ID

46169

Beschreibung

Principal Investigator: William L. Lowe, Jr, MD, Northwestern University Feinberg School of Medicine, Chicago, IL, USA MeSH: Pregnancy https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000096 Low and high birth weight are not only major causes of neonatal morbidity and mortality, but epidemiological data have established an association between birth weight and later life risk of adult metabolic diseases. Fetal growth is determined by complex interactions between fetal genes and the maternal uterine environment. Subtle or overt variation in maternal glucose tolerance, which is, in part, genetically determined, is related to fetal size at birth. Moreover, new emerging data suggest that genetic variation in the fetus can impact maternal metabolism (e.g., blood pressure and glucose tolerance). Given the above, we are addressing the hypothesis that, during pregnancy, gene-environment interactions in the context of the maternal-fetal unit impact fetal size at birth and maternal metabolism. Genes that control fetal growth or maternal metabolism during pregnancy are largely unknown, so the first step to address our hypothesis will be to identify genetic variation that impacts fetal growth and maternal metabolism and to determine the interaction of that variation with the intrauterine and fetal environment. To accomplish this, we are performing genome wide association (GWA) mapping on a subset of ~37,000 DNA samples that were collected from mothers and their offspring as part of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. HAPO is a multicenter, international study in which high quality phenotypic data related to fetal growth and maternal glucose metabolism has been collected from 25,000 pregnant women of varied racial and socio-demographic backgrounds using standardized protocols that were uniform across centers. For these studies, we are genotyping 1,500 infants and their mothers of European descent, 1,250 Afro-Caribbean infants and mothers, 800 Hispanic (Mexican-American) infants and mothers, and 1200 Thai infants and mothers. Genotyping is being performed using the Illumina Human610 Quad (European ancestry participants), Human1M Duo (Afro-Caribbean and Hispanic participants), and Omni1-Quad_v1-0_B (Thai participants). The specific aims for the project are as follows: (1) To apply analytic approaches for conducting GWA mapping studies on quantitative phenotypes related to offspring size at birth (birth weight, ponderal index, head circumference and adiposity) allowing for other known influences such as gestational age, parity, and maternal weight gain. (2) To apply the above approaches to identify genetic variation that impacts maternal glucose tolerance at ~28 weeks of gestation (fasting glucose, glucose during an oral glucose tolerance test, and insulin sensitivity expressed as quantitative traits) allowing for other known influences such as maternal weight gain, parity and age. (3) To examine the interaction between maternal genes, the intrauterine environment, and fetal genes to identify interactions that modulate genetic regulation of size at birth and fetal genetic variation that impacts on maternal glucose tolerance. GWA mapping will provide initial evidence for association of specific SNPs with the quantitative traits outlined above. As low and high birth weight are not only major causes of neonatal morbidity and mortality but have also been associated with increased risk of metabolic diseases in adults, identification of genes that regulate fetal growth and maternal metabolism will provide novel information about the pathways that regulate these processes as well as important insight into susceptibility genes for chronic diseases like type 2 diabetes. The Version 1 (v1) dbGaP release will include data only from the Hispanic study participants. The Version 2 (v2) dbGaP release will include data from the Hispanic and European ancestry study participants. The Version 3 (v3) dbGaP release will include data from the Afro-Caribbean, Hispanic and European ancestry participants. The Version 4 (v4) dbGaP release will include data from all participants (i.e., Afro-Caribbean, Hispanic, European ancestry, and Thai participants). This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to maternal metabolism and birthweight through large-scale genome-wide association studies of infants and their mothers at multiple international sites. Genotyping was performed at the Broad Institute of MIT and Harvard, and at CIDR of Johns Hopkins University, GENEVA genotyping centers. Data cleaning and harmonization was performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Link

dbGaP study=phs000096

Stichworte

  1. 11.07.22 11.07.22 - Chiara Middel
  2. 12.10.22 12.10.22 - Adrian Schulz
  3. 29.01.25 29.01.25 - Akane Nishihara
Rechteinhaber

William L. Lowe, Jr, MD, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Hochgeladen am

29. Januar 2025

DOI

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Lizenz

Creative Commons BY 4.0

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dbGaP phs000096 HAPO Maternal Glycemia and Birthweight GEI Study

Statistical pedigree analysis of participants affected with metabolic diseases.

pht001425
Beschreibung

pht001425

First geneva.id of cryptic relatedness [HS-like]
Beschreibung

geneva.id1

Datentyp

text

Alias
UMLS CUI [1,1]
C0205435
UMLS CUI [1,2]
C2348585
UMLS CUI [1,3]
C1547655
Second geneva.id of cryptic relatedness [HS-like]
Beschreibung

geneva.id2

Datentyp

text

Alias
UMLS CUI [1,1]
C0205436
UMLS CUI [1,2]
C1547655
UMLS CUI [1,3]
C2348585
K0 [probability of having zero pairs of IBD alleles] estimate
Beschreibung

k0

Datentyp

float

Alias
UMLS CUI [1,1]
C0033204
UMLS CUI [1,2]
C1298908
UMLS CUI [1,3]
C3846158
UMLS CUI [1,4]
C0002085
K1 [probability of having one pairs of IBD alleles] estimate
Beschreibung

k1

Datentyp

float

Alias
UMLS CUI [1,1]
C0033204
UMLS CUI [1,2]
C0205447
UMLS CUI [1,3]
C3846158
UMLS CUI [1,4]
C0002085
Kinship coefficient estimate
Beschreibung

KC

Datentyp

float

Alias
UMLS CUI [1,1]
C0870772
UMLS CUI [1,2]
C1707429
UMLS CUI [1,3]
C0750572

Ähnliche Modelle

Statistical pedigree analysis of participants affected with metabolic diseases.

Name
Typ
Description | Question | Decode (Coded Value)
Datentyp
Alias
Item Group
pht001425
geneva.id1
Item
First geneva.id of cryptic relatedness [HS-like]
text
C0205435 (UMLS CUI [1,1])
C2348585 (UMLS CUI [1,2])
C1547655 (UMLS CUI [1,3])
geneva.id2
Item
Second geneva.id of cryptic relatedness [HS-like]
text
C0205436 (UMLS CUI [1,1])
C1547655 (UMLS CUI [1,2])
C2348585 (UMLS CUI [1,3])
k0
Item
K0 [probability of having zero pairs of IBD alleles] estimate
float
C0033204 (UMLS CUI [1,1])
C1298908 (UMLS CUI [1,2])
C3846158 (UMLS CUI [1,3])
C0002085 (UMLS CUI [1,4])
k1
Item
K1 [probability of having one pairs of IBD alleles] estimate
float
C0033204 (UMLS CUI [1,1])
C0205447 (UMLS CUI [1,2])
C3846158 (UMLS CUI [1,3])
C0002085 (UMLS CUI [1,4])
KC
Item
Kinship coefficient estimate
float
C0870772 (UMLS CUI [1,1])
C1707429 (UMLS CUI [1,2])
C0750572 (UMLS CUI [1,3])

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