The Effect of Interactions between Folic Acid Supplementation and One Carbon Metabolism Gene Variants on Small-for-Gestational-Age Births in the Screening for Pregnancy Endpoints (SCOPE) Cohort Study

Bulloch, Rhodi E.; Wall, Clare; McCowan, Lesley; Taylor, Rennae S.; Roberts, Claire T.; Thompson, John M. D.

doi:10.3390/nu12061677

Cited by 17 publications

(19 citation statements)

References 45 publications

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“…Fetal growth and SGA or LGA results are influenced by different factors including maternal socio-demographic characteristics, health status, nutritional intake, environmental exposures, genetic background and gene-environment interactions [ 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Methylenetetrahydrofolate Reductase (MTHFR) Gene Polymorphism and Infant’s Anthropometry at Birth

et al. 2021

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Identification of causal factors that influence fetal growth and anthropometry at birth is of great importance as they provide information about increased risk of disease throughout life. The association between maternal genetic polymorphism MTHFR(677)C>T and anthropometry at birth has been widely studied because of its key role in the one-carbon cycle. MTHFR(677) CT and TT genotypes have been associated with a greater risk of low birth weight, especially in case of deficient intake of folic acid during pregnancy. This study aimed to analyze the association between the maternal MTHFR(677)C>T genetic polymorphism and anthropometry at birth in a population with adequate folate consumption. We included 694 mother–newborn pairs from a prospective population-based birth cohort in Spain, in the Genetics, Early life enviroNmental Exposures and Infant Development in Andalusia (GENEIDA) project. Women were genotyped for MTHFR(677)C>T SNP by Q-PCR using TaqMan© probes. Relevant maternal and newborn information was obtained from structured questionnaires and medical records. Results showed that maternal MTHFR(677)C>T genotype was associated with newborn anthropometry. Genotypes CT or CT/TT showed statistically significant associations with increased or decreased risk of large-for-gestational-age (LGA) or small-for-gestational-age (SGA) based on weight and height, depending on the newborn’s sex, as well as with SGA in premature neonates. The relationships between this maternal genotype and anthropometry at birth remained despite an adequate maternal folate intake.

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Section: Introductionmentioning

confidence: 99%

Methylenetetrahydrofolate Reductase (MTHFR) Gene Polymorphism and Infant’s Anthropometry at Birth

et al. 2021

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“…Nurk’s study found no significant associations between MTHFR C677T and LBW in Norway [ 41 ]. Moreover, the Screening for Pregnancy Endpoints (SCOPE) prospective cohort study found no significant gene-nutrient interactions between maternal MTHFR C677T, MTHFR A1298C, and folic acid use, and their association with PTB and SGA [ 42 , 43 ]. The results of the three studies mentioned above were collaborative with our study.…”

Section: Discussionmentioning

confidence: 99%

Relationships between Maternal Gene Polymorphisms in One Carbon Metabolism and Adverse Pregnancy Outcomes: A Prospective Mother and Child Cohort Study in China

et al. 2022

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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 > 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.

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“…Furthermore, new, emerging biomarkers have been discovered in the fields of genomics and proteomics, like exosomes, which are involved in the cellular cross-talks and related biological processes [16]. Nutrigenomics [17,18], epigenomics [19] and nutriepigenomics [20,21] investigate how dietary habits and nutrition, as well as environmental factors, and their complex, non-linear interactions can finely modulate the human genome and its expression, and impact on human diseases, including gynecological conditions. For instance, a study explored the relationship between folic acid supplementation and one carbon metabolism gene single nucleotide polymorphisms (SNPs) on small-for-gestationalage (SGA) births [17].…”

Section: Gynecology and Omics Datamentioning

confidence: 99%

“…Nutrigenomics [17,18], epigenomics [19] and nutriepigenomics [20,21] investigate how dietary habits and nutrition, as well as environmental factors, and their complex, non-linear interactions can finely modulate the human genome and its expression, and impact on human diseases, including gynecological conditions. For instance, a study explored the relationship between folic acid supplementation and one carbon metabolism gene single nucleotide polymorphisms (SNPs) on small-for-gestationalage (SGA) births [17]. Other studies assessed the association between pregnancy and childhood epigenetics [19,20].…”

Section: Gynecology and Omics Datamentioning

confidence: 99%

Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects

Khamisy‐Farah

Furstenau

Kong

et al. 2021

IJERPH

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Tremendous scientific and technological achievements have been revolutionizing the current medical era, changing the way in which physicians practice their profession and deliver healthcare provisions. This is due to the convergence of various advancements related to digitalization and the use of information and communication technologies (ICTs)—ranging from the internet of things (IoT) and the internet of medical things (IoMT) to the fields of robotics, virtual and augmented reality, and massively parallel and cloud computing. Further progress has been made in the fields of addictive manufacturing and three-dimensional (3D) printing, sophisticated statistical tools such as big data visualization and analytics (BDVA) and artificial intelligence (AI), the use of mobile and smartphone applications (apps), remote monitoring and wearable sensors, and e-learning, among others. Within this new conceptual framework, big data represents a massive set of data characterized by different properties and features. These can be categorized both from a quantitative and qualitative standpoint, and include data generated from wet-lab and microarrays (molecular big data), databases and registries (clinical/computational big data), imaging techniques (such as radiomics, imaging big data) and web searches (the so-called infodemiology, digital big data). The present review aims to show how big and smart data can revolutionize gynecology by shedding light on female reproductive health, both in terms of physiology and pathophysiology. More specifically, they appear to have potential uses in the field of gynecology to increase its accuracy and precision, stratify patients, provide opportunities for personalized treatment options rather than delivering a package of “one-size-fits-it-all” healthcare management provisions, and enhance its effectiveness at each stage (health promotion, prevention, diagnosis, prognosis, and therapeutics).

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The Effect of Interactions between Folic Acid Supplementation and One Carbon Metabolism Gene Variants on Small-for-Gestational-Age Births in the Screening for Pregnancy Endpoints (SCOPE) Cohort Study

Cited by 17 publications

References 45 publications

Methylenetetrahydrofolate Reductase (MTHFR) Gene Polymorphism and Infant’s Anthropometry at Birth

Methylenetetrahydrofolate Reductase (MTHFR) Gene Polymorphism and Infant’s Anthropometry at Birth

Relationships between Maternal Gene Polymorphisms in One Carbon Metabolism and Adverse Pregnancy Outcomes: A Prospective Mother and Child Cohort Study in China

Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects

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