconception and throughout pregnancy has been proposed as an approach to promoting healthy postnatal weight gain in the offspring but few randomised trials have examined this. METHODS Measurements of weight and length were obtained at multiple time points from birth to 2 years among 576 offspring of women randomised to receive preconception and antenatally either a supplement containing myo-inositol, probiotics, and additional micronutrients (intervention) or a standard micronutrient supplement (control). We examined the influence on age- and sex-standardised BMI at 2 years (WHO standards, adjusting for study site, sex, maternal parity, smoking and pre-pregnancy BMI, and gestational age), together with the change in weight, length, BMI from birth, and weight gain trajectories using latent class growth analysis. RESULTS At 2 years, there was a trend towards lower mean BMI among intervention offspring (adjusted mean difference [aMD] - 0.14 SD [95% CI 0.30, 0.02], p = 0.09), and fewer had a BMI > 95th percentile (i.e. > 1.65 SD, 9.2% vs 18.0%, adjusted risk ratio [aRR] 0.51 [95% CI 0.31, 0.82], p = 0.006). Longitudinal data revealed that intervention offspring had a 24% reduced risk of experiencing rapid weight gain > 0.67 SD in the first year of life (21.9% vs 31.1%, aRR 0.76 [95% CI 0.58, 1.00], p = 0.047). The risk was likewise decreased for sustained weight gain > 1.34 SD in the first 2 years of life (7.7% vs 17.1%, aRR 0.55 [95% CI 0.34, 0.88], p = 0.014). From five weight gain trajectories identified, there were more intervention offspring in the "normal" weight gain trajectory characterised by stable weight SDS around 0 SD from birth to 2 years (38.8% vs 30.1%, RR 1.29 [95% CI 1.03, 1.62], p = 0.029). CONCLUSIONS Supplementation with myo-inositol, probiotics, and additional micronutrients preconception and in pregnancy reduced the incidence of rapid weight gain and obesity at 2 years among offspring. Previous reports suggest these effects will likely translate to health benefits, but longer-term follow-up is needed to evaluate this. TRIAL REGISTRATION ClinicalTrials.gov, NCT02509988 (Universal Trial Number U1111-1171-8056). Registered on 16 July 2015.
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Affiliation(s)
- Jaz Lyons-Reid
- Liggins Institute, The University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - José G B Derraik
- Liggins Institute, The University of Auckland, Private Bag 92019, Auckland, New Zealand
- Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
- Environmental-Occupational Health Sciences and Non-Communicable Diseases Research Group, Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Timothy Kenealy
- Liggins Institute, The University of Auckland, Private Bag 92019, Auckland, New Zealand
- Department of Medicine and Department of General Practice and Primary Health Care, The University of Auckland, Auckland, New Zealand
| | - Benjamin B Albert
- Liggins Institute, The University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - J Manuel Ramos Nieves
- Nestlé Institute of Health Sciences, Nestlé Research, Société Des Produits Nestlé S.A, Lausanne, Switzerland
| | - Cathriona R Monnard
- Nestlé Institute of Health Sciences, Nestlé Research, Société Des Produits Nestlé S.A, Lausanne, Switzerland
| | - Phil Titcombe
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Heidi Nield
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Sheila J Barton
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Sarah El-Heis
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Elizabeth Tham
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Obstetrics & Gynaecology, National University of Singapore, Singapore, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Obstetrics & Gynaecology, National University of Singapore, Singapore, Singapore
| | - Wayne S Cutfield
- Liggins Institute, The University of Auckland, Private Bag 92019, Auckland, New Zealand.
- A Better Start - National Science Challenge, The University of Auckland, Auckland, New Zealand.
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9
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Alterman N, Youssim I, Nevo D, Calderon-Margalit R, Yuval, Broday D, Hauzer M, Raz R. Prenatal and postnatal exposure to NO 2 and rapid infant weight gain - A population-based cohort study. Paediatr Perinat Epidemiol 2023; 37:669-678. [PMID: 37565531 DOI: 10.1111/ppe.13000] [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: 04/09/2023] [Revised: 07/07/2023] [Accepted: 07/29/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Childhood overweight and obesity is a global public health problem. Rapid infant weight gain is predictive of childhood overweight. Studies found that exposure to ambient air pollution is associated with childhood overweight, and have linked prenatal exposure to air pollution with rapid infant weight gain. OBJECTIVES To examine the association between prenatal and postnatal ambient NO2 exposure, a traffic-related marker, with rapid weight gain in infants. METHODS We carried out a population-based historical cohort study using data from the Israeli national network of maternal and child health clinics. The study included 474,136 infants born at term with birthweight ≥2500 g in 2011-2019 in central Israel. Weekly averages of NO2 concentration throughout pregnancy (prenatal) and the first 4 weeks of life (postnatal) were assessed using an optimized dispersion model and were linked to geocoded home addresses. We modelled weight gain velocity throughout infancy using the SuperImposition by Translation and Rotation (SITAR) method, a mixed-effects nonlinear model specialized for modelling growth curves, and defined rapid weight gain as the highest velocity tertile. Distributed-lag models were used to assess critical periods of risk and to measure relative risks for rapid weight gain. Adjustments were made for socioeconomic status, population group, subdistrict, month and year of birth, and the alternate exposure period - prenatal or postnatal. RESULTS The cumulative adjusted relative risk for rapid weight gain of NO2 exposure was 1.02 (95% confidence intereval [CI] 1.00, 1.04) for exposure throughout pregnancy and 1.02 (95% CI 1.01, 1.04) for exposure during the first four postnatal weeks per NO2 interquartile range increase (7.3 ppb). An examination of weekly associations revealed that the critical period of risk for the prenatal exposure was from mid-pregnancy to birth. CONCLUSIONS Prenatal and postnatal exposures to higher concentrations of traffic-related air pollution are each independently associated with rapid infant weight gain, a risk factor for childhood overweight and obesity.
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Affiliation(s)
- Neora Alterman
- Braun School of Public Health and Community Medicine, The Hebrew University at Jerusalem - Hadassah, Jerusalem, Israel
| | - Iaroslav Youssim
- Braun School of Public Health and Community Medicine, The Hebrew University at Jerusalem - Hadassah, Jerusalem, Israel
| | - Daniel Nevo
- Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv, Israel
| | - Ronit Calderon-Margalit
- Braun School of Public Health and Community Medicine, The Hebrew University at Jerusalem - Hadassah, Jerusalem, Israel
| | - Yuval
- Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel
| | - David Broday
- Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel
| | - Michael Hauzer
- Bonen Clinic, Haifa and Western Galilee District, Israel
- Clalit Health Services Community Division, Haifa, Israel
| | - Raanan Raz
- Braun School of Public Health and Community Medicine, The Hebrew University at Jerusalem - Hadassah, Jerusalem, Israel
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10
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Zheng W, Zhang KX, Yuan XX, Luo JY, Wang J, Song W, Liang SN, Wang XX, Guo CM, Li GH. Maternal weight, blood lipids, and the offspring weight trajectories during infancy and early childhood in twin pregnancies. World J Pediatr 2023; 19:961-971. [PMID: 36877432 DOI: 10.1007/s12519-023-00703-z] [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: 10/30/2022] [Accepted: 02/07/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND The intrauterine environment has a profound and long-lasting influence on the health of the offspring. However, its impact on the postnatal catch-up growth of twin children remains unclarified. Therefore, this study aimed to explore the maternal factors in pregnancy associated with twin offspring growth. METHODS This study included 3142 live twin children born to 1571 mothers from the Beijing Birth Cohort Study conducted from 2016 to 2021 in Beijing, China. Original and corrected weight-for-age standard deviation scores of the twin offspring from birth to 36 months of age were calculated according to the World Health Organization Child Growth Standards. The corresponding weight trajectories were identified by the latent trajectory model. Maternal factors in pregnancy associated with the weight trajectories of the twin offspring were examined after adjustment for potential confounders. RESULTS Five weight trajectories of the twin children were identified, with 4.9% (154/3142) exhibiting insufficient catch-up growth, 30.6% (961/3142), and 46.8% (1469/3142) showing adequate catch-up growth from different birth weights, and 15.0% (472/3142) and 2.7% (86/3142) showing various degrees of excessive catch-up growth. Maternal short stature [adjusted odds ratio (OR) = 0.691, 95% confidence interval (CI) = 0.563-0.848, P = 0.0004] and lower total gestational weight gain (GWG) (adjusted OR = 0.774, 95% CI = 0.616-0.972, P = 0.03) were associated with insufficient catch-up growth of the offspring. Maternal stature (adjusted OR = 1.331, 95% CI = 1.168-1.518, P < 0.001), higher pre-pregnancy body mass index (BMI) (adjusted OR = 1.230, 95% CI = 1.090-1.387, P < 0.001), total GWG (adjusted OR = 1.207, 95% CI = 1.068-1.364, P = 0.002), GWG rate (adjusted OR = 1.165, 95% CI = 1.027-1.321, P = 0.02), total cholesterol (TC) (adjusted OR = 1.150, 95% CI = 1.018-1.300, P = 0.03) and low-density lipoprotein-cholesterol (LDL-C) (adjusted OR = 1.177, 95% CI = 1.041-1.330) in early pregnancy were associated with excessive growth of the offspring. The pattern of weight trajectories was similar between monochorionic and dichorionic twins. Maternal height, pre-pregnancy BMI, GWG, TC and LDL-C in early pregnancy were positively associated with excess growth in dichorionic twins, yet a similar association was observed only between maternal height and postnatal growth in monochorionic twins. CONCLUSION This study identified the effect of maternal stature, weight status, and blood lipid profiles during pregnancy on postnatal weight trajectories of the twin offspring, thereby providing a basis for twin pregnancy management to improve the long-term health of the offspring.
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Affiliation(s)
- Wei Zheng
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Ke-Xin Zhang
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Xian-Xian Yuan
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Jin-Ying Luo
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
- Obstetrics and Gynecology Department, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350001, China
| | - Jia Wang
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Wei Song
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Sheng-Nan Liang
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Xiao-Xin Wang
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Cui-Mei Guo
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China
| | - Guang-Hui Li
- Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China.
- Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China.
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11
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Constantine-Cooke N, Monterrubio-Gómez K, Plevris N, Derikx LAAP, Gros B, Jones GR, Marioni RE, Lees CW, Vallejos CA. Longitudinal Fecal Calprotectin Profiles Characterize Disease Course Heterogeneity in Crohn's Disease. Clin Gastroenterol Hepatol 2023; 21:2918-2927.e6. [PMID: 37004971 DOI: 10.1016/j.cgh.2023.03.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 03/06/2023] [Accepted: 03/21/2023] [Indexed: 04/04/2023]
Abstract
BACKGROUND AND AIMS The progressive nature of Crohn's disease is highly variable and hard to predict. In addition, symptoms correlate poorly with mucosal inflammation. There is therefore an urgent need to better characterize the heterogeneity of disease trajectories in Crohn's disease by utilizing objective markers of inflammation. We aimed to better understand this heterogeneity by clustering Crohn's disease patients with similar longitudinal fecal calprotectin profiles. METHODS We performed a retrospective cohort study at the Edinburgh IBD Unit, a tertiary referral center, and used latent class mixed models to cluster Crohn's disease subjects using fecal calprotectin observed within 5 years of diagnosis. Information criteria, alluvial plots, and cluster trajectories were used to decide the optimal number of clusters. Chi-square test, Fisher's exact test, and analysis of variance were used to test for associations with variables commonly assessed at diagnosis. RESULTS Our study cohort comprised 356 patients with newly diagnosed Crohn's disease and 2856 fecal calprotectin measurements taken within 5 years of diagnosis (median 7 per subject). Four distinct clusters were identified by characteristic calprotectin profiles: a cluster with consistently high fecal calprotectin and 3 clusters characterized by different downward longitudinal trends. Cluster membership was significantly associated with smoking (P = .015), upper gastrointestinal involvement (P < .001), and early biologic therapy (P < .001). CONCLUSIONS Our analysis demonstrates a novel approach to characterizing the heterogeneity of Crohn's disease by using fecal calprotectin. The group profiles do not simply reflect different treatment regimens and do not mirror classical disease progression endpoints.
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Affiliation(s)
- Nathan Constantine-Cooke
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
| | - Karla Monterrubio-Gómez
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Nikolas Plevris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh IBD Unit, Western General Hospital, Edinburgh, United Kingdom
| | - Lauranne A A P Derikx
- Inflammatory Bowel Disease Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Beatriz Gros
- Edinburgh IBD Unit, Western General Hospital, Edinburgh, United Kingdom
| | - Gareth-Rhys Jones
- Edinburgh IBD Unit, Western General Hospital, Edinburgh, United Kingdom; Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Charlie W Lees
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh IBD Unit, Western General Hospital, Edinburgh, United Kingdom
| | - Catalina A Vallejos
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom; Alan Turing Institute, British Library, London, United Kingdom
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12
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Plaku B, Williams PL, Sergeyev O, Korrick SA, Burns JS, Bather JR, Hauser R, Lee MM. Pubertal progression in relation to peripubertal exposure to organochlorine chemicals in a cohort of Russian boys. Int J Hyg Environ Health 2023; 254:114096. [PMID: 37981979 PMCID: PMC10653680 DOI: 10.1016/j.ijheh.2022.114096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Peripubertal concentrations of serum dioxins and polychlorinated biphenyls (PCBs) have demonstrated associations with altered age of pubertal onset and sexual maturity in boys, but associations with pubertal progression have received less attention. Methods The Russian Children's Study is a prospective cohort of 516 boys enrolled in 2003-2005 at age 8 or 9 and followed annually up to 19 years of age. Serum concentrations of dioxin-like toxic equivalents (TEQs), polychlorinated dibenzodioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and non-dioxin-like PCBs (NDL-PCBs) and whole blood lead levels (BLLs) were quantified from blood samples collected at study entry (age 8-9). Testicular volume (TV) was assessed annually using a Prader orchidometer. Pubertal trajectories were identified by applying Group-Based Trajectory Models (GBTMs) to TV measured from ages 8-19. Associations of peripubertal serum TEQs, PCDDs, PCDFs, and NDL-PCBs with specific progression trajectories were modeled using multinomial logistic regression, adjusting for each boy's birthweight, and for BLL, body mass index and nutritional factors at study entry. Results Among 489 eligible boys with available exposure measures, we identified three pubertal trajectories using GBTMs: slower (34% of boys), moderate (48%) and faster (18%). Boys with higher peripubertal serum TEQs had higher adjusted odds of being in the moderate versus faster trajectory (adjusted odds ratio (aOR) 1.79, 95% CI 1.01, 3.13) and the slower versus faster trajectory (aOR 1.52, 95% CI 0.82, 2.78) per 1 log unit increase in serum TEQs. Boys with higher peripubertal serum PCDFs had higher adjusted odds of being in the moderate compared to the faster trajectory (aOR 1.92, 95% CI 1.20, 3.03) and of being in the slower versus the faster trajectory (aOR 1.42, 95% CI 0.91, 2.33) per 1 log unit increase. Boys with higher NDL-PCBs had higher adjusted odds of being in the faster trajectory versus the moderate (aOR 2.56, 95% CI 0.91-7.20) or slower (aOR 3.31, 95% CI 1.07, 10.25) trajectory. Boys with higher blood lead levels also had higher adjusted odds of being in the slower trajectory of pubertal progression, compared to either the faster (aOR 1.47, 95% CI 0.89, 2.44) or moderate (aOR 1.20, 95% CI 0.83, 1.75) trajectories, per 1 log unit increase in BLL, although these associations did not attain statistical significance. Conclusion Boys' peripubertal exposure to dioxins and certain PCBs may alter pubertal progression.
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Affiliation(s)
- Bora Plaku
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115 (Present address: Optum Inc, Eden Prairie, MN 55344)
| | - Paige L Williams
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA 02115
| | - Oleg Sergeyev
- Belozersky Research Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Susan A Korrick
- Department of Environmental Health, Harvard T. H. Chan School of Public Health; 677 Huntington Ave, Boston, MA 02115; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115
| | - Jane S Burns
- Department of Environmental Health, Harvard T. H. Chan School of Public Health; 677 Huntington Ave, Boston, MA 02115
| | - Jemar R Bather
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA 02115
| | - Russ Hauser
- Departments of Environmental Health and Epidemiology, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115
| | - Mary M Lee
- Nemours Children's Health, 1600 Rockland Rd, Wilmington, DE 19803; Sidney Kimmel Medical College/Jefferson University, 1025 Walnut St, Philadelphia, PA 19107
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Poiret C, Bouyeure A, Patil S, Grigis A, Duchesnay E, Faillot M, Bottlaender M, Lemaitre F, Noulhiane M. A fast and robust hippocampal subfields segmentation: HSF revealing lifespan volumetric dynamics. Front Neuroinform 2023; 17:1130845. [PMID: 37396459 PMCID: PMC10308024 DOI: 10.3389/fninf.2023.1130845] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 05/22/2023] [Indexed: 07/04/2023] Open
Abstract
The hippocampal subfields, pivotal to episodic memory, are distinct both in terms of cyto- and myeloarchitectony. Studying the structure of hippocampal subfields in vivo is crucial to understand volumetric trajectories across the lifespan, from the emergence of episodic memory during early childhood to memory impairments found in older adults. However, segmenting hippocampal subfields on conventional MRI sequences is challenging because of their small size. Furthermore, there is to date no unified segmentation protocol for the hippocampal subfields, which limits comparisons between studies. Therefore, we introduced a novel segmentation tool called HSF short for hippocampal segmentation factory, which leverages an end-to-end deep learning pipeline. First, we validated HSF against currently used tools (ASHS, HIPS, and HippUnfold). Then, we used HSF on 3,750 subjects from the HCP development, young adults, and aging datasets to study the effect of age and sex on hippocampal subfields volumes. Firstly, we showed HSF to be closer to manual segmentation than other currently used tools (p < 0.001), regarding the Dice Coefficient, Hausdorff Distance, and Volumetric Similarity. Then, we showed differential maturation and aging across subfields, with the dentate gyrus being the most affected by age. We also found faster growth and decay in men than in women for most hippocampal subfields. Thus, while we introduced a new, fast and robust end-to-end segmentation tool, our neuroanatomical results concerning the lifespan trajectories of the hippocampal subfields reconcile previous conflicting results.
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Affiliation(s)
- Clement Poiret
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Antoine Bouyeure
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Sandesh Patil
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Antoine Grigis
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Edouard Duchesnay
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Matthieu Faillot
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- BioMaps, Service Hospitalier Frédéric Joliot, CNRS, Inserm, Université Paris-Saclay, Orsay, France
| | - Michel Bottlaender
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- BioMaps, Service Hospitalier Frédéric Joliot, CNRS, Inserm, Université Paris-Saclay, Orsay, France
| | - Frederic Lemaitre
- CETAPS EA 3832, Université de Rouen, Rouen, France
- CRIOBE, UAR 3278, CNRS-EPHE-UPVD, Mooréa, France
| | - Marion Noulhiane
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
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Wu J, Xu J, Zhao M, Li K, Yin G, Ge X, Zhao S, Liu X, Wei L, Xu Q. Threshold effect of urinary chromium on kidney function biomarkers: Evidence from a repeated-measures study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 262:115139. [PMID: 37327523 DOI: 10.1016/j.ecoenv.2023.115139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/07/2023] [Accepted: 06/11/2023] [Indexed: 06/18/2023]
Abstract
Chronic kidney disease (CKD) is a public health concern worldwide, and chromium exposure may be a risk factor due to its potential nephrotoxicity. However, research on the association between chromium exposure and kidney function especially the potential threshold effect of chromium exposure is limited. A repeated-measures study involving 183 adults (641 observations) was conducted from 2017 to 2021 in Jinzhou, China. Urinary albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) were measured as kidney function biomarkers. Generalized mixed models and two-piecewise linear spline mixed models were used to assess the dose-response relationship and potential threshold effect of chromium on kidney function, respectively. Temporal analysis was conducted by the latent process mixed model to depict the longitudinal change of kidney function over age. Urinary chromium was associated with CKD (odds ratio [OR] = 1.29; 95 % confidence interval [CI], 6.41, 14.06) and UACR (Percent change = 10.16 %; 95 % CI, 6.41 %, 14.06 %), and we did not find significant association between urinary chromium and eGFR (Percent change = 0.06 %; 95 % CI, -0.80 %, 0.95 %). The threshold analyses suggested the existence of threshold effects of urinary chromium, with inflection points at 2.74 μg/L for UACR and 3.95 μg/L for eGFR. Furthermore, we found that chromium exposure exhibited stronger kidney damage over age. Our study provided evidence for the threshold effects of chromium exposure on kidney function biomarkers and the heightened nephrotoxicity of chromium in older adults. More attention should be paid to the supervision of chromium exposure concentrations for preventing kidney damage, especially in older adults.
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Affiliation(s)
- Jingtao Wu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Guohuan Yin
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Shuanzheng Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xiaolin Liu
- Department of Epidemiology and Biostatistics, Jinzhou Medical University, Jinzhou 121001, Liaoning Province, China
| | - Lanping Wei
- Jinzhou Central Hospital, Jinzhou 121001, Liaoning Province, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
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15
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Elhakeem A, Taylor AE, Inskip HM, Huang JY, Mansell T, Rodrigues C, Asta F, Blaauwendraad SM, Håberg SE, Halliday J, Harskamp-van Ginkel MW, He JR, Jaddoe VWV, Lewis S, Maher GM, Manios Y, McCarthy FP, Reiss IKM, Rusconi F, Salika T, Tafflet M, Qiu X, Åsvold BO, Burgner D, Chan JKY, Gagliardi L, Gaillard R, Heude B, Magnus MC, Moschonis G, Murray D, Nelson SM, Porta D, Saffery R, Barros H, Eriksson JG, Vrijkotte TGM, Lawlor DA. Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis. Eur Heart J 2023; 44:1464-1473. [PMID: 36740401 PMCID: PMC10119029 DOI: 10.1093/eurheartj/ehac726] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/23/2022] [Accepted: 11/23/2022] [Indexed: 02/07/2023] Open
Abstract
AIMS To examine associations of assisted reproductive technology (ART) conception (vs. natural conception: NC) with offspring cardiometabolic health outcomes and whether these differ with age. METHODS AND RESULTS Differences in systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), lipids, and hyperglycaemic/insulin resistance markers were examined using multiple linear regression models in 14 population-based birth cohorts in Europe, Australia, and Singapore, and results were combined using meta-analysis. Change in cardiometabolic outcomes from 2 to 26 years was examined using trajectory modelling of four cohorts with repeated measures. 35 938 (654 ART) offspring were included in the meta-analysis. Mean age ranged from 13 months to 27.4 years but was <10 years in 11/14 cohorts. Meta-analysis found no statistical difference (ART minus NC) in SBP (-0.53 mmHg; 95% CI:-1.59 to 0.53), DBP (-0.24 mmHg; -0.83 to 0.35), or HR (0.02 beat/min; -0.91 to 0.94). Total cholesterol (2.59%; 0.10-5.07), HDL cholesterol (4.16%; 2.52-5.81), LDL cholesterol (4.95%; 0.47-9.43) were statistically significantly higher in ART-conceived vs. NC offspring. No statistical difference was seen for triglycerides (TG), glucose, insulin, and glycated haemoglobin. Long-term follow-up of 17 244 (244 ART) births identified statistically significant associations between ART and lower predicted SBP/DBP in childhood, and subtle trajectories to higher SBP and TG in young adulthood; however, most differences were not statistically significant. CONCLUSION These findings of small and statistically non-significant differences in offspring cardiometabolic outcomes should reassure people receiving ART. Longer-term follow-up is warranted to investigate changes over adulthood in the risks of hypertension, dyslipidaemia, and preclinical and clinical cardiovascular disease.
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Affiliation(s)
- Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amy E Taylor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Hazel M Inskip
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Jonathan Y Huang
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Duke-NUS Medical School, Centre for Quantitative Medicine,Singapore, Singapore
| | - Toby Mansell
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC, Australia
- University of Melbourne, Parkville, VIC, Australia
| | - Carina Rodrigues
- EPIUnit—Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
- Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal
| | - Federica Asta
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Sophia M Blaauwendraad
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Paediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jane Halliday
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC, Australia
- University of Melbourne, Parkville, VIC, Australia
| | - Margreet W Harskamp-van Ginkel
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jian-Rong He
- Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Vincent W V Jaddoe
- Department of Paediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Sharon Lewis
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC, Australia
- University of Melbourne, Parkville, VIC, Australia
| | - Gillian M Maher
- School of Public Health, University College Cork, Cork, Ireland
- The Irish Centre for Maternal and Child Health Research (INFANT), University College Cork, Cork, Ireland
| | - Yannis Manios
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
- Institute of Agri-Food and Life Sciences, Hellenic Mediterranean University Research Centre, Heraklion, Greece
| | - Fergus P McCarthy
- The Irish Centre for Maternal and Child Health Research (INFANT), University College Cork, Cork, Ireland
- Department of Obstetrics and Gynaecology, University College Cork, Cork, Ireland
| | - Irwin K M Reiss
- Department of Paediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Franca Rusconi
- Department of Mother and Child Health, Ospedale Versilia, Viareggio, AUSL Toscana Nord Ovest, Pisa, Italy
| | - Theodosia Salika
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Muriel Tafflet
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
| | - Xiu Qiu
- Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Bjørn O Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - David Burgner
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Department of Paediatrics, Monash University, Clayton, VIC, Australia
| | - Jerry K Y Chan
- Department of Reproductive Medicine, KK Women’s and Children’s Hospital, Singapore, Singapore
- Academic Clinical Program in Obstetrics and Gynaecology, Duke-NUS Medical School, Singapore, Singapore
| | - Luigi Gagliardi
- Department of Mother and Child Health, Ospedale Versilia, Viareggio, AUSL Toscana Nord Ovest, Pisa, Italy
| | - Romy Gaillard
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Paediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Barbara Heude
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - George Moschonis
- Department of Food, Nutrition and Dietetics, School of Allied Health, Human Services and Sport, College of Science, Health and Engineering, La Trobe University, Melbourne, Australia
| | - Deirdre Murray
- The Irish Centre for Maternal and Child Health Research (INFANT), University College Cork, Cork, Ireland
- Department of Pediatrics and Child Health, University College Cork, Cork, Ireland
| | - Scott M Nelson
- NIHR Bristol Biomedical Research Centre, Bristol, UK
- School of Medicine, University of Glasgow, Glasgow, UK
| | - Daniela Porta
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Richard Saffery
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC, Australia
- University of Melbourne, Parkville, VIC, Australia
| | - Henrique Barros
- EPIUnit—Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
- Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal
| | - Johan G Eriksson
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Tanja G M Vrijkotte
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
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16
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Elhakeem A, Ronkainen J, Mansell T, Lange K, Mikkola TM, Mishra BH, Wahab RJ, Cadman T, Yang T, Burgner D, Eriksson JG, Järvelin MR, Gaillard R, Jaddoe VWV, Lehtimäki T, Raitakari OT, Saffery R, Wake M, Wright J, Sebert S, Lawlor DA. Effect of common pregnancy and perinatal complications on offspring metabolic traits across the life course: a multi-cohort study. BMC Med 2023; 21:23. [PMID: 36653824 PMCID: PMC9850719 DOI: 10.1186/s12916-022-02711-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 12/14/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Common pregnancy and perinatal complications are associated with offspring cardiometabolic risk factors. These complications may influence multiple metabolic traits in the offspring and these associations might differ with offspring age. METHODS We used data from eight population-based cohort studies to examine and compare associations of pre-eclampsia (PE), gestational hypertension (GH), gestational diabetes (GD), preterm birth (PTB), small (SGA) and large (LGA) for gestational age (vs. appropriate size for gestational age (AGA)) with up to 167 plasma/serum-based nuclear magnetic resonance-derived metabolic traits encompassing lipids, lipoproteins, fatty acids, amino acids, ketones, glycerides/phospholipids, glycolysis, fluid balance, and inflammation. Confounder-adjusted regression models were used to examine associations (adjusted for maternal education, parity age at pregnancy, ethnicity, pre/early pregnancy body mass index and smoking, and offspring sex and age at metabolic trait assessment), and results were combined using meta-analysis by five age categories representing different periods of the offspring life course: neonates (cord blood), infancy (mean ages: 1.1-1.6 years), childhood (4.2-7.5 years); adolescence (12.0-16.0 years), and adulthood (22.0-67.8 years). RESULTS Offspring numbers for each age category/analysis varied from 8925 adults (441 PTB) to 1181 infants (135 GD); 48.4% to 60.0% were females. Pregnancy complications (PE, GH, GD) were each associated with up to three metabolic traits in neonates (P≤0.001) with some evidence of persistence to older ages. PTB and SGA were associated with 32 and 12 metabolic traits in neonates respectively, which included an adjusted standardised mean difference of -0.89 standard deviation (SD) units for albumin with PTB (95% CI: -1.10 to -0.69, P=1.3×10-17) and -0.41 SD for total lipids in medium HDL with SGA (95% CI: -0.56 to -0.25, P=2.6×10-7), with some evidence of persistence to older ages. LGA was inversely associated with 19 metabolic traits including lower levels of cholesterol, lipoproteins, fatty acids, and amino acids, with associations emerging in adolescence, (e.g. -0.11 SD total fatty acids, 95% CI: -0.18 to -0.05, P=0.0009), and attenuating with older age across adulthood. CONCLUSIONS These reassuring findings suggest little evidence of wide-spread and long-term impact of common pregnancy and perinatal complications on offspring metabolic traits, with most associations only observed for newborns rather than older ages, and for perinatal rather than pregnancy complications.
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Affiliation(s)
- Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Justiina Ronkainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Toby Mansell
- Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Katherine Lange
- Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Tuija M Mikkola
- Folkhälsan Research Center, Helsinki, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Binisha H Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Rama J Wahab
- Department of Paediatrics, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Centre, Rotterdam, Netherlands
| | - Tim Cadman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tiffany Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, UK
| | - David Burgner
- Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Department of Paediatrics, Monash University, Clayton, VIC, Australia
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science and Technology (A*STAR), Singapore, Singapore
| | - Marjo-Riitta Järvelin
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Romy Gaillard
- Department of Paediatrics, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Centre, Rotterdam, Netherlands
| | - Vincent W V Jaddoe
- Department of Paediatrics, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Centre, Rotterdam, Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Richard Saffery
- Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Melissa Wake
- Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, UK
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
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