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Highlights • Low and middle-income (LMIC) countries still suffer with pre-eclampsia. • Risk assessment of pre-eclampsia has evolved in high-income countries. • Biobanks can provide a unique opportunity to understand preeclampsia in LMIC. • Databanks can provide a unique opportunity to understand preeclampsia in LMIC., The Millennium Development Goal 5, a project signed in 2000, intended to improve maternal health and reduce maternal mortality by 75% by 2015. Despite all efforts, little progress has been achieved in low and middle-income countries (LMIC) and 99% of all maternal deaths related to pre-eclampsia (PE) still occur in these settings. It is important to determine whether women in LMIC, where PE carries a greater risk than in high-income countries (HIC), have unique risk factors. Some variances may alter the risk, severity and pertinent pathophysiology of PE. We posit based upon this, that women from LMIC may have biomarkers specific to this population. Discovering such specific biomarkers and testing the relevance of biomarkers developed in high-income populations could increase the clinical usefulness of these analyses without increasing cost-effective approaches for prediction of PE. Here we briefly describe our platform to develop the PREPARE – Biobank in tertiary hospitals or basic units for antenatal care from 6 different cities in Brazil. The PREPARE – Biobank has been developed with two arms. The first arm is a cross-sectional study that will collect clinical information and biosamples from more than 1000 women who developed preterm PE. The second arm is a cohort study of 7000 women. It will collect clinical information and longitudinal biosamples from women at three times during pregnancy

Made available in DSpace on 2018-11-26T16:28:07Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-01-01 Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health National Institute for Health Research Background: A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. Methods: Using circulating placental growth factor (PIGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preeclampsia, as an example, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PIGF measurements (gestational age >= 20 weeks) analyzed on one of four platforms: R & Systems, Alere (R) Triage, Roche (R) Elecsys or Abbott (R) Architect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. Results: Best reference curves (BRC), based on merged, transformed PIGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PIGF-BRCS was compared to that of platform-specific curves. Conclusions: We demonstrate the feasibility of merging PIGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes. (C) 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved. Univ Oxford, Nuffield Dept Populat Hlth, Old Rd Campus, Oxford OX3 7LF, England Univ British Columbia, Dept Obstet & Gynaecol, Vancouver, BC V5Z 1M9, Canada Univ British Columbia, Child & Family Res Inst, Vancouver, BC V5Z 1M9, Canada Univ Oxford, Nuffield Dept Obstet & Gynaecol, Oxford, England Yale Univ, New Haven, CT USA Univ Milan, I-20122 Milan, Italy Kings Coll London, Womens Hlth Acad Ctr, London WC2R 2LS, England Univ Barcelona, Hosp Clin, Barcelona, Spain Hosp Univ 12 Octubre, Dept Obstet & Gynecol, Fetal Med Unit, Madrid, Spain Univ Complutense, E-28040 Madrid, Spain Michigan State Univ, E Lansing, MI 48824 USA Univ Pittsburgh, Magee Womens Res Inst, Pittsburgh, PA USA Aarhus Univ Hosp, Dept Obstet & Gynecol, DK-8000 Aarhus, Denmark Aarhus Univ, Aarhus, Denmark Aarhus Univ Hosp, Dept Oncol, DK-8000 Aarhus, Denmark Univ Helsinki, Med Genet Obstet & Gynaecol, Helsinki, Finland Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland Helsinki Univ Hosp, Helsinki, Finland Univ Basel, Basel, Switzerland Harvard Univ, Brigham & Womens Hosp, Sch Med, Boston, MA 02115 USA Klagenfurt & Med Univ, Interdisciplinary Ctr Gynecol Gynecooncol & Fetom, Graz, Austria St Marys Hosp, Maternal & Fetal Hlth Res Ctr, Manchester M13 0JH, Lancs, England Univ Manchester, Manchester, Lancs, England Univ Texas Houston, Sch Publ Hlth, Houston, TX USA Univ Estadual Paulista, Dept Obstet, Botucatu, SP, Brazil Univ Texas Med Branch, Galveston, TX 77555 USA Univ Amsterdam, Acad Med Ctr, Dept Obstet & Gynaecol, Meibergdreef 9, NL-1105 AZ Amsterdam, Netherlands Erasmus MC, Rotterdam, Netherlands Univ Jena, D-07745 Jena, Germany Univ Leipzig, D-04109 Leipzig, Germany Univ Paris 05, Paris, France Charite, D-13353 Berlin, Germany Univ Helsinki, Obstet & Gynecol, Helsinki, Finland NIHR Univ Coll London Hosp, Biomed Res Ctr, Inst Womens Hlth, London, England Med Univ Vienna, Dept Obstet & Gynecol, Vienna, Austria Oslo Univ Hosp, Dept Obstet & Gynecol, Oslo, Norway Univ Oslo, Oslo, Norway Univ Estadual Paulista, Dept Obstet, Botucatu, SP, Brazil National Institute for Health Research: RP-2014-05-019