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Genetically predicted circulating concentrations of micronutrients and risk of hypertensive disorders of pregnancy: a Mendelian randomization study

  • Maternal-Fetal Medicine
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Purpose

Epidemiological studies examining the association between circulating micronutrients and the risk of hypertensive disorders during pregnancy (HDP) have produced inconsistent results. Therefore, we conducted a Mendelian randomization (MR) analysis to evaluate the potential causal relationship between micronutrients and HDP.

Methods

Nine micronutrients (beta-carotene, vitamin B6, vitamin B12, calcium, zinc, selenium, copper, folate, and phosphorus) were selected as the exposure factors. Summary data for gestational hypertension (14,727 cases and 196,143 controls) and preeclampsia/eclampsia (7212 cases and 174,266 controls) were extracted from the FinnGen consortium. The MR analysis employed the inverse variance weighted method and conducted a range of sensitivity analyses.

Results

The inverse variance weighted method indicated no significant causal relationship between nine genetically predicted micronutrient concentrations and gestational hypertension, as well as preeclampsia/eclampsia. Sensitivity analyses suggested the absence of pleiotropy.

Conclusion

There is no strong evidence to support the causation between circulating micronutrients and hypertensive disorder during pregnancy.

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Data availability

The study utilized exclusively data that is accessible to the public, with the sources of this data detailed in the Materials and Methods section.

References

  1. Kassebaum NJ, Bertozzi-Villa A, Coggeshall MS et al (2014) Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 384:980–1004. https://doi.org/10.1016/S0140-6736(14)60696-6

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ahsan T, Banu S, Nahar Q et al (2013) Serum trace elements levels in preeclampsia and eclampsia: correlation with the pregnancy disorder. Biol Trace Elem Res 152:327–332. https://doi.org/10.1007/s12011-013-9637-4

    Article  CAS  PubMed  Google Scholar 

  3. Chen Y, Ou QX, Chen Y et al (2022) Association between trace elements and preeclampsia: a retrospective cohort study. J Trace Elem Med Biol 72:126971. https://doi.org/10.1016/j.jtemb.2022.126971

    Article  CAS  PubMed  Google Scholar 

  4. Kang T, Liu Y, Chen X et al (2022) Dietary carotenoid intake and risk of developing preeclampsia: a hospital-based case-control study. BMC Pregnancy Childbirth 22:427. https://doi.org/10.1186/s12884-022-04737-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Bodnar LM, Kirkpatrick SI, Roberts JM et al (2023) Is the association between fruits and vegetables and preeclampsia due to higher dietary vitamin C and carotenoid intakes? Am J Clin Nutr 118:459–467. https://doi.org/10.1016/j.ajcnut.2023.06.007

    Article  CAS  PubMed  Google Scholar 

  6. Lewandowska M, Sajdak S, Marciniak W, Lubiński J (2019) First trimester serum copper or zinc levels, and risk of pregnancy-induced hypertension. Nutrients 11:2479. https://doi.org/10.3390/nu11102479

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Jin S, Hu C, Zheng Y (2022) Maternal serum zinc level is associated with risk of preeclampsia: a systematic review and meta-analysis. Front Public Health 10:968045. https://doi.org/10.3389/fpubh.2022.968045

    Article  PubMed  PubMed Central  Google Scholar 

  8. Papadimitriou N, Dimou N, Gill D et al (2021) Genetically predicted circulating concentrations of micronutrients and risk of breast cancer: a Mendelian randomization study. Int J Cancer 148:646–653. https://doi.org/10.1002/ijc.33246

    Article  CAS  PubMed  Google Scholar 

  9. Flatby HM, Ravi A, Damås JK et al (2023) Circulating levels of micronutrients and risk of infections: a Mendelian randomization study. BMC Med 21:84. https://doi.org/10.1186/s12916-023-02780-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Lo ACQ, Lo CCW (2022) Vitamin D supplementation and incident preeclampsia: an updated meta-analysis of randomized clinical trials. Clin Nutr 41:1852–1853. https://doi.org/10.1016/j.clnu.2022.06.017

    Article  CAS  PubMed  Google Scholar 

  11. Liu Y, Ma S, Huang X et al (2023) Dietary intake and serum concentrations of vitamin A and vitamin E and pre-eclampsia risk in Chinese pregnant women: a matched case-control study. Front Nutr 10:1049055. https://doi.org/10.3389/fnut.2023.1049055

    Article  PubMed  PubMed Central  Google Scholar 

  12. Li Q, Xu S, Chen X et al (2020) folic acid supplement use and increased risk of gestational hypertension. Hypertension 76:150–156. https://doi.org/10.1161/HYPERTENSIONAHA.119.14621

    Article  CAS  PubMed  Google Scholar 

  13. Palan PR, Mikhail MS, Romney SL (2001) Placental and serum levels of carotenoids in preeclampsia. Obstet Gynecol 98:459–462. https://doi.org/10.1016/s0029-7844(01)01437-5

    Article  CAS  PubMed  Google Scholar 

  14. Major JM, Yu K, Wheeler W et al (2011) Genome-wide association study identifies common variants associated with circulating vitamin E levels. Hum Mol Genet 20:3876–3883. https://doi.org/10.1093/hmg/ddr296

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Magnus MC, Miliku K, Bauer A et al (2018) Vitamin D and risk of pregnancy related hypertensive disorders: Mendelian randomisation study. BMJ 361:k2167. https://doi.org/10.1136/bmj.k2167

    Article  PubMed  PubMed Central  Google Scholar 

  16. Rogne T, Burgess S, Gill D (2022) Systemic iron status and maternal pregnancy complications: a Mendelian randomization study. Int J Epidemiol 51:1024–1027. https://doi.org/10.1093/ije/dyac037

    Article  PubMed  Google Scholar 

  17. Ferrucci L, Perry JRB, Matteini A et al (2009) Common variation in the beta-carotene 15,15’-monooxygenase 1 gene affects circulating levels of carotenoids: a genome-wide association study. Am J Hum Genet 84:123–133. https://doi.org/10.1016/j.ajhg.2008.12.019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hazra A, Kraft P, Lazarus R et al (2009) Genome-wide significant predictors of metabolites in the one-carbon metabolism pathway. Hum Mol Genet 18:4677–4687. https://doi.org/10.1093/hmg/ddp428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Grarup N, Sulem P, Sandholt CH et al (2013) Genetic architecture of vitamin B12 and folate levels uncovered applying deeply sequenced large datasets. PLoS Genet 9:e1003530. https://doi.org/10.1371/journal.pgen.1003530

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Evans DM, Zhu G, Dy V et al (2013) Genome-wide association study identifies loci affecting blood copper, selenium and zinc. Hum Mol Genet 22:3998–4006. https://doi.org/10.1093/hmg/ddt239

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kestenbaum B, Glazer NL, Köttgen A et al (2010) Common genetic variants associate with serum phosphorus concentration. J Am Soc Nephrol 21:1223–1232. https://doi.org/10.1681/ASN.2009111104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Zheng J, Baird D, Borges M-C et al (2017) Recent developments in Mendelian randomization studies. Curr Epidemiol Rep 4:330–345. https://doi.org/10.1007/s40471-017-0128-6

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bowden J, Davey Smith G, Haycock PC, Burgess S (2016) Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol 40:304–314. https://doi.org/10.1002/gepi.21965

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bowden J, Davey Smith G, Burgess S (2015) Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 44:512–525. https://doi.org/10.1093/ije/dyv080

    Article  PubMed  PubMed Central  Google Scholar 

  25. Burgess S, Thompson SG, Genetics Collaboration CRPCHD (2011) Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 40:755–764. https://doi.org/10.1093/ije/dyr036

    Article  PubMed  Google Scholar 

  26. Burgess S, Dudbridge F, Thompson SG (2016) Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med 35:1880–1906. https://doi.org/10.1002/sim.6835

    Article  PubMed  Google Scholar 

  27. Staley JR, Blackshaw J, Kamat MA et al (2016) PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics 32:3207–3209. https://doi.org/10.1093/bioinformatics/btw373

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Buniello A, MacArthur JAL, Cerezo M et al (2019) The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res 47:D1005–D1012. https://doi.org/10.1093/nar/gky1120

    Article  CAS  PubMed  Google Scholar 

  29. Yang Y, Le Ray I, Zhu J et al (2021) Preeclampsia prevalence, risk factors, and pregnancy outcomes in Sweden and China. JAMA Netw Open 4:e218401. https://doi.org/10.1001/jamanetworkopen.2021.8401

    Article  PubMed  PubMed Central  Google Scholar 

  30. Staff AC, Johnsen GM, Dechend R, Redman CWG (2014) Preeclampsia and uteroplacental acute atherosis: immune and inflammatory factors. J Reprod Immunol 101–102:120–126. https://doi.org/10.1016/j.jri.2013.09.001

    Article  CAS  PubMed  Google Scholar 

  31. Scholl TO, Leskiw M, Chen X et al (2005) Oxidative stress, diet, and the etiology of preeclampsia2. Am J Clin Nutr 81:1390–1396. https://doi.org/10.1093/ajcn/81.6.1390

    Article  CAS  PubMed  Google Scholar 

  32. Chappell LC, Seed PT, Briley AL et al (1999) Effect of antioxidants on the occurrence of pre-eclampsia in women at increased risk: a randomised trial. Lancet 354:810–816. https://doi.org/10.1016/S0140-6736(99)80010-5

    Article  CAS  PubMed  Google Scholar 

  33. Pisal H, Dangat K, Randhir K et al (2019) Higher maternal plasma folate, vitamin B12 and homocysteine levels in women with preeclampsia. J Hum Hypertens 33:393–399. https://doi.org/10.1038/s41371-019-0164-4

    Article  CAS  PubMed  Google Scholar 

  34. Roberts JM, Cooper DW (2001) Pathogenesis and genetics of pre-eclampsia. Lancet 357:53–56. https://doi.org/10.1016/s0140-6736(00)03577-7

    Article  CAS  PubMed  Google Scholar 

  35. Wen SW, White RR, Rybak N et al (2018) Effect of high dose folic acid supplementation in pregnancy on pre-eclampsia (FACT): double blind, phase III, randomised controlled, international, multicentre trial. BMJ 362:k3478. https://doi.org/10.1136/bmj.k3478

    Article  PubMed  PubMed Central  Google Scholar 

  36. Timmermans S, Jaddoe VWV, Silva LM et al (2011) Folic acid is positively associated with uteroplacental vascular resistance: the Generation R study. Nutr Metab Cardiovasc Dis 21:54–61. https://doi.org/10.1016/j.numecd.2009.07.002

    Article  CAS  PubMed  Google Scholar 

  37. Serrano NC, Quintero-Lesmes DC, Becerra-Bayona S et al (2018) Association of pre-eclampsia risk with maternal levels of folate, homocysteine and vitamin B12 in Colombia: a case-control study. PLoS One 13:e0208137. https://doi.org/10.1371/journal.pone.0208137

    Article  PubMed  PubMed Central  Google Scholar 

  38. Furness D, Fenech M, Dekker G et al (2013) Folate, vitamin B12, vitamin B6 and homocysteine: impact on pregnancy outcome. Matern Child Nutr 9:155–166. https://doi.org/10.1111/j.1740-8709.2011.00364.x

    Article  PubMed  Google Scholar 

  39. Sanchez SE, Zhang C, Rene Malinow M et al (2001) Plasma folate, vitamin B(12), and homocyst(e)ine concentrations in preeclamptic and normotensive Peruvian women. Am J Epidemiol 153:474–480. https://doi.org/10.1093/aje/153.5.474

    Article  CAS  PubMed  Google Scholar 

  40. Jain S, Sharma P, Kulshreshtha S et al (2010) The role of calcium, magnesium, and zinc in pre-eclampsia. Biol Trace Elem Res 133:162–170. https://doi.org/10.1007/s12011-009-8423-9

    Article  CAS  PubMed  Google Scholar 

  41. Kim J, Kim YJ, Lee R et al (2012) Serum levels of zinc, calcium, and iron are associated with the risk of preeclampsia in pregnant women. Nutr Res 32:764–769. https://doi.org/10.1016/j.nutres.2012.09.007

    Article  CAS  PubMed  Google Scholar 

  42. Hamdan HZ, Hamdan SZ, Adam I (2023) Association of selenium levels with preeclampsia: a systematic review and meta-analysis. Biol Trace Elem Res 201:2105–2122. https://doi.org/10.1007/s12011-022-03316-1

    Article  CAS  PubMed  Google Scholar 

  43. Roy H, Nargis S, Rahman M et al (2018) Evaluation of serum calcium levels in pre-eclampsia. Medicine Today 30:57. https://doi.org/10.3329/medtoday.v30i2.37810

    Article  Google Scholar 

  44. Rafeeinia A, Tabandeh A, Khajeniazi S, Marjani AJ (2014) Serum copper, zinc and lipid peroxidation in pregnant women with preeclampsia in Gorgan. Open Biochem J 8:83–88. https://doi.org/10.2174/1874091X01408010083

    Article  PubMed  PubMed Central  Google Scholar 

  45. da Silva AC, Martins-Costa SH, Valério EG, Lopes Ramos JG (2017) Comparison of serum selenium levels among hypertensive and normotensive pregnant women. Hypertens Pregnancy 36:64–69. https://doi.org/10.1080/10641955.2016.1237645

    Article  CAS  PubMed  Google Scholar 

  46. Tenório MB, Ferreira RC, Moura FA et al (2018) Oral antioxidant therapy for prevention and treatment of preeclampsia: Meta-analysis of randomized controlled trials. Nutr Metab Cardiovasc Dis 28:865–876. https://doi.org/10.1016/j.numecd.2018.06.002

    Article  CAS  PubMed  Google Scholar 

  47. Callaway LK, Prins JB, Chang AM, McIntyre HD (2006) The prevalence and impact of overweight and obesity in an Australian obstetric population. Med J Aust 184:56–59. https://doi.org/10.5694/j.1326-5377.2006.tb00115.x

    Article  PubMed  Google Scholar 

  48. Patrick TE, Powers RW, Daftary AR et al (2004) Homocysteine and folic acid are inversely related in black women with preeclampsia. Hypertension 43:1279–1282. https://doi.org/10.1161/01.HYP.0000126580.81230.da

    Article  CAS  PubMed  Google Scholar 

  49. Eskenazi B, Fenster L, Sidney S (1991) A multivariate analysis of risk factors for preeclampsia. JAMA 266:237–241

    Article  CAS  PubMed  Google Scholar 

  50. Liu C, Liu C, Wang Q, Zhang Z (2018) Supplementation of folic acid in pregnancy and the risk of preeclampsia and gestational hypertension: a meta-analysis. Arch Gynecol Obstet 298:697–704. https://doi.org/10.1007/s00404-018-4823-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. World Health Organization (2016) WHO recommendations on antenatal care for a positive pregnancy experience. World Health Organization, Geneva

    Google Scholar 

  52. Flynn E, Tanigawa Y, Rodriguez F et al (2021) Sex-specific genetic effects across biomarkers. Eur J Hum Genet 29:154–163. https://doi.org/10.1038/s41431-020-00712-w

    Article  CAS  PubMed  Google Scholar 

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TH: Study conception and design, explore the literature, manuscript writing. FL: Data collection and analysis, explore the literature, manuscript editing.

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Correspondence to Fan Lu.

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Huang, T., Lu, F. Genetically predicted circulating concentrations of micronutrients and risk of hypertensive disorders of pregnancy: a Mendelian randomization study. Arch Gynecol Obstet (2024). https://doi.org/10.1007/s00404-023-07331-y

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