Centre for Population and Disease Genomics - Earmarked
Sometimes Correlation does Equal Causation: Developing Statistical Methods to Determine Causality Using Genetic Data
Principal Advisor: Prof David Evans (IMB)
This project requires candidates to commence no later than Research Quarter 1, 2024, which means you must apply no later than 30 September, 2023.
There is a well-known mantra that correlation does not necessarily equal causation. This is why randomized controlled trials in which participants are physically randomized into treatment and placebo groups are the gold standard for assessing causality in epidemiological investigations. However, what is less appreciated is that strong evidence for causality can sometimes be obtained using observational data only. In particular, genotypes are randomly transmitted from parents to their offspring independent of the environment and other confounding factors, meaning that genotypes associated with particular traits can be used like natural “randomized controlled trials” to examine whether these traits causally affect risk of disease.
The aim of this PhD project is to develop statistical methods to assess causality using observational data alone. 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), structural equation modelling, genome-wide association analysis (GWAS), 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, and instrumental variables analysis (using natural “experiments” to obtain information on causality from observational data). The candidate will apply the new statistical methods that they develop to large genetically informative datasets like the UK Biobank (500,000 individuals with genome-wide SNP data).
*Qualifies for an Earmarked Scholarship.
Testing effect of environmental exposures on subsequent human generations
Principal Advisor: Dr Gunn-Helen Moen (IMB)
This project requires candidates to commence no later than Research Quarter 1, 2024, which means you must apply no later than 30 September, 2023.
This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.
We are seeking a PhD candidate to join our research team in this exciting project funded by the Australian Research Council. The research group has conducted work within genetic epidemiology, focusing on pregnancy related exposures and outcomes.
Depending on the student’s level of experience and aptitude, they will help develop and/or apply statistical genetics approaches to investigate the possible existence of transgenerational epigenetic effects on human phenotypes.
A PhD is about learning new skills and learning how to do research. Our ideal candidate will have knowledge or keen interest in learning genetics, epidemiology, statistics, unix and shell scripting, and statistical software such as R. You will work closely with an experienced researcher on the project. There will also be possibility for a research stay in Norway during this PhD.
The main purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The advertised projects are fundamentally quantitative and computer-based, and so evidence of aptitude in these areas is essential. The candidate should also have the ability to design, plan, and execute experiments and be proficient in English, both written and oral.
We are looking for someone who is:
- Excellent communication and team working skills
- Organized and structured
- Flexible
- Enthusiastic and willing to learn new methods and techniques
*Qualifies for an Earmarked Scholarship.
Using genetics to understand the relationship between early life growth and future risk of cardio-metabolic disease
Principal Advisor: Dr Nicole Warrington (IMB)
This project requires candidates to commence no later than Research Quarter 1, 2024, which means you must apply no later than 30 September, 2023.
This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.
Rapid weight growth during infancy and changes in body mass index (BMI) throughout childhood are associated with increased risk of cardio-metabolic diseases in later life, suggesting that early life interventions could be beneficial. Although implementing lifestyle interventions prior to the onset of disease is likely to be the most cost-effective strategy for reducing the impact of these conditions on society, the optimal time to intervene remains unclear. Mendelian randomization, a method that is analogous to a randomized controlled trial but involves individuals’ genotypes rather than treatments, can assess the causal effect of early life weight growth on cardio-metabolic disease risk, therefore identifying potential times for intervention. This project will use statistical genetics methods to investigate whether there is a time period in early life where rapid weight growth causes increased risk of cardio-metabolic disease in later life.
The successful candidate will gain experience across a wide range of advanced statistical genetics methodologies including Mendelian randomization, genome-wide association analysis (GWAS), 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. Depending on the candidate’s level of experience, they will help develop and/or apply statistical genetics approaches to longitudinal data from the UK Biobank and the Early Growth Genetics Consortium.
*Qualifies for an Earmarked Scholarship.