{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T03:37:01Z","timestamp":1781581021724,"version":"3.54.5"},"reference-count":49,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T00:00:00Z","timestamp":1652832000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Program for Healthcare Reform from the Chinese National Health and Family Planning Commission"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background: To investigate relationships between five single nucleotide polymorphisms (SNP) in four maternal genes involved in one carbon metabolism and adverse pregnancy outcomes, including preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). Methods: This was a prospective mother and child cohort study in Wuqiang, China. Pregnant women (n = 939) were recruited from Jun 2016 to Oct 2018. Pregnancy outcomes (PTB, LBW, and SGA) were extracted from medical records and other information including age at childbearing, maternal education level, gravidity, parity, pre-pregnancy weight and height was collected by using a structured questionnaire. The maternal serum folate concentration was measured by using Abbott Architect i2000SR chemiluminescence analyzer in the first prenatal care visit. DNA genotyping of methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, methionine synthase reductase (MTRR) A66G, methionine synthase (MTR) A2756G, and thymidylate synthetase (TYMS) rs3819102 was processed by Sequenom MassARRAY iPLEX Platform. Univariate and multivariate logistics regression analysis were used to test the relationships between 5 SNPs and PTB, LBW, SGA. Results: Totally, 849 dyads of women and infants were included in the analysis. The prevalence of PTD, LBW, and SGA were 3.76%, 1.58%, and 5.31% respectively. The homozygote frequencies of MTHFR C677T, MTHFR A1298C, MTRR A66G, MTR A2756G, and TYMS rs3819102 were 44.2%, 1.4%, 6.7%, 1.3%, and 3.2%, and the alt allele frequencies were 66.1%, 10.8%, 24.9%, 10.5%, and 20.5% respectively. The average serum folate concentration was 11.95 ng\/mL and the folate deficiency rate was 0.47%. There were no significant associations between MTHFR C677T, MTHFR A1298C, MTRR A66G, MTR A2756G, TYMS rs3819102 alleles and PTD, LBW, SGA (p &gt; 0.05). Conclusions: In the population with adequate folate status and low prevalence of adverse pregnancy outcomes, MTHFR C677T, MTHFR A1298C, MTRR A66G, MTR A2756G, TYMS rs3819102 alleles may not be related to PTD, LBW, and SGA.<\/jats:p>","DOI":"10.3390\/nu14102108","type":"journal-article","created":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T23:14:26Z","timestamp":1652915666000},"page":"2108","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Relationships between Maternal Gene Polymorphisms in One Carbon Metabolism and Adverse Pregnancy Outcomes: A Prospective Mother and Child Cohort Study in China"],"prefix":"10.3390","volume":"14","author":[{"given":"Shuxia","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7900-6541","authenticated-orcid":false,"given":"Yifan","family":"Duan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Bi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8169-7943","authenticated-orcid":false,"given":"Xuehong","family":"Pang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang 050021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianqiang","family":"Lai","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition, Health Chinese Center for Disease Control and Prevention, Beijing 102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2151","DOI":"10.1016\/S0140-6736(12)60560-1","article-title":"Global, regional, and national causes of child mortality: An updated systematic analysis for 2010 with time trends since 2000","volume":"379","author":"Liu","year":"2012","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e37","DOI":"10.1016\/S2214-109X(18)30451-0","article-title":"Global, regional, and national estimates of levels of preterm birth in 2014: A systematic review and modelling analysis","volume":"7","author":"Chawanpaiboon","year":"2019","journal-title":"Lancet Glob. 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