My research focuses on social genetic effects (SGE, also called indirect genetic effects) and their impact on complex traits, health and disease.
SGE are emerging as an important component of the genotype to phenotype path. A social genetic effect is an association between genotype of one individual and phenotype of another individual. SGE arise when two individuals interact socially and a genetically-controlled trait of one individual influences a phenotype of the other individual.
SGE are an overlooked dimension of genetics with important evolutionary consequences [Wolf et al. Evolutionary consequences of indirect genetic effects, Trends in Ecology and Evolution, 1998]. They are also a tool to better understand the social aetiology of health and disease.
In the first paper I published on SGE [Baud et al. Genetic variation in the social environment influences health and disease, PLoS Genetics, 2017], I reported evidence that SGE affect traits of biomedical relevance in laboratory mice. I showed that the aggregate (genome-wide) contribution of SGE to phenotypic variation can be large and greater than that of direct genetic effects (DGE, effect of an individual's own genes on its phenotype) in some cases. I also explained why SGE might be a cause of missing heritability. Blog associated with this paper: http://blogs.plos.org/biologue/2017/03/16/understanding-images-how-genetic-makeup-of-a-roommate-can-influence-health.
I am now working on characterising the genetic architecture of SGE.
My doctoral work was on the genetic basis of complex traits - which at the time meant DGE only - in outbred rats [Baud et al. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats, Nature Genetics, 2013]. I worked with the EURATRANS consortium that was collecting sequence, genotype, and phenotype data on a population of outbred rats with unique genetic characteristics that made it possible to ask important quantitative genetics questions. I demonstrated the following:
(a) A large proportion of genotype-phenotype associations (~40%) are not caused by single variants but rather by haplotypes (allelic heterogeneity). This result is fundamental for interpreting results from genome-wide association studies (GWAS) and for choosing the right strategy to follow up on GWAS loci. Allelic heterogeneity has now been shown to be widespread in humans too [e.g. Hormozdiari et al. Widespread allelic heterogeneity in complex traits, American Journal of Human Genetics, 2017].
(b) At 35 loci harbouring a single causal variant, I identified the likely causal variant and/or gene, providing novel insights into the aetiology of anxiety, type 2 diabetes, osteoporosis, and multiple sclerosis. Association between one of these causal genes (Ctnnd2) and anxiety has been replicated in a human study [Nivard et al. Further confirmation of the association between anxiety and CTNND2: replication in humans, Genes Brain and Behaviour, 2014] and others have already been partially validated in rat models.
(c) I showed that different loci contribute to variation in the same traits in mice and rats. This cross-species comparison was carried out using data from the previously published study of Heterogeneous Stock mice [Valdar et al. Genome-wide genetic association of complex traits in heterogeneous stock mice, Nature Genetics, 2006]. While this result may be due to limited sampling of loci in each species, it shows that a large proportion of the overlaps reported in the literature between mouse and rat loci may be non-significant, arising simply because the loci identified using traditional rodent resources usually span tens of megabases.
Piter Bijma's talk (given by Bruce Walsh) at the International Conference on Quantitative Genetics in Edinburgh in 2012 opened my eyes to the existence of social genetic effects, and life hasn't been the same since then! ;)