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Estimating onset time from longitudinal data in the presence of measurement error with application to estimating gestational age from maternal anthropometry during pregnancy.

ABSTRACT: Accurate assessment of gestational age at birth is necessary for optimal pediatric care. In high resource countries, several methods using ultrasound have been proposed to assess gestational age at birth; however, these methods are not easily accessible for low-resource populations. We develop a shared random parameter model for estimating gestational age at birth from longitudinal maternal anthropometry that incorporates additional maternal information from the last menstrual period, a measure of gestational age collected with sizable measurement error. The proposed methodology is evaluated using simulation studies under a training-test set paradigm. In addition, we propose methodology to validate prediction when some measurements of the gold standard are collected with measurement error. We illustrate the proposed methodologies with data from the NICHD Fetal Growth Studies.

SUBMITTER: Ortega-Villa AM

PROVIDER: S-EPMC6497444 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Estimating onset time from longitudinal data in the presence of measurement error with application to estimating gestational age from maternal anthropometry during pregnancy.

Ortega-Villa Ana M AM Albert Paul S PS

Statistics in medicine 20180917 30

Accurate assessment of gestational age at birth is necessary for optimal pediatric care. In high resource countries, several methods using ultrasound have been proposed to assess gestational age at birth; however, these methods are not easily accessible for low-resource populations. We develop a shared random parameter model for estimating gestational age at birth from longitudinal maternal anthropometry that incorporates additional maternal information from the last menstrual period, a measure ...[more]

PMID: 30295951

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Project description:OBJECTIVE:Pregnancy is accompanied by dramatic physiological changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age and determine biological processes that are perturbed in normal pregnancy. STUDY DESIGN:A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median, 5) were profiled to measure the abundance of 1125 proteins using multiplex assays. Linear mixed-effects models with polynomial splines were used to model protein abundance as a function of gestational age, and the significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having the following: (1) >1.5-fold change between 8 and 40 weeks of gestation; and (2) a false discovery rate-adjusted value of P < .1. Gene ontology enrichment analysis was used to identify biological processes overrepresented among the proteins that changed with advancing gestation. RESULTS:The following results were found: (1) Ten percent (112 of 1125) of the profiled proteins changed in abundance as a function of gestational age; (2) of the 1125 proteins analyzed, glypican-3, sialic acid-binding immunoglobulin-type lectin-6, placental growth factor, C-C motif-28, carbonic anhydrase 6, prolactin, interleukin-1 receptor 4, dual-specificity mitogen-activated protein kinase 4, and pregnancy-associated plasma protein-A had more than a 5-fold change in abundance across gestation (these 9 proteins are known to be involved in a wide range of both physiological and pathological processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc); and (3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis, and leukocyte migration (false discovery rate, 10%). CONCLUSION:The plasma proteome of normal pregnancy demonstrates dramatic changes in both the magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy and the development of biomarkers to differentiate normal vs abnormal pregnancy and determine the response to interventions.

Project description:As surrogate readouts reflecting mitochondrial dysfunction, elevated levels of plasma acylcarnitines have been associated with cardiometabolic disorders, such as obesity, gestational diabetes, and type 2 diabetes. This study aimed to examine prospective associations of acylcarnitine profiles across gestation with neonatal anthropometry, including birthweight, birthweight z score, body length, sum of skinfolds, and sum of body circumferences. We quantified 28 acylcarnitines using electrospray ionization tandem mass spectrometry in plasma collected at gestational weeks 10-14, 15-26, 23-31, and 33-39 among 321 pregnant women from the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons. A latent-class trajectory approach was applied to identify trajectories of acylcarnitines across gestation. We examined the associations of individual acylcarnitines and distinct trajectory groups with neonatal anthropometry using weighted generalized linear models adjusting for maternal age, race/ethnicity, education, parity, gestational age at blood collection, and pre-pregnancy body mass index (BMI). We identified three distinct trajectory groups in C2, C3, and C4 and two trajectory groups in C5, C10, C5-DC, C8:1, C10:1, and C12, respectively. Women with nonlinear decreasing C12 levels across gestation (5.7%) had offspring with significantly lower birthweight (-475 g; 95% CI, -942, -6.79), birthweight z score (-0.39, -0.71, -0.06), and birth length (-1.38 cm, -2.49, -0.27) than those with persistently stable C12 levels (94.3%) (all nominal p value < 0.05). Women with consistently higher levels of C10 (6.1%) had offspring with thicker sum of skinfolds (4.91 mm, 0.85, 8.98) than did women with lower levels (93.9%) during pregnancy, whereas women with lower C10:1 levels (12.6%) had offspring with thicker sum of skinfolds (3.23 mm, 0.19, 6.27) than did women with abruptly increasing levels (87.4%) (p < 0.05). In conclusion, this study suggests that distinctive trajectories of C10, C10:1, and C12 acylcarnitine levels throughout pregnancy were significantly associated with neonatal anthropometry.

Dataset Information

Estimating onset time from longitudinal data in the presence of measurement error with application to estimating gestational age from maternal anthropometry during pregnancy.

Publications

Estimating onset time from longitudinal data in the presence of measurement error with application to estimating gestational age from maternal anthropometry during pregnancy.

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