{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T15:43:34Z","timestamp":1772639014476,"version":"3.50.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"University of California Los Angeles Children&apos;s Discovery and Innovation Institute, Department of Pediatrics"},{"DOI":"10.13039\/100000062","name":"U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R01-124417-01"],"award-info":[{"award-number":["R01-124417-01"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R01-124417-01"],"award-info":[{"award-number":["R01-124417-01"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"name":"U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Perinatol"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1038\/s41372-022-01549-5","type":"journal-article","created":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T12:15:05Z","timestamp":1667304905000},"page":"44-51","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Pregnancies complicated by gestational diabetes and fetal growth restriction: an analysis of maternal and fetal body composition using magnetic resonance imaging"],"prefix":"10.1038","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7717-0425","authenticated-orcid":false,"given":"Katie M.","family":"Strobel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sevgi Gokce","family":"Kafali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shu-Fu","family":"Shih","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6322-1554","authenticated-orcid":false,"given":"Alexandra M.","family":"Artura","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rinat","family":"Masamed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Elashoff","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2585-5916","authenticated-orcid":false,"given":"Holden H.","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6658-7981","authenticated-orcid":false,"given":"Kara L.","family":"Calkins","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,1]]},"reference":[{"key":"1549_CR1","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.reprotox.2011.05.002","volume":"32","author":"A Ornoy","year":"2011","unstructured":"Ornoy A. Prenatal origin of obesity and their complications: Gestational diabetes, maternal overweight and the paradoxical effects of fetal growth restriction and macrosomia. Reprod Toxicol. 2011;32:205\u201312. https:\/\/doi.org\/10.1016\/j.reprotox.2011.05.002.","journal-title":"Reprod Toxicol"},{"key":"1549_CR2","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1016\/j.tem.2018.09.004","volume":"29","author":"EC Johns","year":"2018","unstructured":"Johns EC, Denison FC, Norman JE, Reynolds RM. Gestational diabetes mellitus: mechanisms, treatment, and complications. Trends Endocrinol Metab. 2018;29:743\u201354. https:\/\/doi.org\/10.1016\/j.tem.2018.09.004.","journal-title":"Trends Endocrinol Metab"},{"key":"1549_CR3","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1055\/s-0031-1275516","volume":"29","author":"SR Thorn","year":"2011","unstructured":"Thorn SR, Rozance PJ, Brown LD, Hay WW. The intrauterine growth restriction phenotype: fetal adaptations and potential implications for later life insulin resistance and diabetes. Semin Reprod Med. 2011;29:225\u201336.","journal-title":"Semin Reprod Med"},{"key":"1549_CR4","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1097\/GRF.0b013e318299c39d.","volume":"56","author":"MG Ross","year":"2013","unstructured":"Ross MG, Desai M. Developmental programming of offspring obesity, adipogenesis, and appetite. Clin Obstet Gynecol. 2013;56:529\u201336. https:\/\/doi.org\/10.1097\/GRF.0b013e318299c39d.","journal-title":"Clin Obstet Gynecol"},{"key":"1549_CR5","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1159\/000371628","volume":"66","author":"K Kc","year":"2015","unstructured":"Kc K, Shakya S, Zhang H. Gestational diabetes mellitus and macrosomia: a literature review. Ann Nutr Metab. 2015;66:14\u201320. https:\/\/doi.org\/10.1159\/000371628.","journal-title":"Ann Nutr Metab"},{"key":"1549_CR6","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1007\/s00059-014-4175-1","volume":"40","author":"Y Wang","year":"2015","unstructured":"Wang Y, He S, He J, Wang S, Liu K, Chen X. Predictive value of visceral adiposity index for type 2 diabetes mellitus: a 15-year prospective cohort study. Herz. 2015;40:277\u201381. https:\/\/doi.org\/10.1007\/s00059-014-4175-1.","journal-title":"Herz"},{"key":"1549_CR7","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1097\/MPG.0000000000002309","volume":"68","author":"KV Ly","year":"2019","unstructured":"Ly KV, Armstrong T, Yeh J, Ghahremani S, Kim GH, Wu HH, et al. Free-breathing magnetic resonance imaging assessment of body composition in healthy and overweight children: an observational study. J Pediatr Gastroenterol Nutr. 2019;68:782\u20137. https:\/\/doi.org\/10.1097\/MPG.0000000000002309.","journal-title":"J Pediatr Gastroenterol Nutr"},{"key":"1549_CR8","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/j.jpeds.2017.12.017","volume":"196","author":"A Frondas-Chauty","year":"2018","unstructured":"Frondas-Chauty A, Simon L, Flamant C, Hanf M, Darmaun D, Roz\u00e9 JC. Deficit of fat free mass in very preterm infants at discharge is associated with neurological impairment at age 2 years. J Pediatr. 2018;196:301\u20134. https:\/\/doi.org\/10.1016\/j.jpeds.2017.12.017.","journal-title":"J Pediatr"},{"key":"1549_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1136\/jim-2018-000722","volume":"66","author":"M Borga","year":"2018","unstructured":"Borga M, West J, Bell JD, Harvey NC, Romu T, Heymsfield SB, et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. 2018;66:1\u20139. https:\/\/doi.org\/10.1136\/jim-2018-000722.","journal-title":"J Investig Med"},{"key":"1549_CR10","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1139\/y96-072","volume":"74","author":"R Ross","year":"1996","unstructured":"Ross R. Magnetic resonance imaging provides new insights into the characterization of adipose and lean tissue distribution. Can J Physiol Pharm. 1996;74:778\u201385.","journal-title":"Can J Physiol Pharm"},{"key":"1549_CR11","doi-asserted-by":"publisher","first-page":"876","DOI":"10.1007\/s00247-019-04384-7","volume":"49","author":"T Armstrong","year":"2019","unstructured":"Armstrong T, Ly KV, Ghahremani S, Calkins KL, Wu HH. Free-breathing 3-D quantification of infant body composition and hepatic fat using a stack-of-radial magnetic resonance imaging technique. Pediatr Radiol. 2019;49:876\u201388. https:\/\/doi.org\/10.1007\/s00247-019-04384-7.","journal-title":"Pediatr Radiol"},{"key":"1549_CR12","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1002\/jmri.23741","volume":"36","author":"SB Reeder","year":"2012","unstructured":"Reeder SB, Hu HH, Sirlin CB. Proton density fat-fraction: a standardized MR-based biomarker of tissue fat concentration. J Magn Reson Imaging. 2012;36:1011\u20134. https:\/\/doi.org\/10.1002\/jmri.23741.","journal-title":"J Magn Reson Imaging"},{"key":"1549_CR13","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1148\/radiol.2017170550","volume":"286","author":"T Yokoo","year":"2018","unstructured":"Yokoo T, Serai SD, Pirasteh A, Bashir MR, Hamilton G, Hernando D, et al. RSNA-QIBA PDFF Biomarker Committee. Linearity, bias, and precision of hepatic proton density fat fraction measurements by using MR imaging: a meta-analysis. Radiology. 2018;286:486\u201398. https:\/\/doi.org\/10.1148\/radiol.2017170550.","journal-title":"Radiology"},{"key":"1549_CR14","doi-asserted-by":"publisher","first-page":"1887","DOI":"10.1002\/hep.27666","volume":"61","author":"JB Schwimmer","year":"2015","unstructured":"Schwimmer JB, Middleton MS, Behling C, Newton KP, Awai HI, Paiz MN, et al. Magnetic resonance imaging and liver histology as biomarkers of hepatic steatosis in children with nonalcoholic fatty liver disease. Hepatology. 2015;61:1887\u201395. https:\/\/doi.org\/10.1002\/hep.27666.","journal-title":"Hepatology"},{"key":"1549_CR15","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1002\/hep.29797","volume":"68","author":"C Caussy","year":"2018","unstructured":"Caussy C, Reeder SB, Sirlin CB, Loomba R. Non\u2010invasive, quantitative assessment of liver fat by MRI\u2010PDFF as an endpoint in NASH trials. Hepatology. 2018;68:763\u2013772.","journal-title":"Hepatology"},{"key":"1549_CR16","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1002\/hep.31624","volume":"73","author":"R Loomba","year":"2021","unstructured":"Loomba R. MRI-proton density fat fraction treatment response criteria in nonalcoholic steatohepatitis. Hepatology. 2021;73:881\u20133. https:\/\/doi.org\/10.1002\/hep.31624.","journal-title":"Hepatology"},{"key":"1549_CR17","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s00247-017-4038-z","volume":"48","author":"E Blondiaux","year":"2018","unstructured":"Blondiaux E, Chougar L, Gelot A, Valence S, Audureau E, Ducou le Pointe H, et al. Developmental patterns of fetal fat and corresponding signal on T1-weighted magnetic resonance imaging. Pediatr Radiol. 2018;48:317\u201324. https:\/\/doi.org\/10.1007\/s00247-017-4038-z.","journal-title":"Pediatr Radiol"},{"key":"1549_CR18","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/s00247-013-2857-0","volume":"44","author":"T Victoria","year":"2014","unstructured":"Victoria T, Jaramillo D, Roberts TP, Zarnow D, Johnson AM, Delgado J, et al. Fetal magnetic resonance imaging: jumping from 1.5 to 3 tesla (preliminary experience). Pediatr Radiol. 2014;44:376\u201386. https:\/\/doi.org\/10.1007\/s00247-013-2857-0.","journal-title":"Pediatr Radiol"},{"key":"1549_CR19","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1002\/jmri.26203","volume":"49","author":"T Armstrong","year":"2019","unstructured":"Armstrong T, Liu D, Martin T, Masamed R, Janzen C, Wong C, et al. 3D R2* mapping of the placenta during early gestation using free-breathing multiecho stack-of-radial MRI at 3\u2009T. J Magn Reson Imaging. 2019;49:291\u2013303. https:\/\/doi.org\/10.1002\/jmri.26203.","journal-title":"J Magn Reson Imaging"},{"key":"1549_CR20","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1001\/jama.2021.11922","volume":"326","author":"KW Davidson","year":"2021","unstructured":"US Preventive Services Task Force, Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, et al. Screening for gestational diabetes: US preventive services task force recommendation statement. JAMA. 2021;326:531\u20138. https:\/\/doi.org\/10.1001\/jama.2021.11922.","journal-title":"JAMA"},{"key":"1549_CR21","doi-asserted-by":"publisher","first-page":"100382","DOI":"10.1016\/j.ajogmf.2021.100382","volume":"3","author":"CA Combs","year":"2021","unstructured":"Combs CA, Castillo R, Webb GW, Del Rosario A. Impact of adding abdominal circumference to the definition of fetal growth restriction. Am J Obstet Gynecol MFM. 2021;3:100382. https:\/\/doi.org\/10.1016\/j.ajogmf.2021.100382.","journal-title":"Am J Obstet Gynecol MFM"},{"key":"1549_CR22","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1002\/mrm.25054","volume":"72","author":"X Zhong","year":"2014","unstructured":"Zhong X, Nickel MD, Kannengiesser SA, Dale BM, Kiefer B, Bashir MR. Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med. 2014;72:1353\u201365. https:\/\/doi.org\/10.1002\/mrm.25054.","journal-title":"Magn Reson Med"},{"key":"1549_CR23","doi-asserted-by":"publisher","first-page":"3915","DOI":"10.1002\/mrm.27689","volume":"81","author":"S Mandava","year":"2019","unstructured":"Mandava S, Keerthivasan MB, Martin DR, Altbach MI, Bilgin A. Radial streak artifact reduction using phased array beamforming. Magn Reson Med. 2019;81:3915\u201323. https:\/\/doi.org\/10.1002\/mrm.27689.","journal-title":"Magn Reson Med"},{"key":"1549_CR24","unstructured":"Shih S-F, Wu HH. A beamforming-based coil combination method to reduce streaking artifacts and preserve phase fidelity in radial MRI. Proceedings of the ISMRM 30th Annual Meeting, 2022, p1697."},{"key":"1549_CR25","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s00247-018-4127-7","volume":"48","author":"T Armstrong","year":"2018","unstructured":"Armstrong T, Ly KV, Murthy S, Ghahremani S, Kim GHJ, Calkins KL, et al. Free-breathing quantification of hepatic fat in healthy children and children with nonalcoholic fatty liver disease using a multi-echo 3-D stack-of-radial MRI technique. Pediatr Radiol. 2018;48:941\u201353. https:\/\/doi.org\/10.1007\/s00247-018-4127-7.","journal-title":"Pediatr Radiol"},{"key":"1549_CR26","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.mri.2021.10.016","volume":"85","author":"T Armstrong","year":"2022","unstructured":"Armstrong T, Zhong X, Shih SF, Felker E, Lu DS, Dale BM, et al. Free-breathing 3D stack-of-radial MRI quantification of liver fat and R2* in adults with fatty liver disease. Magn Reson Imaging. 2022;85:141\u201352. https:\/\/doi.org\/10.1016\/j.mri.2021.10.016.","journal-title":"Magn Reson Imaging"},{"key":"1549_CR27","doi-asserted-by":"publisher","unstructured":"Story JD, Ghahremani S, Kafali SG, Shih S-F, Kuwahara K, Calkins KL, et al. Using free-breathing MRI to quantify pancreatic fat and investigate spatial heterogeneity in children. J Magn Reson Imaging. 2022, in press. https:\/\/doi.org\/10.1002\/jmri.28337. PMID: 35778376.","DOI":"10.1002\/jmri.28337"},{"key":"1549_CR28","doi-asserted-by":"publisher","first-page":"e214","DOI":"10.1542\/peds.2009-0913","volume":"125","author":"IE Olsen","year":"2010","unstructured":"Olsen IE, Groveman SA, Lawson ML, Clark RH, Zemel BS. New intrauterine growth curves based on United States data. Pediatrics. 2010;125:e214\u201324. https:\/\/doi.org\/10.1542\/peds.2009-0913.","journal-title":"Pediatrics"},{"key":"1549_CR29","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1016\/j.jbi.2008.08.010","volume":"42","author":"PA Harris","year":"2009","unstructured":"Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377\u201381. https:\/\/doi.org\/10.1016\/j.jbi.2008.08.010.","journal-title":"J Biomed Inform"},{"key":"1549_CR30","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1515\/JPM.2011.122","volume":"40","author":"V Berger-Kulemann","year":"2011","unstructured":"Berger-Kulemann V, Brugger PC, Reisegger M, Klein K, Hachemian N, Koelblinger C, et al. Quantification of the subcutaneous fat layer with MRI in fetuses of healthy mothers with no underlying metabolic disease vs. fetuses of diabetic and obese mothers. J Perinat Med. 2011;40:179\u201384. https:\/\/doi.org\/10.1515\/JPM.2011.122.","journal-title":"J Perinat Med"},{"key":"1549_CR31","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1080\/14767058.2018.1506438","volume":"33","author":"SA Giza","year":"2020","unstructured":"Giza SA, Olmstead C, McCooeye DA, Miller MR, Penava DA, Eastabrook GD, et al. Measuring fetal adipose tissue using 3D water-fat magnetic resonance imaging: a feasibility study. J Matern Fetal Neonatal Med. 2020;33:831\u20137. https:\/\/doi.org\/10.1080\/14767058.2018.1506438.","journal-title":"J Matern Fetal Neonatal Med"},{"key":"1549_CR32","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1002\/uog.12382","volume":"42","author":"D Anblagan","year":"2013","unstructured":"Anblagan D, Deshpande R, Jones NW, Costigan C, Bugg G, Raine-Fenning N, et al. Measurement of fetal fat in utero in normal and diabetic pregnancies using magnetic resonance imaging. Ultrasound Obstet Gynecol. 2013;42:335\u201340. https:\/\/doi.org\/10.1002\/uog.12382.","journal-title":"Ultrasound Obstet Gynecol"},{"key":"1549_CR33","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1080\/01443615.2018.1530971","volume":"39","author":"N K\u00f6\u015f\u00fc\u015f","year":"2019","unstructured":"K\u00f6\u015f\u00fc\u015f N, K\u00f6\u015f\u00fc\u015f A. Can fetal abdominal visceral adipose tissue and subcutaneous fat thickness be used for correct estimation of fetal weight? A preliminary study. J Obstet Gynaecol. 2019;39:594\u2013600. https:\/\/doi.org\/10.1080\/01443615.2018.1530971.","journal-title":"J Obstet Gynaecol"},{"key":"1549_CR34","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.1001\/jama.2021.6949","volume":"325","author":"KW Davidson","year":"2021","unstructured":"US Preventive Services Task Force, Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, et al. Behavioral counseling interventions for healthy weight and weight gain in pregnancy: US preventive services task force recommendation statement. JAMA. 2021;325:2087\u201393. https:\/\/doi.org\/10.1001\/jama.2021.6949.","journal-title":"JAMA"},{"key":"1549_CR35","doi-asserted-by":"publisher","first-page":"3342","DOI":"10.3390\/ijms19113342","volume":"19","author":"JF Plows","year":"2018","unstructured":"Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The pathophysiology of gestational diabetes mellitus. Int J Mol Sci. 2018;19:3342. https:\/\/doi.org\/10.3390\/ijms19113342.","journal-title":"Int J Mol Sci"},{"key":"1549_CR36","doi-asserted-by":"publisher","first-page":"4554","DOI":"10.18632\/oncotarget.27832","volume":"11","author":"J Bader","year":"2020","unstructured":"Bader J, Carson M, Enos R, Velazquez K, Sougiannis A, Singh U, et al. High-fat diet-fed ovariectomized mice are susceptible to accelerated subcutaneous tumor growth potentially through adipose tissue inflammation, local insulin-like growth factor release, and tumor associated macrophages. Oncotarget. 2020;11:4554\u201369. https:\/\/doi.org\/10.18632\/oncotarget.27832.","journal-title":"Oncotarget"},{"key":"1549_CR37","doi-asserted-by":"publisher","first-page":"3644","DOI":"10.3390\/nu13103644","volume":"13","author":"Y Zhou","year":"2021","unstructured":"Zhou Y, Zhao R, Lyu Y, Shi H, Ye W, Tan Y, et al. Serum and amniotic fluid metabolic profile changes in response to gestational diabetes mellitus and the association with maternal-fetal outcomes. Nutrients. 2021;13:3644. https:\/\/doi.org\/10.3390\/nu13103644.","journal-title":"Nutrients"},{"key":"1549_CR38","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1038\/s41366-021-00975-3","volume":"46","author":"K Tan","year":"2022","unstructured":"Tan K, Tint MT, Michael N, Yap F, Chong YS, Tan KH, et al. Determinants of cord blood adipokines and association with neonatal abdominal adipose tissue distribution. Int J Obes (Lond). 2022;46:637\u201345. https:\/\/doi.org\/10.1038\/s41366-021-00975-3.","journal-title":"Int J Obes (Lond)"},{"key":"1549_CR39","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1080\/01443610120071947","volume":"21","author":"J Skinner","year":"2001","unstructured":"Skinner J, O\u2019Donoghue K, Gardeil F, Greene R, Turner MJ. Is fetal abdominal subcutaneous fat comparable with established indices of growth restriction? J Obstet Gynaecol. 2001;21:439\u201342. https:\/\/doi.org\/10.1080\/01443610120071947.","journal-title":"J Obstet Gynaecol"},{"key":"1549_CR40","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.mce.2016.03.017","volume":"435","author":"LD Brown","year":"2016","unstructured":"Brown LD, Hay WW Jr. Impact of placental insufficiency on fetal skeletal muscle growth. Mol Cell Endocrinol. 2016;435:69\u201377. https:\/\/doi.org\/10.1016\/j.mce.2016.03.017.","journal-title":"Mol Cell Endocrinol"},{"key":"1549_CR41","doi-asserted-by":"publisher","first-page":"1141","DOI":"10.1001\/jamapediatrics.2020.2673","volume":"174","author":"KS de Fluiter","year":"2020","unstructured":"de Fluiter KS, van Beijsterveldt IALP, Breij LM, Acton D, Hokken-Koelega ACS. Association between fat mass in early life and later fat mass trajectories. JAMA Pediatr. 2020;174:1141\u20138. https:\/\/doi.org\/10.1001\/jamapediatrics.2020.2673.","journal-title":"JAMA Pediatr"},{"key":"1549_CR42","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1093\/ije\/dyaa143","volume":"49","author":"YY Ong","year":"2020","unstructured":"Ong YY, Sadananthan SA, Aris IM, Tint MT, Yuan WL, Huang JY, et al. Mismatch between poor fetal growth and rapid postnatal weight gain in the first 2 years of life is associated with higher blood pressure and insulin resistance without increased adiposity in childhood: the GUSTO cohort study. Int J Epidemiol. 2020;49:1591\u2013603. https:\/\/doi.org\/10.1093\/ije\/dyaa143.","journal-title":"Int J Epidemiol"},{"key":"1549_CR43","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1159\/000342564","volume":"106","author":"MF Rolland-Cachera","year":"2013","unstructured":"Rolland-Cachera MF, P\u00e9neau S. Growth trajectories associated with adult obesity. World Rev Nutr Diet. 2013;106:127\u201334. https:\/\/doi.org\/10.1159\/000342564.","journal-title":"World Rev Nutr Diet"},{"key":"1549_CR44","doi-asserted-by":"publisher","first-page":"e0192900","DOI":"10.1371\/journal.pone.0192900","volume":"13","author":"KJ Sinclair","year":"2018","unstructured":"Sinclair KJ, Friesen-Waldner LJ, McCurdy CM, Wiens CN, Wade TP, de Vrijer B, et al. Quantification of fetal organ volume and fat deposition following in utero exposure to maternal Western Diet using MRI. PLoS One. 2018;13:e0192900. https:\/\/doi.org\/10.1371\/journal.pone.0192900.","journal-title":"PLoS One"},{"key":"1549_CR45","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1186\/s12944-021-01521-w","volume":"20","author":"SW Huang","year":"2021","unstructured":"Huang SW, Ou YC, Tang KS, Yu HR, Huang LT, Tain YL, et al. Metformin ameliorates maternal high-fat diet-induced maternal dysbiosis and fetal liver apoptosis. Lipids Health Dis. 2021;20:100 https:\/\/doi.org\/10.1186\/s12944-021-01521-w.","journal-title":"Lipids Health Dis"},{"key":"1549_CR46","doi-asserted-by":"publisher","first-page":"736944","DOI":"10.3389\/fnut.2021.736944","volume":"8","author":"YW Wang","year":"2021","unstructured":"Wang YW, Yu HR, Tiao MM, Tain YL, Lin IC, Sheen JM, et al. Maternal obesity related to high fat diet induces placenta remodeling and gut microbiome shaping that are responsible for fetal liver lipid dysmetabolism. Front Nutr. 2021;8:736944. https:\/\/doi.org\/10.3389\/fnut.2021.736944.","journal-title":"Front Nutr"},{"key":"1549_CR47","doi-asserted-by":"publisher","first-page":"12107","DOI":"10.1523\/JNEUROSCI.2642-08.2008","volume":"28","author":"GQ Chang","year":"2008","unstructured":"Chang GQ, Gaysinskaya V, Karatayev O, Leibowitz SF. Maternal high-fat diet and fetal programming: increased proliferation of hypothalamic peptide-producing neurons that increase risk for overeating and obesity. J Neurosci. 2008;28:12107\u201319. https:\/\/doi.org\/10.1523\/JNEUROSCI.2642-08.2008.","journal-title":"J Neurosci"},{"key":"1549_CR48","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1002\/pd.5784","volume":"40","author":"S Kislal","year":"2020","unstructured":"Kislal S, Shook LL, Edlow AG. Perinatal exposure to maternal obesity: Lasting cardiometabolic impact on offspring. Prenat Diagn. 2020;40:1109\u201325. https:\/\/doi.org\/10.1002\/pd.5784.","journal-title":"Prenat Diagn"},{"key":"1549_CR49","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-76741-8","volume":"10","author":"E Lindberger","year":"2020","unstructured":"Lindberger E, Wikstr\u00f6m AK, Bergman E, Eurenius K, Mulic-Lutvica A, Sundstr\u00f6m Poromaa I, et al. Association of maternal central adiposity measured by ultrasound in early mid pregnancy with infant birth size. Sci Rep. 2020;10:19702. https:\/\/doi.org\/10.1038\/s41598-020-76741-8.","journal-title":"Sci Rep."},{"key":"1549_CR50","doi-asserted-by":"publisher","first-page":"dgz248","DOI":"10.1210\/clinem\/dgz248","volume":"105","author":"EM Jarvie","year":"2020","unstructured":"Jarvie EM, Stewart FM, Ramsay JE, Brown EA, Meyer BJ, Olivecrona G, et al. Maternal adipose tissue expansion, a missing link in the prediction of birth weight centile. J Clin Endocrinol Metab. 2020;105:dgz248. https:\/\/doi.org\/10.1210\/clinem\/dgz248.","journal-title":"J Clin Endocrinol Metab"},{"key":"1549_CR51","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1093\/biolre\/ioab195","volume":"106","author":"VG Paula","year":"2022","unstructured":"Paula VG, Sinzato YK, de Moraes-Souza RQ, Soares TS, Souza FQG, Karki B, et al. Metabolic changes in female rats exposed to intrauterine hyperglycemia and postweaning consumption of high-fat diet\u2020. Biol Reprod. 2022;106:200\u201312. https:\/\/doi.org\/10.1093\/biolre\/ioab195.","journal-title":"Biol Reprod"},{"key":"1549_CR52","doi-asserted-by":"publisher","first-page":"3427","DOI":"10.1210\/jc.2013-4074","volume":"99","author":"M Haghiac","year":"2014","unstructured":"Haghiac M, Basu S, Presley L, Serre D, Catalano PM, Hauguel-de Mouzon S. Patterns of adiponectin expression in term pregnancy: impact of obesity. J Clin Endocrinol Metab. 2014;99:3427\u201334. https:\/\/doi.org\/10.1210\/jc.2013-4074.","journal-title":"J Clin Endocrinol Metab"},{"key":"1549_CR53","doi-asserted-by":"publisher","first-page":"708767","DOI":"10.3389\/fendo.2021.708767","volume":"12","author":"S Ikenoue","year":"2021","unstructured":"Ikenoue S, Kasuga Y, Endo T, Tanaka M, Ochiai D. Newer insights into fetal growth and body composition. Front Endocrinol (Lausanne). 2021;12:708767. https:\/\/doi.org\/10.3389\/fendo.2021.708767.","journal-title":"Front Endocrinol (Lausanne)"},{"key":"1549_CR54","doi-asserted-by":"publisher","first-page":"1698","DOI":"10.1016\/s0002-9378(03)00828-7","volume":"189","author":"PM Catalano","year":"2003","unstructured":"Catalano PM, Thomas A, Huston-Presley L, Amini SB. Increased fetal adiposity: a very sensitive marker of abnormal in utero development. Am J Obstet Gynecol. 2003;189:1698\u2013704. https:\/\/doi.org\/10.1016\/s0002-9378(03)00828-7.","journal-title":"Am J Obstet Gynecol"},{"key":"1549_CR55","doi-asserted-by":"publisher","first-page":"930","DOI":"10.1016\/j.jpeds.2012.11.017","volume":"162","author":"DE Brumbaugh","year":"2013","unstructured":"Brumbaugh DE, Tearse P, Cree-Green M, Fenton LZ, Brown M, Scherzinger A, et al. Intrahepatic fat is increased in the neonatal offspring of obese women with gestational diabetes. J Pediatr. 2013;162:930\u20136.e1. https:\/\/doi.org\/10.1016\/j.jpeds.2012.11.017.","journal-title":"J Pediatr"},{"key":"1549_CR56","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/s10334-019-00775-x","volume":"33","author":"M Shulman","year":"2020","unstructured":"Shulman M, Cho E, Aasi B, Cheng J, Nithiyanantham S, Waddell N, et al. Quantitative analysis of fetal magnetic resonance phantoms and recommendations for an anthropomorphic motion phantom. MAGMA. 2020;33:257\u201372. https:\/\/doi.org\/10.1007\/s10334-019-00775-x.","journal-title":"MAGMA"},{"key":"1549_CR57","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1002\/lt.24965","volume":"24","author":"J Satkunasingham","year":"2018","unstructured":"Satkunasingham J, Nik HH, Fischer S, Menezes R, Selzner N, Cattral M, et al. Can negligible hepatic steatosis determined by magnetic resonance imaging-proton density fat fraction obviate the need for liver biopsy in potential liver donors? Liver Transpl. 2018;24:470\u20137. https:\/\/doi.org\/10.1002\/lt.24965.","journal-title":"Liver Transpl"}],"container-title":["Journal of Perinatology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41372-022-01549-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41372-022-01549-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41372-022-01549-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T15:09:19Z","timestamp":1673622559000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41372-022-01549-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,1]]},"references-count":57,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["1549"],"URL":"https:\/\/doi.org\/10.1038\/s41372-022-01549-5","relation":{},"ISSN":["0743-8346","1476-5543"],"issn-type":[{"value":"0743-8346","type":"print"},{"value":"1476-5543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,1]]},"assertion":[{"value":"16 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 October 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 October 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 November 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"KLC has received research support from Fresenius Kabi. KLC has served as an advisor for Fresenius Kabi, Mead Johnson, Baxter, and Prolacta. KLC serves as an institutional principal investigator, with no salary funding, for a consortium database sponsored by Mead Johnson. HHW receives research support from Siemens Medical Solutions USA.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The University of California Los Angeles Institutional review board approved the study. Each participant participated with informed consent. The study was performed in accordance with Declaration of Helsinki.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}