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Tekola-Ayele F, Biedrzycki RJ, Habtewold TD, Wijesiriwardhana P, Burt A, Marsit CJ, Ouidir M, Wapner R. Sex-differentiated placental methylation and gene expression regulation has implications for neonatal traits and adult diseases. Nat Commun 2025; 16:4004. [PMID: 40312437 PMCID: PMC12045980 DOI: 10.1038/s41467-025-58128-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 03/10/2025] [Indexed: 05/03/2025] Open
Abstract
Sex differences in physiological and disease traits are pervasive and begin during early development, but the genetic architecture of these differences is largely unknown. Here, we leverage the human placenta, a transient organ during pregnancy critical to fetal development, to investigate the impact of sex in the regulatory landscape of placental autosomal methylome and transcriptome, and its relevance to health and disease. We find that placental methylation and its genetic regulation are extensively impacted by fetal sex, whereas sex differences in placental gene expression and its genetic regulation are limited. We identify molecular processes and regulatory targets that are enriched in a sex-specific manner, and find enrichment of imprinted genes in sex-differentiated placental methylation, including female-biased methylation within the well-known KCNQ1OT1/CDKN1C imprinting cluster of genes expressed in a parent-of-origin dependent manner. We establish that several sex-differentiated genetic effects on placental methylation and gene expression colocalize with birthweight and adult disease genetic associations, facilitating mechanistic insights on early life origins of health and disease outcomes shaped by sex.
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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.
| | - 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, Bethesda, MD, USA
| | - Tesfa Dejenie Habtewold
- 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
| | - Prabhavi Wijesiriwardhana
- 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
| | - Amber Burt
- Gangarosa Department of Environmental Health, Rollins School of Public Health of Emory University, Atlanta, GA, USA
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Rollins School of Public Health of Emory University, Atlanta, GA, 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
- University of Grenoble Alpes, Inserm, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
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Le R, Biedrzycki RJ, Tekola-Ayele F. Maternal obesity and ancestry distance in influencing birth outcomes. Int J Obes (Lond) 2025:10.1038/s41366-025-01783-9. [PMID: 40221546 DOI: 10.1038/s41366-025-01783-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 03/25/2025] [Accepted: 04/01/2025] [Indexed: 04/14/2025]
Abstract
BACKGROUND Maternal pre-pregnancy obesity has been associated with birth outcomes, but the influence of genetic distance (GD) on this relationship is unclear. Therefore, the objective of this study was to assess the interplay of GD and maternal obesity on birthweight, placental weight, and large for gestational age (LGA). METHODS We used data from the NICHD Fetal Growth Studies-Singletons cohort, a prospective cohort study of multi-ancestral pregnant women. GD was estimated using data from 1810 women across four ancestral reference populations. We categorized GD into five quintiles, with quintile one and quintile five representing the closest and farthest distances, respectively. Linear regression models were used to test association between GD and birth outcomes and to estimate the association of interaction of GD and maternal obesity with birth outcomes. RESULTS Farther maternal GD from an African reference was significantly associated with higher birthweight and higher odds of LGA, with associations persisting after adjusting for socioeconomic status (SES). The interaction between the third Amerindigenous GD quintile and obesity was significantly associated with a 198 g larger placental weight (95% CI = 51-345, p = 0.009) compared to the first Amerindigenous GD quintile. We also found the interaction between East Asian fourth GD quintile and obesity to be significantly associated with 86.0% lower odds of infants being born LGA (OR = 0.14 g, 95% CI = 0.02-74, p = 0.031) compared to the first quintile. These associations persisted after SES adjustment. CONCLUSIONS Interplays between maternal GD from Amerindigenous and East Asian references and pre-pregnancy obesity influence placental weight and risk of LGA. The results underline that consideration of maternal obesity in the context of GD from multiple ancestries and SES may facilitate interventions that will minimize adverse pregnancy outcomes. CLINICAL TRIAL REGISTRATION The study has been registered at ClinicalTrials.gov (Trial registration: NCT00912132).
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Affiliation(s)
- Randy Le
- 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, USA
- National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, 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, Bethesda, 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, MD, USA.
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Grantz KL, Lee W, Mack LM, Sanz Cortes M, Goncalves LF, Espinoza J, Newman RB, Grobman WA, Wapner RJ, Fuchs K, D'Alton ME, Skupski DW, Owen J, Sciscione A, Wing DA, Nageotte MP, Ranzini AC, Chien EK, Craigo S, Sherman S, Gore-Langton RE, He D, Tekola-Ayele F, Zhang C, Grewal J, Chen Z. Multiethnic growth standards for fetal body composition and organ volumes derived from 3D ultrasonography. Am J Obstet Gynecol 2025; 232:324.e1-324.e160. [PMID: 38838912 PMCID: PMC11612034 DOI: 10.1016/j.ajog.2024.05.049] [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: 02/22/2024] [Revised: 05/24/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND A major goal of contemporary obstetrical practice is to optimize fetal growth and development throughout pregnancy. To date, fetal growth during prenatal care is assessed by performing ultrasonographic measurement of 2-dimensional fetal biometry to calculate an estimated fetal weight. Our group previously established 2-dimensional fetal growth standards using sonographic data from a large cohort with multiple sonograms. A separate objective of that investigation involved the collection of fetal volumes from the same cohort. OBJECTIVE The Fetal 3D Study was designed to establish standards for fetal soft tissue and organ volume measurements by 3-dimensional ultrasonography and compare growth trajectories with conventional 2-dimensional measures where applicable. STUDY DESIGN The National Institute of Child Health and Human Development Fetal 3D Study included research-quality images of singletons collected in a prospective, racially and ethnically diverse, low-risk cohort of pregnant individuals at 12 U.S. sites, with up to 5 scans per fetus (N=1730 fetuses). Abdominal subcutaneous tissue thickness was measured from 2-dimensional images and fetal limb soft tissue parameters extracted from 3-dimensional multiplanar views. Cerebellar, lung, liver, and kidney volumes were measured using virtual organ computer aided analysis. Fractional arm and thigh total volumes, and fractional lean limb volumes were measured, with fractional limb fat volume calculated by subtracting lean from total. For each measure, weighted curves (fifth, 50th, 95th percentiles) were derived from 15 to 41 weeks' using linear mixed models for repeated measures with cubic splines. RESULTS Subcutaneous thickness of the abdomen, arm, and thigh increased linearly, with slight acceleration around 27 to 29 weeks. Fractional volumes of the arm, thigh, and lean limb volumes increased along a quadratic curvature, with acceleration around 29 to 30 weeks. In contrast, growth patterns for 2-dimensional humerus and femur lengths demonstrated a logarithmic shape, with fastest growth in the second trimester. The mid-arm area curve was similar in shape to fractional arm volume, with an acceleration around 30 weeks, whereas the curve for the lean arm area was more gradual. The abdominal area curve was similar to the mid-arm area curve with an acceleration around 29 weeks. The mid-thigh and lean area curves differed from the arm areas by exhibiting a deceleration at 39 weeks. The growth curves for the mid-arm and thigh circumferences were more linear. Cerebellar 2-dimensional diameter increased linearly, whereas cerebellar 3-dimensional volume growth gradually accelerated until 32 weeks followed by a more linear growth. Lung, kidney, and liver volumes all demonstrated gradual early growth followed by a linear acceleration beginning at 25 weeks for lungs, 26 to 27 weeks for kidneys, and 29 weeks for liver. CONCLUSION Growth patterns and timing of maximal growth for 3-dimensional lean and fat measures, limb and organ volumes differed from patterns revealed by traditional 2-dimensional growth measures, suggesting these parameters reflect unique facets of fetal growth. Growth in these three-dimensional measures may be altered by genetic, nutritional, metabolic, or environmental influences and pregnancy complications, in ways not identifiable using corresponding 2-dimensional measures. Further investigation into the relationships of these 3-dimensional standards to abnormal fetal growth, adverse perinatal outcomes, and health status in postnatal life is warranted.
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Affiliation(s)
- Katherine L Grantz
- 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.
| | - Wesley Lee
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX
| | - Lauren M Mack
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX
| | | | - Luis F Goncalves
- Department of Radiology, Phoenix Children's Hospital, Phoenix, AZ; Departments of Child Health and Radiology, University of Arizona College of Medicine, Phoenix, AZ; Department of Radiology, Mayo Clinic, Phoenix, AZ; Department of Radiology, Creighton University, Phoenix, AZ
| | - Jimmy Espinoza
- Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology and Reproductive Sciences, McGovern Medical School at the University of Texas Health Science Center Houston (UTHealth)
| | - Roger B Newman
- Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC
| | - William A Grobman
- Department of Obstetrics and Gynecology, The Ohio State University Wexner Medical Center
| | - Ronald J Wapner
- Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, NY
| | - Karin Fuchs
- Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, NY
| | - Mary E D'Alton
- Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, NY
| | | | - John Owen
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, AL
| | - Anthony Sciscione
- Department of Obstetrics and Gynecology, Thomas Jefferson School of Medicine
| | - Deborah A Wing
- University of California, Irvine, Orange, CA; Fountain Valley Regional Hospital and Medical Center, Fountain Valley, CA
| | - Michael P Nageotte
- Miller Children's and Women's Hospital Long Beach/Long Beach Memorial Medical Center, Long Beach, CA
| | - Angela C Ranzini
- Women and Infants Hospital of Rhode Island; Saint Peter's University Hospital, New Brunswick, NJ
| | - Edward K Chien
- Women and Infants Hospital of Rhode Island; Case Western Reserve University, Cleveland Clinic Health System, Cleveland, OH
| | - Sabrina Craigo
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, MA
| | | | | | - Dian He
- 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; The Prospective Group, Inc, Fairfax, VA
| | - 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
| | - 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, MD; Global Center for Asian Women's Health (GloW) and Bia-Echo Asia Centre for Reproductive Longevity & Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jagteshwar Grewal
- Biostatistics and Bioinformatics 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
| | - Zhen Chen
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX
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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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Lee S, Hahn G, Hecker J, Lutz SM, Mullin K, Hide W, Bertram L, DeMeo DL, Tanzi RE, Lange C, Prokopenko D. A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets. Brief Bioinform 2023; 24:bbac611. [PMID: 36585781 PMCID: PMC9851291 DOI: 10.1093/bib/bbac611] [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] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/07/2022] [Accepted: 12/11/2022] [Indexed: 01/01/2023] Open
Abstract
Genetic similarity matrices are commonly used to assess population substructure (PS) in genetic studies. Through simulation studies and by the application to whole-genome sequencing (WGS) data, we evaluate the performance of three genetic similarity matrices: the unweighted and weighted Jaccard similarity matrices and the genetic relationship matrix. We describe different scenarios that can create numerical pitfalls and lead to incorrect conclusions in some instances. We consider scenarios in which PS is assessed based on loci that are located across the genome ('globally') and based on loci from a specific genomic region ('locally'). We also compare scenarios in which PS is evaluated based on loci from different minor allele frequency bins: common (>5%), low-frequency (5-0.5%) and rare (<0.5%) single-nucleotide variations (SNVs). Overall, we observe that all approaches provide the best clustering performance when computed based on rare SNVs. The performance of the similarity matrices is very similar for common and low-frequency variants, but for rare variants, the unweighted Jaccard matrix provides preferable clustering features. Based on visual inspection and in terms of standard clustering metrics, its clusters are the densest and the best separated in the principal component analysis of variants with rare SNVs compared with the other methods and different allele frequency cutoffs. In an application, we assessed the role of rare variants on local and global PS, using WGS data from multiethnic Alzheimer's disease data sets and European or East Asian populations from the 1000 Genome Project.
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Affiliation(s)
- Sanghun Lee
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Consilience, Division of Medicine, Graduate school, Dankook University, South Korea
- NH Institute for Natural Product Research, Myungji Hospital, South Korea
| | - Georg Hahn
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sharon M Lutz
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Winston Hide
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rudolph E Tanzi
- Harvard Medical School, Boston, MA, USA
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dmitry Prokopenko
- Harvard Medical School, Boston, MA, USA
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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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: 15] [Impact Index Per Article: 5.0] [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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Grantz KL, Grewal J, Kim S, Grobman WA, Newman RB, Owen J, Sciscione A, Skupski D, Chien EK, Wing DA, Wapner RJ, Ranzini AC, Nageotte MP, Craigo S, Hinkle SN, D’Alton ME, He D, Tekola-Ayele F, Hediger ML, Buck Louis GM, Zhang C, Albert PS. Unified standard for fetal growth: the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies. Am J Obstet Gynecol 2022; 226:576-587.e2. [PMID: 34906542 DOI: 10.1016/j.ajog.2021.12.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/03/2021] [Accepted: 12/06/2021] [Indexed: 11/25/2022]
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8
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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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