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Tian Y, Zhang H, Bureau A, Hochner H, Chen J. Efficient inference of parent-of-origin effect using case-control mother-child genotype data. J Stat Plan Inference 2024; 233:106190. [PMID: 38818512 PMCID: PMC11135462 DOI: 10.1016/j.jspi.2024.106190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.
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Affiliation(s)
- Yuang Tian
- Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China
| | - Hong Zhang
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Alexandre Bureau
- Department of Social and Preventive Medicine, Université Laval, Québec, Canada
| | - Hagit Hochner
- Braun School of Public Health, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
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2
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Westergaard D, Steinthorsdottir V, Stefansdottir L, Rohde PD, Wu X, Geller F, Tyrmi J, Havulinna AS, Solé-Navais P, Flatley C, Ostrowski SR, Pedersen OB, Erikstrup C, Sørensen E, Mikkelsen C, Bruun MT, Aagaard Jensen B, Brodersen T, Ullum H, Magnus P, Andreassen OA, Njolstad PR, Kolte AM, Krebs L, Nyegaard M, Hansen TF, Feenstra B, Daly M, Lindgren CM, Thorleifsson G, Stefansson OA, Sveinbjornsson G, Gudbjartsson DF, Thorsteinsdottir U, Banasik K, Jacobsson B, Laisk T, Laivuori H, Stefansson K, Brunak S, Nielsen HS. Genome-wide association meta-analysis identifies five loci associated with postpartum hemorrhage. Nat Genet 2024; 56:1597-1603. [PMID: 39039282 PMCID: PMC11319197 DOI: 10.1038/s41588-024-01839-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 06/21/2024] [Indexed: 07/24/2024]
Abstract
Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severe impact on maternal-fetal health. We identified five genetic loci linked to PPH in a meta-analysis. Functional annotation analysis indicated candidate genes HAND2, TBX3 and RAP2C/FRMD7 at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors. There were strong genetic correlations with birth weight, gestational duration and uterine fibroids. Bleeding in early pregnancy yielded no genome-wide association signals but showed strong genetic correlation with various human traits, suggesting a potentially complex, polygenic etiology. Our results suggest that PPH is related to progesterone signaling dysregulation, whereas early bleeding is a complex trait associated with underlying health and possibly socioeconomic status and may include genetic factors that have not yet been identified.
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Affiliation(s)
- David Westergaard
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Methods and Analysis, Statistics Denmark, Copenhagen, Denmark
| | | | | | - Palle Duun Rohde
- Department of Health Science and Technology, Aalborg University, Gistrup, Denmark
| | - Xiaoping Wu
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Frank Geller
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Jaakko Tyrmi
- Centre for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare - THL, Helsinki, Finland
| | - Pol Solé-Navais
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Christopher Flatley
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sisse Rye Ostrowski
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Birger Pedersen
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical immunology, Zealand University Hospital, Køge, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Erik Sørensen
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Christina Mikkelsen
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Mie Topholm Bruun
- Clinical Immunological Research Unit, Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | | | - Thorsten Brodersen
- Department of Clinical immunology, Zealand University Hospital, Køge, Denmark
| | - Henrik Ullum
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Per Magnus
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Pål R Njolstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Astrid Marie Kolte
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Lone Krebs
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Aalborg University, Gistrup, Denmark
| | - Thomas Folkmann Hansen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Danish Headache Center, Department of neurology, Copenhagen University Hospital, Glostrup, Denmark
| | - Bjarke Feenstra
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Mark Daly
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cecilia M Lindgren
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Big Data Institute Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Wellcome Trust Centre Human Genetics, University of Oxford, Oxford, UK
| | | | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, Reykjavik University, Reykjavik, Iceland
| | - Karina Banasik
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bo Jacobsson
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hannele Laivuori
- Centre for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynaecology, Tampere University Hospital, Tampere, Finland
| | - Kari Stefansson
- deCODE genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, Reykjavik University, Reykjavik, Iceland
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Henriette Svarre Nielsen
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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Jácome-Ferrer P, Costas J. Exploring the causal effect of placental physiology in susceptibility to mental and addictive disorders: a Mendelian randomization study. Front Psychiatry 2024; 15:1396837. [PMID: 39135989 PMCID: PMC11317394 DOI: 10.3389/fpsyt.2024.1396837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 07/02/2024] [Indexed: 08/15/2024] Open
Abstract
Background Epidemiological studies have linked low birth weight to psychiatric disorders, including substance use disorders. Genomic analyses suggest a role of placental physiology on psychiatric risk. We investigated whether this association is causally related to impaired trophoblast function. Methods We conducted a two-sample summary-data Mendelian randomization study using as instrumental variables those genetic variants strongly associated with birth weight, whose effect is exerted through the fetal genome, and are located near genes with differential expression in trophoblasts. Eight psychiatric and substance use disorders with >10,000 samples were included as outcomes. The inverse variance weighted method was used as the main analysis and several sensitivity analyses were performed for those significant results. Results The inverse variance weighted estimate, based on 14 instrumental variables, revealed an association, after correction for multiple tests, between birth weight and broadly defined depression (β = -0.165, 95% CI = -0.282 to -0.047, P = 0.0059). Sensitivity analyses revealed the absence of heterogeneity in the effect of instrumental variables, confirmed by leave-one-out analysis, MR_Egger intercept, and MR_PRESSO. The effect was consistent using robust methods. Reverse causality was not detected. The effect was specifically linked to genetic variants near genes involved in trophoblast physiology instead of genes with fetal effect on birth weight or involved in placenta development. Conclusion Impaired trophoblast functioning, probably leading to reduced fetal brain oxygen and nutrient supply, is causally related to broadly defined depression. Considering the therapeutic potential of some agents to treat fetal growth restriction, further research on the effect of trophoblast physiology on mental disorders may have future implications in prevention.
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Affiliation(s)
- Pablo Jácome-Ferrer
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - Javier Costas
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Spain
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Habtewold TD, Wijesiriwardhana P, Biedrzycki RJ, Tekola-Ayele F. Genetic distance and ancestry proportion modify the association between maternal genetic risk score of type 2 diabetes and fetal growth. Hum Genomics 2024; 18:81. [PMID: 39030631 PMCID: PMC11264503 DOI: 10.1186/s40246-024-00645-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/27/2024] [Indexed: 07/21/2024] Open
Abstract
BACKGROUND Maternal genetic risk of type 2 diabetes (T2D) has been associated with fetal growth, but the influence of genetic ancestry is not yet fully understood. We aimed to investigate the influence of genetic distance (GD) and genetic ancestry proportion (GAP) on the association of maternal genetic risk score of T2D (GRST2D) with fetal weight and birthweight. METHODS Multi-ancestral pregnant women (n = 1,837) from the NICHD Fetal Growth Studies - Singletons cohort were included in the current analyses. Fetal weight (in grams, g) was estimated from ultrasound measurements of fetal biometry, and birthweight (g) was measured at delivery. GRST2D was calculated using T2D-associated variants identified in the latest trans-ancestral genome-wide association study and was categorized into quartiles. GD and GAP were estimated using genotype data of four reference populations. GD was categorized into closest, middle, and farthest tertiles, and GAP was categorized as highest, medium, and lowest. Linear regression analyses were performed to test the association of GRST2D with fetal weight and birthweight, adjusted for covariates, in each GD and GAP category. RESULTS Among women with the closest GD from African and Amerindigenous ancestries, the fourth and third GRST2D quartile was significantly associated with 5.18 to 7.48 g (weeks 17-20) and 6.83 to 25.44 g (weeks 19-27) larger fetal weight compared to the first quartile, respectively. Among women with middle GD from European ancestry, the fourth GRST2D quartile was significantly associated with 5.73 to 21.21 g (weeks 18-26) larger fetal weight. Furthermore, among women with middle GD from European and African ancestries, the fourth and second GRST2D quartiles were significantly associated with 117.04 g (95% CI = 23.88-210.20, p = 0.014) and 95.05 g (95% CI = 4.73-185.36, p = 0.039) larger birthweight compared to the first quartile, respectively. The absence of significant association among women with the closest GD from East Asian ancestry was complemented by a positive significant association among women with the highest East Asian GAP. CONCLUSIONS The association between maternal GRST2D and fetal growth began in early-second trimester and was influenced by GD and GAP. The results suggest the use of genetic GD and GAP could improve the generalizability of GRS.
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Affiliation(s)
- Tesfa Dejenie Habtewold
- 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, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA
| | - Prabhavi Wijesiriwardhana
- 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, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA
| | - Richard J Biedrzycki
- Glotech, Inc., contractor for Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, 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, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA.
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Liu J, Sun Q, Liu D, Liang H, Chen Y, Ye F, Zhang Q. Epigenome-850K-wide profiling reveals peripheral blood differential methylation in term low birth weight. Epigenomics 2024:1-13. [PMID: 38957889 DOI: 10.1080/17501911.2024.2358744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 05/20/2024] [Indexed: 07/04/2024] Open
Abstract
Aim: We investigate the genome-wide DNA methylation (DNAm) patterns of term low birth weight (TLBW) neonates. Methods: In the discovery phase, we assayed 32 samples (TLBW/control:16/16) using the EPIC 850k BeadChip Array. Targeted pyrosequencing of in 60 samples (TLBW/control:28/32) using targeted pyrosequencing during the replication phase. Results: The 850K array identified TLBW-associated 144 differentially methylated positions (DMPs) and 149 DMRs. Nearly 77% DMPs exhibited hypomethylation, located in the opensea and gene body regions. The most significantly enriched pathway in KEGG is sphingolipid metabolism (hsa00600), and the genes GALC and SGMS1 related to this pathway both show hypomethylation. Conclusion: Our analysis provides evidence of genome-wide DNAm alterations in TLBW. Further investigations are needed to elucidate the functional significance of these DNAm changes.
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Affiliation(s)
- Jing Liu
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Qi Sun
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Die Liu
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Haixiao Liang
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Yuanmei Chen
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Fang Ye
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Qi Zhang
- Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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Srivastava AK, Monangi N, Ravichandran V, Solé-Navais P, Jacobsson B, Muglia LJ, Zhang G. Recent Advances in Genomic Studies of Gestational Duration and Preterm Birth. Clin Perinatol 2024; 51:313-329. [PMID: 38705643 PMCID: PMC11189662 DOI: 10.1016/j.clp.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
Preterm birth (PTB) is the leading cause of infant mortality and morbidity. For several decades, extensive epidemiologic and genetic studies have highlighted the significant contribution of maternal and offspring genetic factors to PTB. This review discusses the challenges inherent in conventional genomic analyses of PTB and underscores the importance of adopting nonconventional approaches, such as analyzing the mother-child pair as a single analytical unit, to disentangle the intertwined maternal and fetal genetic influences. We elaborate on studies investigating PTB phenotypes through 3 levels of genetic analyses: single-variant, multi-variant, and genome-wide variants.
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Affiliation(s)
- Amit K Srivastava
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - Nagendra Monangi
- Department of Pediatrics, University of Cincinnati College of Medicine, Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative; Division of Neonatology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - Vidhya Ravichandran
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA; Division of Neonatology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - Pol Solé-Navais
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Box 100, Gothenburg 405 30, Sweden
| | - Bo Jacobsson
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Box 100, Gothenburg 405 30, Sweden; Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Lovisenberggata 8, Oslo 0456, Norway
| | - Louis J Muglia
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative; The Burroughs Wellcome Fund, 21 Tw Alexander Drive, Research Triangle Park, NC 27709, USA
| | - Ge Zhang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative.
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Peng Q, Qiu W, Li Z, Zhao J, Zhu C. Fetal genetically determined birth weight plays a causal role in earlier puberty timing: evidence from human genetic studies. Hum Reprod 2024; 39:792-800. [PMID: 38384258 DOI: 10.1093/humrep/deae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/27/2023] [Indexed: 02/23/2024] Open
Abstract
STUDY QUESTION Does fetal genetically determined birth weight associate with the timing of puberty? SUMMARY ANSWER Lower fetal genetically determined birth weight was causally associated with an earlier onset of puberty, independent of the indirect effects of the maternal intrauterine environment. WHAT IS KNOWN ALREADY Previous Mendelian randomization (MR) studies have indicated a potential causal link between birth weight, childhood BMI, and the onset of puberty. However, they did not distinguish between genetic variants that have a direct impact on birth weight through the fetal genome (referred to as fetal genetic effects) and those that influence birth weight indirectly by affecting the intrauterine environment (known as maternal genetic effects). It is crucial to emphasize that previous studies were limited because they did not account for the potential bias caused by unaddressed correlations between maternal and fetal genetic effects. Additionally, the proportion of birth weight variation explained by the fetal genome is considerably larger than that of the maternal genome. STUDY DESIGN, SIZE, DURATION We performed two-sample MR analyses to investigate the causal effect of fetal genetically determined birth weight on puberty timing using summary data from large-scale genome-wide association studies (GWASs) in individuals of European ancestry. PARTICIPANTS/MATERIALS, SETTING, METHODS From the two most recent GWASs specifically centered on birth weight, which included 406 063 individuals and 423 683 individuals (63 365 trios) respectively, we identified genetic variants associated with fetal genetically determined birth weight, while adjusting for maternal genetic effects. We identified genetic variants associated with childhood BMI from an independent GWAS involving 21 309 European participants. On this basis, we employed two-sample MR techniques to examine the possible causal effects of fetal genetically determined birth weight on puberty timing using a large-scale GWAS of puberty timing (including 179 117 females of European ancestry). Furthermore, we employed advanced analytical methods, specifically MR mediation and MR-Cluster, to enhance our comprehension of the causal relationship between birth weight determined by fetal genetics and the timing of puberty. We also explored the pathways through which childhood BMI might act as a mediator in this relationship. MAIN RESULTS AND THE ROLE OF CHANCE In the univariable MR analysis, a one SD decrease in fetal genetically determined birth weight (∼ 418 g) was associated with a 0.16 (95% CI [0.07-0.26]) years earlier onset of puberty. The multivariable MR analysis including fetal genetically determined birth weight and childhood BMI in relation to puberty timing provided compelling evidence that birth weight had a direct influence on the timing of puberty. Lower birth weight (one SD) was associated with an earlier onset of puberty, with a difference of 0.23 (95% CI [0.05-0.42]) years. We found little evidence to support a mediating role of childhood BMI between birth weight and puberty timing (-0.07 years, 95% CI [-0.20 to 0.06]). LIMITATIONS, REASONS FOR CAUTION Our data came from European ancestry populations, which may restrict the generalizability of our results to other populations. Moreover, our analysis could not investigate potential non-linear relationships between birth weight and puberty timing due to limitations in genetic summary data. WIDER IMPLICATIONS OF THE FINDINGS Findings from this study suggested that low birth weight, determined by the fetal genome, contributes to early puberty, and offered supporting evidence to enhance comprehension of the fetal origins of disease hypothesis. STUDY FUNDING/COMPETING INTEREST(S) C.Z. was funded by the Sichuan Province Science and Technology Program [grant number 2021JDR0189]. J.Z. was supported by grants from the National Natural Science Foundation of China [grant number 82373588]. No other authors declare any sources of funding. The authors have no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Qinghui Peng
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenjuan Qiu
- Department of Paediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, Shanghai Institute of Paediatric Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zengjun Li
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jian Zhao
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Cairong Zhu
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Kentistou KA, Lim BEM, Kaisinger LR, Steinthorsdottir V, Sharp LN, Patel KA, Tragante V, Hawkes G, Gardner EJ, Olafsdottir T, Wood AR, Zhao Y, Thorleifsson G, Day FR, Ozanne SE, Hattersley AT, O'Rahilly S, Stefansson K, Ong KK, Beaumont RN, Perry JRB, Freathy RM. Rare variant associations with birth weight identify genes involved in adipose tissue regulation, placental function and insulin-like growth factor signalling. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.03.24305248. [PMID: 38633783 PMCID: PMC11023655 DOI: 10.1101/2024.04.03.24305248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Investigating the genetic factors influencing human birth weight may lead to biological insights into fetal growth and long-term health. Genome-wide association studies of birth weight have highlighted associated variants in more than 200 regions of the genome, but the causal genes are mostly unknown. Rare genetic variants with robust evidence of association are more likely to point to causal genes, but to date, only a few rare variants are known to influence birth weight. We aimed to identify genes that harbour rare variants that impact birth weight when carried by either the fetus or the mother, by analysing whole exome sequence data in UK Biobank participants. We annotated rare (minor allele frequency <0.1%) protein-truncating or high impact missense variants on whole exome sequence data in up to 234,675 participants with data on their own birth weight (fetal variants), and up to 181,883 mothers who reported the birth weight of their first child (maternal variants). Variants within each gene were collapsed to perform gene burden tests and for each associated gene, we compared the observed fetal and maternal effects. We identified 8 genes with evidence of rare fetal variant effects on birth weight, of which 2 also showed maternal effects. One additional gene showed evidence of maternal effects only. We observed 10/11 directionally concordant associations in an independent sample of up to 45,622 individuals (sign test P=0.01). Of the genes identified, IGF1R and PAPPA2 (fetal and maternal-acting) have known roles in insulin-like growth factor bioavailability and signalling. PPARG, INHBE and ACVR1C (all fetal-acting) have known roles in adipose tissue regulation and rare variants in the latter two also showed associations with favourable adiposity patterns in adults. We highlight the dual role of PPARG in both adipocyte differentiation and placental angiogenesis. NOS3, NRK, and ADAMTS8 (fetal and maternal-acting) have been implicated in both placental function and hypertension. Analysis of rare coding variants has identified regulators of fetal adipose tissue and fetoplacental angiogenesis as determinants of birth weight, as well as further evidence for the role of insulin-like growth factors.
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Affiliation(s)
- Katherine A Kentistou
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Brandon E M Lim
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Lena R Kaisinger
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | | | - Luke N Sharp
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Kashyap A Patel
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | | | - Gareth Hawkes
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Eugene J Gardner
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | | | - Andrew R Wood
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Yajie Zhao
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | | | - Felix R Day
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Susan E Ozanne
- MRC Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Andrew T Hattersley
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Stephen O'Rahilly
- MRC Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Ken K Ong
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
- Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Robin N Beaumont
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - John R B Perry
- MRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
- MRC Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
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9
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Devisri B, Kavitha M. Fetal growth analysis from ultrasound videos based on different biometrics using optimal segmentation and hybrid classifier. Stat Med 2024; 43:1019-1047. [PMID: 38155152 DOI: 10.1002/sim.9995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/04/2023] [Accepted: 12/04/2023] [Indexed: 12/30/2023]
Abstract
Birth defects and their associated deaths, high health and financial costs of maternal care and associated morbidity are major contributors to infant mortality. If permitted by law, prenatal diagnosis allows for intrauterine care, more complicated hospital deliveries, and termination of pregnancy. During pregnancy, a set of measurements is commonly used to monitor the fetal health, including fetal head circumference, crown-rump length, abdominal circumference, and femur length. Because of the intricate interactions between the biological tissues and the US waves mother and fetus, analyzing fetal US images from a specialized perspective is difficult. Artifacts include acoustic shadows, speckle noise, motion blur, and missing borders. The fetus moves quickly, body structures close, and the weeks of pregnancy vary greatly. In this work, we propose a fetal growth analysis through US image of head circumference biometry using optimal segmentation and hybrid classifier. First, we introduce a hybrid whale with oppositional fruit fly optimization (WOFF) algorithm for optimal segmentation of segment fetal head which improves the detection accuracy. Next, an improved U-Net design is utilized for the hidden feature (head circumference biometry) extraction which extracts features from the segmented extraction. Then, we design a modified Boosting arithmetic optimization (MBAO) algorithm for feature optimization to selects optimal best features among multiple features for the reduction of data dimensionality issues. Furthermore, a hybrid deep learning technique called bi-directional LSTM with convolutional neural network (B-LSTM-CNN) for fetal growth analysis to compute the fetus growth and health. Finally, we validate our proposed method through the open benchmark datasets are HC18 (Ultrasound image) and oxford university research archive (ORA-data) (Ultrasound video frames). We compared the simulation results of our proposed algorithm with the existing state-of-art techniques in terms of various metrics.
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Affiliation(s)
- B Devisri
- Department of Electronics and communication Engineering, K. Ramakrishnan College of Technology, (Affiliated to Anna University Chennai), Trichy, India
| | - M Kavitha
- Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Trichy, India
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10
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Hubert JN, Perret M, Riquet J, Demars J. Livestock species as emerging models for genomic imprinting. Front Cell Dev Biol 2024; 12:1348036. [PMID: 38500688 PMCID: PMC10945557 DOI: 10.3389/fcell.2024.1348036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/19/2024] [Indexed: 03/20/2024] Open
Abstract
Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.
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Affiliation(s)
| | | | | | - Julie Demars
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
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11
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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] [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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12
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Ardissino M, Morley AP, Slob EAW, Schuermans A, Rayes B, Raisi-Estabragh Z, de Marvao A, Burgess S, Rogne T, Honigberg MC, Ng FS. Birth weight influences cardiac structure, function, and disease risk: evidence of a causal association. Eur Heart J 2024; 45:443-454. [PMID: 37738114 PMCID: PMC10849320 DOI: 10.1093/eurheartj/ehad631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/09/2023] [Accepted: 09/10/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND AND AIMS Low birth weight is a common pregnancy complication, which has been associated with higher risk of cardiometabolic disease in later life. Prior Mendelian randomization (MR) studies exploring this question do not distinguish the mechanistic contributions of variants that directly influence birth weight through the foetal genome (direct foetal effects), vs. variants influencing birth weight indirectly by causing an adverse intrauterine environment (indirect maternal effects). In this study, MR was used to assess whether birth weight, independent of intrauterine influences, is associated with cardiovascular disease risk and measures of adverse cardiac structure and function. METHODS Uncorrelated (r2 < .001), genome-wide significant (P < 5 × 10-8) single nucleotide polymorphisms were extracted from genome-wide association studies summary statistics for birth weight overall, and after isolating direct foetal effects only. Inverse-variance weighted MR was utilized for analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 16 measures of cardiac structure and function. Multiple comparisons were accounted for by Benjamini-Hochberg correction. RESULTS Lower genetically-predicted birth weight, isolating direct foetal effects only, was associated with an increased risk of coronary artery disease (odds ratio 1.21, 95% confidence interval 1.06-1.37; P = .031), smaller chamber volumes, and lower stroke volume, but higher contractility. CONCLUSIONS The results of this study support a causal role of low birth weight in cardiovascular disease, even after accounting for the influence of the intrauterine environment. This suggests that individuals with a low birth weight may benefit from early targeted cardiovascular disease prevention strategies, independent of whether this was linked to an adverse intrauterine environment during gestation.
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Affiliation(s)
- Maddalena Ardissino
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, UK
| | - Alec P Morley
- Department of Medicine, School of Clinical Medicine, University of Cambridge, UK
| | - Eric A W Slob
- Medical Research Council Biostatistics Unit, University of Cambridge, UK
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, the Netherlands
- Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, the Netherlands
| | - Art Schuermans
- Department of Cardiovascular Sciences, KU Leuven, Flanders, Leuven, Belgium
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bilal Rayes
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
| | - Zahra Raisi-Estabragh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, UK
| | - Antonio de Marvao
- Department of Women and Children’s Health, King’s College London, UK
- British Heart Foundation Centre of Research Excellence, School of Cardiovascular Medicine and Sciences, King’s College London, UK
- Medical Research Council, London Institute of Medical Sciences, Imperial College London, UK
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Tormod Rogne
- Department of Chronic Disease Epidemiology, Yale School of Public Health, USA
| | - Michael C Honigberg
- Department of Cardiovascular Sciences, KU Leuven, Flanders, Leuven, Belgium
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Fu Siong Ng
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
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13
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Affiliation(s)
- Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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14
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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] [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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15
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Huang S, Liu S, Huang M, He JR, Wang C, Wang T, Feng X, Kuang Y, Lu J, Gu Y, Xia X, Lin S, Zhou W, Fu Q, Xia H, Qiu X. The Born in Guangzhou Cohort Study enables generational genetic discoveries. Nature 2024; 626:565-573. [PMID: 38297123 DOI: 10.1038/s41586-023-06988-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 12/15/2023] [Indexed: 02/02/2024]
Abstract
Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.
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Affiliation(s)
- Shujia Huang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Mingxi Huang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jian-Rong He
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Chengrui Wang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Tianyi Wang
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Xiaotian Feng
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Yashu Kuang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Jinhua Lu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Yuqin Gu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xiaoyan Xia
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Shanshan Lin
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Wenhao Zhou
- Division of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Qiaomei Fu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Huimin Xia
- Provincial Clinical Research Center for Child Health, Guangzhou, China.
- Provincial Key Laboratory of Research in Structure Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
- Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
| | - Xiu Qiu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
- Provincial Clinical Research Center for Child Health, Guangzhou, China.
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
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16
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Rogne T, Gill D, Liew Z, Shi X, Stensrud VH, Nilsen TIL, Burgess S. Mediating Factors in the Association of Maternal Educational Level With Pregnancy Outcomes: A Mendelian Randomization Study. JAMA Netw Open 2024; 7:e2351166. [PMID: 38206626 PMCID: PMC10784860 DOI: 10.1001/jamanetworkopen.2023.51166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/20/2023] [Indexed: 01/12/2024] Open
Abstract
Importance Lower educational attainment is associated with increased risk of adverse pregnancy outcomes, but it is unclear which pathways mediate this association. Objective To investigate the association between educational attainment and pregnancy outcomes and the proportion of this association that is mediated through modifiable cardiometabolic risk factors. Design, Setting, and Participants In this 2-sample mendelian randomization (MR) cohort study, uncorrelated (R2 < 0.01) single-nucleotide variants (formerly single-nucleotide polymorphisms) associated with the exposure (P < 5 × 10-8) and mediators and genetic associations with the pregnancy outcomes from genome-wide association studies were extracted. All participants were of European ancestry and were largely from Finland, Iceland, the United Kingdom, or the US. The inverse variance-weighted method was used in the main analysis, and the weighted median, weighted mode, and MR Egger regression were used in sensitivity analyses. In mediation analyses, the direct effect of educational attainment estimated in multivariable MR was compared with the total effect estimated in the main univariable MR analysis. Data were extracted between December 1, 2022, and April 30, 2023. Exposure Genetically estimated educational attainment. The mediators considered were genetically estimated type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure. Main Outcomes and Measures Ectopic pregnancy, hyperemesis gravidarum, gestational diabetes, preeclampsia, preterm birth, and offspring birth weight. Results The analyses included 3 037 499 individuals with data on educational attainment, and those included in studies on pregnancy outcomes ranged from 141 014 for ectopic pregnancy to 270 002 with data on offspring birth weight. Each SD increase in genetically estimated educational attainment (ie, 3.4 years) was associated with an increased birth weight of 42 (95% CI, 28-56) g and an odds ratio ranging from 0.53 (95% CI, 0.46-0.60) for ectopic pregnancy to 0.81 (95% CI, 0.71-0.93) for preeclampsia. The combined proportion of the association that was mediated by the 5 cardiometabolic risk factors ranged from -17% (95% CI, -46% to 26%) for hyperemesis gravidarum to 78% (95% CI, 10%-208%) for preeclampsia. Sensitivity analyses accounting for pleiotropy were consistent with the main analyses. Conclusions and Relevance In this MR cohort study, intervening for type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure may lead to reductions in several adverse pregnancy outcomes associated with lower levels of education. Such public health interventions would serve to reduce health disparities attributable to social inequalities.
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Affiliation(s)
- Tormod Rogne
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Zeyan Liew
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, Connecticut
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut
| | - Xiaoting Shi
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut
| | - Vilde Hatlevoll Stensrud
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Anesthesia and Intensive Care, St Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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17
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Kong L, Wang Y, Ye C, Dou C, Liu D, Xu M, Zheng J, Zheng R, Xu Y, Li M, Zhao Z, Lu J, Chen Y, Wang W, Liu R, Bi Y, Wang T, Ning G. Opposite causal effects of birthweight on myocardial infarction and atrial fibrillation and the distinct mediating pathways: a Mendelian randomization study. Cardiovasc Diabetol 2023; 22:338. [PMID: 38087288 PMCID: PMC10716951 DOI: 10.1186/s12933-023-02062-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 11/10/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Previous observational studies have documented an inverse association of birthweight with myocardial infarction (MI) but a positive association with atrial fibrillation (AF). However, the causality of these associations and the underlying mediating pathways remain unclear. We aimed to investigate the causal effects of birthweight, incorporating both fetal and maternal genetic effects, on MI and AF, and identify potential mediators in their respective pathways. METHODS We performed Mendelian randomization (MR) analyses using genome-wide association study summary statistics for birthweight (N = 297,356 for own birthweight and 210,248 for offspring birthweight), MI (Ncase=61,000, Ncontrol=577,000), AF (Ncase=60,620, Ncontrol=970,216), and 52 candidate mediators (N = 13,848-1,295,946). Two-step MR was employed to identify and assess the mediation proportion of potential mediators in the associations of birthweight with MI and AF, respectively. As a complement, we replicated analyses for fetal-specific birthweight and maternal-specific birthweight. RESULTS Genetically determined each 1-SD lower birthweight was associated with a 40% (95% CI: 1.22-1.60) higher risk of MI, whereas each 1-SD higher birthweight was causally associated with a 29% (95% CI: 1.16-1.44) higher risk of AF. Cardiometabolic factors, including lipids and lipoproteins, glucose and insulin, blood pressure, and fatty acids, each mediated 4.09-23.71% of the total effect of birthweight on MI, followed by body composition and strength traits (i.e., appendicular lean mass, height, and grip strength) and socioeconomic indicators (i.e., education and household income), with the mediation proportion for each factor ranging from 8.08 to 16.80%. By contrast, appendicular lean mass, height, waist circumference, childhood obesity, and body mass index each mediated 15.03-45.12% of the total effect of birthweight on AF. Both fetal-specific birthweight and maternal-specific birthweight were inversely associated with MI, while only fetal-specific birthweight was positively associated with AF. Psychological well-being and lifestyle factors conferred no mediating effect in either association. CONCLUSIONS Cardiometabolic factors mainly mediated the association between lower birthweight and MI, while body composition and strength traits mediated the association between higher birthweight and AF. These findings provide novel evidence for the distinct pathogenesis of MI and AF and advocate adopting a life-course approach to improving fetal development and subsequent causal mediators to mitigate the prevalence and burden of cardiovascular diseases.
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Affiliation(s)
- Lijie Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiying Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaojie Ye
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chun Dou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dong Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruizhi Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruixin Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rujin 2nd Road, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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18
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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] [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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19
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Beaumont RN, Flatley C, Vaudel M, Wu X, Chen J, Moen GH, Skotte L, Helgeland Ø, Solé-Navais P, Banasik K, Albiñana C, Ronkainen J, Fadista J, Stinson SE, Trajanoska K, Wang CA, Westergaard D, Srinivasan S, Sánchez-Soriano C, Bilbao JR, Allard C, Groleau M, Kuulasmaa T, Leirer DJ, White F, Jacques PÉ, Cheng H, Hao K, Andreassen OA, Åsvold BO, Atalay M, Bhatta L, Bouchard L, Brumpton BM, Brunak S, Bybjerg-Grauholm J, Ebbing C, Elliott P, Engelbrechtsen L, Erikstrup C, Estarlich M, Franks S, Gaillard R, Geller F, Grove J, Hougaard DM, Kajantie E, Morgen CS, Nohr EA, Nyegaard M, Palmer CNA, Pedersen OB, Rivadeneira F, Sebert S, Shields BM, Stoltenberg C, Surakka I, Thørner LW, Ullum H, Vaarasmaki M, Vilhjalmsson BJ, Willer CJ, Lakka TA, Gybel-Brask D, Bustamante M, Hansen T, Pearson ER, Reynolds RM, Ostrowski SR, Pennell CE, Jaddoe VWV, Felix JF, Hattersley AT, Melbye M, Lawlor DA, Hveem K, Werge T, Nielsen HS, Magnus P, Evans DM, Jacobsson B, Järvelin MR, Zhang G, Hivert MF, Johansson S, Freathy RM, Feenstra B, Njølstad PR. Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth. Nat Genet 2023; 55:1807-1819. [PMID: 37798380 PMCID: PMC10632150 DOI: 10.1038/s41588-023-01520-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 08/31/2023] [Indexed: 10/07/2023]
Abstract
A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.
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Affiliation(s)
- Robin N Beaumont
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Christopher Flatley
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Xiaoping Wu
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Jing Chen
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Gunn-Helen Moen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Frazer Institute, The University of Queensland, Brisbane, Queensland, 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
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Line Skotte
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Øyvind Helgeland
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Pol Solé-Navais
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Clara Albiñana
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | | | - João Fadista
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Clinical Sciences, Lund University Diabetes Centre, Malmö, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Sara Elizabeth Stinson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Katerina Trajanoska
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Carol A Wang
- School of Medicine and Public Health, College of Medicine, Public Health and Wellbeing, The University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, New South Wales, Australia
| | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Denmark
- Methods and Analysis, Statistics Denmark, Copenhagen, Denmark
| | - Sundararajan Srinivasan
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | | | - Jose Ramon Bilbao
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain
- Biobizkaia Health Research Institute, Barakaldo, Spain
- Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Barcelona, Spain
| | - Catherine Allard
- Centre de recherche du Centre Hospitalier de l'Universite de Sherbrooke, Sherbrooke, Québec, Canada
| | - Marika Groleau
- Département de Biologie, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Teemu Kuulasmaa
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Daniel J Leirer
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Frédérique White
- Département de Biologie, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Pierre-Étienne Jacques
- Centre de recherche du Centre Hospitalier de l'Universite de Sherbrooke, Sherbrooke, Québec, Canada
- Département de Biologie, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Haoxiang Cheng
- Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Ke Hao
- Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Mustafa Atalay
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-St-Jean-Hôpital Universitaire de Chicoutimi, Saguenay, Québec, Canada
| | - Ben Michael Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Jonas Bybjerg-Grauholm
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Cathrine Ebbing
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Gynecology and Obstetrics, Haukeland University Hospital, Bergen, Norway
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Line Engelbrechtsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Herlev Hospital, Herlev, Denmark
| | - Christian Erikstrup
- Department Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Marisa Estarlich
- Faculty of Nursing and Chiropody, Universitat de València, C/Menendez Pelayo, Valencia, Spain
- Epidemiology and Environmental Health Joint Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO-Public Health, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Stephen Franks
- Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Romy Gaillard
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Jakob Grove
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Biomedicine-Human Genetics and the iSEQ Center, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - David M Hougaard
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Eero Kajantie
- Research Unit of Clinical Medicine, Medical Research Center, University of Oulu, Oulu, Finland
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Camilla S Morgen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Ellen A Nohr
- Institute of Clinical research, University of Southern Denmark, Odense, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Colin N A Palmer
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ole Birger Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sylvain Sebert
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Beverley M Shields
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Camilla Stoltenberg
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Lise Wegner Thørner
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | | | - Marja Vaarasmaki
- Research Unit of Clinical Medicine, Medical Research Center, University of Oulu, Oulu, Finland
- Department of Obstetrics and Gynaecology, Oulu University Hospital, Oulu, Finland
| | - Bjarni J Vilhjalmsson
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Timo A Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Dorte Gybel-Brask
- Psychotherapeutic Outpatient Clinic, Mental Health Services, Capital Region, Copenhagen, Denmark
| | - Mariona Bustamante
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ewan R Pearson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
| | - Sisse R Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Craig E Pennell
- School of Medicine and Public Health, College of Medicine, Public Health and Wellbeing, The University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, New South Wales, Australia
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrew T Hattersley
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Mads Melbye
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Danish Cancer Institute, Copenhagen, Denmark
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Deborah A Lawlor
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
| | - Thomas Werge
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark
- Lundbeck Center for Geogenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Henriette Svarre Nielsen
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - David M Evans
- Frazer Institute, The University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - Ge Zhang
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - 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
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway.
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20
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Su S, Fan J, Yang Y, Yang C, Jia X. Birth Weight, Cardiometabolic Factors, and Coronary Heart Disease: A Mendelian Randomization Study. J Clin Endocrinol Metab 2023; 108:e1245-e1252. [PMID: 37246707 DOI: 10.1210/clinem/dgad308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/25/2023] [Accepted: 05/26/2023] [Indexed: 05/30/2023]
Abstract
CONTEXT Observational studies have shown associations of birth weight (BW) with coronary heart disease (CHD), but results are inconsistent and do not distinguish the fetal or maternal effect of BW. OBJECTIVE This study aims to explore the causal association between BW and CHD, analyze the fetal and maternal contribution, and quantify mediating effects of cardiometabolic factors. METHODS Genetic variants from genome-wide association study summary-level data of own BW (N = 298 142), offspring BW (N = 210 267 mothers), and 16 cardiometabolic (anthropometric, glycemic, lipidemic, and blood pressure) factors were extracted as instrumental variables. We used two-sample Mendelian randomization study (MR) to estimate the causal effect of BW on CHD (60 801 cases and 123 504 controls from mixed ancestry) and explore the fetal and maternal contributions. Mediation analyses were conducted to analyze the potential mediating effects of 16 cardiometabolic factors using two-step MR. RESULTS Inverse variance weighted analysis showed that lower BW raised the CHD risk (β -.30; 95% CI: -0.40, -0.20) and consistent results were observed in fetal-specific/maternal-specific BW. We identified 5 mediators in the causal pathway from BW to CHD, including body mass index-adjusted hip circumference, triglycerides, fasting insulin, diastolic blood pressure, and systolic blood pressure (SBP), with mediated proportion ranging from 7.44% for triglycerides to 27.75% for SBP. Causality between fetal-specific and maternal-specific BW and CHD was mediated by glycemic factors and SBP, respectively. CONCLUSION Our findings supported that lower BW increased CHD risk and revealed that fetal-specific and maternal-specific BW may both contribute to this effect. The causality between BW and CHD was mediated by several cardiometabolic factors.
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Affiliation(s)
- Shuyao Su
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jingwen Fan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chaojun Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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21
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He Y, Guo Y, Zheng W, Yue T, Zhang H, Wang B, Feng Z, Ouzhuluobu, Cui C, Liu K, Zhou B, Zeng X, Li L, Wang T, Wang Y, Zhang C, Xu S, Qi X, Su B. Polygenic adaptation leads to a higher reproductive fitness of native Tibetans at high altitude. Curr Biol 2023; 33:4037-4051.e5. [PMID: 37643619 DOI: 10.1016/j.cub.2023.08.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 06/01/2023] [Accepted: 08/04/2023] [Indexed: 08/31/2023]
Abstract
The adaptation of Tibetans to high-altitude environments has been studied extensively. However, the direct assessment of evolutionary adaptation, i.e., the reproductive fitness of Tibetans and its genetic basis, remains elusive. Here, we conduct systematic phenotyping and genome-wide association analysis of 2,252 mother-newborn pairs of indigenous Tibetans, covering 12 reproductive traits and 76 maternal physiological traits. Compared with the lowland immigrants living at high altitudes, indigenous Tibetans show better reproductive outcomes, reflected by their lower abortion rate, higher birth weight, and better fetal development. The results of genome-wide association analyses indicate a polygenic adaptation of reproduction in Tibetans, attributed to the genomic backgrounds of both the mothers and the newborns. Furthermore, the EPAS1-edited mice display higher reproductive fitness under chronic hypoxia, mirroring the situation in Tibetans. Collectively, these results shed new light on the phenotypic pattern and the genetic mechanism of human reproductive fitness in extreme environments.
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Affiliation(s)
- Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Tian Yue
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650000, China
| | - Bin Wang
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China
| | - Zhanying Feng
- CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing 100080, China
| | - Ouzhuluobu
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa 850000, China
| | - Chaoying Cui
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa 850000, China
| | - Kai Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Bin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Liya Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Tianyun Wang
- Department of Medical Genetics, Center for Medical Genetics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Yong Wang
- CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing 100080, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.
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22
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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 : THE PREPRINT SERVER FOR HEALTH SCIENCES 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] [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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23
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Westergaard D, Steinthorsdottir V, Stefansdottir L, Rohde PD, Wu X, Geller F, Tyrmi J, Havulinna AS, Navais PS, Flatley C, Ostrowski SR, Pedersen OB, Erikstrup C, Sørensen E, Mikkelsen C, Brun MT, Jensen BA, Brodersen T, Ullum H, Magnus P, Andreassen OA, Njolstad PR, Kolte AM, Krebs L, Nyegaard M, Hansen TF, Fenstra B, Daly M, Lindgren CM, Thorleifsson G, Stefansson OA, Sveinbjornsson G, Gudbjartsson DF, Thorsteinsdottir U, Banasik K, Jacobsson B, Laisk T, Laivuori H, Stefansson K, Brunak S, Nielsen HS. Pregnancy-Associated Bleeding and Genetics: Five Sequence Variants in the Myometrium and Progesterone Signaling Pathway are associated with postpartum hemorrhage. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.10.23293932. [PMID: 37645979 PMCID: PMC10462219 DOI: 10.1101/2023.08.10.23293932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severity of these complications in maternal-fetal health. Here, we investigated the genetic variation underlying aspects of pregnancy-associated bleeding and identified five loci associated with PPH through a meta-analysis of 21,512 cases and 259,500 controls. Functional annotation analysis indicated candidate genes, HAND2, TBX3, and RAP2C/FRMD7, at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors (PGR). Furthermore, there were strong genetic correlations with birth weight, gestational duration, and uterine fibroids. Early bleeding during pregnancy (28,898 cases and 302,894 controls) yielded no genome-wide association signals, but showed strong genetic correlation with a variety of human traits, indicative of polygenic and pleiotropic effects. Our results suggest that postpartum bleeding is related to myometrium dysregulation, whereas early bleeding is a complex trait related to underlying health and possibly socioeconomic status.
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Affiliation(s)
- David Westergaard
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Methods and Analysis, Statistics Denmark, Copenhagen, Denmark
| | | | | | - Palle Duun Rohde
- Department of Health Science and Technology, Aalborg University, Gistrup, Denmark
| | - Xiaoping Wu
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Frank Geller
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Jaakko Tyrmi
- Centre for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare - THL, Helsinki, Finland
| | - Pol Sole Navais
- Department of Obstetrics and Gynaecology, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | - Christopher Flatley
- Department of Obstetrics and Gynaecology, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | - Sisse Rye Ostrowski
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Birger Pedersen
- Department of Clinical immunology, Zealand University Hospital, Køge, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Erik Sørensen
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Christina Mikkelsen
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Mie Topholm Brun
- Clinical Immunological Research Unit, Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | | | - Thorsten Brodersen
- Department of Clinical immunology, Zealand University Hospital, Køge, Denmark
| | - Henrik Ullum
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Per Magnus
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Pål R Njolstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Astrid Marie Kolte
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Lone Krebs
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Aalborg University, Gistrup, Denmark
| | - Thomas Folkmann Hansen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Danish Headache Center, Department of neurology, Copenhagen University Hospital, Glostrup, Denmark
| | - Bjarke Fenstra
- Department of Clinical immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Mark Daly
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cecilia M Lindgren
- Big Data Institute Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Wellcome Trust Centre Human Genetics, University of Oxford, Oxford, UK
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, Reykjavik University, Reykjavik, Iceland
| | - Karina Banasik
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bo Jacobsson
- Department of Obstetrics and Gynaecology, 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
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynaecology, Tampere University Hospital, Tampere, Finland
- Centre for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, Reykjavik University, Reykjavik, Iceland
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henriette Svarre Nielsen
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Clinical medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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24
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Liu D, Gan Y, Zhang Y, Cui L, Tao T, Zhang J, Zhao J. Fetal genome predicted birth weight and polycystic ovary syndrome in later life: a Mendelian randomization study. Front Endocrinol (Lausanne) 2023; 14:1140499. [PMID: 37351103 PMCID: PMC10282929 DOI: 10.3389/fendo.2023.1140499] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/25/2023] [Indexed: 06/24/2023] Open
Abstract
Associations between lower birth weight and higher polycystic ovary syndrome (PCOS) risk have been reported in previous observational studies, however, the causal relationship is still unknown. Based on decomposed fetal and maternal genetic effects on birth weight (n = 406,063), we conducted a two-sample Mendelian randomization (MR) analysis to assess potential causal relationships between fetal genome predicted birth weight and PCOS risk using a large-scale genome-wide association study (GWAS) including 4,138 PCOS cases and 20,129 controls. To further eliminate the maternally transmitted or non-transmitted effects on fetal growth, we performed a secondary MR analysis by utilizing genetic instruments after excluding maternally transmitted or non-transmitted variants, which were identified in another birth weight GWAS (n = 63,365 parent-offspring trios from Icelandic birth register). Linkage disequilibrium score regression (LDSR) analysis was conducted to estimate the genetic correlation. We found little evidence to support a causal effect of fetal genome determined birth weight on the risk of developing PCOS (primary MR analysis, OR: 0.86, 95% CI: 0.52 to 1.43; secondary MR analysis, OR: 0.86, 95% CI: 0.54 to 1.39). In addition, a marginally significant genetic correlation (rg = -0.14, se = 0.07) between birth weight and PCOS was revealed via LDSR analysis. Our findings indicated that observed associations between birth weight and future PCOS risk are more likely to be attributable to genetic pleiotropy driven by the fetal genome rather than a causal mechanism.
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Affiliation(s)
- Dong Liu
- Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuexin Gan
- Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Zhang
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Linlin Cui
- Center for Reproductive Medicine, The Second Hospital, Cheeloo College of Medicine, National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, China
| | - Tao Tao
- Department of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Jun Zhang
- Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Jian Zhao
- Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
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25
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Jin G, Ma H, Shen H, Hu Z. Polygenic score: An anchor holding the whole life course. Chin Med J (Engl) 2023; 136:883-885. [PMID: 37026867 PMCID: PMC10278760 DOI: 10.1097/cm9.0000000000002648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Indexed: 04/08/2023] Open
Affiliation(s)
- Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211112, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211112, China
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211112, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu 215000, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211112, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211112, China
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211112, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu 215000, China
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Zheng W, He Y, Guo Y, Yue T, Zhang H, Li J, Zhou B, Zeng X, Li L, Wang B, Cao J, Chen L, Li C, Li H, Cui C, Bai C, Qi X, Su B. Large-scale genome sequencing redefines the genetic footprints of high-altitude adaptation in Tibetans. Genome Biol 2023; 24:73. [PMID: 37055782 PMCID: PMC10099689 DOI: 10.1186/s13059-023-02912-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/29/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Tibetans are genetically adapted to high-altitude environments. Though many studies have been conducted, the genetic basis of the adaptation remains elusive due to the poor reproducibility for detecting selective signatures in the Tibetan genomes. RESULTS Here, we present whole-genome sequencing (WGS) data of 1001 indigenous Tibetans, covering the major populated areas of the Qinghai-Tibetan Plateau in China. We identify 35 million variants, and more than one-third of them are novel variants. Utilizing the large-scale WGS data, we construct a comprehensive map of allele frequency and linkage disequilibrium and provide a population-specific genome reference panel, referred to as 1KTGP. Moreover, with the use of a combined approach, we redefine the signatures of Darwinian-positive selection in the Tibetan genomes, and we characterize a high-confidence list of 4320 variants and 192 genes that have undergone selection in Tibetans. In particular, we discover four new genes, TMEM132C, ATP13A3, SANBR, and KHDRBS2, with strong signals of selection, and they may account for the adaptation of cardio-pulmonary functions in Tibetans. Functional annotation and enrichment analysis indicate that the 192 genes with selective signatures are likely involved in multiple organs and physiological systems, suggesting polygenic and pleiotropic effects. CONCLUSIONS Overall, the large-scale Tibetan WGS data and the identified adaptive variants/genes can serve as a valuable resource for future genetic and medical studies of high-altitude populations.
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Affiliation(s)
- Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Tian Yue
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Jun Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Bin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Liya Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bin Wang
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Jingxin Cao
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Li Chen
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chunxia Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Hongyan Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chaoying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Caijuan Bai
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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27
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Solé-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J, Laisk T, LaBella AL, Westergaard D, Bacelis J, Brumpton B, Skotte L, Borges MC, Helgeland Ø, Mahajan A, Wielscher M, Lin F, Briggs C, Wang CA, Moen GH, Beaumont RN, Bradfield JP, Abraham A, Thorleifsson G, Gabrielsen ME, Ostrowski SR, Modzelewska D, Nohr EA, Hypponen E, Srivastava A, Talbot O, Allard C, Williams SM, Menon R, Shields BM, Sveinbjornsson G, Xu H, Melbye M, Lowe W, Bouchard L, Oken E, Pedersen OB, Gudbjartsson DF, Erikstrup C, Sørensen E, Lie RT, Teramo K, Hallman M, Juliusdottir T, Hakonarson H, Ullum H, Hattersley AT, Sletner L, Merialdi M, Rifas-Shiman SL, Steingrimsdottir T, Scholtens D, Power C, West J, Nyegaard M, Capra JA, Skogholt AH, Magnus P, Andreassen OA, Thorsteinsdottir U, Grant SFA, Qvigstad E, Pennell CE, Hivert MF, Hayes GM, Jarvelin MR, McCarthy MI, Lawlor DA, Nielsen HS, Mägi R, Rokas A, Hveem K, Stefansson K, Feenstra B, Njolstad P, Muglia LJ, Freathy RM, Johansson S, Zhang G, Jacobsson B. Genetic effects on the timing of parturition and links to fetal birth weight. Nat Genet 2023; 55:559-567. [PMID: 37012456 PMCID: PMC10101852 DOI: 10.1038/s41588-023-01343-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 02/22/2023] [Indexed: 04/05/2023]
Abstract
The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal-fetal relationship between gestational duration and birth weight.
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Affiliation(s)
- Pol Solé-Navais
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden.
| | - Christopher Flatley
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | | | - Marc Vaudel
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Julius Juodakis
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | - Jing Chen
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Abigail L LaBella
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Methods and Analysis, Statistics Denmark, Copenhagen, Denmark
| | - Jonas Bacelis
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Line Skotte
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Maria C Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Øyvind Helgeland
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Frederick Lin
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Catherine Briggs
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Carol A Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, The University of Newcastle, Callaghan, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, New South Wales, Australia
| | - Gunn-Helen Moen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- University of Queensland Diamantina Institute, University of Queensland, Woolloongabba, Australia
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | | | - Abin Abraham
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Dominika Modzelewska
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Science, University of Gothenburg, Gothenburg, Sweden
| | - Ellen A Nohr
- Research Unit of Gynecology and Obstetrics, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Elina Hypponen
- Australian Centre for Precision Health, Uni Clinical & Health Sciences, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Amit Srivastava
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Octavious Talbot
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Catherine Allard
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CHUS), Sherbrooke, Québec, Canada
| | - Scott M Williams
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Ramkumar Menon
- Department of Obstetrics and Gynaecology, University of Texas Medical Branch, Galveston, TX, USA
| | - Beverley M Shields
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | | | - Huan Xu
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Mads Melbye
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - William Lowe
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-St-Jean - Hôpital Universitaire de Chicoutimi, Saguenay, Québec, Canada
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Ole B Pedersen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Faculty of Health, University of Aarhus, Aarhus, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Rolv T Lie
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Kari Teramo
- Department of Obstetrics and Gynecology, Helsinki University Central Hospital, Helsinki, Finland
- University of Helsinki, Helsinki, Finland
| | - Mikko Hallman
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | | | - Hakon Hakonarson
- The Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Pulmonary Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Line Sletner
- Department of Pediatric and Adolescents Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Mario Merialdi
- Maternal Newborn Health Innovations, PBC, Geneva, Switzerland
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Thora Steingrimsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Obstetrics and Gynecology, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Denise Scholtens
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Christine Power
- Population, Policy, Practice. Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Jane West
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Mette Nyegaard
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - John A Capra
- Bakar Computational Health Sciences Institute and Department of Epidemiology and Statistics, University of California San Francisco, San Francisco, CA, USA
| | - Anne H Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ole A Andreassen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Struan F A Grant
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Divisions of Human Genetics and Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elisabeth Qvigstad
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Craig E Pennell
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, The University of Newcastle, Callaghan, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, New South Wales, Australia
| | - 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
| | - Geoffrey M Hayes
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter of Oulu, University of Oulu, Linnanmaa, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Henriette S Nielsen
- Department of Obstetrics and Gynaecology, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- The Recurrent Pregnancy Loss Unit, The Capital Region, Copenhagen University Hospitals Rigshospitalet & Hvidovre Hospital, Hvidovre, Denmark
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Department of Medicine, Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Kari Stefansson
- deCODE genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Pål Njolstad
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Louis J Muglia
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Rachel M Freathy
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Stefan Johansson
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Ge Zhang
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - 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.
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28
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Decina CS, Hopkins R, Bowden J, Shields BM, Lawlor DA, Warrington NM, Evans DM, Freathy RM, Beaumont RN. Investigating a possible causal relationship between maternal serum urate concentrations and offspring birthweight: a Mendelian randomization study. Int J Epidemiol 2023; 52:178-189. [PMID: 36191079 PMCID: PMC9908052 DOI: 10.1093/ije/dyac186] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 09/14/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Higher urate levels are associated with higher systolic blood pressure (SBP) in adults, and in pregnancy with lower offspring birthweight. Mendelian randomization (MR) analyses suggest a causal effect of higher urate on higher SBP and of higher maternal SBP on lower offspring birthweight. If urate causally reduces birthweight, it might confound the effect of SBP on birthweight. We therefore tested for a causal effect of maternal urate on offspring birthweight. METHODS We tested the association between maternal urate levels and offspring birthweight using multivariable linear regression in the Exeter Family Study of Childhood Health (EFSOCH; n = 872) and UK Biobank (UKB; n = 133 187). We conducted two-sample MR to test for a causal effect of maternal urate [114 single-nucleotide polymorphisms (SNPs); n = 288 649 European ancestry] on offspring birthweight (n = 406 063 European ancestry; maternal SNP effect estimates adjusted for fetal effects). We assessed a causal relationship between urate and SBP using one-sample MR in UKB women (n = 199 768). RESULTS Higher maternal urate was associated with lower offspring birthweight with similar confounder-adjusted magnitudes in EFSOCH [22 g lower birthweight per 1-SD higher urate (95% CI: -50, 6); P = 0.13] and UKB [-28 g (95% CI: -31, -25); P = 1.8 × 10-75]. The MR causal effect estimate was directionally consistent, but smaller [-11 g (95% CI: -25, 3); PIVW = 0.11]. In women, higher urate was causally associated with higher SBP [1.7 mmHg higher SBP per 1-SD higher urate (95% CI: 1.4, 2.1); P = 7.8 × 10-22], consistent with that previously published in women and men. CONCLUSION The marked attenuation of the MR result of maternal urate on offspring birthweight compared with the multivariable regression result suggests previous observational associations may be confounded. The 95% CIs of the MR result included the null but suggest a possible small effect on birthweight. Maternal urate levels are unlikely to be an important contributor to offspring birthweight.
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Affiliation(s)
- Caitlin S Decina
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Rhian Hopkins
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Jack Bowden
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Beverly M Shields
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Nicole M Warrington
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - David M Evans
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Robin N Beaumont
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
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29
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Krushkal J, Vural S, Jensen TL, Wright G, Zhao Y. Increased copy number of imprinted genes in the chromosomal region 20q11-q13.32 is associated with resistance to antitumor agents in cancer cell lines. Clin Epigenetics 2022; 14:161. [PMID: 36461044 PMCID: PMC9716673 DOI: 10.1186/s13148-022-01368-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Parent of origin-specific allelic expression of imprinted genes is epigenetically controlled. In cancer, imprinted genes undergo both genomic and epigenomic alterations, including frequent copy number changes. We investigated whether copy number loss or gain of imprinted genes in cancer cell lines is associated with response to chemotherapy treatment. RESULTS We analyzed 198 human imprinted genes including protein-coding genes and noncoding RNA genes using data from tumor cell lines from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer datasets. We examined whether copy number of the imprinted genes in 35 different genome locations was associated with response to cancer drug treatment. We also analyzed associations of pretreatment expression and DNA methylation of imprinted genes with drug response. Higher copy number of BLCAP, GNAS, NNAT, GNAS-AS1, HM13, MIR296, MIR298, and PSIMCT-1 in the chromosomal region 20q11-q13.32 was associated with resistance to multiple antitumor agents. Increased expression of BLCAP and HM13 was also associated with drug resistance, whereas higher methylation of gene regions of BLCAP, NNAT, SGK2, and GNAS was associated with drug sensitivity. While expression and methylation of imprinted genes in several other chromosomal regions was also associated with drug response and many imprinted genes in different chromosomal locations showed a considerable copy number variation, only imprinted genes at 20q11-q13.32 had a consistent association of their copy number with drug response. Copy number values among the imprinted genes in the 20q11-q13.32 region were strongly correlated. They were also correlated with the copy number of cancer-related non-imprinted genes MYBL2, AURKA, and ZNF217 in that chromosomal region. Expression of genes at 20q11-q13.32 was associated with ex vivo drug response in primary tumor samples from the Beat AML 1.0 acute myeloid leukemia patient cohort. Association of the increased copy number of the 20q11-q13.32 region with drug resistance may be complex and could involve multiple genes. CONCLUSIONS Copy number of imprinted and non-imprinted genes in the chromosomal region 20q11-q13.32 was associated with cancer drug resistance. The genes in this chromosomal region may have a modulating effect on tumor response to chemotherapy.
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Affiliation(s)
- Julia Krushkal
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA.
| | - Suleyman Vural
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA.,Marie-Josee and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | | | - George Wright
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA
| | - Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA
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30
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Hofmeister RJ, Rubinacci S, Ribeiro DM, Buil A, Kutalik Z, Delaneau O. Parent-of-Origin inference for biobanks. Nat Commun 2022; 13:6668. [PMID: 36335127 PMCID: PMC9637181 DOI: 10.1038/s41467-022-34383-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
Abstract
Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.
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Affiliation(s)
- Robin J Hofmeister
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Simone Rubinacci
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Diogo M Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.,University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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31
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Assessing the contribution of genetic nurture to refractive error. Eur J Hum Genet 2022; 30:1226-1232. [PMID: 35618892 PMCID: PMC9626539 DOI: 10.1038/s41431-022-01126-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 05/10/2022] [Accepted: 05/16/2022] [Indexed: 02/04/2023] Open
Abstract
Parents pass on both their genes and environment to offspring, prompting debate about the relative importance of nature versus nurture in the inheritance of complex traits. Advances in molecular genetics now make it possible to quantify an individual's genetic predisposition to a trait via his or her 'polygenic score'. However, part of the risk captured by an individual's polygenic score may actually be attributed to the genotype of their parents. In the most well-studied example of this indirect 'genetic nurture' effect, about half the genetic contribution to educational attainment was found to be attributed to parental alleles, even if those alleles were not inherited by the child. Refractive errors, such as myopia, are a common cause of visual impairment and pose high economic and quality-of-life costs. Despite strong evidence that refractive errors are highly heritable, the extent to which genetic risk is conferred directly via transmitted risk alleles or indirectly via the environment that parents create for their children is entirely unknown. Here, an instrumental variable analysis in 1944 pairs of adult siblings from the United Kingdom was used to quantify the proportion of the genetic risk ('single nucleotide polymorphism (SNP) heritability') of refractive error contributed by genetic nurture. We found no evidence of a contribution from genetic nurture: non-within-family SNP-heritability estimate = 0.213 (95% confidence interval 0.134-0.310) and within-family SNP-heritability estimate = 0.250 (0.152-0.372). Our findings imply the genetic contribution to refractive error is principally an intrinsic effect from alleles transmitted from parents to offspring.
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32
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Wang LQ, Fernandez-Boyano I, Robinson WP. Genetic variation in placental insufficiency: What have we learned over time? Front Cell Dev Biol 2022; 10:1038358. [PMID: 36313546 PMCID: PMC9613937 DOI: 10.3389/fcell.2022.1038358] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/03/2022] [Indexed: 11/28/2022] Open
Abstract
Genetic variation shapes placental development and function, which has long been known to impact fetal growth and pregnancy outcomes such as miscarriage or maternal pre-eclampsia. Early epidemiology studies provided evidence of a strong heritable component to these conditions with both maternal and fetal-placental genetic factors contributing. Subsequently, cytogenetic studies of the placenta and the advent of prenatal diagnosis to detect chromosomal abnormalities provided direct evidence of the importance of spontaneously arising genetic variation in the placenta, such as trisomy and uniparental disomy, drawing inferences that remain relevant to this day. Candidate gene approaches highlighted the role of genetic variation in genes influencing immune interactions at the maternal-fetal interface and angiogenic factors. More recently, the emergence of molecular techniques and in particular high-throughput technologies such as Single-Nucleotide Polymorphism (SNP) arrays, has facilitated the discovery of copy number variation and study of SNP associations with conditions related to placental insufficiency. This review integrates past and more recent knowledge to provide important insights into the role of placental function on fetal and perinatal health, as well as into the mechanisms leading to genetic variation during development.
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Affiliation(s)
- Li Qing Wang
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Icíar Fernandez-Boyano
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Wendy P. Robinson
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- *Correspondence: Wendy P. Robinson,
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33
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Maternal genetic factors in the development of congenital heart defects. Curr Opin Genet Dev 2022; 76:101961. [PMID: 35882070 DOI: 10.1016/j.gde.2022.101961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 06/20/2022] [Accepted: 06/25/2022] [Indexed: 11/24/2022]
Abstract
Congenital heart defects (CHDs) are among the most common, serious birth defects. However, the cause of CHDs is unknown for approximately half of affected individuals and there are few prevention strategies. Although not extensively investigated, maternal genes may contribute to CHD etiology by modifying the effects of maternal exposures (e.g. medications, nutrients), contributing to maternal phenotypes that are associated with an increased risk of CHDs in offspring (e.g. diabetes), or acting as maternal effect genes. Since maternal genes could serve as a target for the primary prevention of CHDs, efforts to further define the contribution of the maternal genome to CHD etiology are warranted.
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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: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [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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35
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Sandovici I, Fernandez-Twinn DS, Hufnagel A, Constância M, Ozanne SE. Sex differences in the intergenerational inheritance of metabolic traits. Nat Metab 2022; 4:507-523. [PMID: 35637347 DOI: 10.1038/s42255-022-00570-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 04/05/2022] [Indexed: 02/02/2023]
Abstract
Strong evidence suggests that early-life exposures to suboptimal environmental factors, including those in utero, influence our long-term metabolic health. This has been termed developmental programming. Mounting evidence suggests that the growth and metabolism of male and female fetuses differ. Therefore, sexual dimorphism in response to pre-conception or early-life exposures could contribute to known sex differences in susceptibility to poor metabolic health in adulthood. However, until recently, many studies, especially those in animal models, focused on a single sex, or, often in the case of studies performed during intrauterine development, did not report the sex of the animal at all. In this review, we (a) summarize the evidence that male and females respond differently to a suboptimal pre-conceptional or in utero environment, (b) explore the potential biological mechanisms that underlie these differences and (c) review the consequences of these differences for long-term metabolic health, including that of subsequent generations.
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Affiliation(s)
- Ionel Sandovici
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Denise S Fernandez-Twinn
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Antonia Hufnagel
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Miguel Constância
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK.
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
| | - Susan E Ozanne
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
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36
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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] [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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Enquobahrie DA, Tekola-Ayele F, Mersha TB. Editorial: Genetic and Epigenetic Insights Into the Developmental Origins of Health and Disease. Front Genet 2022; 12:814126. [PMID: 35186017 PMCID: PMC8856002 DOI: 10.3389/fgene.2021.814126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 11/29/2021] [Indexed: 11/23/2022] Open
Affiliation(s)
- Daniel A. Enquobahrie
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States
| | - 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, MD, United States
| | - Tesfaye B. Mersha
- Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- *Correspondence: Tesfaye B. Mersha,
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38
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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] [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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Affiliation(s)
| | | | | | | | - 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, MD
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Affiliation(s)
- David M Evans
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.
- The University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK.
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40
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Fetal growth: a family affair. Nat Rev Genet 2021; 22:624-625. [PMID: 34302144 DOI: 10.1038/s41576-021-00399-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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