Twin studies allow us to estimate the relative contributions of nature and nurture to human phenotypes by comparing the resemblance of identical and fraternal twins. Variation in complex traits is a balance of genetic and environmental influences; these influences are typically estimated at a population level. But what if the balance of nature and nurture varies depending on where we grow up? We developed the spACE approach to analyse and map genetic and environmental hotspots using data from large twin cohorts.
PhD studentship available
We have a PhD studentship available to start October 2017 as part of our EMBERS project, funded through the Medical Research Council (MRC) GW4 BioMed Doctoral Training Partnership (deadline 9.30am 8th June 2017):
Tracking dynamic genetic and environmental influences on mood in young adults through social media analysis
A fascinating finding from human genetics is that for many complex traits the balance of nature and nurture is not fixed, but can vary in response to different life stages or environments. This project will study how genetic and environmental influences on mood vary across emerging adulthood using high-resolution time course data from social media.
This project would suit a student who wishes to develop interdisciplinary skills in behavioural science, genetics and data science, using big data from social media and the human genome. You will be based at the MRC Integrative Epidemiology Unit at the University of Bristol, in the Dynamic Genetics lab.
Born around the same time as the commercial Internet, today’s emerging adults are the Internet generation, with most engaging frequently with their real-life peer groups through online social networks. For this generation, online social networks are integrated with offline networks, and are an important source of social support and interaction. If we are to understand social influences on mental health and disorder in this or future generations of adults, then we must take notice of online, as well as offline social activity. But although offline social networks are difficult to assess and track, online social networks are detailed databases of real-time social activity. Since social networks are an important factor in both positive and negative behaviours, with peer influence leading to outcomes such as depression, obesity and positive mental wellbeing, learning about these interactions is crucially important to our understanding of mental health and wellbeing.
The rapid evolution of genotyping and sequencing technologies means that genetic variation data are becoming readily available in the large populations necessary for research into the aetiology of complex traits and disorders. Now, rather than being limited by genotyping, we are starting to be restricted by the availability of phenotypic and environmental information. To understand the dynamics of genetic influences across development and in different contexts, we must develop new approaches that will complement traditional questionnaires and clinical data to give us affordable, repeatable and detailed assessments on a scale to match our vast repositories of genetic data.
Fortunately, new digital technologies can help us to do that. Our EMBERS (Emotion Monitoring by Electronic Remote Sensing) project uses online social networks and other electronic resources to collect high-resolution phenotypic and environmental data in genetically informative population samples. For example, we have collected over five million tweets from 2,500 participants in the Twins Early Development Study (TEDS). By comparing scores automatically coded from their tweets with standard questionnaire data collected at the same time, we have been able to establish the effectiveness of Twitter data for measuring positive and negative mood in emerging adulthood. This project will use these data to track the dynamics of genetic and environmental influences on positive and negative mood through this important life stage. The findings will help us to understand the complex aetiology of mental health and disorder, and how important influences evolve across time and in response to events.
You can apply for the studentship through the MRC GW4 BioMed DTP web site before 9.30am on Thursday 8th June 2017. For more information or an informal discussion before you apply, contact Oliver Davis or Claire Haworth.
Computational behavioural genetics
I was asked to give a fifteen-minute talk on Computational Behavioural Genetics at Europe’s first Computational Social Science conference at the University of Warwick last year. It was recorded for Warwick’s Big Data MOOC, and the organisers, Suzy Moat and Tobias Preis, have kindly allowed us to re-post it here. Thanks, guys!