Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713128
Title: Wide methods applied to study gene-environment interplay
Author: Coleman, Jonathan Richard Iain
ISNI:       0000 0004 6349 5194
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2017
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Abstract:
Information-rich genomic data have transformed the study of genetic variants but have affected investigations of gene-environment interplay less, partly due to the multiple testing involved in genome-wide interaction studies. This thesis explores alternative uses of genome-wide techniques to investigate gene-environment interplay. Genetic associations with individual differences in response to an environment can be examined by performing genome-wide association studies in individuals with a shared exposure. Cognitive behavioural therapy is a controllable environment that can be studied prospectively. Genetic variants and RNA transcript expression were used to predict therapeutic outcome. No significant predictors were identified, suggesting that effects are likely to be small. Genome-wide association studies remain underpowered to detect small effects, despite increasingly large cohorts. Polygenic risk scores incorporating variants below traditional thresholds of statistical significance can capture true signal. These scores can act as a proxy for the effect of the genome in genome-by-environment interaction studies, and were used in this thesis to dissect the observed increase in body mass index in individuals with depression. Results suggest that this relationship is likely to result primarily from causes other than the additive effects of common genetic variation. Polygenic risk scores were also used to assess the effects of social environmental and genetic influences on body mass index before and during adolescence, using a risk score primarily derived from adult participants. Positive associations between this risk score and adolescent body mass index phenotypes suggest a stable genetic influence on body mass. Social environmental influences on body mass had small effects, with weak evidence for an interaction between socioeconomic status and genetic risk influencing body mass. Statistical limitations on genomic analyses can be reduced by using alternative methods to complement genome-wide interaction studies. These approaches provide insight into the interactive effects of the genome and the environment on behavioural phenotypes.
Supervisor: Breen, Gerome Daniel ; Eley, Thalia Catherine Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.713128  DOI: Not available
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