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  Cohort profile: the MUNICH Preterm and Term Clinical study (MUNICH-PreTCl), a neonatal birth cohort with focus on prenatal and postnatal determinants of infant and childhood morbidity

Pangratz-Fuehrer, S., Genzel-Boroviczeny, O., Bodensohn, W. E., Eisenburger, R., Scharpenack, J., Geyer, P. E., et al. (2021). Cohort profile: the MUNICH Preterm and Term Clinical study (MUNICH-PreTCl), a neonatal birth cohort with focus on prenatal and postnatal determinants of infant and childhood morbidity. BMJ Open, 11(6): e050652. doi:10.1136/bmjopen-2021-050652.

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 Creators:
Pangratz-Fuehrer, Susanne1, Author
Genzel-Boroviczeny, Orsolya1, Author
Bodensohn, Wolfgang Emanuel1, Author
Eisenburger, Robin1, Author
Scharpenack, Janne1, Author
Geyer, Philipp E.2, Author              
Müller-Reif, Johannes B.2, Author              
van Hagen, Nadja1, Author
Muller, Alina M.1, Author
Jensen, Majken Karoline1, Author
Klein, Christoph1, Author
Mann, Matthias2, Author              
Nussbaum, Claudia1, Author
Affiliations:
1external, ou_persistent22              
2Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              

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Free keywords: GESTATIONAL-AGE; WEIGHTGeneral & Internal Medicine; neonatology; paediatrics; cell biology; preventive medicine;
 Abstract: Purpose The MUNICH Preterm and Term Clinical (MUNICH-PreTCl) birth cohort was established to uncover pathological processes contributing to infant/childhood morbidity and mortality. We collected comprehensive medical information of healthy and sick newborns and their families, together with infant blood samples for proteomic analysis. MUNICH-PreTCl aims to identify mechanism-based biomarkers in infant health and disease to deliver more precise diagnostic and predictive information for disease prevention. We particularly focused on risk factors for pregnancy complications, family history of genetically influenced health conditions such as diabetes and paediatric long-term health-all to be further monitored and correlated with proteomics data in the future. Participants Newborns and their parents were recruited from the Perinatal Center at the LMU University Hospital, Munich, between February 2017 and June 2019. Infants without congenital anomalies, delivered at 23-41 weeks of gestation, were eligible. Findings Findings to date concern the clinical data and extensive personal patient information. A total of 662 infants were recruited, 44% were female (36% in preterm, 46% in term). 90% of approached families agreed to participate. Neonates were grouped according to gestational age: extremely preterm (<28 weeks, N=28), very preterm (28 to <32 weeks, N=36), late preterm (32 to <37 weeks, N=97) and term infants (>37+0 weeks, N=501). We collected over 450 data points per child-parent set, (family history, demographics, pregnancy, birth and daily follow-ups throughout hospitalisation) and 841 blood samples longitudinally. The completion rates for medical examinations and blood samples were 100% and 95% for the questionnaire. Future plans The correlation of large clinical datasets with proteomic phenotypes, together with the use of medical registries, will enable future investigations aiming to decipher mechanisms of disorders in a systems biology perspective.

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: 13
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: BMJ Open
Source Genre: Journal
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Publ. Info: London, United Kingdom : BMJ Publ. Group
Pages: - Volume / Issue: 11 (6) Sequence Number: e050652 Start / End Page: - Identifier: ISSN: 2044-6055
CoNE: https://pure.mpg.de/cone/journals/resource/2044-6055