D2K, PEALS, Newcastle University

ELSA: METADAC project approvals

Title of Application Plain Language Summary Committee Date Applicant Project Keywords
Decision Letter Institution
Final Approval Coapplicants
  Funders
The genetic basis of the height premium We analyze the contribution of height towards economic performance. Many studies have reported a significant positive correlation between height and outcomes such as educational attainment, earnings and productivity. No earlier study investigated this question from a genetic perspective. In genetic data from the Health and Retirement Study we do find a significant correlation between a polygenic risk score for height and outcomes such as education and earnings. Our plan is to replicate these findings in the English Longitudinal Study of Ageing dataset. 30-Nov-2016 REITVELD, Prof Niels Height, Earnings, Education, Ability, Polygenic risk score
14-Dec-2016 Erasmus University Rotterdam
06-Apr-2016 Prof Dinand WEBBINK, Hans VAN KIPPERSLUIS, Eric SLOB
n/a
Increasing the Power of GWAS Through Multi-Trait Meta-Analysis: Application to Depressive Symptoms, Neuroticism, and Subjective Well-Being There are many human traits that are of interest scientifically but for which sample sizes are too small to produce reliable results in a genetic study. For this project, we have developed a statistical approach to optimally extract information from a set of related traits to improve the reliability of analyses of the trait of interest. An advantage of our method is that it can be applied to results from existing genetic studies, which are nearly always publicly available. We will illustrate the power of this method to jointly analyze subjective well-being, depressive symptoms, and neuroticism. Measures of these traits are available in the ELSA data. We plan to combine results from ELSA with published and newly-collected data for each trait, and we will then jointly analyze all three traits using our proposed method. Preliminary results have shown dramatic improvements in the precision and reliability by using this method. 30-Nov-2016 BENJAMIN, Prof Daniel GWAS, health, behaviours, mental health, social science genomics, depressive symptoms, neuroticism, subjective well-being
14-Dec-2016 University of Southern California
15-Mar-2017 (558-578) WATSON, C; OKBAY, A; BURIK, C; CESARINI, D; CONLEY, D; KONG, E; LEE, J; YANG, J; BEAUCHAMP, J; THOM, K; FONTANA, M; ROBINSON, M; ZACHER, M; MAGHZIAN, O; TURLEY, P; VISSCHER, P; KOELLINGER, P; ROYER, R; WEDOW, R; OSKARSSON, S; NGUYEN, T
National Institutes of Health (NIH)
Genetic Analyses of Educational Attainment We, the Social Science Genetic Association Consortium (SSGAC), aim to bring together the expertise of geneticists and social scientists to study the genetic architecture of outcomes that are of interest to social scientists (e.g. subjective well-being, risk tolerance, etc.). Specifically, we study how such outcomes are influenced by specific genetic variants, the environment (including lifestyle), and their interaction. We will use the ELSA genetics and survey data to pursue discovery of particular genetic variants that are associated with educational attainment. Prior research has established that there is considerable overlap between genetic variants associated with educational attainment and those with cognitive function and (absence of) dementia, we will further exploit the uniquely rich data in the ELSA through analyses that will shed light on the genetics of these outcomes and several others related to educational attainment. 30-Nov-2016 BENJAMIN, Prof Daniel GWAS, education, cognitive function, dementia, social science genomics
14-Dec-2016 University of Southern California
15-Mar-2017 (558-578) WATSON, C; OKBAY, A; BURIK, C; CESARINI, D; CONLEY, D; KONG, E; LEE, J; YANG, J; BEAUCHAMP, J; THOM, K; FONTANA, M; ROBINSON, M; ZACHER, M; MAGHZIAN, O; TURLEY, P; VISSCHER, P; KOELLINGER, P; ROYER, R; WEDOW, R; OSKARSSON, S; NGUYEN, T
National Institutes of Health (NIH)
Genetic Analyses of Risk Preferences We, the Social Science Genetic Association Consortium (SSGAC), aim to bring together the expertise of geneticists and social scientists to study the genetic architecture of outcomes that are of interest to social scientists (e.g. subjective well-being, risk tolerance, etc.). Risk tolerance—or the willingness to take risks to obtain rewards–is an important concept for a wide range of models in all branches of economics. Measures of risk tolerance have been shown to predict a wide range of economic and social behaviors, such as portfolio allocation and occupational choice, as well as important health related behaviors, such as smoking cigarettes and drinking alcohol. It has also been shown that genetic factors account for some of the variation in risk tolerance. We will use the ELSA data to pursue discovery of particular genetic variants that are associated with risk tolerance, and to study the extent to which a polygenic score for risk tolerance to predict other outcomes available in the ELSA data. 30-Nov-2016 BENJAMIN, Prof Daniel GWAS, risk, social science genomics
14-Dec-2016 University of Southern California
15-Mar-2017 (558-578) WATSON, C; OKBAY, A; BURIK, C; CESARINI, D; CONLEY, D; KONG, E; LEE, J; YANG, J; BEAUCHAMP, J; THOM, K; FONTANA, M; ROBINSON, M; ZACHER, M; MAGHZIAN, O; TURLEY, P; VISSCHER, P; KOELLINGER, P; ROYER, R; WEDOW, R; OSKARSSON, S; NGUYEN, T
National Institutes of Health (NIH)
Increasing the Power of GWAS Through Multi-Trait Meta-Analysis: Application to Depressive Symptoms, Neuroticism, and Subjective Well-Being There are many human traits that are of interest scientifically but for which sample sizes are too small to produce reliable results in a genetic study. For this project, we have developed a statistical approach to optimally extract information from a set of related traits to improve the reliability of analyses of the trait of interest. An advantage of our method is that it can be applied to results from existing genetic studies, which are nearly always publicly available. We will illustrate the power of this method to jointly analyze subjective well-being, depressive symptoms, and neuroticism. Measures of these traits are available in the ELSA data. We plan to combine results from ELSA with published and newly-collected data for each trait, and we will then jointly analyze all three traits using our proposed method. Preliminary results have shown dramatic improvements in the precision and reliability by using this method. 30-Nov-2016 KOELLINGER, Prof Philipp GWAS, health, behaviours, mental health, social science genomics, depressive symptoms, neuroticism, subjective well-being
14-Dec-2016 Vrije Universiteit Amsterdam
15-Mar-2017 MEDDENS, Fleur; KARLSSON LINNER, Richard; OKBAY, Aysu; de VLAMING, Ronald; RIETVELD, Niels
European Research Council
Genetic Analyses of Risk Preferences We, the Social Science Genetic Association Consortium (SSGAC), aim to bring together the expertise of geneticists and social scientists to study the genetic architecture of outcomes that are of interest to social scientists (e.g. subjective well-being, risk tolerance, etc.). Risk tolerance—or the willingness to take risks to obtain rewards–is an important concept for a wide range of models in all branches of economics. Measures of risk tolerance have been shown to predict a wide range of economic and social behaviors, such as portfolio allocation and occupational choice, as well as important health related behaviors, such as smoking cigarettes and drinking alcohol. It has also been shown that genetic factors account for some of the variation in risk tolerance. We will use the ELSA data to pursue discovery of particular genetic variants that are associated with risk tolerance, and to study the extent to which a polygenic score for risk tolerance to predict other outcomes available in the ELSA data. 30-Nov-2016 KOELLINGER, Prof Philipp GWAS, risk, social science genomics
14-Dec-2016 Vrije Universiteit Amsterdam
15-Mar-2017 MEDDENS, Fleur; KARLSSON LINNER, Richard; OKBAY, Aysu; de VLAMING, Ronald; RIETVELD, Niels
European Research Council
Genetic Analyses of Educational Attainment We, the Social Science Genetic Association Consortium (SSGAC), aim to bring together the expertise of geneticists and social scientists to study the genetic architecture of outcomes that are of interest to social scientists (e.g. subjective well-being, risk tolerance, etc.). Specifically, we study how such outcomes are influenced by specific genetic variants, the environment (including lifestyle), and their interaction. We will use the ELSA genetics and survey data to pursue discovery of particular genetic variants that are associated with educational attainment. Prior research has established that there is considerable overlap between genetic variants associated with educational attainment and those with cognitive function and (absence of) dementia, we will further exploit the uniquely rich data in the ELSA through analyses that will shed light on the genetics of these outcomes and several others related to educational attainment. 30-Nov-2016 KOELLINGER, Prof Philipp GWAS, education, cognitive function, dementia, social science genomics
14-Dec-2016 Vrije Universiteit Amsterdam
15-Mar-2016 MEDDENS, Fleur; KARLSSON LINNER, Richard; OKBAY, Aysu; de VLAMING, Ronald; RIETVELD, Niels
European Research Council
Investigation of the genetic overlap between health literacy, cognitive function, education and health outcomes. Health literacy is the ability to understand and use health information to make decisions relating to one’s own health. Individuals with lower health literacy are more likely to suffer from chronic diseases, such as type 2 diabetes. Cognitive functions, such as memory and problem solving, are also strongly related to health literacy. Individuals with higher health literacy tend to score higher on tests of cognitive function. This has led some researchers to propose that health literacy and cognitive function overlap and are measuring the same skill. To investigate why there is an overlap between health literacy and cognitive function, this project will examine whether the genes that are associated with health literacy are also associated with cognitive function. If there is a large overlap in the genes involved in these two skills, it will provide further support that health literacy and cognitive function measures assess the same underlying ability. 27-Feb-2017 DEARY, Prof Ian Health literacy, cognitive function, genetics, pleiotropy
07-Mar-2017 University of Edinburgh
22-Mar-2017 FAWNS-RITCHIE, Ms Chloe; DAVIES, Dr Gail; HILL, Dr W David; HARRIS, Dr Sarah
Centre for cognitive ageing and cognitive epidemiology
Investigating the genetic relationships between depression and cardiovascular risk factors and disease. This study aims to use cardiovascular risk measurements and diagnosis, together with questionnaire data on mental and physical health in ELSA in two ways: 1- To discover and validate previous findings from large psychiatric genetics studies. These studies identified inherited genetic changes which may increase risk of depression. 2- To investigate shared genetic factors affecting mental and cardiovascular health (heart disease), as these conditions often occur together. The ultimate aim is to uncover biological pathways underlying the relationship between cardiovascular disease and depression. The proposed work will be achieved through analysis of genetic and health data, using existing methods. This research will assist in risk prediction, informing treatment, and forming a better understanding of the shared genetics between traits. 25-May-2017 Prof Cathryn LEWIS Depression, polygenic risk scores, cardiovascular disease risk, pleiotropy.
08-Jun-2017 King’s College London
09-Aug-2017 Gerome BREEN, Paul O’REILLY, Delilah ZABENEH, Saskia HAGENAARS, Karen HODGSON
NIHR Maudsley Biomedical Centre

Last updated with approved projects: 26-9-2017

css.php