Maternal RFC1 Gene Polymorphisms and Neural Tube Defects: A Case–Control Study in Ethiopia
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Setting
2.2. Data Collection
2.3. Ethical Approval and Consent for Research Participation
2.4. Blood Collection for Genetic Analysis
2.5. DNA Extraction and Genotyping
3. Results
3.1. Participants’ Characteristics
3.2. Hardy–Weinberg Equilibrium (HWE) Analysis of RFC1 Polymorphisms
3.3. Comparison of RFC1 Allele Frequencies in Ethiopian and African Reference Populations
3.4. RFC1 Gene Polymorphism (rs1131596 & rs1051266) Using the Additive Genetic Model
3.5. RFC1 Gene Polymorphism (rs1131596 & rs1051266) Using the Recessive Genetic Model
3.6. Sensitivity Analysis
4. Discussion
4.1. Strengths of the Study
4.2. Limitations of the Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| AAU | Addis Ababa University |
| ALFA | Allele Frequency Aggregator |
| EPHI | Ethiopian Public Health Institute |
| HWE | Hardy–Weinberg equilibrium |
| ICD | International Classification of Diseases |
| MAF | Mean Allele Frequency |
| MTHFR | Methylenetetrahydrofolate Reductase |
| NCBI | National Center for Biotechnology Information |
| NTD | Neural Tube Defect |
| ODK | Open Data Kit |
| OSU | Oklahoma State University |
| PCR | Polymerase Chain Reaction |
| RFC | Reduced Folate Carrier |
| SNP | Single Nucleotide Polymorphism |
References
- Isaković, J.; Šimunić, I.; Jagečić, D.; Hribljan, V.; Mitrečić, D. Overview of Neural Tube Defects: Gene–Environment Interactions, Preventative Approaches and Future Perspectives. Biomedicines 2022, 10, 965. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Copp, A.J.; Stanier, P.; Greene, N.D. Neural Tube Defects: Recent Advances, Unsolved Questions, and Controversies. Lancet Neurol. 2013, 12, 799–810. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wilde, J.J.; Petersen, J.R.; Niswander, L. Genetic, Epigenetic, and Environmental Contributions to Neural Tube Closure. Annu. Rev. Genet. 2014, 48, 583–611. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ravi, K.S.; Divasha; Hassan, S.B.; Pasi, R.; Mittra, S.; Kumar, R. Neural Tube Defects: Different types and brief review of neurulation process and its clinical implication. J Fam. Med. Prim. Care 2021, 10, 4383–4390. [Google Scholar] [CrossRef] [Scilit]
- Kancherla, V. Neural Tube Defects: A Review of Global Prevalence, Causes, and Primary Prevention. Childs Nerv. Syst. 2023, 39, 1703–1710. [Google Scholar] [CrossRef] [Scilit]
- Berihu, B.A.; Welderufael, A.L.; Berhe, Y.; Magana, T.; Mulugeta, A.; Asfaw, S.; Gebreselassie, K. High Burden of Neural Tube Defects in Tigray, Northern Ethiopia: Hospital-Based Study. PLoS ONE 2018, 13, e0206212. [Google Scholar] [CrossRef] [Scilit]
- Madrid, L.; Vyas, K.J.; Kancherla, V.; Leulseged, H.; Suchdev, P.S.; Bassat, Q.; Sow, S.O.; Arifeen, S.E.; Madhi, S.A.; Onyango, D.; et al. Neural Tube Defects as a Cause of Death among Stillbirths, Infants, and Children Younger than 5 Years in Sub-Saharan Africa and Southeast Asia: An Analysis of the CHAMPS Network. Lancet Glob. Health 2023, 11, e1041–e1052. [Google Scholar] [CrossRef] [Scilit]
- Molloy, A.M.; Pangilinan, F.; Brody, L.C. Genetic Risk Factors for Folate-Responsive Neural Tube Defects. Annu. Rev. Nutr. 2017, 37, 269–291. [Google Scholar] [CrossRef] [Scilit]
- Cai, C.-Q.; Fang, Y.-L.; Shu, J.-B.; Zhao, L.-S.; Zhang, R.-P.; Cao, L.-R.; Wang, Y.-Z.; Zhi, X.-F.; Cui, H.-L.; Shi, O.-Y.; et al. Association of Neural Tube Defects with Maternal Alterations and Genetic Polymorphisms in One-Carbon Metabolic Pathway. Ital. J. Pediatr. 2019, 45, 37. [Google Scholar] [CrossRef] [Scilit]
- Finnell, R.H.; Caiaffa, C.D.; Kim, S.-E.; Lei, Y.; Steele, J.; Cao, X.; Tukeman, G.; Lin, Y.L.; Cabrera, R.M.; Wlodarczyk, B.J. Gene Environment Interactions in the Etiology of Neural Tube Defects. Front. Genet. 2021, 12, 659612. [Google Scholar] [CrossRef] [Scilit]
- Rochtus, A.; Jansen, K.; Geet, C.; Freson, K. Nutri-Epigenomic Studies Related to Neural Tube Defects: Does Folate Affect Neural Tube Closure Via Changes in DNA Methylation? MRMC 2015, 15, 1095–1102. [Google Scholar] [CrossRef] [Scilit]
- Yee, S.W.; Gong, L.; Badagnani, I.; Giacomini, K.M.; Klein, T.E.; Altman, R.B. SLC19A1 Pharmacogenomics Summary. Pharmacogenetics Genom. 2010, 20, 708–715. [Google Scholar] [CrossRef] [Scilit]
- Gao, Y.; Sheng, C.; Xie, R.; Sun, W.; Asztalos, E.; Moddemann, D.; Zwaigenbaum, L.; Walker, M.; Wen, S.W. New Perspective on Impact of Folic Acid Supplementation during Pregnancy on Neurodevelopment/Autism in the Offspring Children—A Systematic Review. PLoS ONE 2016, 11, e0165626. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Shaw, G.M.; Zhu, H.; Lammer, E.J.; Yang, W.; Finnell, R.H. Genetic Variation of Infant Reduced Folate Carrier (A80G) and Risk of Orofacial and Conotruncal Heart Defects. Am. J. Epidemiol. 2003, 158, 747–752. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Kakebeen, A.D.; Niswander, L. Micronutrient Imbalance and Common Phenotypes in Neural Tube Defects. Genesis 2021, 59, e23455. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Relton, C.L.; Wilding, C.S.; Pearce, M.S.; Laffling, A.J.; Jonas, P.A.; Lynch, S.A.; Tawn, E.J.; Burn, J. Gene–Gene Interaction in Folate-Related Genes and Risk of Neural Tube Defects in a UK Population. J. Med. Genet. 2004, 41, 256–260. [Google Scholar] [CrossRef] [Scilit]
- Untergasser, A.; Cutcutache, I.; Koressaar, T.; Ye, J.; Faircloth, B.C.; Remm, M.; Rozen, S.G. Primer3—New Capabilities and Interfaces. Nucleic Acids Res. 2012, 40, e115. [Google Scholar] [CrossRef] [Scilit]
- Hart, M.D.; Girma, M.; Strong, M.D.; Tadesse, B.T.; Taddesse, B.M.; Alemayehu, F.R.; Stoecker, B.J.; Chowanadisai, W. Vitamin D Binding Protein Gene Polymorphisms Are Associated with Lower Plasma 25-Hydroxy-Cholecalciferol Concentrations in Ethiopian Lactating Women. Nutr. Res. 2022, 107, 86–95. [Google Scholar] [CrossRef] [Scilit]
- National Center for Biotechnology Information. dbSNP: Rs1051266. Available online: https://www.ncbi.nlm.nih.gov/snp/rs1051266 (accessed on 16 April 2024).
- National Center for Biotechnology Information. dbSNP: Rs1131596. Available online: https://www.ncbi.nlm.nih.gov/snp/rs1131596 (accessed on 16 April 2024).
- De Marco, P.; Calevo, M.G.; Moroni, A.; Merello, E.; Raso, A.; Finnell, R.H.; Zhu, H.; Andreussi, L.; Cama, A.; Capra, V. Reduced Folate Carrier Polymorphism (80A→G) and Neural Tube Defects. Eur. J. Hum. Genet. 2003, 11, 245–252. [Google Scholar] [CrossRef] [Scilit]
- Franke, B.; Vermeulen, S.H.H.M.; Steegers-Theunissen, R.P.M.; Coenen, M.J.; Schijvenaars, M.M.V.A.P.; Scheffer, H.; Den Heijer, M.; Blom, H.J. An Association Study of 45 Folate-related Genes in Spina Bifida: Involvement of Cubilin (CUBN) and tRNA Aspartic Acid Methyltransferase 1 (TRDMT1). Birth Defects Res. 2009, 85, 216–226. [Google Scholar] [CrossRef] [Scilit]
- O’Leary, V.B.; Pangilinan, F.; Cox, C.; Parle-McDermott, A.; Conley, M.; Molloy, A.M.; Kirke, P.N.; Mills, J.L.; Brody, L.C.; Scott, J.M. Reduced Folate Carrier Polymorphisms and Neural Tube Defect Risk. Mol. Genet. Metab. 2006, 87, 364–369. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, T.; Lou, J.; Zhong, R.; Wu, J.; Zou, L.; Sun, Y.; Lu, X.; Liu, L.; Miao, X.; Xiong, G. Variants in the Folate Pathway and the Risk of Neural Tube Defects: A Meta-Analysis of the Published Literature. PLoS ONE 2013, 8, e59570. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Dewelle, W.K.; Melka, D.S.; Aklilu, A.T.; Gebremariam, M.Y.; Alemayehu, M.A.; Alemayehu, D.H.; Woldemichael, T.S.; Gebre, S.G. Polymorphisms in Maternal Selected Folate Metabolism-Related Genes in Neural Tube Defect-Affected Pregnancy. Adv. Biomed. Res. 2023, 12, 160. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lee, S.; Gleeson, J.G. Closing in on Mechanisms of Open Neural Tube Defects. Trends Neurosci. 2020, 43, 519–532. [Google Scholar] [CrossRef] [Scilit]
- Cao, L.; Wang, Y.; Zhang, R.; Dong, L.; Cui, H.; Fang, Y.; Zhao, L.; Shi, O.; Cai, C. Association of Neural Tube Defects with Gene Polymorphisms in One-Carbon Metabolic Pathway. Childs Nerv. Syst. 2018, 34, 277–284. [Google Scholar] [CrossRef] [Scilit]
- Darweesh, H.; Eissa, A.A. Effect of SLC19A1 Gene Polymorphism and Haplotypes on Idiopathic Recurrent Pregnancy Loss Among Women In Duhok City. Sci. J. Univ. Zakho 2025, 13, 620–627. [Google Scholar] [CrossRef] [Scilit]
- Cho, Y.; Kim, J.O.; Lee, J.H.; Park, H.M.; Jeon, Y.J.; Oh, S.H.; Bae, J.; Park, Y.S.; Kim, O.J.; Kim, N.K. Association of Reduced Folate Carrier-1 (RFC-1) Polymorphisms with Ischemic Stroke and Silent Brain Infarction. PLoS ONE 2015, 10, e0115295. [Google Scholar] [CrossRef] [Scilit]
- Mohamed, F.A.; Dheresa, M.; Raru, T.B.; Yusuf, N.; Hassen, T.A.; Mehadi, A.; Wilfong, T.; Tukeni, K.N.; Kure, M.A.; Roba, K.T. Determinants of Neural Tube Defects among Newborns in Public Referral Hospitals in Eastern Ethiopia. BMC Nutr. 2023, 9, 93. [Google Scholar] [CrossRef] [Scilit]
- Mulu, G.B.; Atinafu, B.T.; Tarekegn, F.N.; Adane, T.D.; Tadese, M.; Wubetu, A.D.; Kebede, W.M. Factors Associated with Neural Tube Defects among Newborns Delivered at Debre Berhan Specialized Hospital, North Eastern Ethiopia, 2021. Case-Control Study. Front. Pediatr. 2022, 9, 795637. [Google Scholar] [CrossRef] [Scilit]
- Yang, J.; Carmichael, S.L.; Canfield, M.; Song, J.; Shaw, G.M.; the National Birth Defects Prevention Study. Socioeconomic Status in Relation to Selected Birth Defects in a Large Multicentered US Case-Control Study. Am. J. Epidemiol. 2008, 167, 145–154. [Google Scholar] [CrossRef] [Scilit]
- Bitew, Z.W.; Worku, T.; Alebel, A.; Alemu, A. Magnitude and Associated Factors of Neural Tube Defects in Ethiopia: A Systematic Review and Meta-Analysis. Glob. Pediatr. Health 2020, 7, 2333794X20939423. [Google Scholar] [CrossRef] [Scilit]
- Hosking, L.; Lumsden, S.; Lewis, K.; Yeo, A.; McCarthy, L.; Bansal, A.; Riley, J.; Purvis, I.; Xu, C.-F. Detection of Genotyping Errors by Hardy–Weinberg Equilibrium Testing. Eur. J. Hum. Genet. 2004, 12, 395–399. [Google Scholar] [CrossRef] [Scilit]
| Characteristics | Cases (n = 63) | Controls (n = 187) | Total (n = 250) | χ2 | p-Value |
|---|---|---|---|---|---|
| Maternal age (years) | 1.34 | 0.935 | |||
| 16–20 | 1 (1.6%) | 3 (1.6%) | 4 (1.6%) | ||
| 20–34 | 51 (81.0%) | 155 (82.9%) | 206 (82.4%) | ||
| 35–45 | 11 (17.5%) | 29 (15.5%) | 40 (16.0%) | ||
| Residence | 12.40 | <0.001 | |||
| Urban | 51 (81.0%) | 178 (95.2%) | 229 (91.6%) | ||
| Rural | 12 (19.0%) | 9 (4.8%) | 21 (8.4%) | ||
| Marital status | 1.33 | 0.249 | |||
| Unmarried | 2 (3.2%) | 2 (1.1%) | 4 (1.6%) | ||
| Married | 61 (96.8%) | 185 (98.9%) | 246 (98.4%) | ||
| Educational status | 5.53 | 0.137 | |||
| No formal education | 7 (11.1%) | 13 (7.0%) | 20 (8.0%) | ||
| Primary school | 23 (36.5%) | 70 (37.4%) | 93 (37.2%) | ||
| Secondary school | 30 (47.6%) | 76 (40.6%) | 106 (42.4%) | ||
| Higher education and above | 3 (4.8%) | 28 (15.0%) | 31 (12.4%) | ||
| Occupation | 47.41 | <0.001 | |||
| Housewife | 62 (98.4%) | 93 (49.7%) | 155 (62.0%) | ||
| Employed/business | 1 (1.6%) | 94 (50.3%) | 95 (38.0%) | ||
| Monthly income | 26.70 | <0.001 | |||
| Low | 40 (63.5%) | 51 (27.3%) | 91 (36.4%) | ||
| Lower-middle | 23 (36.5%) | 136 (72.7%) | 159 (63.6%) | ||
| Religion | 4.52 | 0.341 | |||
| Orthodox | 48 (76.2%) | 136 (72.7%) | 184 (73.6%) | ||
| Muslim | 13 (20.6%) | 29 (15.5%) | 42 (16.8%) | ||
| Protestant | 2 (3.2%) | 20 (10.7%) | 22 (8.8%) | ||
| Number of children | 1.21 | 0.750 | |||
| One | 35 (55.6%) | 114 (61.0%) | 149 (59.6%) | ||
| Two | 24 (38.1%) | 58 (31.0%) | 82 (32.8%) | ||
| ≥Three | 4 (6.4%) | 15 (8.0%) | 19 (7.6%) |
| SNP | Genotype | Cases (n = 63) Observed | Expected | Controls (n = 187) Observed | Expected | χ2 (Case) | χ2 (Control) | p-Value (Case) | p-Value (Control) |
|---|---|---|---|---|---|---|---|---|---|
| rs1131596 (−43T>C) | TT | 48 (76.2%) | 42.36 | 134 (71.6%) | 108.01 | 0.75 | 6.25 | <0.001 | <0.001 |
| TC | 7 (11.1%) | 18.59 | 19 (10.2%) | 68.21 | 7.23 | 35.50 | |||
| CC | 8 (12.7%) | 2.04 | 34 (18.2%) | 10.77 | 17.41 | 20.07 | |||
| Total χ2 | 25.39 | 61.82 | |||||||
| rs1051266 (80A>G) | AA | 36 (57.1%) | 33.58 | 103 (55.1%) | 87.62 | 0.18 | 2.55 | 0.127 | <0.001 |
| AG | 20 (31.7%) | 24.82 | 50 (26.7%) | 80.76 | 0.94 | 11.06 | |||
| GG | 7 (11.1%) | 4.60 | 34 (18.2%) | 18.62 | 0.52 | 3.96 | |||
| Total χ2 | 1.64 | 18.74 |
| SNP | Population | Group | Reference Allele | Alternate Allele |
|---|---|---|---|---|
| rs1131596 (−43T>C) | Ethiopia (n = 250) | Cases | G = 0.818 | A = 0.182 |
| Controls | G = 0.767 | A = 0.232 | ||
| Africa (n = 1322) | — | G = 0.719 | A = 0.280 | |
| rs1051266 (80A>G) | Ethiopia (n = 250) | Cases | T = 0.762 | C = 0.238 |
| Controls | T = 0.685 | C = 0.315 | ||
| Africa (n = 1322) | — | T = 0.673 | C = 0.327 |
| SNP/Genotype | Total (n = 250) | Cases (n = 63) | Controls (n = 187) | p-Value | OR | 95% CI |
|---|---|---|---|---|---|---|
| rs1131596 (−43T>C) | ||||||
| TT (Reference) | 182 (72.8%) | 48 (76.2%) | 134 (71.7%) | 0.605 | — | — |
| TC | 26 (10.4%) | 7 (11.1%) | 19 (10.2%) | 0.953 | 1.029 | 0.407–2.599 |
| CC (Alternate) | 42 (16.8%) | 8 (12.7%) | 34 (18.2%) | 0.325 | 0.657 | 0.284–1.518 |
| C allele | 110 (22.0%) | 23 (18.2%) | 87 (23.2%) | — | — | — |
| T allele | 390 (78.0%) | 103 (81.8%) | 287 (76.7%) | — | — | — |
| rs1051266 (80A>G) | ||||||
| AA (Reference) | 139 (55.6%) | 36 (57.1%) | 103 (55.1%) | 0.425 | — | — |
| AG | 70 (28.0%) | 20 (31.7%) | 50 (26.7%) | 0.681 | 1.144 | 0.602–2.176 |
| GG (Alternate) | 41 (16.4%) | 7 (11.1%) | 34 (18.2%) | 0.248 | 0.589 | 0.240–1.445 |
| A allele | 313 (72.8%) | 94 (76.2%) | 256 (68.5%) | — | — | — |
| G allele | 117 (27.2%) | 34 (23.8%) | 118 (31.5%) | — | — | — |
| Genotype (Recessive Model) | Total (n = 250) | Cases (n = 63) | Controls (n = 187) | p-Value | OR | 95% CI |
|---|---|---|---|---|---|---|
| rs1131596 (−43T>C) | ||||||
| CC (Alternate) | 42 (16.8%) | 8 (12.7%) | 34 (18.2%) | 0.317 | 0.654 | 0.284–1.498 |
| TT + TC | 208 (83.2%) | 55 (87.3%) | 153 (81.9%) | — | — | — |
| rs1051266 (80A>G) | ||||||
| GG (Alternate) | 41 (16.4%) | 7 (11.1%) | 34 (18.2%) | 0.194 | 0.563 | 0.236–1.340 |
| AG + AA | 209 (83.6%) | 56 (88.8%) | 153 (81.8%) | — | — |
| SNP | Model | OR | 95% CI | p-Value |
|---|---|---|---|---|
| rs1131596 (−43T>C) | ||||
| CC vs. (TT + TC) | Unadjusted | 0.654 | 0.284–1.498 | 0.317 |
| Adjusted * | 1.333 | 0.543–3.267 | 0.530 | |
| rs1051266 (80A>G) | ||||
| GG vs. (AG + AA) | Unadjusted | 0.563 | 0.236–1.340 | 0.194 |
| Adjusted * | 1.256 | 0.470–3.358 | 0.649 |
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Molla, H.T.; Gashu, D.; Stoecker, B.; Chowanadisai, W. Maternal RFC1 Gene Polymorphisms and Neural Tube Defects: A Case–Control Study in Ethiopia. Genes 2026, 17, 478. https://doi.org/10.3390/genes17040478
Molla HT, Gashu D, Stoecker B, Chowanadisai W. Maternal RFC1 Gene Polymorphisms and Neural Tube Defects: A Case–Control Study in Ethiopia. Genes. 2026; 17(4):478. https://doi.org/10.3390/genes17040478
Chicago/Turabian StyleMolla, Hasset Tamirat, Dawd Gashu, Barbara Stoecker, and Winyoo Chowanadisai. 2026. "Maternal RFC1 Gene Polymorphisms and Neural Tube Defects: A Case–Control Study in Ethiopia" Genes 17, no. 4: 478. https://doi.org/10.3390/genes17040478
APA StyleMolla, H. T., Gashu, D., Stoecker, B., & Chowanadisai, W. (2026). Maternal RFC1 Gene Polymorphisms and Neural Tube Defects: A Case–Control Study in Ethiopia. Genes, 17(4), 478. https://doi.org/10.3390/genes17040478

