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Location
Brisbane City
Queensland, Australia
Date Posted
18 Apr 2018

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Type
PhD Project
University of Queensland

Using genetics to investigate the developmental origins of health and disease in the UK bio-bank study and other large scale population based cohorts

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Brisbane City
Queensland, Australia
18 Apr 2018

NOTE: this position listing has expired and may no longer be relevant!

Position Description


Expressions of interest are now open for scholarships for a joint PhD at the University of Queensland (Australia) and the University of Exeter (UK). Great opportunity to live in two countries and study at two world class universities. Deadline is 26 May 2018.

We are offering scholarships for the following research project:

Using genetics to investigate the developmental origins of health and disease in the UK bio-bank study and other large scale population based cohorts
UQ academic leads
Professor David Evans, Statistical Genetics, University of Queensland Diamantina Institute
Dr Nicole Warrington, Statistical Genetics, University of Queensland Diamantina Institute
Exeter academic leads
Dr Rachel Freathy, Genetics of Complex Traits, Institute of Biomedical and Clinical Science, University of Exeter
Dr Robin Beaumont, Genetics of Complex Traits, Institute of Biomedical and Clinical Science, University of Exeter

Project description
There is a well-documented observational relationship between low birthweight infants and a higher risk of cardiometabolic disease in later life (e.g. type 2 diabetes, hypertension, cardiovascular disease). The “Developmental Origins of Health and Disease” (DOHaD) hypothesis proposes that an adverse intrauterine environment (e.g. due to poor maternal nutrition) might explain this relationship because it would lead not only to reduced fetal growth, but also to higher later-life disease risk through physiological adaptations made during fetal development. The DOHaD hypothesis has been one of the preeminent paradigms in life-course epidemiology over the last thirty years.

In a recent ground-breaking study (Horikoshi et al. 2016 Nature), we showed that the inverse correlation between birthweight and cardiometabolic disease may in fact be predominantly mediated by genetic rather than environmental factors. However, maternal and offspring genotypes are correlated, meaning that dissecting the genetic and environmental contributions to this relationship is fraught with difficulties, including the possibility that any genetic effects may be mediated through the mother’s (rather than the offspring’s) genotype operating on the intrauterine environment.

There is a pressing need to develop novel approaches to reduce the prevalence and burden of cardiometabolic diseases. The use of novel statistical methods and large datasets represents a unique opportunity to extend our understanding of the biology underlying DOHAD, and will help identify genes that underpin key pathways important for the development of disease.

The aim of this PhD is to dissect the maternal and fetal contributions to the relationship between offspring birthweight and risk of cardiometabolic disease. The successful candidate will perform analyses on a number of large datasets including (but not limited to) the UK Biobank (a large cohort of 500,000 participants who have been genome-wide genotyped and have relevant phenotype data including own/offspring’s birth weight and later life diseases), and studies in the Early Growth Genetics (EGG) consortium (more than 40 international pregnancy and birth cohorts with genetic data, including studies with data on mother/offspring pairs). The successful candidate will gain experience across a wide range of advanced statistical genetics methodologies including Mendelian randomization (a way of using genetic variants to investigate putatively causal relationships), genome-wide association analysis (GWAS), and genetic restricted maximum likelihood (G-REML) analysis of genome-wide data which can be used to partition variation in phenotypes into genetic and environmental sources of variation. The candidate will also assist in the development of new statistical genetics and causal modelling methods.

For more information contact David Evans (d.evans1@uq.edu.au) or Rachel Freathy (R.Freathy@exeter.ac.uk).


How to Apply

Submit UQ expression of interest form by 26 May 2018: https://survey.its.uq.edu.au/checkbox/QUEX2018.aspx

Position Category: Medical & Biological Sciences. Position Type: PhD Project.

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