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Project Topic
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The frequency of twin pregnancies is rising globally due to increased assisted conception and advanced maternal age in pregnancy. Twin pregnancies have 5-9 times higher frequencies of fetal chromosomal and structural abnormalities, often deliver preterm, and have high prevalence of gestational diabetes mellitus (GDM), preeclampsia (PE), and intrauterine growth restriction (IUGR) compared to singletons. Twins have special complications such as twins-to twin transfusion syndrome in monochorionic (MC) twins. Consequently, more twins are born prematurely, suffer from low birth weight, cerebral palsy, etc., often requiring admission to newborn intensive care units, and develop motor and cognitive disorders for life. These impose a huge burden on individuals, families, and the society. We aim to develop a multi-marker, personalized, prenatal diagnostics model to predict feto-maternal complications in twins. A multi-national network will recruit a statistically powered cohort of 1,200 twins, and follow them through pregnancy up to delivery utilizing prior risk, biochemical, endocrine, imagine, immunology and cell free DNA (cfDNA) measures. Initial twin cohorts (Prof. Maymon, Israel), revealed good prediction of Down syndrome, PE, and GDM by prior risk, ultrasound and serum markers. We will test all the abve, add cfDNA and evaluate structural and chromosomal abnormalities developed by Prof. Kagan (Tubingen, Germany), imagine standardised Prof.'s Brown and Miron (McGill, Canada) for MC twins, and endocrine, sonographic, and biophysical markers of Prof. Borrell (Barcelona, Spain), and of Dr. Geipel (Bonn, Germany). Prof. Nicolaides (London, UK) will contribute his twin cohort data at no charge. Prof. Cuckle (Israel) will conduct modelling with our large depository to yield risk stratification algorithms for twins, offering personalized, preventive clinical care of feto-maternal disorders. This would enable a paradigm shift in prenatal personalized care for twin pregnancy.
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