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Van den Bergh BRH, Antonelli MC, Stein DJ. Current perspectives on perinatal mental health and neurobehavioral development: focus on regulation, coregulation and self-regulation. Curr Opin Psychiatry 2024; 37:237-250. [PMID: 38415742 DOI: 10.1097/yco.0000000000000932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
PURPOSE OF REVIEW Perinatal mental health research provides an important perspective on neurobehavioral development. Here, we aim to review the association of maternal perinatal health with offspring neurodevelopment, providing an update on (self-)regulation problems, hypothesized mechanistic pathways, progress and challenges, and implications for mental health. RECENT FINDINGS (1) Meta-analyses confirm that maternal perinatal mental distress is associated with (self-)regulation problems which constitute cognitive, behavioral, and affective social-emotional problems, while exposure to positive parental mental health has a positive impact. However, effect sizes are small. (2) Hypothesized mechanistic pathways underlying this association are complex. Interactive and compensatory mechanisms across developmental time are neglected topics. (3) Progress has been made in multiexposure studies. However, challenges remain and these are shared by clinical, translational and public health sciences. (4) From a mental healthcare perspective, a multidisciplinary and system level approach employing developmentally-sensitive measures and timely treatment of (self-)regulation and coregulation problems in a dyadic caregiver-child and family level approach seems needed. The existing evidence-base is sparse. SUMMARY During the perinatal period, addressing vulnerable contexts and building resilient systems may promote neurobehavioral development. A pluralistic approach to research, taking a multidisciplinary approach to theoretical models and empirical investigation needs to be fostered.
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Affiliation(s)
| | - Marta C Antonelli
- Laboratorio de Programación Perinatal del Neurodesarrollo, Instituto de Biología Celular y Neurociencias "Prof.E. De Robertis", Facultad de Medicina. Universidad de Buenos Aires, Buenos Aires, Argentina
- Frauenklinik und Poliklinik, Klinikum rechts der Isar, Munich, Germany
| | - Dan J Stein
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
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Walhovd KB, Krogsrud SK, Amlien IK, Sørensen Ø, Wang Y, Bråthen ACS, Overbye K, Kransberg J, Mowinckel AM, Magnussen F, Herud M, Håberg AK, Fjell AM, Vidal-Pineiro D. Fetal influence on the human brain through the lifespan. eLife 2024; 12:RP86812. [PMID: 38602745 PMCID: PMC11008813 DOI: 10.7554/elife.86812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024] Open
Abstract
Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - Stine K Krogsrud
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | | | - Knut Overbye
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Jonas Kransberg
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | | | - Fredrik Magnussen
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Martine Herud
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and TechnologyOsloNorway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - Didac Vidal-Pineiro
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
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Wang R, Zhao J, Li L, Huo Y. Associations between lipid-lowering drugs and pregnancy and perinatal outcomes: a Mendelian randomization study. J Hypertens 2024; 42:727-734. [PMID: 38230624 DOI: 10.1097/hjh.0000000000003664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
INTRODUCTION Mounting evidence has indicated that maternal dyslipidemia is associated with adverse obstetric outcomes, and the actions of lipid-lowering drugs in pregnant women remain controversial. Hence, this study aimed to appraise the causal relationship of lipid-lowering drugs [hydroxymethylglutaryl-coenzyme reductase (HMGCR) inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors] with pregnancy and perinatal outcomes using drug-targeting Mendelian randomization analysis. METHODS As a proxy for lipid-lowering drug exposure, two genetic instruments were used: genetic variants within or near the gene linked to low-density lipoprotein cholesterol (LDL-C) and the expression of quantitative trait loci of the drug target gene. Effect estimates were calculated using the inverse variance weighting (IVW) method and summary data-based Mendelian randomization (SMR) method. Heterogeneity and pleiotropy were assessed by Mendelian randomization-Egger regression, the Cochran Q test, and MR-PRESSO analysis. RESULTS HMGCR inhibitors were ascribed to a reduced risk of preeclampsia in both the IVW-MR method [odds ratio (OR) 0.583; 95% confidence interval (CI) 0.418-0.812; P = 0.001] and SMR analysis (OR 0.816; 95% CI 0.675-0.986; P = 0.036). The causal link between HMGCR inhibitors and offspring birthweight was statistically significant only in the analysis using the IVW method (OR, 0.879; 95% CI, 0.788-0.980; P = 0.020), and the combined results of the OR values supported the potential inhibitory effect of HMGCR inhibitors on offspring birthweight. Causal associations between lipid-lowering drugs and gestational diabetes, preterm birth, and congenital anomalies were not detected in either analysis. CONCLUSION No causal associations were observed between lipid-lowering drugs and gestational diabetes, preterm birth or congenital anomalies, whereas genetically predicted HMGCR inhibition dramatically reduced the risk of preeclampsia but attenuated offspring birthweight.
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Affiliation(s)
- Runfang Wang
- Department of Obstetrics and Gynecology, Hebei General Hospital, Hebei, China
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Tian Y, Ma G, Zi J, Hu Y, Zeng Y, Li H, Luo H, Shan S, Xiong J, Cheng G. Sex- and time-specific associations of obesity with glycaemic traits: A two-step multivariate Mendelian randomization study. Diabetes Obes Metab 2024; 26:1443-1453. [PMID: 38240050 DOI: 10.1111/dom.15445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/15/2023] [Accepted: 12/22/2023] [Indexed: 03/05/2024]
Abstract
AIM To assess the sex- and time-specific causal effects of obesity-related anthropometric traits on glycaemic traits. MATERIALS AND METHODS We used univariate and multivariate Mendelian randomization to assess the causal associations of anthropometric traits (gestational variables, birth weight, childhood body mass index [BMI], BMI, waist-to-hip ratio [WHR], BMI-adjusted WHR [WHRadj BMI]) with fasting glucose and insulin in Europeans from the Early Growth Genetics Consortium (n ≤ 298 142), the UK Biobank, the Genetic Investigation of Anthropometric Traits Consortium (n ≤ 697 734; females: n ≤ 434 794; males: n ≤ 374 754) and the Meta-Analyses of Glucose and Insulin-related traits Consortium (n ≤ 151 188; females: n ≤ 73 089; males: n ≤ 67 506), adjusting for maternal genetic effects, smoking, alcohol consumption, and age at menarche. RESULTS We observed a null association for gestational variables, a negative association for birth weight, and positive associations for childhood BMI and adult traits (BMI, WHR, and WHRadj BMI). In female participants, increased birth weight causally decreased fasting insulin (betaIVW , -0.07, 95% confidence interval [CI] -0.11 to -0.03; p = 1.92 × 10-3 ), but not glucose levels, which was annulled by adjusting for age at menarche. In male participants, increased birth weight causally decreased fasting glucose (betainverse-variance-weighted (IVW) , -0.07, 95% CI -0.11 to -0.03; p = 3.22 × 10-4 ), but not insulin levels. In time-specific analyses, independent effects of birth weight were absent in female participants, and were more pronounced in male participants. Independent effects of childhood BMI were attenuated in both sexes; independent effects of adult traits differed by sex. CONCLUSIONS Our findings provide evidence for causal and independent effects of sex- and time-specific anthropometric traits on glycaemic variables, and highlight the importance of considering multiple obesity exposures at different time points in the life course.
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Affiliation(s)
- Ye Tian
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Guochen Ma
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jing Zi
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yifan Hu
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yaxian Zeng
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Haoqi Li
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Hang Luo
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Shufang Shan
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Jingyuan Xiong
- Department of Occupational and Environmental Health, Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, China
| | - Guo Cheng
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
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Leinonen JT, Pirinen M, Tukiainen T. Disentangling the link between maternal influences on birth weight and disease risk in 36,211 genotyped mother-child pairs. Commun Biol 2024; 7:175. [PMID: 38347176 PMCID: PMC10861556 DOI: 10.1038/s42003-024-05872-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 01/29/2024] [Indexed: 02/15/2024] Open
Abstract
Epidemiological studies have robustly linked lower birth weight to later-life disease risks. These observations may reflect the adverse impact of intrauterine growth restriction on a child's health. However, causal evidence supporting such a mechanism in humans is largely lacking. Using Mendelian Randomization and 36,211 genotyped mother-child pairs from the FinnGen study, we assessed the relationship between intrauterine growth and five common health outcomes (coronary heart disease (CHD), hypertension, statin use, type 2 diabetes and cancer). We proxied intrauterine growth with polygenic scores for maternal effects on birth weight and took into account the transmission of genetic variants between a mother and a child in the analyses. We find limited evidence for contribution of normal variation in maternally influenced intrauterine growth on later-life disease. Instead, we find support for genetic pleiotropy in the fetal genome linking birth weight to CHD and hypertension. Our study illustrates the opportunities that data from genotyped parent-child pairs from a population-based biobank provides for addressing causality of maternal influences.
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Affiliation(s)
- Jaakko T Leinonen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
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Suthon S, Tangjittipokin W. Mechanisms and Physiological Roles of Polymorphisms in Gestational Diabetes Mellitus. Int J Mol Sci 2024; 25:2039. [PMID: 38396716 PMCID: PMC10888615 DOI: 10.3390/ijms25042039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/03/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is a significant pregnancy complication linked to perinatal complications and an elevated risk of future metabolic disorders for both mothers and their children. GDM is diagnosed when women without prior diabetes develop chronic hyperglycemia due to β-cell dysfunction during gestation. Global research focuses on the association between GDM and single nucleotide polymorphisms (SNPs) and aims to enhance our understanding of GDM's pathogenesis, predict its risk, and guide patient management. This review offers a summary of various SNPs linked to a heightened risk of GDM and explores their biological mechanisms within the tissues implicated in the development of the condition.
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Affiliation(s)
- Sarocha Suthon
- Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand;
- Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Center of Research Excellence Management, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Watip Tangjittipokin
- Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand;
- Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
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7
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Wang G, Warrington NM, Evans DM. Partitioning genetic effects on birthweight at classical human leukocyte antigen loci into maternal and fetal components, using structural equation modelling. Int J Epidemiol 2024; 53:dyad142. [PMID: 37831898 PMCID: PMC10859143 DOI: 10.1093/ije/dyad142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 10/03/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Single nucleotide polymorphisms in the human leukocyte antigen (HLA) region in both maternal and fetal genomes have been robustly associated with birthweight (BW) in previous genetic association studies. However, no study to date has partitioned the association between BW and classical HLA alleles into maternal and fetal components. METHODS We used structural equation modelling (SEM) to estimate the maternal and fetal effects of classical HLA alleles on BW. Our SEM leverages the data structure of the UK Biobank (UKB), which includes ∼270 000 participants' own BW and/or the BW of their firstborn child. RESULTS We show via simulation that our model yields asymptotically unbiased estimates of the maternal and fetal allelic effects on BW and appropriate type I error rates, in contrast to simple regression models. Asymptotic power calculations show that we have sufficient power to detect moderate-sized maternal or fetal allelic effects of common HLA alleles on BW in the UKB. Applying our SEM to imputed classical HLA alleles and own and offspring BW from the UKB replicated the previously reported association at the HLA-C locus and revealed strong evidence for maternal (HLA-A*03:01, B*35:01, B*39:06, P <0.001) and fetal allelic effects (HLA-B*39:06, P <0.001) of non-HLA-C alleles on BW. CONCLUSIONS Our model yields asymptotically unbiased estimates, appropriate type I error rates and appreciable power to estimate maternal and fetal effects on BW. These novel allelic associations between BW and classical HLA alleles provide insight into the immunogenetics of fetal growth in utero.
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Affiliation(s)
- Geng Wang
- Frazer Institute, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Nicole M Warrington
- Frazer Institute, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - David M Evans
- Frazer Institute, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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Sánchez-Soriano C, Pearson ER, Reynolds RM. Associations of offspring birthweight and placental weight with subsequent parental coronary heart disease: survival regression using the walker cohort. J Dev Orig Health Dis 2023; 14:746-754. [PMID: 38192014 DOI: 10.1017/s2040174423000430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
Low birth weight (BW) is consistently correlated with increased parental risk of subsequent cardiovascular disease, but the links with offspring placental weight (PW) are mostly unexplored. We have investigated the associations between parental coronary heart disease (CHD) and offspring BW and PW using the Walker cohort, a collection of 48,000 birth records from Dundee, Scotland, from the 1950s and 1960s. We linked the medical history of 13,866 mothers and 8,092 fathers to their offspring's records and performed Cox survival analyses modelling maternal and paternal CHD risk by their offspring's BW, PW, and the ratio between both measurements. We identified negative associations between offspring BW and both maternal (hazard ratio [HR]: 0.91, 95% confidence interval [CI]: 0.88-0.95) and paternal (HR: 0.96, 95% CI: 0.93-1.00) CHD risk, the stronger maternal correlation being consistent with previous reports. Offspring PW to BW ratio was positively associated with maternal CHD risk (HR: 1.14, 95% CI: 1.08-1.21), but the associations with paternal CHD were not significant. These analyses provide additional evidence for intergenerational associations between early growth and parental disease, identifying directionally opposed correlations of maternal CHD with offspring BW and PW, and highlight the importance of the placenta as a determinant of early development and adult disease.
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Affiliation(s)
- Carlos Sánchez-Soriano
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Ewan R Pearson
- Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, UK
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
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Bakulski KM, Blostein F, London SJ. Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations. Environ Health Perspect 2023; 131:126001. [PMID: 38048101 PMCID: PMC10695268 DOI: 10.1289/ehp12956] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 10/06/2023] [Accepted: 10/16/2023] [Indexed: 12/05/2023]
Abstract
BACKGROUND The prenatal environment influences lifetime health; epigenetic mechanisms likely predominate. In 2016, the first international consortium paper on cigarette smoking during pregnancy and offspring DNA methylation identified extensive, reproducible exposure signals. This finding raised expectations for epigenome-wide association studies (EWAS) of other exposures. OBJECTIVE We review the current state-of-the-science for DNA methylation associations across prenatal exposures in humans and provide future recommendations. METHODS We reviewed 134 prenatal environmental EWAS of DNA methylation in newborns, focusing on 51 epidemiological studies with meta-analysis or replication testing. Exposures spanned cigarette smoking, alcohol consumption, air pollution, dietary factors, psychosocial stress, metals, other chemicals, and other exogenous factors. Of the reproducible DNA methylation signatures, we examined implementation as exposure biomarkers. RESULTS Only 19 (14%) of these prenatal EWAS were conducted in cohorts of 1,000 or more individuals, reflecting the still early stage of the field. To date, the largest perinatal EWAS sample size was 6,685 participants. For comparison, the most recent genome-wide association study for birth weight included more than 300,000 individuals. Replication, at some level, was successful with exposures to cigarette smoking, folate, dietary glycemic index, particulate matter with aerodynamic diameter < 10 μ m and < 2.5 μ m , nitrogen dioxide, mercury, cadmium, arsenic, electronic waste, PFAS, and DDT. Reproducible effects of a more limited set of prenatal exposures (smoking, folate) enabled robust methylation biomarker creation. DISCUSSION Current evidence demonstrates the scientific premise for reproducible DNA methylation exposure signatures. Better powered EWAS could identify signatures across many exposures and enable comprehensive biomarker development. Whether methylation biomarkers of exposures themselves cause health effects remains unclear. We expect that larger EWAS with enhanced coverage of epigenome and exposome, along with improved single-cell technologies and evolving methods for integrative multi-omics analyses and causal inference, will expand mechanistic understanding of causal links between environmental exposures, the epigenome, and health outcomes throughout the life course. https://doi.org/10.1289/EHP12956.
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Affiliation(s)
| | - Freida Blostein
- University of Michigan, Ann Arbor, Michigan, USA
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Stephanie J. London
- National Institute of Environmental Health Sciences, National Institutes of Health, U.S. Department of Health and Human Services, Research Triangle Park, North Carolina, USA
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Reim PK, Engelbrechtsen L, Gybel-Brask D, Schnurr TM, Kelstrup L, Høgdall EV, Hansen T. The influence of insulin-related genetic variants on fetal growth, fetal blood flow, and placental weight in a prospective pregnancy cohort. Sci Rep 2023; 13:19638. [PMID: 37949941 PMCID: PMC10638310 DOI: 10.1038/s41598-023-46910-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 11/07/2023] [Indexed: 11/12/2023] Open
Abstract
The fetal insulin hypothesis proposes that low birthweight and type 2 diabetes (T2D) in adulthood may be two phenotypes of the same genotype. In this study we aimed to explore this theory further by testing the effects of GWAS-identified genetic variants related to insulin release and sensitivity on fetal growth and blood flow from week 20 of gestation to birth and on placental weight at birth. We calculated genetic risk scores (GRS) of first phase insulin release (FPIR), fasting insulin (FI), combined insulin resistance and dyslipidaemia (IR + DLD) and insulin sensitivity (IS) in a study population of 665 genotyped newborns. Two-dimensional ultrasound measurements with estimation of fetal weight and blood flow were carried out at week 20, 25, and 32 of gestation in all 665 pregnancies. Birthweight and placental weight were registered at birth. Associations between the GRSs and fetal growth, blood flow and placental weight were investigated using linear mixed models. The FPIR GRS was directly associated with fetal growth from week 20 to birth, and both the FI GRS, IR + DLD GRS, and IS GRS were associated with placental weight at birth. Our findings indicate that insulin-related genetic variants might primarily affect fetal growth via the placenta.
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Affiliation(s)
- Pauline K Reim
- Faculty of Health Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Maersk Tower, Blegdamsvej 3B, 8th Floor, 2200, Copenhagen, Denmark
| | - Line Engelbrechtsen
- Faculty of Health Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Maersk Tower, Blegdamsvej 3B, 8th Floor, 2200, Copenhagen, Denmark
- Department of Gynaecology and Obstetrics, Herlev Hospital, University of Copenhagen, Herlev, Denmark
| | - Dorte Gybel-Brask
- Psycotherapeutic Outpatient Clinic, Department of Psychiatry, Ballerup Hospital, Ballerup, Denmark
| | - Theresia M Schnurr
- Faculty of Health Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Maersk Tower, Blegdamsvej 3B, 8th Floor, 2200, Copenhagen, Denmark
| | - Louise Kelstrup
- Department of Gynaecology and Obstetrics, Herlev Hospital, University of Copenhagen, Herlev, Denmark
| | - Estrid V Høgdall
- Molecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev, Denmark
| | - Torben Hansen
- Faculty of Health Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Maersk Tower, Blegdamsvej 3B, 8th Floor, 2200, Copenhagen, Denmark.
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11
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Pasanen A, Karjalainen MK, Zhang G, Tiensuu H, Haapalainen AM, Ojaniemi M, Feenstra B, Jacobsson B, Palotie A, Laivuori H, Muglia LJ, Rämet M, Hallman M. Meta-analysis of genome-wide association studies of gestational duration and spontaneous preterm birth identifies new maternal risk loci. PLoS Genet 2023; 19:e1010982. [PMID: 37871108 PMCID: PMC10621942 DOI: 10.1371/journal.pgen.1010982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 11/02/2023] [Accepted: 09/19/2023] [Indexed: 10/25/2023] Open
Abstract
BACKGROUND Preterm birth (<37 weeks of gestation) is a major cause of neonatal death and morbidity. Up to 40% of the variation in timing of birth results from genetic factors, mostly due to the maternal genome. METHODS We conducted a genome-wide meta-analysis of gestational duration and spontaneous preterm birth in 68,732 and 98,370 European mothers, respectively. RESULTS The meta-analysis detected 15 loci associated with gestational duration, and four loci associated with preterm birth. Seven of the associated loci were novel. The loci mapped to several biologically plausible genes, for example HAND2 whose expression was previously shown to decrease during gestation, associated with gestational duration, and GC (Vitamin D-binding protein), associated with preterm birth. Downstream in silico-analysis suggested regulatory roles as underlying mechanisms for the associated loci. LD score regression found birth weight measures as the most strongly correlated traits, highlighting the unique nature of spontaneous preterm birth phenotype. Tissue expression and colocalization analysis revealed reproductive tissues and immune cell types as the most relevant sites of action. CONCLUSION We report novel genetic risk loci that associate with preterm birth or gestational duration, and reproduce findings from previous genome-wide association studies. Altogether, our findings provide new insight into the genetic background of preterm birth. Better characterization of the causal genetic mechanisms will be important to public health as it could suggest new strategies to treat and prevent preterm birth.
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Affiliation(s)
- Anu Pasanen
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Minna K. Karjalainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | | | - Ge Zhang
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Center for Prevention of Preterm Birth, Perinatal Institute and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Heli Tiensuu
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Antti M. Haapalainen
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Marja Ojaniemi
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Bo Jacobsson
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Analytic and Translational Genetics Unit, Department of Medicine, and the Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Center for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, University of Tampere, Tampere, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland
| | - Louis J. Muglia
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Center for Prevention of Preterm Birth, Perinatal Institute and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Burroughs Wellcome Fund, Research Triangle Park, Durham, North Carolina, United States of America
| | - Mika Rämet
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mikko Hallman
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
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12
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Walhovd KB, Lövden M, Fjell AM. Timing of lifespan influences on brain and cognition. Trends Cogn Sci 2023; 27:901-915. [PMID: 37563042 DOI: 10.1016/j.tics.2023.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/04/2023] [Accepted: 07/04/2023] [Indexed: 08/12/2023]
Abstract
Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Martin Lövden
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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13
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Jansen EC, Zhang KP, Dolinoy DC, Burgess HJ, O'Brien LM, Langen E, Unwala N, Ehlinger J, Mulcahy MC, Goodrich JM. Early-to-mid pregnancy sleep and circadian markers in relation to birth outcomes: An epigenetics pilot study. Chronobiol Int 2023; 40:1224-1234. [PMID: 37722702 PMCID: PMC10626590 DOI: 10.1080/07420528.2023.2256854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 09/03/2023] [Indexed: 09/20/2023]
Abstract
Maternal sleep and circadian health during pregnancy are emerging as important predictors of pregnancy outcomes, but examination of potential epigenetic mechanisms is rare. We investigated links between maternal leukocyte DNA methylation of circadian genes and birth outcomes within a pregnancy cohort. Women (n = 96) completed a questionnaire and provided a blood sample at least once during early-to-mid pregnancy (average gestation weeks = 14.2). Leukocyte DNA was isolated and DNA methylation (average percent of methylation) at multiple CpG sites within BMAL1, PER1, and MTNR1B genes were quantified by pyrosequencing. Birth outcomes including gestational age at delivery, birthweight, and head circumference were abstracted from medical charts. Linear regression analyses were run between each CpG site with birth outcomes, adjusting for important confounders. Sleep duration and timing were assessed as secondary exposures. Higher methylation of a CpG site in PER1 was associated with smaller log-transformed head circumference (β=-0.02 with 95% CI -0.02 to 0.01; P, trend = 0.04). Higher methylation of MTNR1B (averaged across sites) was associated with lower log-transformed birthweight (-0.08 with 95% CI -0.16 to -0.01; P, trend = 0.0495). In addition, longer sleep duration was associated with higher birthweight (0.10 with 95% CI 0.02 to 0.18 comparing > 9 h to < 8 h; P, trend = 0.04). This pilot investigation revealed that higher methylation of PER1 and MTNR1B genes, and sleep duration measured in early-to-mid pregnancy were related to birth outcomes.
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Affiliation(s)
- Erica C Jansen
- Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Kelvin Pengyuan Zhang
- Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Dana C Dolinoy
- Environmental Health Sciences and Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | | | | | - Elizabeth Langen
- Obstetrics and Gynecology, Michigan Medicine, Ann Arbor, Michigan, USA
| | - Naquia Unwala
- Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Jessa Ehlinger
- Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Molly C Mulcahy
- Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Jaclyn M Goodrich
- Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
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14
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Hwang LD, Cuellar-Partida G, Yengo L, Zeng J, Beaumont RN, Freathy RM, Moen GH, Warrington NM, Evans DM. Direct and INdirect effects analysis of Genetic lOci (DINGO): A software package to increase the power of locus discovery in GWAS meta-analyses of perinatal phenotypes and traits influenced by indirect genetic effects. medRxiv 2023:2023.08.22.23294446. [PMID: 37693475 PMCID: PMC10491281 DOI: 10.1101/2023.08.22.23294446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Perinatal traits are influenced by genetic variants from both fetal and maternal genomes. Genome-wide association studies (GWAS) of these phenotypes have typically involved separate fetal and maternal scans, however, this approach may be inefficient as it does not utilize the information shared across the individual GWAS. In this manuscript we investigate the performance of three strategies to detect loci in maternal and fetal GWAS of the same trait: (i) the traditional strategy of analysing maternal and fetal GWAS separately; (ii) a novel two degree of freedom test which combines information from maternal and fetal GWAS; and (iii) a novel one degree of freedom test where signals from maternal and fetal GWAS are meta-analysed together conditional on the estimated sample overlap. We demonstrate through a combination of analytical formulae and data simulation that the optimal strategy depends on the extent of sample overlap/relatedness between the maternal and fetal GWAS, the correlation between own and offspring phenotypes, whether loci jointly exhibit fetal and maternal effects, and if so, whether these effects are directionally concordant. We apply our methods to summary results statistics from a recent GWAS meta-analysis of birth weight from deCODE, the UK Biobank and the Early Growth Genetics (EGG) consortium. Both the two degree of freedom (213 loci) and meta-analytic approach (226 loci) dramatically increase the number of robustly associated genetic loci for birth weight relative to separately analysing the scans (183 loci). Our best strategy identifies an additional 62 novel loci compared to the most recent published meta-analysis of birth weight and implicates both known and new biological pathways in the aetiology of the trait. We implement our methods in the online DINGO (Direct and INdirect effects analysis of Genetic lOci) software package, which allows users to perform one and/or two degree of freedom tests easily and computationally efficiently across the genome. We conclude that whilst the novel two degree of freedom test may be particularly useful for the analysis of certain perinatal phenotypes where many loci exhibit discordant maternal and fetal genetic effects, for most phenotypes, a simple meta-analytic strategy is likely to perform best, particularly in situations where maternal and fetal GWAS only partially overlap.
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Affiliation(s)
- Liang-Dar Hwang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | | | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Robin N Beaumont
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Gunn-Helen Moen
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- The Frazer Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia
| | - Nicole M Warrington
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- The Frazer Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia
| | - David M Evans
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- The Frazer Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia
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15
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Reshetnikova Y, Churnosova M, Stepanov V, Bocharova A, Serebrova V, Trifonova E, Ponomarenko I, Sorokina I, Efremova O, Orlova V, Batlutskaya I, Ponomarenko M, Churnosov V, Eliseeva N, Aristova I, Polonikov A, Reshetnikov E, Churnosov M. Maternal Age at Menarche Gene Polymorphisms Are Associated with Offspring Birth Weight. Life (Basel) 2023; 13:1525. [PMID: 37511900 PMCID: PMC10381708 DOI: 10.3390/life13071525] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
In this study, the association between maternal age at menarche (AAM)-related polymorphisms and offspring birth weight (BW) was studied. The work was performed on a sample of 716 pregnant women and their newborns. All pregnant women underwent genotyping of 50 SNPs of AAM candidate genes. Regression methods (linear and Model-Based Multifactor Dimensionality Reduction (MB-MDR)) with permutation procedures (the indicator pperm was calculated) were used to identify the correlation between SNPs and newborn weight (transformed BW values were analyzed) and in silico bioinformatic examination was applied to assess the intended functionality of BW-associated loci. Four AAM-related genetic variants were BW-associated including genes such as POMC (rs7589318) (βadditive = 0.202/pperm = 0.015), KDM3B (rs757647) (βrecessive = 0.323/pperm = 0.005), INHBA (rs1079866) (βadditive = 0.110/pperm = 0.014) and NKX2-1 (rs999460) (βrecessive = -0.176/pperm = 0.015). Ten BW-significant models of interSNPs interactions (pperm ≤ 0.001) were identified for 20 polymorphisms. SNPs rs7538038 KISS1, rs713586 RBJ, rs12324955 FTO and rs713586 RBJ-rs12324955 FTO two-locus interaction were included in the largest number of BW-associated models (30% models each). BW-associated AAM-linked 22 SNPs and 350 proxy loci were functionally related to 49 genes relevant to pathways such as the hormone biosynthesis/process and female/male gonad development. In conclusion, maternal AMM-related genes polymorphism is associated with the offspring BW.
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Affiliation(s)
- Yuliya Reshetnikova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Vadim Stepanov
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia
| | - Anna Bocharova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia
| | - Victoria Serebrova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia
| | - Ekaterina Trifonova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Olga Efremova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Valentina Orlova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Irina Batlutskaya
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Marina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Vladimir Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Natalya Eliseeva
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Alexey Polonikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Biology, Medical Genetics and Ecology and Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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16
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Floris J, Matthes KL, Le Vu M, Staub K. Intergenerational transmission of height in a historical population: From taller mothers to larger offspring at birth (and as adults). PNAS Nexus 2023; 2:pgad208. [PMID: 37388921 PMCID: PMC10306274 DOI: 10.1093/pnasnexus/pgad208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 06/06/2023] [Accepted: 06/16/2023] [Indexed: 07/01/2023]
Abstract
Changes in growth and height reflect changes in nutritional status and health. The systematic surveillance of growth can suggest areas for interventions. Moreover, phenotypic variation has a strong intergenerational component. There is a lack of historical family data that can be used to track the transmission of height over subsequent generations. Maternal height is a proxy for conditions experienced by one generation that relates to the health/growth of future generations. Cross-sectional/cohort studies have shown that shorter maternal height is closely associated with lower birth weight of offspring. We analyzed the maternal height and offspring weight at birth in the maternity hospital in Basel, Switzerland, from 1896 to 1939 (N = ∼12,000) using generalized additive models (GAMs). We observed that average height of the mothers increased by ∼4 cm across 60 birth years and that average birth weight of their children shows a similarly shaped and upward trend 28 years later. Our final model (adjusted for year, parity, sex of the child, gestational age, and maternal birth year) revealed a significant and almost linear association between maternal height and birth weight. Maternal height was the second most important variable modeling birth weight, after gestational age. In addition, we found a significant association between maternal height and aggregated average height of males from the same birth years at time of conscription, 19 years later. Our results have implications for public health: When (female/maternal) height increases due to improved nutritional status, size at birth-and subsequently also the height in adulthood of the next generation-increases as well. However, the directions of development in this regard may currently differ depending on the world region.
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Affiliation(s)
| | | | - Mathilde Le Vu
- Institute of Evolutionary Medicine, University of Zurich, CH-8057 Zurich, Switzerland
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17
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Brockway HM, Wilson SL, Kallapur SG, Buhimschi CS, Muglia LJ, Jones HN. Characterization of methylation profiles in spontaneous preterm birth placental villous tissue. PLoS One 2023; 18:e0279991. [PMID: 36952446 PMCID: PMC10035933 DOI: 10.1371/journal.pone.0279991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Indexed: 03/25/2023] Open
Abstract
Preterm birth is a global public health crisis which results in significant neonatal and maternal mortality. Yet little is known regarding the molecular mechanisms of idiopathic spontaneous preterm birth, and we have few diagnostic markers for adequate assessment of placental development and function. Previous studies of placental pathology and our transcriptomics studies suggest a role for placental maturity in idiopathic spontaneous preterm birth. It is known that placental DNA methylation changes over gestation. We hypothesized that if placental hypermaturity is present in our samples, we would observe a unique idiopathic spontaneous preterm birth DNA methylation profile potentially driving the gene expression differences we previously identified in our placental samples. Our results indicate the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern suggesting hypermaturity. Only seven significant differentially methylated regions fitting the idiopathic spontaneous preterm birth specific (relative to the controls) profile were identified, indicating unusually high similarity in DNA methylation between idiopathic spontaneous preterm birth and term birth samples. We identified an additional 1,718 significantly methylated regions in our gestational age matched controls where the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern, again indicating a striking level of similarity between the idiopathic spontaneous preterm birth and term birth samples. Pathway analysis of these regions revealed differences in genes within the WNT and Cadherin signaling pathways, both of which are essential in placental development and maturation. Taken together, these data demonstrate that the idiopathic spontaneous preterm birth samples display a hypermature methylation signature than expected given their respective gestational age which likely impacts birth timing.
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Affiliation(s)
- Heather M. Brockway
- Department of Physiology and Functional Genomics, College of Medicine at the University of Florida, Gainesville, Florida, United States of America
| | - Samantha L. Wilson
- Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Suhas G. Kallapur
- Divisions of Neonatology and Developmental Biology, David Geffen School of Medicine at the University of California, UCLA Mattel Children’s Hospital, Los Angeles, California, United States of America
| | - Catalin S. Buhimschi
- Department of Obstetrics and Gynecology, The University of Illinois College of Medicine, Chicago, Illinois, United States of America
| | - Louis J. Muglia
- Burroughs Wellcome Fund, Research Triangle Park, North Carolina, United States of America
| | - Helen N. Jones
- Department of Physiology and Functional Genomics, College of Medicine at the University of Florida, Gainesville, Florida, United States of America
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18
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Wei L, Jiang Y, Gao P, Zhang J, Zhou X, Zhu S, Chen Y, Zhang H, DU Y, Fang C, Li J, Gao X, He M, Wang S, Feng L, Yu J. Role of melatonin receptor 1B gene polymorphism and its effect on the regulation of glucose transport in gestational diabetes mellitus. J Zhejiang Univ Sci B 2023; 24:78-88. [PMID: 36632752 DOI: 10.1631/jzus.B2200136] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Melatonin receptor 1B (MT2, encoded by the MTNR1B gene), a high-affinity receptor for melatonin, is associated with glucose homeostasis including glucose uptake and transport. The rs10830963 variant in the MTNR1B gene is linked to glucose metabolism disorders including gestational diabetes mellitus (GDM); however, the relationship between MT2-mediated melatonin signaling and a high birth weight of GDM infants from maternal glucose abnormality remains poorly understood. This article aims to investigate the relationship between rs10830963 variants and GDM development, as well as the effects of MT2 receptor on glucose uptake and transport in trophoblasts. TaqMan-MGB (minor groove binder) probe quantitative real-time polymerase chain reaction (qPCR) assays were used for rs10930963 genotyping. MT2 expression in the placenta of GDM and normal pregnant women was detected by immunofluorescence, western blot, and qPCR. The relationship between MT2 and glucose transporters (GLUTs) or peroxisome proliferator-activated receptor γ (PPARγ) was established by western blot, and glucose consumption of trophoblasts was measured by a glucose assay kit. The results showed that the genotype and allele frequencies of rs10830963 were significantly different between GDM and normal pregnant women (P<0.05). The fasting, 1-h and 2-h plasma glucose levels of G-allele carriers were significantly higher than those of C-allele carriers (P<0.05). Besides, the protein and messenger RNA (mRNA) expression of MT2 in the placenta of GDM was significantly higher than that of normal pregnant women (P<0.05). Melatonin could stimulate glucose uptake and GLUT4 and PPARγ protein expression in trophoblasts, which could be attenuated by MT2 receptor knockdown. In conclusion, the rs10830963 variant was associated with an increased risk of GDM. The MT2 receptor is essential for melatonin to raise glucose uptake and transport, which may be mediated by PPARγ.
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19
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Wang H, Jiang J, Jin T, Wang Y, Li M, Huang S, Xie J, Chen Z, Guo Y, Zheng J, Jiang Y, Mo Z. Associations of circulation levels of cytokines with birthweight, preterm birth, spontaneous miscarriages, and stillbirth: A Mendelian randomization analysis. Front Genet 2023; 14:1113804. [PMID: 36891154 PMCID: PMC9986262 DOI: 10.3389/fgene.2023.1113804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/08/2023] [Indexed: 02/22/2023] Open
Abstract
Background: The association between immune imbalances and adverse pregnancy outcomes has been extensive investigated by observational studies, but remain unclear. Thus, this study aimed to establish the causality of the circulation levels of cytokines on adverse pregnancy outcomes, such as offspring's birthweight (BW), preterm birth (PTB), spontaneous miscarriage (SM), and stillbirth (SB). Methods: Two-sample Mendelian randomization (MR) analysis was employed to investigate potential causal relations between 41 cytokines and pregnancy outcomes on the basis of previously published GWAS datasets. Multivariable MR (MVMR) analysis was implemented to investigate the effect of the composition of cytokine networks on the pregnancy outcomes. Potential risk factors were further estimated to explore the potential mediators. Results: Genetic correlation analysis based on large GWAS data sources revealed that genetically predicted MIP1b (β = -0.027, S.E. = 0.010, p = 0.009) and MCSF (β = -0.024, S.E. = 0.011, p = 0.029) were associated with reduced offspring's BW, MCP1 (OR: 0.90, 95% CI: 0.83-0.97, p = 0.007) was associated with reduced SM risk, SCF (β = -0.014, S.E. = 0.005, p = 0.012) associated with decreased number of SB in MVMR. The univariable MR showed that GROa (OR: 0.92, 95% CI: 0.87-0.97, p = 0.004) was associated with decreased PTB risk. Except for the MCSF-BW association, all above associations surpassed the Bonferroni corrected threshold. The MVMR results revealed that MIF, SDF1a, MIP1b, MCSF and IP10 composed cytokine networks, associated with offspring's BW. Risk factors analysis indicated that the above causal associations might be mediated by smoking behaviors. Conclusion: These findings suggest the causal associations of several cytokines with adverse pregnancy outcomes, which were potentially mediated by smoking and obesity. Some of the results did not been corrected through multiple tests and larger samples verification is required in further studies.
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Affiliation(s)
- Honghong Wang
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.,Department of Pharmacy, Liuzhou Maternity and Child Healthcare Hospital, Affiliated Maternity Hospital and Affiliated Children's Hospital of Guangxi University of Science and Technology, Liuzhou, Guangxi, China.,Department of Pharmacy, Liuzhou Hospital of Guangzhou Women and Children's Medical Center, Liuzhou, Guangxi, China
| | - Jinghang Jiang
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.,The Reproductive Medicine Center, Jingmen No. 2 People's Hospital, JingChu University of Technology Affiliated Central Hospital, Jingmen, Hubei, China
| | - Tingwei Jin
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Yifu Wang
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Mingli Li
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Shengzhu Huang
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Juanjuan Xie
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Zhongyuan Chen
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Guangxi Collaborative Innovation Center for Biomedicine (Guangxi-ASEAN Collaborative Innovation Center for Major Disease Prevention and Treatment), Guangxi Medical University, Nanning, Guangxi, China
| | - Yi Guo
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Jie Zheng
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Yonghua Jiang
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Department of Gynecology, The Second Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, Guangxi, China.,Life Sciences Institute, Guangxi Medical University, Nanning, Guangxi, China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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20
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Belfort MB, Wheeler SM, Burris HH. Health inequities start early in life, even before birth: Why race-specific fetal and neonatal growth references disadvantage Black infants. Semin Perinatol 2022; 46:151662. [PMID: 36180263 DOI: 10.1016/j.semperi.2022.151662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Clinicians and researchers use published standards to assess and classify the size and growth of the fetus and newborn infant. Fetal growth is slower on average in Black fetuses as compared with White fetuses, and existing standards differ in whether they are race-specific or not. Here, we apply a health equity lens to the topic of fetal and newborn growth assessment by critically appraising two widely available growth standards. We conclude that using race-based standards is not well-justified and could perpetuate or even worsen inequities in perinatal health outcomes. We therefore recommend that neonatal and perinatal providers remove race from the assessment of fetal and newborn size.
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21
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Fernandez-Jimenez N, Fore R, Cilleros-Portet A, Lepeule J, Perron P, Kvist T, Tian FY, Lesseur C, Binder AM, Lozano M, Martorell-Marugán J, Loke YJ, Bakulski KM, Zhu Y, Forhan A, Sammallahti S, Everson TM, Chen J, Michels KB, Belmonte T, Carmona-Sáez P, Halliday J, Daniele Fallin M, LaSalle JM, Tost J, Czamara D, Fernández MF, Gómez-Martín A, Craig JM, Gonzalez-Alzaga B, Schmidt RJ, Dou JF, Muggli E, Lacasaña M, Vrijheid M, Marsit CJ, Karagas MR, Räikkönen K, Bouchard L, Heude B, Santa-Marina L, Bustamante M, Hivert MF, Bilbao JR. A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health. Commun Biol 2022; 5:1313. [PMID: 36446949 PMCID: PMC9709064 DOI: 10.1038/s42003-022-04267-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 11/16/2022] [Indexed: 12/05/2022] Open
Abstract
Higher maternal pre-pregnancy body mass index (ppBMI) is associated with increased neonatal morbidity, as well as with pregnancy complications and metabolic outcomes in offspring later in life. The placenta is a key organ in fetal development and has been proposed to act as a mediator between the mother and different health outcomes in children. The overall aim of the present work is to investigate the association of ppBMI with epigenome-wide placental DNA methylation (DNAm) in 10 studies from the PACE consortium, amounting to 2631 mother-child pairs. We identify 27 CpG sites at which we observe placental DNAm variations of up to 2.0% per 10 ppBMI-unit. The CpGs that are differentially methylated in placenta do not overlap with CpGs identified in previous studies in cord blood DNAm related to ppBMI. Many of the identified CpGs are located in open sea regions, are often close to obesity-related genes such as GPX1 and LGR4 and altogether, are enriched in cancer and oxidative stress pathways. Our findings suggest that placental DNAm could be one of the mechanisms by which maternal obesity is associated with metabolic health outcomes in newborns and children, although further studies will be needed in order to corroborate these findings.
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Affiliation(s)
- Nora Fernandez-Jimenez
- grid.11480.3c0000000121671098Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, Leioa, Basque Country Spain
| | - Ruby Fore
- grid.38142.3c000000041936754XDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA USA
| | - Ariadna Cilleros-Portet
- grid.11480.3c0000000121671098Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, Leioa, Basque Country Spain
| | - Johanna Lepeule
- grid.418110.d0000 0004 0642 0153University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, Grenoble, France
| | - Patrice Perron
- grid.411172.00000 0001 0081 2808Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC Canada
| | - Tuomas Kvist
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Fu-Ying Tian
- grid.189967.80000 0001 0941 6502Gangarosa Department of Environmental Health, Rollins School of Public Health at Emory University, Atlanta, GA USA
| | - Corina Lesseur
- grid.59734.3c0000 0001 0670 2351Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Alexandra M. Binder
- grid.410445.00000 0001 2188 0957Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI USA ,grid.19006.3e0000 0000 9632 6718Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA USA
| | - Manuel Lozano
- grid.5338.d0000 0001 2173 938XEpidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain ,grid.5338.d0000 0001 2173 938XPreventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain
| | - Jordi Martorell-Marugán
- grid.4489.10000000121678994Department of Statistics and Operations Research, University of Granada, Granada, Spain ,grid.4489.10000000121678994Bioinformatics Unit. GENYO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Granada, Spain
| | - Yuk J. Loke
- grid.1058.c0000 0000 9442 535XMurdoch Children’s Research Institute, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Paediatrics, University of Melbourne, Parkville, VIC Australia
| | - Kelly M. Bakulski
- grid.214458.e0000000086837370Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI USA
| | - Yihui Zhu
- grid.27860.3b0000 0004 1936 9684Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA USA
| | - Anne Forhan
- grid.508487.60000 0004 7885 7602Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | - Sara Sammallahti
- grid.5645.2000000040459992XDepartment of Child and Adolescent Psychiatry and Psychology, Erasmus MC Rotterdam, The Netherlands
| | - Todd M. Everson
- grid.189967.80000 0001 0941 6502Gangarosa Department of Environmental Health, Rollins School of Public Health at Emory University, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Epidemiology, Rollins School of Public health at Emory University, Atlanta, GA USA
| | - Jia Chen
- grid.59734.3c0000 0001 0670 2351Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Karin B. Michels
- grid.19006.3e0000 0000 9632 6718Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA USA ,grid.5963.9Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Thalia Belmonte
- grid.411342.10000 0004 1771 1175Health Research Institute of Asturias, ISPA and Biomedical Research and Innovation Institute of Cadiz (INiBICA), Research Unit, Puerta del Mar University Hospital, Cadiz, Spain
| | - Pedro Carmona-Sáez
- grid.4489.10000000121678994Department of Statistics and Operations Research, University of Granada, Granada, Spain ,grid.4489.10000000121678994Bioinformatics Unit. GENYO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Granada, Spain
| | - Jane Halliday
- grid.1058.c0000 0000 9442 535XMurdoch Children’s Research Institute, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Paediatrics, University of Melbourne, Parkville, VIC Australia
| | - M. Daniele Fallin
- grid.21107.350000 0001 2171 9311Wendy Klag Center for Autism and Developmental Disabilities, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD USA
| | - Janine M. LaSalle
- grid.27860.3b0000 0004 1936 9684Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA USA
| | - Jorg Tost
- grid.418135.a0000 0004 0641 3404Laboratory for Epigenetics & Environment, Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, Evry, France
| | - Darina Czamara
- grid.419548.50000 0000 9497 5095Max-Planck-Institute of Psychiatry, Department of Translational Research in Psychiatry, Munich, Germany
| | - Mariana F. Fernández
- grid.4489.10000000121678994University of Granada, Center for Biomedical Research (CIBM), Granada, Spain ,grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.466571.70000 0004 1756 6246CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Antonio Gómez-Martín
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.413740.50000 0001 2186 2871Andalusian School of Public Health (EASP), Granada, Spain
| | - Jeffrey M. Craig
- grid.1058.c0000 0000 9442 535XMurdoch Children’s Research Institute, Parkville, VIC Australia ,grid.1021.20000 0001 0526 7079Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Geelong, Australia
| | - Beatriz Gonzalez-Alzaga
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.413740.50000 0001 2186 2871Andalusian School of Public Health (EASP), Granada, Spain
| | - Rebecca J. Schmidt
- grid.27860.3b0000 0004 1936 9684Department of Public Health Sciences and the MIND Institute, University of California Davis School of Medicine, Davis, CA USA
| | - John F. Dou
- grid.214458.e0000000086837370Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI USA
| | - Evelyne Muggli
- grid.1058.c0000 0000 9442 535XMurdoch Children’s Research Institute, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Paediatrics, University of Melbourne, Parkville, VIC Australia
| | - Marina Lacasaña
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.466571.70000 0004 1756 6246CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain ,grid.413740.50000 0001 2186 2871Andalusian School of Public Health (EASP), Granada, Spain
| | - Martine Vrijheid
- grid.466571.70000 0004 1756 6246CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain ,grid.434607.20000 0004 1763 3517ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carmen J. Marsit
- grid.189967.80000 0001 0941 6502Gangarosa Department of Environmental Health, Rollins School of Public Health at Emory University, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Epidemiology, Rollins School of Public health at Emory University, Atlanta, GA USA
| | - Margaret R. Karagas
- grid.86715.3d0000 0000 9064 6198Department of Biochemistry and Functional Genomics, Universite de Sherbrooke, Sherbrooke, QC Canada
| | - Katri Räikkönen
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Luigi Bouchard
- grid.86715.3d0000 0000 9064 6198Department of Biochemistry and Functional Genomics, Universite de Sherbrooke, Sherbrooke, QC Canada ,grid.459278.50000 0004 4910 4652Department of Laboratory Medicine, CIUSSS du Saguenay–Lac-St-Jean – Hôpital Universitaire de Chicoutimi, Chicoutimi, QC Canada
| | - Barbara Heude
- grid.508487.60000 0004 7885 7602Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | - Loreto Santa-Marina
- grid.466571.70000 0004 1756 6246CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain ,grid.432380.eBiodonostia, Epidemiology and Public Health Area, Environmental Epidemiology and Child Development Group, 20014 San Sebastian, Basque Country Spain ,Health Department of Basque Government, Sub-directorate of Public Health of Gipuzkoa, San Sebastian, Basque Country Spain
| | - Mariona Bustamante
- grid.466571.70000 0004 1756 6246CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain ,grid.434607.20000 0004 1763 3517ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Marie-France Hivert
- grid.38142.3c000000041936754XDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA USA ,grid.411172.00000 0001 0081 2808Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC Canada ,grid.32224.350000 0004 0386 9924Diabetes Unit, Massachusetts General Hospital, Boston, MA USA
| | - Jose Ramon Bilbao
- grid.11480.3c0000000121671098Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, Leioa, Basque Country Spain ,grid.512890.7CIBER of diabetes and associated metabolic disorders (CIBERDEM), Madrid, Spain
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22
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Bajinka O, Barrow A, Mendy S, Jallow BJJ, Jallow J, Barrow S, Bah O, Camara S, Colley ML, Nyabally S, Joof AN, Qi M, Tan Y. The Influence of Parental Environmental Exposure and Nutrient Restriction on the Early Life of Offspring Growth in Gambia-A Pilot Study. Int J Environ Res Public Health 2022; 19:13045. [PMID: 36293620 PMCID: PMC9603272 DOI: 10.3390/ijerph192013045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND The role of the germline in epigenetic transgenerational inheritance starts with environmental factors, acting on the first generation of a gestating mother. These factors influence the developing second-generation fetus by altering gonadal development, thereby reprogramming the primordial germ cell DNA methylation and leading to consequences that might be seen along generations. OBJECTIVE Despite these epigenetic factors now surfacing, the few available studies are on animal-based experiments, and conducting a follow-up on human intergenerational trials might take decades. To this response, this study aimed to determine the influence of parental energy, toxicant exposure, age, and nutrient restriction on the early life of offspring growth in Gambia. METHOD This pilot study was based on population observation and combined both maternal and paternal factors across the country between August and October 2021. It captures the lifestyle and health detailed account of 339 reproductive parents and their last born (child under 5 years) using a structured interview questionnaire performed by nurses and public health officers. RESULTS This study showed that parents who worked in industrial areas were more likely to have offspring with poor psychosocial skills. In addition, mothers who are exposed to oxidative stress and high temperatures are more likely to have offspring with poor psychosocial skills. Mothers who consume a high-protein diet were almost three times more likely to have infants with good psychosocial skills in their offspring. Furthermore, there was a negative correlation between maternal stress during pregnancy and the psychosocial skills of offspring. CONCLUSION This study was able to ascertain if the maternal diet during gestation, toxicant exposure, maternal stress, and parental smoking habits have an influence on the early life of offspring. While the study recommends a large sample size study to eliminate selection bias, there should be an increased level of awareness of mothers of their offspring's health and their husbands' lifestyles that might influence the adulthood health of their offspring.
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Affiliation(s)
- Ousman Bajinka
- Department of Medical Microbiology, Central South University, Changsha 410078, China
- China-Africa Research Center of Infectious Diseases, School of Basic and Medical Sciences, Central South University, Changsha 410078, China
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Amadou Barrow
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Sang Mendy
- Ministry of Health, Banjul P.O. Box 273, The Gambia
| | - Binta J. J. Jallow
- Department of Medical Microbiology, Central South University, Changsha 410078, China
| | - Jarry Jallow
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Sulayman Barrow
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Ousman Bah
- Ministry of Health, Banjul P.O. Box 273, The Gambia
| | - Saikou Camara
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Modou Lamin Colley
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Sankung Nyabally
- School of Medicine and Allied Health Sciences, University of The Gambia, Kanifing 3530, The Gambia
| | - Amie N. Joof
- Department of Medical Microbiology, Central South University, Changsha 410078, China
| | - Mingming Qi
- Department of Obstetrics, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Changsha 410017, China
| | - Yurong Tan
- Department of Medical Microbiology, Central South University, Changsha 410078, China
- China-Africa Research Center of Infectious Diseases, School of Basic and Medical Sciences, Central South University, Changsha 410078, China
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23
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Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet 2022; 31:3377-3391. [PMID: 35220425 PMCID: PMC9523562 DOI: 10.1093/hmg/ddac050] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/09/2022] [Accepted: 02/23/2022] [Indexed: 11/12/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.
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Affiliation(s)
- Natalia Pervjakova
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Gunn-Helen Moen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Diamantina Institute, The University of Queensland, Woolloongabba QLD 4102, Australia
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Maria-Carolina Borges
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Teresa Ferreira
- Big Data Institute, Li Ka Shing Center for Health for Health Information and Discovery, Oxford University, Oxford, UK
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Universite de Sherbrooke, Quebec, Canada
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
| | - Gad Hatem
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund University Diabetes Centre, Malmö SE-20502, Sweden
| | - Anni Heiskala
- Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Anni Joensuu
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ville Karhunen
- Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Hospital, London, UK
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Frederick T J Lin
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jun Liu
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sheryl Rifas-Shiman
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Claudia H Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, The People's Republic of China
| | - Wing Hung Tam
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong SAR, The People's Republic of China
| | | | - Toby Andrew
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Juha Auvinen
- Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Bishwajit Bhowmik
- Centre of Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
| | - Amélie Bonnefond
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Fabien Delahaye
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
| | - Ayse Demirkan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Section of Statistical Multi-omics, Department of Clinical and Experimental Research, University of Surrey, Surrey, UK
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Kadri Haller-Kikkatalo
- Department of Immunology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Hildur Hardardottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Livio Reykjavik, Reykjavik, Iceland
| | - Sandra Hummel
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Forschergruppe Diabetes, Technical University Munich, at Klinikum rechts der Isar, Munich, Germany
| | - Akhtar Hussain
- Centre of Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
- Faculty of Health Sciences, Nord University, Bodø, Norway
| | - Eero Kajantie
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Elina Keikkala
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Amna Khamis
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille F-59000, France
- University of Lille, Lille University Hospital, Lille F-59000, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Tove Lekva
- Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway
| | - Sanna Mustaniemi
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Aili Tagoma
- Department of Immunology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Evangelia Tzala
- School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Hospital, London, UK
| | - Raivo Uibo
- Department of Immunology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Marja Vääräsmäki
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
| | - Pia M Villa
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Hyvinkää Hospital, Helsinki and Uusimaa Hospital District, Hyvinkää, Finland
| | - Kåre I Birkeland
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Universite de Sherbrooke, Quebec, Canada
- Department of Medical Biology, Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-St-Jean – Hôpital de Chicoutimi, Québec, Canada
| | - Cornelia M Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sarah Finer
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Leif Groop
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund University Diabetes Centre, Malmö SE-20502, Sweden
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Esa Hämäläinen
- Department of Clinical Chemistry, University of Eastern Finland, Kuopio, Finland
| | - Geoffrey M Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Department of Anthropology, Northwestern University, Evanston, IL 60208, USA
| | - Graham A Hitman
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Hak C Jang
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Marjo-Riitta Järvelin
- Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Hospital, London, UK
| | - Anne Karen Jenum
- General Practice Research Unit (AFE), Department of General Practice, Institute of Health and Society, Faculty of Medicine, University of Oslo, Post Box 1130 Blindern, Oslo 0318, Norway
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University, Hospital and Faculty of Medicine and Health Technology, Center for Child, Adolescent, and Maternal Health, Tampere University, Tampere, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Ronald C Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, The People's Republic of China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, The People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, The People's Republic of China
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund University Diabetes Centre, Malmö SE-20502, Sweden
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - Patrice Perron
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Universite de Sherbrooke, Quebec, Canada
- Department of Medicine, Faculty of Medicine and Health Sciences, University of Sherbrook, Québec, Canada
| | - Rashmi B Prasad
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund University Diabetes Centre, Malmö SE-20502, Sweden
| | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Sylvain Sebert
- Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund University Diabetes Centre, Malmö SE-20502, Sweden
- Department of Endocrinology, Abdominal Centre, Helsinki University Hospital, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Medicine, Faculty of Medicine and Health Sciences, University of Sherbrook, Québec, Canada
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Center for Health for Health Information and Discovery, Oxford University, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical and Population Genetics, Broad Institute, Boston, MA, USA
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Deborah A Lawlor
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
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24
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Liu Y, Jin C, Ni LF, Zheng T, Liu XC, Wang SS, Huang HJ, Jin MM, Cheng BW, Yan HT, Yang XJ. Educational attainment and offspring birth weight: A bidirectional Mendelian randomization study. Front Genet 2022; 13:922382. [PMID: 36437958 PMCID: PMC9682907 DOI: 10.3389/fgene.2022.922382] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 07/19/2022] [Indexed: 09/03/2023] Open
Abstract
Background: The association between educational attainment (EA) and offspring birth weight (BW) has been reported by several traditional epidemiological studies. However, evidence for this association tends to be mixed and confounded. This study aimed to investigate the causal association between EA of parents and offspring BW. Methods: Here, we carried out a two-sample bidirectional Mendelian randomization (MR) analysis to examine the causal association between EA of males (n = 131,695) and females (n = 162,028) and offspring BW using genetic instruments. Summary statistics of EA associated single nucleotide polymorphisms (SNPs) were extracted from a GWAS incorporating 293,723 individuals of European descent performed by the Social Science Genetic Association Consortium (SSGAC), and the effects of these SNPs on offspring BW were estimated using a GWAS meta-analysis of 86,577 participants of European descent from 25 studies. Univariable MR analyses were conducted using the inverse-variance weighted (IVW) method and four other methods. Further sensitivity analyses were carried out to test the viability of the results. Multivariable MR was used to examine the confounders between the exposure and outcome. Results: The result shows evidence that the offspring BW is positively causally affected by female EA. Each one standard deviation (SD) increase in female EA was associated with 0.24 SD higher of offspring BW (95% confidence interval [CI], 0.10 to 0.37, p < 0.001 for the IVW method). Similarly, change in offspring BW was 0.21 SD (95% CI: 0.07 to 0.34, p = 2.82 × 10-3) per one SD higher in male EA. No causal effect of BW on EA was found by any of the five methods. The causal association between female EA and offspring BW maintained after adjusting for alcoholic drinks per week and BMI. The effect of male EA on offspring BW was attenuated when we adjusted for BMI and alcoholic drinks per week using multivariable MR analysis. Conclusion: Our study indicated that female EA is positively causally associated with offspring BW. The association between male EA and offspring BW may be confounded by alcoholic drinks per week and BMI.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Xin-Jun Yang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
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Yang Q, Borges MC, Sanderson E, Magnus MC, Kilpi F, Collings PJ, Soares AL, West J, Magnus P, Wright J, Håberg SE, Tilling K, Lawlor DA. Associations between insomnia and pregnancy and perinatal outcomes: Evidence from mendelian randomization and multivariable regression analyses. PLoS Med 2022; 19:e1004090. [PMID: 36067251 PMCID: PMC9488815 DOI: 10.1371/journal.pmed.1004090] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 09/20/2022] [Accepted: 08/15/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Insomnia is common and associated with adverse pregnancy and perinatal outcomes in observational studies. However, those associations could be vulnerable to residual confounding or reverse causality. Our aim was to estimate the association of insomnia with stillbirth, miscarriage, gestational diabetes (GD), hypertensive disorders of pregnancy (HDP), perinatal depression, preterm birth (PTB), and low/high offspring birthweight (LBW/HBW). METHODS AND FINDINGS We used 2-sample mendelian randomization (MR) with 81 single-nucleotide polymorphisms (SNPs) instrumenting for a lifelong predisposition to insomnia. Our outcomes included ever experiencing stillbirth, ever experiencing miscarriage, GD, HDP, perinatal depression, PTB (gestational age <37 completed weeks), LBW (<2,500 grams), and HBW (>4,500 grams). We used data from women of European descent (N = 356,069, mean ages at delivery 25.5 to 30.0 years) from UK Biobank (UKB), FinnGen, Avon Longitudinal Study of Parents and Children (ALSPAC), Born in Bradford (BiB), and the Norwegian Mother, Father and Child Cohort (MoBa). Main MR analyses used inverse variance weighting (IVW), with weighted median and MR-Egger as sensitivity analyses. We compared MR estimates with multivariable regression of insomnia in pregnancy on outcomes in ALSPAC (N = 11,745). IVW showed evidence of an association of genetic susceptibility to insomnia with miscarriage (odds ratio (OR): 1.60, 95% confidence interval (CI): 1.18, 2.17, p = 0.002), perinatal depression (OR 3.56, 95% CI: 1.49, 8.54, p = 0.004), and LBW (OR 3.17, 95% CI: 1.69, 5.96, p < 0.001). IVW results did not support associations of insomnia with stillbirth, GD, HDP, PTB, and HBW, with wide CIs including the null. Associations of genetic susceptibility to insomnia with miscarriage, perinatal depression, and LBW were not observed in weighted median or MR-Egger analyses. Results from these sensitivity analyses were directionally consistent with IVW results for all outcomes, with the exception of GD, perinatal depression, and PTB in MR-Egger. Multivariable regression showed associations of insomnia at 18 weeks of gestation with perinatal depression (OR 2.96, 95% CI: 2.42, 3.63, p < 0.001), but not with LBW (OR 0.92, 95% CI: 0.69, 1.24, p = 0.60). Multivariable regression with miscarriage and stillbirth was not possible due to small numbers in index pregnancies. Key limitations are potential horizontal pleiotropy (particularly for perinatal depression) and low statistical power in MR, and residual confounding in multivariable regression. CONCLUSIONS In this study, we observed some evidence in support of a possible causal relationship between genetically predicted insomnia and miscarriage, perinatal depression, and LBW. Our study also found observational evidence in support of an association between insomnia in pregnancy and perinatal depression, with no clear multivariable evidence of an association with LBW. Our findings highlight the importance of healthy sleep in women of reproductive age, though replication in larger studies, including with genetic instruments specific to insomnia in pregnancy are important.
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Affiliation(s)
- Qian Yang
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Maria C. Magnus
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Fanny Kilpi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Paul J. Collings
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Ana Luiza Soares
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Jane West
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Siri E. Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and 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, United Kingdom
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom
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Silva LR, Melo AS, Salomão KB, Mazin SC, Tone LG, Cardoso VC, Dos Reis RM, Furtado CLM, Ferriani RA. MIR146A and ADIPOQ genetic variants are associated with birth weight in relation to gestational age: a cohort study. J Assist Reprod Genet 2022; 39:1873-86. [PMID: 35689735 DOI: 10.1007/s10815-022-02532-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 06/01/2022] [Indexed: 01/19/2023] Open
Abstract
PURPOSE To evaluate the genetic variants related to polycystic ovary syndrome (PCOS) and its metabolic complications in girls born small for gestational age (SGA). DESIGN Retrospective birth cohort study. MATERIALS AND METHODS We evaluated 66 women of reproductive age born at term (37-42 weeks of gestational age) according to the birth weight in relation to gestational age: 26 SGA and 40 AGA (Adequate for gestational age). Anthropometric and biochemical characteristics were measured, as well as the PCOS prevalence. We analyzed 48 single nucleotide polymorphisms (SNPs) previously associated with PCOS and its comorbidities using TaqMan Low-Density Array (TLDA). miRNet and STRING databases were used to predict target and disease networks. RESULTS Anthropometric and biochemical characteristics did not differ between the SGA and AGA groups, as well as insulin resistance and PCOS prevalence. Two SNPs were not in Hardy-Weinberg equilibrium, the rs2910164 (MIR146A C > G) and rs182052 (ADIPOQ G > A). The rs2910164 minor allele frequency (MAF) was increased in SGA (OR, 2.77; 95%; CI, 1.22-6.29), while the rs182052 was increased AGA (OR, 0.34; 95%; CI, 0.13 - 0.88). The alleles related to reduced miRNA-146a (C) and ADIPOQ (A) activity showed increased frequency in SGA. The mature miR-146a targets 319 genes, been the CXCR4, TMEM167A and IF144L common targets and contributes to PCOS. The ADIPOQ main protein interactions were ERP44, PPARGCIA and CDH13. CONCLUSIONS The miR-146a (rs2910164) and ADIPOQ (rs182052) allelic variants are related to birth weight in SGA and may predict health-related outcomes, such as PCOS and obesity risk.
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Hwang LD, Moen GH, Evans DM. Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes. eLife 2022; 11:73671. [PMID: 35822614 PMCID: PMC9323003 DOI: 10.7554/elife.73671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We assume that in biological families, offspring phenotypes are influenced prenatally by their mother's genotype and postnatally by both parents' genotypes, whereas adopted individuals' phenotypes are influenced prenatally by their biological mother's genotype and postnatally by their adoptive parents' genotypes. Our SEM framework allows us to model the (potentially) unobserved genotypes of biological and adoptive parents as latent variables, permitting us in principle to leverage the thousands of adopted singleton individuals in the UK Biobank. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.
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Barry CJS, Lawlor DA, Shapland CY, Sanderson E, Borges MC. Using Mendelian Randomisation to Prioritise Candidate Maternal Metabolic Traits Influencing Offspring Birthweight. Metabolites 2022; 12:537. [PMID: 35736469 PMCID: PMC9231269 DOI: 10.3390/metabo12060537] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/27/2022] Open
Abstract
Marked physiological changes in pregnancy are essential to support foetal growth; however, evidence on the role of specific maternal metabolic traits from human studies is limited. We integrated Mendelian randomisation (MR) and metabolomics data to probe the effect of 46 maternal metabolic traits on offspring birthweight (N = 210,267). We implemented univariable two-sample MR (UVMR) to identify candidate metabolic traits affecting offspring birthweight. We then applied two-sample multivariable MR (MVMR) to jointly estimate the potential direct causal effect for each candidate maternal metabolic trait. In the main analyses, UVMR indicated that higher maternal glucose was related to higher offspring birthweight (0.328 SD difference in mean birthweight per 1 SD difference in glucose (95% CI: 0.104, 0.414)), as were maternal glutamine (0.089 (95% CI: 0.033, 0.144)) and alanine (0.137 (95% CI: 0.036, 0.239)). In additional analyses, UVMR estimates were broadly consistent when selecting instruments from an independent data source, albeit imprecise for glutamine and alanine, and were attenuated for alanine when using other UVMR methods. MVMR results supported independent effects of these metabolites, with effect estimates consistent with those seen with the UVMR results. Among the remaining 43 metabolic traits, UVMR estimates indicated a null effect for most lipid-related traits and a high degree of uncertainty for other amino acids and ketone bodies. Our findings suggest that maternal gestational glucose and glutamine are causally related to offspring birthweight.
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Affiliation(s)
- Ciarrah-Jane Shannon Barry
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Deborah A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
- NIHR Bristol Biomedical Research Centre, Bristol BS8 2BN, UK
| | - Chin Yang Shapland
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (D.A.L.); (C.Y.S.); (E.S.); (M.C.B.)
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
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Tekola-Ayele F, Zeng X, Chatterjee S, Ouidir M, Lesseur C, Hao K, Chen J, Tesfaye M, Marsit CJ, Workalemahu T, Wapner R. Placental multi-omics integration identifies candidate functional genes for birthweight. Nat Commun 2022; 13:2384. [PMID: 35501330 PMCID: PMC9061712 DOI: 10.1038/s41467-022-30007-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 04/11/2022] [Indexed: 12/27/2022] Open
Abstract
Abnormal birthweight is associated with increased risk for cardiometabolic diseases in later life. Although the placenta is critical to fetal development and later life health, it has not been integrated into largescale functional genomics initiatives, and mechanisms of birthweight-associated variants identified by genome wide association studies (GWAS) are unclear. The goal of this study is to provide functional mechanistic insight into the causal pathway from a genetic variant to birthweight by integrating placental methylation and gene expression with established GWAS loci for birthweight. We identify placental DNA methylation and gene expression targets for several birthweight GWAS loci. The target genes are broadly enriched in cardiometabolic, immune response, and hormonal pathways. We find that methylation causally influences WNT3A, CTDNEP1, and RANBP2 expression in placenta. Multi-trait colocalization identifies PLEKHA1, FES, CTDNEP1, and PRMT7 as likely functional effector genes. These findings reveal candidate functional pathways that underpin the genetic regulation of birthweight via placental epigenetic and transcriptomic mechanisms. Clinical trial registration; ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Fasil Tekola-Ayele
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
| | - Xuehuo Zeng
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Suvo Chatterjee
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Marion Ouidir
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Corina Lesseur
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Markos Tesfaye
- Section of Sensory Science and Metabolism (SenSMet), National Institute on Alcohol Abuse and Alcoholism & National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, USA
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Rollins School of Public Health of Emory University, Atlanta, GA, USA
| | - Tsegaselassie Workalemahu
- Department of Obstetrics and Gynecology, Maternal-Fetal Medicine, University of Utah, Salt Lake City, UT, USA
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
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Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CHD, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations With Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes 2022; 71:821-836. [PMID: 35061033 PMCID: PMC7612532 DOI: 10.2337/db21-0479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 01/11/2022] [Indexed: 11/13/2022]
Abstract
Size at birth is known to be influenced by various fetal and maternal factors, including genetic effects. South Asians have a high burden of low birth weight and cardiometabolic diseases, yet studies of common genetic variations underpinning these phenotypes are lacking. We generated independent, weighted fetal genetic scores (fGSs) and maternal genetic scores (mGSs) from 196 birth weight-associated variants identified in Europeans and conducted an association analysis with various fetal birth parameters and anthropometric and cardiometabolic traits measured at different follow-up stages (5-6-year intervals) from seven Indian and Bangladeshi cohorts of South Asian ancestry. The results from these cohorts were compared with South Asians in UK Biobank and the Exeter Family Study of Childhood Health, a European ancestry cohort. Birth weight increased by 50.7 g and 33.6 g per SD of fGS (P = 9.1 × 10-11) and mGS (P = 0.003), respectively, in South Asians. A relatively weaker mGS effect compared with Europeans indicates possible different intrauterine exposures between Europeans and South Asians. Birth weight was strongly associated with body size in both childhood and adolescence (P = 3 × 10-5 to 1.9 × 10-51); however, fGS was associated with body size in childhood only (P < 0.01) and with head circumference, fasting glucose, and triglycerides in adults (P < 0.01). The substantially smaller newborn size in South Asians with comparable fetal genetic effect to Europeans on birth weight suggests a significant role of factors related to fetal growth that were not captured by the present genetic scores. These factors may include different environmental exposures, maternal body size, health and nutritional status, etc. Persistent influence of genetic loci on size at birth and adult metabolic syndrome in our study supports a common genetic mechanism that partly explains associations between early development and later cardiometabolic health in various populations, despite marked differences in phenotypic and environmental factors in South Asians.
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Affiliation(s)
- Suraj S Nongmaithem
- Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
- Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Akshay Dedaniya
- Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Babatunji-William Ogunkolade
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Zahid Hassan
- Dept of Physiology and Molecular Biology, Bangladesh University of Health Sciences, Dhaka, Bangladesh
| | | | - Kalyanaraman Kumaran
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | | | | | - Murali Krishna
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India
- Foundation for Research and Advocacy in Mental Health (FRAMe) Mysore. India
| | - Chiara Di Gravio
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Inder D Mali
- Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Alagu Sankareswaran
- Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Akhtar Hussain
- Centre of Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
- Faculty of Health Sciences, Nord University, Norway
| | - Biswajit W Bhowmik
- Centre of Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
| | - Abdul Kalam A Khan
- Centre of Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
| | - Bridget A Knight
- NIHR Exeter Clinical Research Facility, University of Exeter, Exeter, UK
- RD&E NHS Foundation Trust, Royal Devon & Exeter Hospital, Exeter, UK
| | - Timothy M Frayling
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Sarah Finer
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Institute of Population Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Caroline HD Fall
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | | | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Graham A Hitman
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Giriraj R Chandak
- Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
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Chatterjee S, Zeng X, Ouidir M, Tesfaye M, Zhang C, Tekola-Ayele F. Sex-specific placental gene expression signatures of small for gestational age at birth. Placenta 2022; 121:82-90. [PMID: 35303517 PMCID: PMC9010378 DOI: 10.1016/j.placenta.2022.03.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 02/14/2022] [Accepted: 03/03/2022] [Indexed: 10/18/2022]
Abstract
INTRODUCTION Small for gestational age at birth (SGA), often a consequence of placental dysfunction, is a risk factor for neonatal morbidity and later life cardiometabolic diseases. There are sex differences in placental gene expression and fetal growth. Here, we investigated sex-specific associations between gene expression in human placenta measured using RNA sequencing and SGA status using data from ethnic diverse pregnant women in the NICHD Fetal Growth Studies cohort (n = 74). METHODS Gene expression measures were obtained using RNA-Sequencing and differential gene expression between SGA (birthweight <10th percentile) and appropriate for gestational age (AGA: ≥10th and <90th percentile) was tested separately in males (12 SGA and 27 AGA) and females (9 SGA and 26 AGA) using a weighted mean of log ratios method with adjustment for mode of delivery and ethnicity. RESULTS At 5% false discovery rate (FDR), we identified 40 differentially expressed genes (DEGs) related to SGA status among males (95% up- and 5% down-regulated) and 314 DEGs among females (32.5% up- and 67.5% down-regulated). Seven female-specific DEGs overlapped with known imprinted genes (AXL, CYP24A1, GPR1, PLAGL1, CMTM1, DLX5, LY6D). The DEGs in males were significantly enriched for immune response and inflammation signaling pathways whereas the DEGs in females were enriched for organ development signaling pathways (FDR<0.05). Sex-combined analysis identified no additional DEGs, rather 98% of the sex-specific DEGs were no longer significant and the remaining 2% were attenuated. DISCUSSION This study revealed sex-specific human placental gene expression changes and molecular pathways associated with SGA and underscored that unravelling the pathogenesis of SGA warrants consideration of fetal sex as a biological variable. TRIAL REGISTRATION https://www. CLINICALTRIALS gov, Unique identifier: NCT00912132.
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Affiliation(s)
- Suvo Chatterjee
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Xuehuo Zeng
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Marion Ouidir
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Markos Tesfaye
- Section of Sensory Science and Metabolism (SenSMet), National Institute on Alcohol Abuse and Alcoholism & National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, 20814, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA.
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Ouidir M, Zeng X, Chatterjee S, Zhang C, Tekola-Ayele F. Ancestry-Matched and Cross-Ancestry Genetic Risk Scores of Type 2 Diabetes in Pregnant Women and Fetal Growth: A Study in an Ancestrally Diverse Cohort. Diabetes 2022; 71:340-349. [PMID: 34789498 PMCID: PMC8914278 DOI: 10.2337/db21-0655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/11/2021] [Indexed: 02/03/2023]
Abstract
Maternal genetic variants associated with offspring birth weight and adult type 2 diabetes (T2D) risk loci show some overlap. Whether T2D genetic risk influences longitudinal fetal weight and the gestational timing when these relationships begin is unknown. We investigated the associations of T2D genetic risk scores (GRS) with longitudinal fetal weight and birth weight among 1,513 pregnant women from four ancestral groups. Women had up to five ultrasonography examinations. Ancestry-matched GRS were constructed separately using 380 European- (GRSeur), 104 African- (GRSafr), and 189 East Asian- (GRSeas) related T2D loci discovered in different population groups. Among European Americans, the highest quartile GRSeur was significantly associated with 53.8 g higher fetal weight (95% CI 19.2-88.5) over the pregnancy. The associations began at gestational week 24 and continued through week 40, with a 106.8 g (95% CI 6.5-207.1) increase in birth weight. The findings were similar in analysis further adjusted for maternal glucose challenge test results. No consistent association was found using ancestry-matched or cross-ancestry GRS in non-Europeans. In conclusion, T2D genetic susceptibility may influence fetal growth starting at midsecond trimester among Europeans. Absence of similar associations in non-Europeans urges the need for further genetic T2D studies in diverse ancestries.
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Mennen R, Hallmark N, Pallardy M, Bars R, Tinwell H, Piersma A. Genome-wide expression screening in the cardiac embryonic stem cell test shows additional differentiation routes that are regulated by morpholines and piperidines. Curr Res Toxicol 2022; 3:100086. [PMID: 36157598 PMCID: PMC9489494 DOI: 10.1016/j.crtox.2022.100086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/08/2022] [Accepted: 09/08/2022] [Indexed: 11/29/2022] Open
Abstract
The cardiac embryonic stem cell test showed additional differentiation routes. Morpholines and piperidines regulated the alternative differentiation routes. The gene expression levels help in understanding the applicability domain.
The cardiac embryonic stem cell test (ESTc) is a well-studied non-animal alternative test method based on cardiac cell differentiation inhibition as a measure for developmental toxicity of tested chemicals. In the ESTc, a heterogenic cell population is generated besides cardiomyocytes. Using the full biological domain of ESTc may improve the sensitivity of the test system, possibly broadening the range of chemicals for which developmental effects can be detected in the test. In order to improve our knowledge of the biological and chemical applicability domains of the ESTc, we applied a hypothesis-generating data-driven approach on control samples as follows. A genome-wide expression screening was performed, using Next Generation Sequencing (NGS), to map the range of developmental pathways in the ESTc and to search for a predictive embryotoxicity biomarker profile, instead of the conventional read-out of beating cardiomyocytes. The detected developmental pathways included circulatory system development, skeletal system development, heart development, muscle and organ tissue development, and nervous system and cell development. Two pesticidal chemical classes, the morpholines and piperidines, were assessed for perturbation of differentiation in the ESTc using NGS. In addition to the anticipated impact on cardiomyocyte differentiation, the other developmental pathways were also regulated, in a concentration–response fashion. Despite the structural differences between the morpholine and piperidine pairs, their gene expression effect patterns were largely comparable. In addition, some chemical-specific gene regulation was also observed, which may help with future mechanistic understanding of specific effects with individual test compounds. These similar and unique regulations of gene expression profiles by the test compounds, adds to our knowledge of the chemical applicability domain, specificity and sensitivity of the ESTc. Knowledge of both the biological and chemical applicability domain contributes to the optimal placement of ESTc in test batteries and in Integrated Approaches to Testing and Assessment (IATA).
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Affiliation(s)
- R.H. Mennen
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Corresponding author at: National Institute for Public Health and Environment (RIVM), Centre for Health Protection (GZB), Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands.
| | - N. Hallmark
- Bayer AG Crop Science Division, Monheim, Germany
| | - M. Pallardy
- Inflammation, Microbiome and Immunosurveillance, Université Paris-Saclay, INSERM UMR996, Châtenay-Malabry 92296, France
| | - R. Bars
- Bayer Crop Science, Sophia-Antipolis, France
| | - H. Tinwell
- Bayer Crop Science, Sophia-Antipolis, France
| | - A.H. Piersma
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, the Netherlands
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Workalemahu T, Rahman ML, Ouidir M, Wu J, Zhang C, Tekola-Ayele F. Associations of maternal blood pressure-raising polygenic risk scores with fetal weight. J Hum Hypertens 2022; 36:69-76. [PMID: 33536548 PMCID: PMC8329099 DOI: 10.1038/s41371-021-00483-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 12/12/2020] [Accepted: 01/13/2021] [Indexed: 01/31/2023]
Abstract
Maternal blood pressure (BP) is associated with variations in fetal weight, an important determinant of neonatal and adult health. However, the association of BP-raising genetic risk with fetal weight is unknown. We tested the associations of maternal BP-raising polygenic risk scores (PRS) with estimated fetal weights (EFWs) at 13, 20, 27, and 40 weeks of gestation. This study included 622 White, 637 Black, 568 Hispanic, and 238 Asian pregnant women with genotype data from the NICHD Fetal Growth Studies. PRS of systolic (SBP) and diastolic BP (DBP) were calculated for each participant based on summary statistics from a recent genome-wide association study. Linear regression models were used to compare mean EFW differences between the highest versus lowest tertile of PRS, adjusting for maternal age, education, parity, genetic principal components and fetal sex. Hispanics in the highest DBP PRS tertile, compared to those in the lowest, had 8.1 g (95% CI: -15.1, -1.1), 32.4 g (-58.4, -6.4) and 119.4 g (-218.1, -20.7) lower EFW at 20, 27 and 40 weeks, respectively. Similarly, Asians in the highest DBP PRS tertile had 137.2 g (-263.5, -10.8) lower EFW at week 40, and those in the highest tertile of SBP PRS had 3.2 g (-5.8, -0.7), 12.9 g (-23.5, -2.4), and 39.8 g (-76.9, -2.7) lower EFWs at 13, 20, and 27 weeks. The findings showed that pregnant women's genetic susceptibility to high BP contributes to reduced fetal growth, suggesting a potential future clinical application in perinatal health.
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Affiliation(s)
- Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Mohammad L. Rahman
- Harvard Medical School, Department of Population Medicine and Harvard Pilgrim Healthcare Institute, Boston, MA, USA
| | - Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Jing Wu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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Nikolaev G, Robeva R, Konakchieva R. Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease. Int J Mol Sci 2021; 23:ijms23010471. [PMID: 35008896 PMCID: PMC8745360 DOI: 10.3390/ijms23010471] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 02/07/2023] Open
Abstract
The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.
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Affiliation(s)
- Georgi Nikolaev
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
- Correspondence:
| | - Ralitsa Robeva
- Department of Endocrinology, Faculty of Medicine, Medical University, 1431 Sofia, Bulgaria;
| | - Rossitza Konakchieva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
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Abstract
The antecedents of asthma and chronic obstructive pulmonary disease (COPD) lie before school age. Adverse effects are transgenerational, antenatal and in the preschool years. Antenatal adverse effects impair spirometry by causing low birth weight, altered lung structure and immune function, and sensitizing the foetus to later insults. The key stages of normal lung health are lung function at birth, lung growth to a plateau age 20-25 years, and the phase of decline thereafter; contrary to perceived wisdom, accelerated decline is not related to smoking. There are different trajectories of lung function. Lung function usually tracks from preschool to late middle age. Asthma is driven by antenatal and early life influences. The airflow obstruction, emphysema and multi-morbidity of COPD all start early. Failure to reach a normal plateau and accelerated decline in lung function are risk factors for COPD. Airway disease cannot be prevented in adult life; prevention must start early.
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Affiliation(s)
- Andrew Bush
- Paediatrics and Paediatric Respirology, Imperial College, UK; Imperial Centre for Paediatrics and Child Health, UK; Consultant Paediatric Chest Physician, Royal Brompton Harefield NHS Foundation Trust, UK.
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Thompson WD, Beaumont RN, Kuang A, Warrington NM, Ji Y, Tyrrell J, Wood AR, Scholtens DM, Knight BA, Evans DM, Lowe WL, Santorelli G, Azad R, Mason D, Hattersley AT, Frayling TM, Yaghootkar H, Borges MC, Lawlor DA, Freathy RM. Higher maternal adiposity reduces offspring birthweight if associated with a metabolically favourable profile. Diabetologia 2021; 64:2790-2802. [PMID: 34542646 PMCID: PMC8563674 DOI: 10.1007/s00125-021-05570-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 07/14/2021] [Indexed: 11/30/2022]
Abstract
AIMS/HYPOTHESIS Higher maternal BMI during pregnancy is associated with higher offspring birthweight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity, coupled with a favourable metabolic profile, in a Mendelian randomisation (MR) study comparing the effect of maternal 'metabolically favourable adiposity' on offspring birthweight with the effect of maternal general adiposity (as indexed by BMI). METHODS To test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birthweight, we performed two-sample MR. We used variants identified in large, published genetic-association studies as being associated with either higher adiposity and a favourable metabolic profile, or higher BMI (n = 442,278 and n = 322,154 for metabolically favourable adiposity and BMI, respectively). We then extracted data on the metabolically favourable adiposity and BMI variants from a large, published genetic-association study of maternal genotype and offspring birthweight controlling for fetal genetic effects (n = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total n = 9323 mother-child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birthweight and cord-blood biomarkers. RESULTS Higher maternal adiposity with a favourable metabolic profile was associated with lower offspring birthweight (-94 [95% CI -150, -38] g per 1 SD [6.5%] higher maternal metabolically favourable adiposity, p = 0.001). By contrast, higher maternal BMI was associated with higher offspring birthweight (35 [95% CI 16, 53] g per 1 SD [4 kg/m2] higher maternal BMI, p = 0.0002). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures; their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that a higher maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels while a higher maternal BMI increases them. The effects on neonatal anthropometric traits were consistent with the overall effect on birthweight but the smaller sample sizes for these analyses meant that the effects were imprecisely estimated. We also found evidence to suggest that higher maternal metabolically favourable adiposity decreases cord-blood leptin while higher maternal BMI increases it. CONCLUSIONS/INTERPRETATION Our results show that higher adiposity in mothers does not necessarily lead to higher offspring birthweight. Higher maternal adiposity can lead to lower offspring birthweight if accompanied by a favourable metabolic profile. DATA AVAILABILITY The data for the genome-wide association studies (GWAS) of BMI are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files . The data for the GWAS of body fat percentage are available at https://walker05.u.hpc.mssm.edu .
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Affiliation(s)
- William D Thompson
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Alan Kuang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nicole M Warrington
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Yingjie Ji
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jessica Tyrrell
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Denise M Scholtens
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Bridget A Knight
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - David M Evans
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Gillian Santorelli
- Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Rafaq Azad
- Department of Biochemistry, Bradford Royal Infirmary, Bradford, UK
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Timothy M Frayling
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Hanieh Yaghootkar
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
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Sato N, Fudono A, Imai C, Takimoto H, Tarui I, Aoyama T, Yago S, Okamitsu M, Mizutani S, Miyasaka N. Placenta mediates the effect of maternal hypertension polygenic score on offspring birth weight: a study of birth cohort with fetal growth velocity data. BMC Med 2021; 19:260. [PMID: 34732167 PMCID: PMC8567693 DOI: 10.1186/s12916-021-02131-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 09/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Low birth weight (LBW) and fetal growth restriction are associated with the development of cardio-metabolic diseases later in life. A recent Mendelian randomization study concluded that the susceptibility of LBW infants to develop hypertension during adulthood is due to the inheritance of hypertension genes from the mother and not to an unfavorable intrauterine environment. Therein, a negative linear association has been assumed between genetically estimated maternal blood pressure (BP) and birth weight, while the observed relationship between maternal BP and birth weight is substantially different from that assumption. As many hypertension genes are likely involved in vasculature development and function, we hypothesized that BP-increasing genetic variants could affect birth weight by reducing the growth of the placenta, a highly vascular organ, without overtly elevating the maternal BP. METHODS Using a birth cohort in the Japanese population possessing time-series fetal growth velocity data as a target and a GWAS summary statistics of BioBank Japan as a base data, we performed polygenic score (PGS) analyses for systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure. A causal mediation analysis was performed to assess the meditation effect of placental weight on birth weight reduced by maternal BP-increasing PGS. Maternal genetic risk score constituted of only "vasculature-related" BP single nucleotide polymorphisms (SNPs) was constructed to examine the involvement of vascular genes in the mediation effect of placental weight. We identified gestational week in which maternal SBP-increasing PGS significantly decreased fetal growth velocity. RESULTS We observed that maternal SBP-increasing PGS was negatively associated with offspring birth weight. A causal mediation analysis revealed that a large proportion of the total maternal PGS effect on birth weight was mediated by placental weight. The placental mediation effect was remarkable when genetic risk score was constituted of "vasculature-related" BP SNPs. The inverse association between maternal SBP PGS and fetal growth velocity only became apparent in late gestation. CONCLUSIONS Our study suggests that maternal hypertension genes are strongly associated with placental growth and that fetal growth inhibition is induced through the intrauterine environment established by the placenta.
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Affiliation(s)
- Noriko Sato
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University (TMDU), 1-5-45, Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan. .,Institute of Advanced Biomedical Engineering and Science, The Public Health Research Foundation, Tokyo, Japan.
| | - Ayako Fudono
- Comprehensive Reproductive Medicine, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Chihiro Imai
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University (TMDU), 1-5-45, Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Hidemi Takimoto
- Department of Nutritional Epidemiology, National Institute of Health and Nutrition, Tokyo, Japan
| | - Iori Tarui
- Department of Nutritional Epidemiology, National Institute of Health and Nutrition, Tokyo, Japan
| | - Tomoko Aoyama
- Department of Nutritional Epidemiology, National Institute of Health and Nutrition, Tokyo, Japan
| | - Satoshi Yago
- Child and Family Nursing, Graduate School of Health Care Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Motoko Okamitsu
- Child and Family Nursing, Graduate School of Health Care Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Shuki Mizutani
- Institute of Advanced Biomedical Engineering and Science, The Public Health Research Foundation, Tokyo, Japan
| | - Naoyuki Miyasaka
- Comprehensive Reproductive Medicine, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
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Howe LJ, Battram T, Morris TT, Hartwig FP, Hemani G, Davies NM, Smith GD. Assortative mating and within-spouse pair comparisons. PLoS Genet 2021; 17:e1009883. [PMID: 34735433 PMCID: PMC8594845 DOI: 10.1371/journal.pgen.1009883] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 11/16/2021] [Accepted: 10/15/2021] [Indexed: 12/20/2022] Open
Abstract
Spousal comparisons have been proposed as a design that can both reduce confounding and estimate effects of the shared adulthood environment. However, assortative mating, the process by which individuals select phenotypically (dis)similar mates, could distort associations when comparing spouses. We evaluated the use of spousal comparisons, as in the within-spouse pair (WSP) model, for aetiological research such as genetic association studies. We demonstrated that the WSP model can reduce confounding but may be susceptible to collider bias arising from conditioning on assorted spouse pairs. Analyses using UK Biobank spouse pairs found that WSP genetic association estimates were smaller than estimates from random pairs for height, educational attainment, and BMI variants. Within-sibling pair estimates, robust to demographic and parental effects, were also smaller than random pair estimates for height and educational attainment, but not for BMI. WSP models, like other within-family models, may reduce confounding from demographic factors in genetic association estimates, and so could be useful for triangulating evidence across study designs to assess the robustness of findings. However, WSP estimates should be interpreted with caution due to potential collider bias.
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Affiliation(s)
- Laurence J. Howe
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Thomas Battram
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Tim T. Morris
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Fernando P. Hartwig
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Neil M. Davies
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Warrington NM, Hwang LD, Nivard MG, Evans DM. Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data. Nat Commun 2021; 12:5420. [PMID: 34521848 PMCID: PMC8440517 DOI: 10.1038/s41467-021-25723-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 08/26/2021] [Indexed: 01/12/2023] Open
Abstract
Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indirect genetic effects. Using data from the UK Biobank, we contrast point estimates and standard errors at individual loci compared to those obtained using individual level data. We show that Genomic structural equation modelling (SEM) outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We apply Genomic SEM to fertility data in the UK Biobank and partition the genetic effect into female and male fertility and a sibling specific effect. We identify a novel locus for fertility and genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We recommend Genomic SEM be used to partition genetic effects into direct and indirect components when using summary results from genome-wide association studies.
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Affiliation(s)
- Nicole M Warrington
- Institute for Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia.
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia.
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.
| | - Liang-Dar Hwang
- Institute for Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
| | - Michel G Nivard
- Department of Biological Psychology, Faculty of Behaviour and Movement Sciences, VU University, Amsterdam, The Netherlands
| | - David M Evans
- Institute for Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
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Golovchenko OV, Abramova MY, Ponomarenko IV, Churnosov MI. Locus rs833061 of the VEGF Gene in Pregnant Women with Preeclampsia Is Associated with Newborn Weight. RUSS J GENET+ 2021. [DOI: 10.1134/s1022795421090039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Ambati A, Hillary R, Leu-Semenescu S, Ollila HM, Lin L, During EH, Farber N, Rico TJ, Faraco J, Leary E, Goldstein-Piekarski AN, Huang YS, Han F, Sivan Y, Lecendreux M, Dodet P, Honda M, Gadoth N, Nevsimalova S, Pizza F, Kanbayashi T, Peraita-Adrados R, Leschziner GD, Hasan R, Canellas F, Kume K, Daniilidou M, Bourgin P, Rye D, Vicario JL, Hogl B, Hong SC, Plazzi G, Mayer G, Landtblom AM, Dauvilliers Y, Arnulf I, Mignot EJ. Kleine-Levin syndrome is associated with birth difficulties and genetic variants in the TRANK1 gene loci. Proc Natl Acad Sci U S A 2021; 118:e2005753118. [PMID: 33737391 DOI: 10.1073/pnas.2005753118] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Kleine-Levin syndrome (KLS) is a rare disorder characterized by severe episodic hypersomnia, with cognitive impairment accompanied by apathy or disinhibition. Pathophysiology is unknown, although imaging studies indicate decreased activity in hypothalamic/thalamic areas during episodes. Familial occurrence is increased, and risk is associated with reports of a difficult birth. We conducted a worldwide case-control genome-wide association study in 673 KLS cases collected over 14 y, and ethnically matched 15,341 control individuals. We found a strong genome-wide significant association (rs71947865, Odds Ratio [OR] = 1.48, P = 8.6 × 10-9) within the 3'region of TRANK1 gene locus, previously associated with bipolar disorder and schizophrenia. Strikingly, KLS cases with rs71947865 variant had significantly increased reports of a difficult birth. As perinatal outcomes have dramatically improved over the last 40 y, we further stratified our sample by birth years and found that recent cases had a significantly reduced rs71947865 association. While the rs71947865 association did not replicate in the entire follow-up sample of 171 KLS cases, rs71947865 was significantly associated with KLS in the subset follow-up sample of 59 KLS cases who reported birth difficulties (OR = 1.54, P = 0.01). Genetic liability of KLS as explained by polygenic risk scores was increased (pseudo R 2 = 0.15; P < 2.0 × 10-22 at P = 0.5 threshold) in the follow-up sample. Pathway analysis of genetic associations identified enrichment of circadian regulation pathway genes in KLS cases. Our results suggest links between KLS, circadian regulation, and bipolar disorder, and indicate that the TRANK1 polymorphisms in conjunction with reported birth difficulties may predispose to KLS.
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Everson TM, Vives-Usano M, Seyve E, Cardenas A, Lacasaña M, Craig JM, Lesseur C, Baker ER, Fernandez-Jimenez N, Heude B, Perron P, Gónzalez-Alzaga B, Halliday J, Deyssenroth MA, Karagas MR, Íñiguez C, Bouchard L, Carmona-Sáez P, Loke YJ, Hao K, Belmonte T, Charles MA, Martorell-Marugán J, Muggli E, Chen J, Fernández MF, Tost J, Gómez-Martín A, London SJ, Sunyer J, Marsit CJ, Lepeule J, Hivert MF, Bustamante M. Placental DNA methylation signatures of maternal smoking during pregnancy and potential impacts on fetal growth. Nat Commun 2021; 12:5095. [PMID: 34429407 PMCID: PMC8384884 DOI: 10.1038/s41467-021-24558-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 06/22/2021] [Indexed: 02/07/2023] Open
Abstract
Maternal smoking during pregnancy (MSDP) contributes to poor birth outcomes, in part through disrupted placental functions, which may be reflected in the placental epigenome. Here we present a meta-analysis of the associations between MSDP and placental DNA methylation (DNAm) and between DNAm and birth outcomes within the Pregnancy And Childhood Epigenetics (PACE) consortium (N = 1700, 344 with MSDP). We identify 443 CpGs that are associated with MSDP, of which 142 associated with birth outcomes, 40 associated with gene expression, and 13 CpGs are associated with all three. Only two CpGs have consistent associations from a prior meta-analysis of cord blood DNAm, demonstrating substantial tissue-specific responses to MSDP. The placental MSDP-associated CpGs are enriched for environmental response genes, growth-factor signaling, and inflammation, which play important roles in placental function. We demonstrate links between placental DNAm, MSDP and poor birth outcomes, which may better inform the mechanisms through which MSDP impacts placental function and fetal growth.
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Affiliation(s)
- Todd M Everson
- Gangarosa Department of Environmental Health, Rollins School of Public Health at Emory University, Atlanta, GA, USA.
| | - Marta Vives-Usano
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Emie Seyve
- University Grenoble Alpes, Inserm, CNRS, IAB, Grenoble, France
| | - Andres Cardenas
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Marina Lacasaña
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Andalusian School of Public Health, Granada, Spain
- Instituto de Investigación Biosantaria (ibs.GRANADA), Granada, Spain
| | - Jeffrey M Craig
- Epigenetics Group, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- IMPACT - the Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia
| | - Corina Lesseur
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Emily R Baker
- Department of Obstetrics & Gynecology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
| | - Nora Fernandez-Jimenez
- University of the Basque Country (UPV/EHU), Leioa, Spain
- Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain
- Public Health Division of Gipuzkoa, Basque Government, San Sebastian, Spain
| | - Barbara Heude
- Université de Paris, CRESS, INSERM, INRAE, Paris, France
| | - Patrice Perron
- Department of Medicine, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Beatriz Gónzalez-Alzaga
- Andalusian School of Public Health, Granada, Spain
- Instituto de Investigación Biosantaria (ibs.GRANADA), Granada, Spain
| | - Jane Halliday
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Reproductive Epidemiology, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Maya A Deyssenroth
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Hanover, NH, USA
| | - Carmen Íñiguez
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Statistics and Computational Research, Universitat de València, València, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, València, Spain
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Pedro Carmona-Sáez
- Bioinformatics Unit, GENYO. Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain
- Department of Statistics, Faculty of Sciences, University of Granada, Granada, Spain
| | - Yuk J Loke
- Epigenetics Group, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | - Jordi Martorell-Marugán
- Bioinformatics Unit, GENYO. Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain
- Atrys Health S.A., Barcelona, Spain
| | - Evelyne Muggli
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Reproductive Epidemiology, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mariana F Fernández
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Instituto de Investigación Biosantaria (ibs.GRANADA), Granada, Spain
- Biomedical Research Centre (CIBM) and School of Medicine, University of Granada, Granada, Spain
| | - Jorg Tost
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, Evry, France
| | - Antonio Gómez-Martín
- Genomics Unit, GENYO. Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain
| | - Stephanie J London
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Durham, NC, USA
| | - Jordi Sunyer
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Rollins School of Public Health at Emory University, Atlanta, GA, USA
- Department of Epidemiology, Rollins School of Public health at Emory University, Atlanta, GA, USA
| | - Johanna Lepeule
- University Grenoble Alpes, Inserm, CNRS, IAB, Grenoble, France
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Mariona Bustamante
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.
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Yu X, Yuan Z, Lu H, Gao Y, Chen H, Shao Z, Yang J, Guan F, Huang S, Zeng P. Relationship between birth weight and chronic kidney disease: evidence from systematics review and two-sample Mendelian randomization analysis. Hum Mol Genet 2021; 29:2261-2274. [PMID: 32329512 DOI: 10.1093/hmg/ddaa074] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 04/14/2020] [Accepted: 04/18/2020] [Indexed: 12/13/2022] Open
Abstract
Observational studies showed an inverse association between birth weight and chronic kidney disease (CKD) in adulthood existed. However, whether such an association is causal remains fully elusive. Moreover, none of prior studies distinguished the direct fetal effect from the indirect maternal effect. Herein, we aimed to investigate the causal relationship between birth weight and CKD and to understand the relative fetal and maternal contributions. Meta-analysis (n = ~22 million) showed that low birth weight led to ~83% (95% confidence interval [CI] 37-146%) higher risk of CKD in late life. With summary statistics from large scale GWASs (n = ~300 000 for birth weight and ~481 000 for CKD), linkage disequilibrium score regression demonstrated birth weight had a negative maternal, but not fetal, genetic correlation with CKD and several other kidney-function related phenotypes. Furthermore, with multiple instruments of birth weight, Mendelian randomization showed there existed a negative fetal casual association (OR = 1.10, 95% CI 1.01-1.16) between birth weight and CKD; a negative but non-significant maternal casual association (OR = 1.09, 95% CI 0.98-1.21) was also identified. Those associations were robust against various sensitivity analyses. However, no maternal/fetal casual effects of birth weight were significant for other kidney-function related phenotypes. Overall, our study confirmed the inverse association between birth weight and CKD observed in prior studies, and further revealed the shared maternal genetic foundation between low birth weight and CKD, and the direct fetal and indirect maternal causal effects of birth weight may commonly drive this negative relationship.
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Affiliation(s)
- Xinghao Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Zhongshang Yuan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Haojie Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yixin Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Haimiao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Zhonghe Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Jiaji Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Fengjun Guan
- Department of Pediatrics, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Shuiping Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ping Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
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Yu XH, Wei YY, Zeng P, Lei SF. Birth weight is positively associated with adult osteoporosis risk: observational and Mendelian randomization studies. J Bone Miner Res 2021; 36:1469-1480. [PMID: 34105796 DOI: 10.1002/jbmr.4316] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 04/08/2021] [Accepted: 04/18/2021] [Indexed: 12/21/2022]
Abstract
The relationship between birth weight and osteoporosis was inconsistent in previous observational studies. Therefore, we performed a systematic evaluation to determine the inconsistent relationship and further make causal inference based on the UK Biobank datasets (~500,000 individuals) and individual/summary-level genetic datasets. Observational analyses found consistent negative associations either between birth weight and estimated bone mineral density (eBMD) or between genetic risk score (GRS) of birth weight and eBMD in total subjects, and sex-stratified subgroups. Mediation analyses detected significant mediation effects of adult weight and height on associations between birth weight and eBMD. Birth weight was causally associated not only with three BMD phenotypes (eBMD, total body [TB]-BMD, and femoral neck [FN]-BMD) under two effect models (total and fetal effect), but also with the risk of fracture using different Mendelian randomization (MR) methods. Multivariable MR analyses detected the pleiotropic effects of some environmental factors (e.g., gestational duration, head circumference, hip circumference) on the associations between birth weight and BMD/fracture. Three BMD phenotypes (eBMD, TB-BMD, and FN-BMD) have significant mediation effects on the associations between birth weight and fracture by using a novel mediation MR analysis under the multivariable MR framework. This multistage systematic study found consistent causal associations between birth weight and osteoporosis risk, fetal origin of genetic effects underlying the associations, and several mediation factors on the detected associations. The results enhanced our understanding of the effects of fetal original phenotypes on outcomes in late adulthood and provided helpful clues for early prevention research on osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Xing-Hao Yu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Yong-Yue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ping Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Shu-Feng Lei
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
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Lightbody RJ, Taylor JMW, Dempsie Y, Graham A. Induction of microRNA hsa-let-7d-5p, and repression of HMGA2, contribute protection against lipid accumulation in macrophage 'foam' cells. Biochim Biophys Acta Mol Cell Biol Lipids 2021; 1866:159005. [PMID: 34274506 DOI: 10.1016/j.bbalip.2021.159005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 07/08/2021] [Accepted: 07/13/2021] [Indexed: 12/14/2022]
Abstract
Accumulation of excess cholesterol and cholesteryl ester in macrophage 'foam' cells within the arterial intima characterises early 'fatty streak' atherosclerotic lesions, and is accompanied by epigenetic changes, including altered expression of microRNA sequences which determine of gene and protein expression. This study established that exposure to lipoproteins, including acetylated LDL, induced macrophage expression of microRNA hsa-let-7d-5p, a sequence previously linked with tumour suppression, and repressed expression of one of its target genes, high mobility group AT hook 2 (HMGA2). A let-7d-5p mimic repressed expression of HMGA2 (18%; p < 0.05) while a marked increase (2.9-fold; p < 0.05) in expression of HMGA2 was noted in the presence of let-7d-5p inhibitor. Under these conditions, let-7d-5p mimic significantly (p < 0.05) decreased total (10%), free (8%) and cholesteryl ester (21%) mass, while the inhibitor significantly (p < 0.05) increased total (29%) and free cholesterol (29%) mass, compared with the relevant controls. Let-7d-5p inhibition significantly (p < 0.05) increased endogenous biosynthesis of cholesterol (38%) and cholesteryl ester (39%) pools in macrophage 'foam' cells, without altering the cholesterol efflux pathway, or esterification of exogenous radiolabelled oleate. Let-7d-5p inhibition in sterol-loaded cells increased the level of HMGA2 protein (32%; p < 0.05), while SiRNA knockdown of this protein (29%; p < 0.05) resulted in a (21%, p < 0.05) reduction in free cholesterol mass. Thus, induction of let-7d-5p, and repression of its target HMGA2, in macrophages is a protective response to the challenge of increased cholesterol influx into these cells; dysregulation of this response may contribute to atherosclerosis and other disorders such as cancer.
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Sánchez-Soriano C, Pearson ER, Reynolds RM. The role of genetics in fetal programming of adult cardiometabolic disease. J Dev Orig Health Dis 2021;:1-8. [PMID: 34176548 DOI: 10.1017/S2040174421000350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Disturbances affecting early development have broad repercussions on the individual's health during infancy and adulthood. Multiple observational studies throughout the years have shown that alterations of fetal growth are associated with increased cardiometabolic disease risks. However, the genetic component of this association only started to be investigated in the last 40 years, when single genes with distinct effects were investigated. Birth weight (BW), commonly reported as the outcome of developmental growth, has been estimated to be 20% to 60% heritable. Through Genome-Wide Association (GWA) meta-analyses, 190 different loci have been identified being associated with BW, and while many of these loci designate genes involved in glucose and lipid metabolism, with clear ties to fetal development, the role of others is not yet understood. In addition, due to its influence over the intrauterine environment, the maternal genotype also plays an important part in the determination of offspring BW, with the same loci having independent effects of different magnitude or even direction. There is still much to uncover regarding the genetic determinants of BW and the interactions between maternal, offspring, and even paternal genotype. To fully understand these, diverse and novel cohorts from multiple ancestries collecting extensive neonatal phenotype will be needed. This review compiles, chronologically, the main findings in the investigation of the genetics of BW.
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Braz CU, Rowan TN, Schnabel RD, Decker JE. Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle. Sci Rep 2021; 11:13335. [PMID: 34172761 PMCID: PMC8233360 DOI: 10.1038/s41598-021-92455-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 06/07/2021] [Indexed: 02/06/2023] Open
Abstract
Understanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that G × E contribute 10.1%, 3.8%, and 2.8% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. G × E genome-wide association analysis (GWAA) detected a large number of G × E loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects regardless of differences in genotypic means. Further, variance-heterogeneity GWAA detected loci enriched with G × E effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of G × E genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neurotransmitter activity, hypoxia-induced processes, keratinization, hormone, thermogenic and immune pathways. We unraveled the relevance and complexity of the genetic basis of G × E underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals.
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Affiliation(s)
- Camila U Braz
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Troy N Rowan
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
- Genetics Area Program, University of Missouri, Columbia, MO, 65211, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
- Genetics Area Program, University of Missouri, Columbia, MO, 65211, USA
- Informatics Institute, University of Missouri, Columbia, MO, 65211, USA
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
- Genetics Area Program, University of Missouri, Columbia, MO, 65211, USA.
- Informatics Institute, University of Missouri, Columbia, MO, 65211, USA.
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Cullen SM, Hassan N, Smith-Raska M. Effects of non-inherited ancestral genotypes on offspring phenotypes. Biol Reprod 2021; 105:747-760. [PMID: 34159361 DOI: 10.1093/biolre/ioab120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 11/13/2022] Open
Abstract
It is well established that environmental exposures can modify the profile of heritable factors in an individual's germ cells, ultimately affecting the inheritance of phenotypes in descendants. Similar to exposures, an ancestor's genotype can also affect the inheritance of phenotypes across generations, sometimes in offspring who do not inherit the genetic aberration. This can occur via a variety of prenatal, in utero, or postnatal mechanisms. In this review, we discuss the evidence for this process in mammals, with a focus on examples that are potentially mediated through the germline, while also considering alternate routes of inheritance. Non-inherited ancestral genotypes may influence descendant's disease risk to a much greater extent than currently appreciated, and focused evaluation of this phenomenon may reveal novel mechanisms of inheritance.
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Affiliation(s)
- Sean M Cullen
- Division of Newborn Medicine, Department of Pediatrics, Weill Cornell Medicine, 413 East 69th Street, Room 1252D, New York, NY 10021
| | - Nora Hassan
- Division of Newborn Medicine, Department of Pediatrics, Weill Cornell Medicine, 413 East 69th Street, Room 1252D, New York, NY 10021
| | - Matthew Smith-Raska
- Division of Newborn Medicine, Department of Pediatrics, Weill Cornell Medicine, 413 East 69th Street, Room 1252D, New York, NY 10021
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Beaumont RN, Mayne IK, Freathy RM, Wright CF. Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders. Hum Mol Genet 2021; 30:1057-1066. [PMID: 33682876 PMCID: PMC8355446 DOI: 10.1093/hmg/ddab060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/11/2021] [Accepted: 02/15/2021] [Indexed: 11/14/2022] Open
Abstract
Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.
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Affiliation(s)
| | | | - Rachel M Freathy
- To whom correspondence should be addressed at: Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, RILD Building Barrack Road, Exeter EX2 5DW, UK. Tel: +44 (0) 1392 408238;
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