Genetic and Environmental Components of Neonatal Weight Gain in Preterm Infants

Brescianini, Sonia; Giampietro, S.; Cotichini, Rodolfo; Lucchini, Renato; Curtis, Mario De

doi:10.1542/peds.2010-0510

Cited by 9 publications

(11 citation statements)

References 17 publications

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“…This might explain why PT-SGAs were often more underweight rather than small. Growth may also be influenced by chronic disease or by genetic factors as was reported recently [19]. Nevertheless, further research on the exact mechanisms of growth in PT-SGAs is needed.…”

Section: Discussionmentioning

confidence: 87%

Growth in Small-for-Gestational-Age Preterm-Born Children from 0 to 4 Years: The Role of both Prematurity and SGA Status

Bocca-Tjeertes¹,

Reijneveld²,

Kerstjens³

et al. 2013

Neonatology

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Background: Fullterm small-for-gestational-age children (SGAs) are known for their ability to catch up on growth. Nevertheless, increased risk of growth restriction remains. Evidence on preterm SGA children's growth is lacking. Objective: To determine absolute gains in height and weight, relative growth, and growth restriction in preterm SGAs from 0 to 4 years and how prematurity and SGA status affect these measures. Design/Methods: Community-based cohort study, n = 1,648 preterm-born (gestational age <36 weeks, 57 SGA) and 605 term-born (12 SGA). We defined SGA as a birth weight less than -2 SD (P 2.3) compared to counterparts matched for gestational age. Height, weight, and head circumference were obtained from medical records and translated to z-scores. We defined growth restriction as height or weight less than -2 SD compared to fullterm appropriate-for-gestational-age children (AGAs). Results: Absolute height and weight gains were similar, but the relative growth of preterms and fullterms differed. Preterm AGAs and fullterm SGAs, although not reaching it, caught up towards the fullterm AGA median (z-scores at 4 years: -0.3 to -1.0). By contrast, preterm SGA children's z-scores were still -1.4 to -1.7. Head circumference growth was less affected by prematurity and SGA birth (z-scores at 1 year: 0.1 to -0.7). Catch-up growth mainly took place during infancy. 30-39% of all preterm SGAs showed growth restriction at 4 years. Conclusions: Growth in preterm SGAs is affected considerably by the joint effects of preterm birth and SGA status, resulting in a high proportion of growth restriction.

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Section: Discussionmentioning

confidence: 87%

Growth in Small-for-Gestational-Age Preterm-Born Children from 0 to 4 Years: The Role of both Prematurity and SGA Status

Bocca-Tjeertes¹,

Reijneveld²,

Kerstjens³

et al. 2013

Neonatology

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“…These parameters can, however, be estimated by fitting model to the WHO population data. Additionally, due to the strong genetic component of growth 33 , the initial height at birth will be taken to represent genetic predisposition to growth. Thus, a linear regression between α values of the mean and mean ± SD and ±2SD growth curves and the corresponding initial heights at birth provides the genetic background in the model.…”

Section: Methodsmentioning

confidence: 99%

A time-varying biased random walk approach to human growth

Suki

Frey

2017

Sci Rep

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Growth and development are dominated by gene-environment interactions. Many approaches have been proposed to model growth, but most are either descriptive or describe population level phenomena. We present a random walk-based growth model capable of predicting individual height, in which the growth increments are taken from time varying distributions mimicking the bursting behaviour of observed saltatory growth. We derive analytic equations and also develop a computational model of such growth that takes into account gene-environment interactions. Using an independent prospective birth cohort study of 190 infants, we predict height at 6 years of age. In a subset of 27 subjects, we adaptively train the model to account for growth between birth and 1 year of age using a Bayesian approach. The 5-year predicted heights compare well with actual data (measured height = 0.838*predicted height + 18.3; R2 = 0.51) with an average error of 3.3%. In one patient, we also exemplify how our growth prediction model can be used for the early detection of growth deficiency and the evaluation of the effectiveness of growth hormone therapy.

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“…For all these phenotypes, heritability was around 33%, while almost all the remaining proportion of variance was due to shared environment, leaving very little to unique environment. ITR focused also on infant growth during the first month of life (Brescianini et al, 2012). The study was performed on preterm twins born in the same hospital in Rome.…”

Section: Perinatal and Pediatric Outcomesmentioning

confidence: 99%

An Update on the Italian Twin Register: Advances in Cohort Recruitment, Project Building and Network Development

et al. 2012

Self Cite

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The Italian Twin Register has been in place for more than 10 years. Since its establishment, it has been focusing, on the one hand, on a continuous update of the existing information, and on the other hand, on new phenotypes and sample collection. Demographic data on about 140,000 twins have been updated using the municipality registries. The Italian Twin Register has been carrying out several new studies during the last few years. A birth cohort of twins, Multiple Births Cohort Study, has been started and the enrollment is ongoing. For this cohort, data on pregnancy and birth are collected, and periodical follow-ups are made. DNA is being collected for the twins and their parents. In the area of behavioral genetics, most efforts have been directed to psychological well being assessed with self-reported tools. Research on age-related traits continues with studies on arteriosclerosis development, early biomarkers in mild cognitive impairment, and the relation between lifestyle habits and mutagen sensitivity. The Italian Twin Register biobanking has grown in its size and in its know-how in terms of both technical issues and ethical procedures implementation. Furthermore, attitudes toward biobank-based research, together with willingness and motivation for donation, are being investigated. A valuable key resource for the Italian Twin Register is the possibility of linking twin data with disease registries. This approach has been yielding several important results, such as the recent study on the heritability of type 1 diabetes.

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Genetic and Environmental Components of Neonatal Weight Gain in Preterm Infants

Abstract: This high heritability estimate could suggest using this set of criteria to identify genes that regulate postnatal weight gain or failure.

Cited by 9 publications

References 17 publications

Growth in Small-for-Gestational-Age Preterm-Born Children from 0 to 4 Years: The Role of both Prematurity and SGA Status

Growth in Small-for-Gestational-Age Preterm-Born Children from 0 to 4 Years: The Role of both Prematurity and SGA Status

A time-varying biased random walk approach to human growth

An Update on the Italian Twin Register: Advances in Cohort Recruitment, Project Building and Network Development

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