Evidence synthesis for genetic association studies
Lead Research Organisation:
London Sch of Hygiene and Trop Medicine
Department Name: Epidemiology and Population Health
Abstract
One explanation for variation in health outcomes, for example why some people get heart disease and others do not, is that genetic variants carried by some proportion of the population increase their risk of disease. However recent intense efforts to find these genetic variants have been only partially successful, apparently because the genetic effects are small and so can only be detected in vary large studies, or by combining or synthesising information across many smaller studies. This evidence synthesis has been very successful in other fields of biomedicine, but application to genetic studies is difficult and new methods are needed. This application will begin to develop such methods.
Technical Summary
We will develop methodology for the meta-analysis of genetic association studies. Specifically, we will:
1) Develop methods for the analysis of candidate genes studies where either, or both, the SNP sets and genetic models used may differ between studies. As a motivating example we consider the relationship between plasma levels of C-reactive protein (CRP) and the CRP gene. An extension will consider the integration of existing candidate gene studies with (possibly multiple) whole genome association studies.
2) Assess the possibility of investigating G * E / G*G interaction in a meta-analytic framework. The additional value of individual patient data to detect such interactions will be assessed, and the value of integrating partial IPD with more extensive study level data determined. The latter in particular requires considerable methodological development. As a motivating example we examine the influence of mean serum folate on the association between the MTHFR/C677T polymorphism and homocysteine.
The methods developed will be based on hierarchical models, mainly fitted in the Bayesian framework using MCMC. Throughout, the sensitivity of our results to modelling assumptions will be carefully assessed. Programs developed during the project will be made freely available.
1) Develop methods for the analysis of candidate genes studies where either, or both, the SNP sets and genetic models used may differ between studies. As a motivating example we consider the relationship between plasma levels of C-reactive protein (CRP) and the CRP gene. An extension will consider the integration of existing candidate gene studies with (possibly multiple) whole genome association studies.
2) Assess the possibility of investigating G * E / G*G interaction in a meta-analytic framework. The additional value of individual patient data to detect such interactions will be assessed, and the value of integrating partial IPD with more extensive study level data determined. The latter in particular requires considerable methodological development. As a motivating example we examine the influence of mean serum folate on the association between the MTHFR/C677T polymorphism and homocysteine.
The methods developed will be based on hierarchical models, mainly fitted in the Bayesian framework using MCMC. Throughout, the sensitivity of our results to modelling assumptions will be carefully assessed. Programs developed during the project will be made freely available.
Publications

Chan K
(2013)
Association between the chromosome 9p21 locus and angiographic coronary artery disease burden: a collaborative meta-analysis.
in Journal of the American College of Cardiology

De Iorio M
(2011)
Bayesian semiparametric meta-analysis for genetic association studies.
in Genetic epidemiology

Holmes MV
(2011)
Effect modification by population dietary folate on the association between MTHFR genotype, homocysteine, and stroke risk: a meta-analysis of genetic studies and randomised trials.
in Lancet (London, England)

Holmes MV
(2014)
Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.
in BMJ (Clinical research ed.)

Joshi R
(2020)
Establishing reference intervals for triglyceride-containing lipoprotein subfraction metabolites measured using nuclear magnetic resonance spectroscopy in a UK population
in Annals of Clinical Biochemistry: International Journal of Laboratory Medicine

Mahmoodi B
(2020)
Association of Factor V Leiden With Subsequent Atherothrombotic Events A GENIUS-CHD Study of Individual Participant Data
in Circulation

Newcombe PJ
(2009)
Multilocus Bayesian meta-analysis of gene-disease associations.
in American journal of human genetics

Parisinos C
(2020)
Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis
in Journal of Hepatology

Shah T
(2010)
Ancestry as a determinant of mean population C-reactive protein values: implications for cardiovascular risk prediction.
in Circulation. Cardiovascular genetics

Silverwood RJ
(2014)
Testing for non-linear causal effects using a binary genotype in a Mendelian randomization study: application to alcohol and cardiovascular traits.
in International journal of epidemiology
Title | meta-analysis |
Description | New tools for genetics meta-analysis |
Type Of Material | Data analysis technique |
Year Produced | 2008 |
Provided To Others? | Yes |
Impact | none |
Description | collaboration with colleagues at UCL |
Organisation | University College London |
Department | Division of Medicine |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Statistical, advice, analysis, methodological development |
Collaborator Contribution | data, usual scientific inputs |
Impact | 19409523, 19409523, 20876875 1 other paper in preperation |
Start Year | 2007 |