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Approved research

Spousal genetic and phenotypic similarity

Principal Investigator: Dr Michelle Luciano
Approved Research ID: 10589
Approval date: October 1st 2015

Lay summary

This proposal aims to investigate the extent of assortative mating of spouses on health, cognitive, socio-demographic, and anthropometric measures. Spousal assortment will be compared across different age groups and socio-economic classes to establish whether the strength and indicators of assortment vary across different generations and social classes. Importantly, we shall investigate the genetic similarity of spouses, who have been hypothesised to share more genes at loci affecting a number of complex traits, including diseases, on average, than non-mating pairs of individuals in the population. Genetic similarity of spouses will be used to predict their similarity on health-related (and other) variables. Homogamy (like marrying like) contributes to socio-economic disparities within developed nations, translating to health disparities: poorer socio-economic classes show poorer health. Understanding social and biological underpinnings of this assortment will provide insight into the relative importance of socio-cultural versus genetic influences in this selection process. Traits showing assortment might be particularly deserving of public health campaign focus because homogamy could increase the good-versus-poor health divide. Assortment due to genes could also assist in gene discovery for these traits. If genetic factors underlie part of the observed assortment on disease, this will affect disease prevalence in the population and in families. Spousal pair linkage is currently being derived in Biobank based on cohabitation information. Health (lifestyle and disease indicators), anthropometric, cognitive and socio-demographic characteristics for men and women will be correlated to estimate phenotypic similarity among pairs. Variables like education and verbal ability are expected to show the most similarity between spouses. Genetic sharing between spouses will be estimated using available genome-wide single nucleotide polymorphism (SNP) data, and trait-specific genetic sharing will be quantified using available genetic predictors. These estimates will be compared to random non-mating pairs, and further used to predict phenotypic similarity between spouses for traits showing assortment. We will focus our analysis on all potential spousal pairs in UK Biobank (not more than ~200 000), data which are currently being compiled and will be available in autumn 2015.