A time-varying biased random walk approach to human growth

Abstract 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 th...

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Autores principales:	Béla Suki, Urs Frey
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ca9d87fe95fd4686a0218e81f2246436
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spelling	oai:doaj.org-article:ca9d87fe95fd4686a0218e81f22464362021-12-02T12:31:59ZA time-varying biased random walk approach to human growth10.1038/s41598-017-07725-42045-2322https://doaj.org/article/ca9d87fe95fd4686a0218e81f22464362017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-07725-4https://doaj.org/toc/2045-2322Abstract 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.Béla SukiUrs FreyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Béla Suki Urs Frey A time-varying biased random walk approach to human growth
description	Abstract 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.
format	article
author	Béla Suki Urs Frey
author_facet	Béla Suki Urs Frey
author_sort	Béla Suki
title	A time-varying biased random walk approach to human growth
title_short	A time-varying biased random walk approach to human growth
title_full	A time-varying biased random walk approach to human growth
title_fullStr	A time-varying biased random walk approach to human growth
title_full_unstemmed	A time-varying biased random walk approach to human growth
title_sort	time-varying biased random walk approach to human growth
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ca9d87fe95fd4686a0218e81f2246436
work_keys_str_mv	AT belasuki atimevaryingbiasedrandomwalkapproachtohumangrowth AT ursfrey atimevaryingbiasedrandomwalkapproachtohumangrowth AT belasuki timevaryingbiasedrandomwalkapproachtohumangrowth AT ursfrey timevaryingbiasedrandomwalkapproachtohumangrowth
_version_	1718394242702770176

A time-varying biased random walk approach to human growth

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