TY - JOUR

T1 - Cohort profile

T2 - 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

AU - Pangratz-Fuehrer, Susanne

AU - Genzel-Boroviczény, Orsolya

AU - Bodensohn, Wolfgang Emanuel

AU - Eisenburger, Robin

AU - Scharpenack, Janne

AU - Geyer, Philipp E

AU - Müller-Reif, Johannes B

AU - van Hagen, Nadja

AU - Müller, Alina M

AU - Jensen, Majken Karoline

AU - Klein, Christoph

AU - Mann, Matthias

AU - Nussbaum, Claudia

PY - 2021

Y1 - 2021

N2 - 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.TRIAL REGISTRATION NUMBER: DRKS (00024189); Pre-results.

AB - 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.TRIAL REGISTRATION NUMBER: DRKS (00024189); Pre-results.

KW - Child

KW - Cohort Studies

KW - Female

KW - Gestational Age

KW - Hospitalization

KW - Humans

KW - Infant

KW - Infant, Newborn

KW - Morbidity

KW - Pregnancy

KW - Premature Birth/epidemiology

KW - Proteomics

U2 - 10.1136/bmjopen-2021-050652

DO - 10.1136/bmjopen-2021-050652

M3 - Journal article

C2 - 34168035

VL - 11

JO - BMJ Open

JF - BMJ Open

SN - 2044-6055

IS - 6

M1 - e050652

ER -