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Genetics of Birth Weight

  1. Nicholas J Timpson

Published Online: 8 DEC 2013

DOI: 10.1002/9780470015902.a0025227



How to Cite

Timpson, N. J. 2013. Genetics of Birth Weight. eLS. .

Author Information

  1. University of Bristol, Bristol, UK

Publication History

  1. Published Online: 8 DEC 2013


Possibly the most ubiquitously measured early life health feature, birth weight is a staple of predelivery consultations and is the perennial statement of the health of the new born. Birth weight as a measurement is simple, fixed in time and recorded with relative stability in comparison to other more labile and less precise measures immediately after birth. However, birth weight can be thought of as a distal snapshot of a collection of complex biological events marking the interplay between endogenous foetal genetics and the in-uterine experience of the new child. Although birth weight is convenient and often well measured, it imperfectly summarises a swathe of biology along with important markers of the environment in which a new life has developed. This article will consider the genetic contributions to birth weight and how these may help to further our understanding of this naturally complex phenotype.

Key Concepts:

  • Birth weight as an epidemiological measurement – This article considers the merits and limitations of birth weight as an epidemiological measurement and the implications of using a cross sectional measure to summarise a complex biological event.

  • Epidemiology of birth weight – This article considers the importance of birth weight as an epidemiological outcome and potential risk factor for later life health.

  • Genomewide genetics association studies – This article summarises and explains the results of genomewide association studies for birth weight.

  • Indirect genetic association or gene–environment interaction – This article considers how apparently indirect genetic associations may be operating through gene–environment interaction and how they may be important for the interpretation of genetic effects.

  • Mendelian randomisation – This article considers applied epidemiological analyses where genetic proxies for hypothetical risk factors are used to deliver improved inference.


  • birth weight;
  • genetics;
  • epidemiology;
  • genomewide association study;
  • causality