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Early gestational profiling of oxidative stress and angiogenic growth mediators as predictive, preventive and personalised (3P) medical approach to identify suboptimal health pregnant mothers likely to develop preeclampsia

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Abstract

Background

Pregnant women, particularly in developing countries are facing a huge burden of preeclampsia (PE) leading to high morbidity and mortality rates. This is due to delayed diagnosis and unrecognised early targeted preventive measures. Adapting innovative solutions via shifting from delayed to early diagnosis of PE in the context of predictive diagnosis, targeted prevention and personalisation of medical care (PPPM/3 PM) is essential. The subjective assessment of suboptimal health status (SHS) and objective biomarkers of oxidative stress (OS) and angiogenic growth mediators (AGMs) could be used as new PPPM approach for PE; however, these factors have only been studied in isolation with no data on their combine assessment. This study profiled early gestational biomarkers of OS and AGMs as 3 PM approach to identify SHS pregnant mothers likely to develop PE specifically, early-onset PE (EO-PE) and late-onset PE (LO-PE).

Methods

A prospective cohort of 593 singleton normotensive pregnant (NTN-P) women were recruited at 10–20th (visit 1) and followed from 21 weeks gestation until the time of PE diagnosis and delivery. At visit 1, SHS was assessed using SHS questionnaire-25 (SHSQ-25) and women were classified as SHS and optimal health status (OHS). Biomarkers of OS (8-hydroxy-2-deoxyguanosine [8-OHdG], 8-epi-prostaglansinF2alpha [8-epi-PGF2α] and total antioxidant capacity [TAC]) and AGMs (vascular endothelial growth factor [VEGF-A], soluble Fms-like tyrosine kinase-1 [sFlt-1], placental growth factor [PlGF] and soluble endoglin [sEng]) were measured at visit 1 and time of PE diagnosis.

Results

Of the 593 mothers, 498 (248 SHS and 250 OHS) returned for delivery and were included in the final analysis. Fifty-six, 97 and 95 of the 248 SHS mothers developed EO-PE, LO-PE and NTN-P respectively, versus 14 EO-PE, 30 LO-PE and 206 NTN-P among the 250 OHS mothers. At the 10–20th week gestation, unbalanced levels of OS and AGMs were observed among SHS women who developed EO-PE than LO-PE compared to NTN-P women (p < 0.0001). The combined ratios of OS and AGMs, mainly the levels of 8-OHdG/PIGF ratio at 10–20th week gestation yielded the best area under the curve (AUC) and highest relative risk (RR) for predicting SHS-pregnant women who developed EO-PE (AUC = 0.93; RR = 6.5; p < 0.0001) and LO-PE (AUC = 0.88, RR = 4.4; p < 0.0001), as well as for OHS-pregnant women who developed EO-PE (AUC = 0.89, RR = 5.6; p < 0.0001) and LO-PE (AUC = 0.85; RR = 5.1; p < 0.0001).

Conclusion

Unlike OHS pregnant women, SHS pregnant women have high incidence of PE coupled with unbalanced levels of OS and AGMs at 10–20 weeks gestation. Combining early gestational profiling of OS and AGMs created an avenue for early differentiation of PE subtypes in the context of 3 PM care for mothers at high risk of PE.

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Abbreviations

sEng:

soluble endoglin

sFlt-1:

soluble Fms-like tyrosine kinase-1

8-epi-PGF2α:

8-epi-prostaglansinF2alpha

8-OHdG:

8-hydroxy-2-deoxyguanosin

AGMs:

angiogenic growth mediators

AUC:

area under the curve

CS:

caesarean section

EO-PE:

early-onset PE

GHOACS:

Ghanaian Suboptimal Health Cohort Study

KATH:

Komfo Anokye Teaching Hospital

LO-PE:

late-onset PE

NPV:

negative predicted value

NTN-P:

normotensive pregnancy

NTN-PW:

normotensive pregnant women

OHS:

optimal health status

OS:

oxidative stress

PE:

preeclampsia

PlGF:

placental growth factor

PPV:

positive predicted value

PWLD:

pregnant women who later developed

RR:

relative risk

SHS:

suboptimal health status

SHSQ-25:

Suboptimal Health Status questionnaire

TAC:

total antioxidant capacity

VEGF-A:

vascular endothelium growth factor-A

References

  1. Phipps E, Prasanna D, Brima W, Jim B. Preeclampsia: updates in pathogenesis, definitions, and guidelines. Clin J Am Soc Nephrol. 2016;11(6):1102–13. Epub 2016/04/21. doi: https://doi.org/10.2215/cjn.12081115. PubMed PMID: 27094609 ; PubMed Central PMCID: PMCPMC4891761.

  2. Tranquilli AL, Brown MA, Zeeman GG, Dekker G, Sibai BM. The definition of severe and early-onset preeclampsia. Statements from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Pregnancy Hypertens. 2013;3(1):44–7. Epub 2013/01/01. https://doi.org/10.1016/j.preghy.2012.11.001.

    Article  PubMed  Google Scholar 

  3. Golubnitschaja O. Flammer syndrome: from phenotype to associated pathologies, prediction, prevention and personalisation. Golubnitschaja O, editor: Springer International publishing; 2019. 1–373 p.

  4. Wang W, Yan Y, Guo Z, Hou H, Garcia M, Tan X, et al. All around suboptimal health - a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine. Epma j. 2021:1–31. Epub 2021/09/21. doi: https://doi.org/10.1007/s13167-021-00253-2. PubMed PMID: 34539937; PubMed Central PMCID: PMCPMC8435766.

  5. Alkema L, Chou D, Hogan D, Zhang S, Moller AB, Gemmill A, et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. Lancet. 2016;387(10017):462–74. Epub 2015/11/21. doi: https://doi.org/10.1016/s0140-6736(15)00838-7. PubMed PMID: 26584737; PubMed Central PMCID: PMCPMC5515236.

  6. Harmon QE, Huang L, Umbach DM, Klungsøyr K, Engel SM, Magnus P, et al. Risk of fetal death with preeclampsia. Obstet Gynecol. 2015;125(3):628–35. Epub 2015/03/03. doi: https://doi.org/10.1097/aog.0000000000000696. PubMed PMID: 25730226; PubMed Central PMCID: PMCPMC4347876.

  7. Lee QY, Odoi AT, Opare-Addo H, Dassah ET. Maternal mortality in Ghana: a hospital-based review. Acta Obstet Gynecol Scand. 2012;91(1):87–92. Epub 2011/07/29. https://doi.org/10.1111/j.1600-0412.2011.01249.x.

    Article  PubMed  Google Scholar 

  8. Dassah ET, Kusi-Mensah E, Morhe ESK, Odoi AT. Maternal and perinatal outcomes among women with hypertensive disorders in pregnancy in Kumasi, Ghana. PLoS One. 2019;14(10):e0223478. Epub 2019/10/05. doi: https://doi.org/10.1371/journal.pone.0223478. PubMed PMID: 31584982; PubMed Central PMCID: PMCPMC6777792.

  9. Salam RA, Das JK, Ali A, Bhaumik S, Lassi ZS. Diagnosis and management of preeclampsia in community settings in low and middle-income countries. J Family Med Prim Care. 2015;4(4):501–6. Epub 2016/03/18. doi: https://doi.org/10.4103/2249-4863.174265. PubMed PMID: 26985406; PubMed Central PMCID: PMCPMC4776599.

  10. Rawlins B, Plotkin M, Rakotovao JP, Getachew A, Vaz M, Ricca J, et al. Screening and management of pre-eclampsia and eclampsia in antenatal and labor and delivery services: findings from cross-sectional observation studies in six sub-Saharan African countries. BMC Pregnancy Childbirth. 2018;18(1):346. Epub 2018/08/25. doi: https://doi.org/10.1186/s12884-018-1972-1. PubMed PMID: 30139342; PubMed Central PMCID: PMCPMC6108136.

  11. Wang W, Russell A, Yan Y. Traditional Chinese medicine and new concepts of predictive, preventive and personalized medicine in diagnosis and treatment of suboptimal health. Epma j. 2014;5(1):4. Epub 2014/02/14. doi: https://doi.org/10.1186/1878-5085-5-4. PubMed PMID: 24521056; PubMed Central PMCID: PMCPMC3926271.

  12. Wang W, Yan Y. Suboptimal health: a new health dimension for translational medicine. Clin Transl Med. 2012;1(1):28. Epub 2013/02/02. doi: 10.1186/2001-1326-1-28. PubMed PMID: 23369267; PubMed Central PMCID: PMCPMC3561061.

  13. Wang Y, Ge S, Yan Y, Wang A, Zhao Z, Yu X, et al. China suboptimal health cohort study: rationale, design and baseline characteristics. J Transl Med. 2016;14(1):291. Epub 2016/10/16. doi: 10.1186/s12967-016-1046-y. PubMed PMID: 27737677; PubMed Central PMCID: PMCPMC5064923.

  14. Yan YX, Liu YQ, Li M, Hu PF, Guo AM, Yang XH, et al. Development and evaluation of a questionnaire for measuring suboptimal health status in urban Chinese. J Epidemiol. 2009;19(6):333–41. Epub 2009/09/15. doi: 10.2188/jea.je20080086. PubMed PMID: 19749497; PubMed Central PMCID: PMCPMC3924103.

  15. Wang X, Zhong Z, Balmer L, Wang W. Glycosylation profiling as a biomarker of suboptimal health status for chronic disease stratification. Adv Exp Med Biol. 2021;1325:321–39. Epub 2021/09/09. https://doi.org/10.1007/978-3-030-70115-4_16.

    Article  PubMed  Google Scholar 

  16. Anto EO, Roberts P, Coall D, Turpin CA, Adua E, Wang Y, et al. Integration of suboptimal health status evaluation as a criterion for prediction of preeclampsia is strongly recommended for healthcare management in pregnancy: a prospective cohort study in a Ghanaian population. Epma j. 2019;10(3):211–26. Epub 2019/08/30. doi: 10.1007/s13167-019-00183-0. PubMed PMID: 31462939; PubMed Central PMCID: PMCPMC6695466.

  17. Anto EO, Roberts P, Coall DA, Adua E, Turpin CA, Tawiah A, et al. Suboptimal health pregnant women are associated with increased oxidative stress and unbalanced pro- and antiangiogenic growth mediators: a cross-sectional study in a Ghanaian population. Free Radic Res. 2020;54(1):27–42. Epub 2019/12/10. https://doi.org/10.1080/10715762.2019.1685668.

    Article  CAS  PubMed  Google Scholar 

  18. Turpin CA, Sakyi SA, Owiredu WK, Ephraim RK, Anto EO. Association between adverse pregnancy outcome and imbalance in angiogenic regulators and oxidative stress biomarkers in gestational hypertension and preeclampsia. BMC Pregnancy Childbirth. 2015;15:189. Epub 2015/08/26. doi: 10.1186/s12884-015-0624-y. PubMed PMID: 26303772; PubMed Central PMCID: PMCPMC4549075.

  19. Anto EO, Roberts P, Turpin CA, Wang W. Oxidative stress as a key signaling pathway in placental angiogenesis changes in preeclampsia: updates in pathogenesis, novel biomarkers and therapeutics. Current Pharmacogenomics and Personalized Medicine (Formerly Current Pharmacogenomics). 2018;16(3):167–81.

    Article  CAS  Google Scholar 

  20. Pereira RD, De Long NE, Wang RC, Yazdi FT, Holloway AC, Raha S. Angiogenesis in the placenta: the role of reactive oxygen species signaling. Biomed Res Int. 2015;2015:814543. Epub 2015/02/24. doi: 10.1155/2015/814543. PubMed PMID: 25705690; PubMed Central PMCID: PMCPMC4325211.

  21. Marín R, Chiarello DI, Abad C, Rojas D, Toledo F, Sobrevia L. Oxidative stress and mitochondrial dysfunction in early-onset and late-onset preeclampsia. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1866;2020(12):165961. https://doi.org/10.1016/j.bbadis.2020.165961.

    Article  CAS  Google Scholar 

  22. Yoshida A, Watanabe K, Iwasaki A, Kimura C, Matsushita H, Wakatsuki A. Placental oxidative stress and maternal endothelial function in pregnant women with normotensive fetal growth restriction. J Matern Fetal Neonatal Med. 2018;31(8):1051–7. Epub 2017/04/04. https://doi.org/10.1080/14767058.2017.1306510 .

    Article  CAS  PubMed  Google Scholar 

  23. Lou WZ, Jiang F, Hu J, Chen XX, Song YN, Zhou XY, et al. Maternal serum angiogenic factor sFlt-1 to PlGF ratio in preeclampsia: a useful marker for differential diagnosis and prognosis evaluation in Chinese women. Dis Markers. 2019;2019:6270187. Epub 2019/08/10. doi: 10.1155/2019/6270187. PubMed PMID: 31396294; PubMed Central PMCID: PMCPMC6664509.

  24. Honigberg MC, Cantonwine DE, Thomas AM, Lim KH, Parry SI, McElrath TF. Analysis of changes in maternal circulating angiogenic factors throughout pregnancy for the prediction of preeclampsia. J Perinatol. 2016;36(3):172–7. Epub 2015/11/20. https://doi.org/10.1038/jp.2015.170.

    Article  CAS  PubMed  Google Scholar 

  25. Torres Crigna A, Link B, Samec M, Giordano FA, Kubatka P, Golubnitschaja O. Endothelin-1 axes in the framework of predictive, preventive and personalised (3P) medicine. EPMA Journal. 2021. https://doi.org/10.1007/s13167-021-00248-z.

  26. Koklesova L, Samec M, Liskova A, Zhai K, Büsselberg D, Giordano FA, et al. Mitochondrial impairments in aetiopathology of multifactorial diseases: common origin but individual outcomes in context of 3P medicine. Epma j. 2021;12(1):1–14. Epub 2021/03/10. doi: 10.1007/s13167-021-00237-2. PubMed PMID: 33686350; PubMed Central PMCID: PMCPMC7931170.

  27. Ahenkorah L. Metabolic syndrome, oxidative stress and putative risk factors amongst Ghanaian women presenting with pregnancy-induced hypertension [Doctorate]. KNUST repository: KNUST; 2009.

  28. Husse S, Gottschlich A, Schrey S, Stepan H, Hoffmann J. Predictive value of the sFlt1/PlGF ratio for the diagnosis of preeclampsia in high-risk patients. Z Geburtshilfe Neonatol. 2014;218(1):34–41. Epub 2014/03/07. https://doi.org/10.1055/s-0034-1368713.

    Article  CAS  PubMed  Google Scholar 

  29. Verlohren S, Herraiz I, Lapaire O, Schlembach D, Moertl M, Zeisler H, et al. The sFlt-1/PlGF ratio in different types of hypertensive pregnancy disorders and its prognostic potential in preeclamptic patients. Am J Obstet Gynecol. 2012;206(1):58.e1–8. Epub 2011/10/18. doi: 10.1016/j.ajog.2011.07.037.

  30. Pratt A, Da Silva CF, Borg AJ, Kalionis B, Keogh R, Murthi P. Placenta-derived angiogenic proteins and their contribution to the pathogenesis of preeclampsia. Angiogenesis. 2015;18(2):115–23. Epub 2014/12/01. https://doi.org/10.1007/s10456-014-9452-3.

    Article  CAS  PubMed  Google Scholar 

  31. Chaiworapongsa T, Chaemsaithong P, Yeo L, Romero R. Pre-eclampsia part 1: current understanding of its pathophysiology. Nat Rev Nephrol. 2014;10(8):466–80. Epub 2014/07/09. doi: 10.1038/nrneph.2014.102. PubMed PMID: 25003615; PubMed Central PMCID: PMCPMC5893150.

  32. O'Brien M, Baczyk D, Kingdom JC. Endothelial dysfunction in severe preeclampsia is mediated by soluble factors, rather than extracellular vesicles. Sci Rep. 2017;7(1):5887. Epub 2017/07/21. doi: 10.1038/s41598-017-06178-z. PubMed PMID: 28725005; PubMed Central PMCID: PMCPMC5517616.

  33. Golubnitschaja O, Liskova A, Koklesova L, Samec M, Biringer K, Büsselberg D, et al. Caution, "normal" BMI: health risks associated with potentially masked individual underweight-EPMA Position Paper 2021. Epma j. 2021;12(3):1–22. Epub 2021/08/24. doi: 10.1007/s13167-021-00251-4. PubMed PMID: 34422142; PubMed Central PMCID: PMCPMC8368050.

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Acknowledgements

The authors are grateful to all study participants, the biomedical staff of the Department of Biochemistry and Serology, and midwives of the Department of Obstetrics and Gynaecology of the Komfo Anokye Teaching Hospital, Ghana, for their support during the participant’s recruitment and biological sample processing. We also thank the research assistants of the Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology for their support during the biological sample analysis.

Availability of data and material

The data used in the analysis is available upon request from the corresponding author.

Funding

The Australia-China International Collaborative Grant (NHMRC-APP1112767- NSFC81561120) and Edith Cowan University (ECU)-Collaborative Enhancement Scheme Round 1 (G1003363) supported this work. Enoch Odame Anto was supported by ECU-International Postgraduate Research Scholarship.

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Contributions

EOA, DAC and WW conceived the study. EOA, AT, OAM, CO, YAW, WKBAO, BAO and YW performed the investigation and collected the data. EOA, SO, EAA, BKD and EA performed the statistical analysis. EOA, EAA, HH, MEAA, AT, EA and XW wrote the initial draft paper. All authors revised, read and approved the final manuscript.

Corresponding author

Correspondence to Wei Wang.

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Ethical approval and consent to participate

Approval for this study was obtained from the Ethics Committees of the School of Medical Science /KNUST and KATH (CHRPE/AP/146/17) and Edith Cowan University (ECU) (17509). This study was conducted in accordance with the guidelines of the Helsinki Declaration. Written informed consent in the form of a signature and fingerprint was obtained from all participants and legally authorised representatives after the protocol of the study was explained to them in plain English language and native Ghanaian language where appropriate.

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Not applicable

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The authors declare no competing interest.

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Anto, E.O., Coall, D.A., Addai-Mensah, O. et al. Early gestational profiling of oxidative stress and angiogenic growth mediators as predictive, preventive and personalised (3P) medical approach to identify suboptimal health pregnant mothers likely to develop preeclampsia. EPMA Journal 12, 517–534 (2021). https://doi.org/10.1007/s13167-021-00258-x

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