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      Genetic and Environmental Influences on Infant Growth: Prospective Analysis of the Gemini Twin Birth Cohort

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          Abstract

          Objective

          Infancy is a critical period during which rapid growth potentially programs future disease risk. Identifying the modifiable determinants of growth is therefore important. To capture the complexity of infant growth, we modeled growth trajectories from birth to six months in order to compare the genetic and environmental influences on growth trajectory parameters with single time-point measures at birth, three and six months of age.

          Methods

          Data were from Gemini, a population sample of 2402 UK families with twins. An average 10 weight measurements per child made by health professionals were available over the first six months. Weights at birth, three and six months were identified. Longitudinal growth trajectories were modeled using SITAR utilizing all available weight measures for each child. SITAR generates three parameters: size (characterizing mean weight throughout infancy), tempo (indicating age at peak weight velocity (PWV)), and velocity (reflecting the size of PWV). Genetic and environmental influences were estimated using quantitative genetic analysis.

          Results

          In line with previous studies, heritability of weight at birth and three months was low (38%), but it was higher at six months (62%). Heritability of the growth trajectory parameters was high for size (69%) and velocity (57%), but low (35%) for tempo. Common environmental influences predominated for tempo (42%).

          Conclusion

          Modeled growth parameters using SITAR indicated that size and velocity were primarily under genetic influence but tempo was predominantly environmentally determined. These results emphasize the importance of identifying specific modifiable environmental determinants of the timing of peak infant growth.

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          Most cited references71

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          R: a language and environment for statistic computing

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            Sympercents: symmetric percentage differences on the 100 log(e) scale simplify the presentation of log transformed data.

            The results of analyses on log transformed data are usually back-transformed and interpreted on the original scale. Yet if natural logs are used this is not necessary--the log scale can be interpreted as it stands. A difference of natural logs corresponds to a fractional difference on the original scale. The agreement is exact if the fractional difference is based on the logarithmic mean. The transform y = 100 log(e)x leads to differences, standard deviations and regression coefficients of y that are equivalent to symmetric percentage differences, standard deviations and regression coefficients of x. Several simple clinical examples show that the 100 log(e) scale is the natural scale on which to express percentage differences. The term sympercent or s% is proposed for them. Sympercents should improve the presentation of log transformed data and lead to a wider understanding of the natural log transformation. Copyright 2000 John Wiley & Sons, Ltd.
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              Rapid infancy weight gain and subsequent obesity: systematic reviews and hopeful suggestions.

              In a systematic review, we identified 21 separate studies with data on the association between rapid infancy weight gain, up to age 2 y, and subsequent obesity risk. Uniformly all studies reported significant positive associations. We transformed the reported effect sizes to a standard infancy weight gain exposure, and found that further differences in study design accounted for much of the variation in risk. An accompanying paper by Melinda Yeung reminds us that there are benefits of postnatal catch-up growth in certain populations, and suggests that genetic and nutritional factors could moderate the unhealthy translation of rapid infancy weight gain to visceral fat and insulin resistance. Further evidence is needed, and we will need to rigorously test the benefits and risks of any interventions. However, the concept of "healthy" rapid catch-up infancy growth is an attractive prospect. Rapid infancy weight gain is consistently associated with increased subsequent obesity risk, but the predictive ability of different weight gain cut-offs needs to be tested.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                27 May 2011
                : 6
                : 5
                : e19918
                Affiliations
                [1 ]Cancer Research UK Health Behavior Research Centre, Department of Epidemiology and Public Health, University College London, London, United Kingdom
                [2 ]Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
                [3 ]MRC Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London, United Kingdom
                Genentech Inc., United States of America
                Author notes

                Conceived and designed the experiments: JW LJ CHMvJ CHL TJC. Analyzed the data: LJ CHL TJC. Wrote the paper: LJ CHL TJC JW CHMvJ. Obtained funding for the study: JW.

                Article
                PONE-D-11-03460
                10.1371/journal.pone.0019918
                3103521
                21637764
                3b480921-91fd-4bdb-9697-3a7053609760
                Johnson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 17 February 2011
                : 14 April 2011
                Page count
                Pages: 6
                Categories
                Research Article
                Biology
                Genetics
                Heredity
                Genetic Determinism
                Human Genetics
                Genetic Association Studies
                Epigenetics
                Medicine
                Clinical Genetics
                Clinical Research Design
                Cohort Studies
                Epidemiology
                Clinical Epidemiology
                Non-Clinical Medicine
                Health Care Policy
                Health Risk Analysis
                Pediatrics
                Growth Retardation
                Neonatalology
                Public Health
                Child Health

                Uncategorized
                Uncategorized

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