MCM6 rs4988235 Allele G, AGT rs699 Allele C, ACE rs4343 Allele A, FADS1 rs174547 Allele C, DCHR7 rs12785878 Allele G, and GC rs7041 Allele T: Candidate Genes for Preeclampsia Prevention
Abstract
BACKGROUND: Preeclampsia is the primary cause of maternal and neonatal morbidity and mortality; however, currently there is no definitive method exists to prevent preeclampsia. Recent findings indicate a possible genetic influence on preeclampsia. Therefore, this study was conducted to assess nutrigenomic patterns in preeclampsia as a potential mechanism for identifying appropriate preventive strategies through a nutrigenomic approach.
METHODS: This descriptive study focused on 15 primiparous pregnant women diagnosed with preeclampsia. The nutrigenomic test was performed using DNA microarray method to examine variant genes associated with food response and nutrient metabolites. The genetic tendencies were categorized as "low," "average," and "high." The frequencies of alleles and probabilities were assessed for gene variants expressing "high" and "low" genotypic tendencies.
RESULTS: The identified genetic variations were MCM6 rs4988235 allele G that indicated lactose intolerance (allele frequency 100%), AGT rs699 allele C and ACE rs4343 allele A that were associated with sodium metabolism (allele frequency 82% and 90%, respectively), as well as FADS1 rs174547 allele C that was pertained to omega metabolism (allele frequency 85%). Likewise, DCHR7 rs12785878 allele G and GC rs7041 allele T were relevant for vitamin D (allele frequencies 82% and 77%, respectively). However, MCM6 rs4988235 allele G, FADS1 rs174547 allele C, DCHR7 rs12785878 allele G, and GC rs7041 allele T had not been explicitly linked to preeclampsia.
CONCLUSION: MCM6 rs4988235 allele G, AGT rs699 allele C, ACE rs4343 allele A, FADS1 rs174547 allele C, DCHR7 rs12785878 allele G, and GC rs7041 allele T are the dominant variant genes observed. The associations between preeclampsia and AGT rs699 allele C and ACE rs4343 allele A are consistent with other study.
KEYWORDS: preeclampsia, nutrigenomics, nutrition metabolism
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DOI: https://doi.org/10.18585/inabj.v17i2.3422
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