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Indirect genetic effects, the effects of the genotype of one individual on the phenotype of other individuals, are environmental factors associated with human disease and complex trait variation that could help to expand our understanding of the environment linked to complex traits. Here, we study indirect genetic effects in 80,889 human couples of European ancestry for 105 complex traits. Using a linear mixed model approach, we estimate partner indirect heritability and find evidence of partner heritability on ~50% of the analysed traits. Follow-up analysis suggests that in at least ~25% of these traits, the partner heritability is consistent with the existence of indirect genetic effects including a wide variety of traits such as dietary traits, mental health and disease. This shows that the environment linked to complex traits is partially explained by the genotype of other individuals and motivates the need to find new ways of studying the environment.
Heritability of disease frequency
Genes and environmental exposures determine susceptibility to common diseases such as diabetes or cancer. The relative contribution of genes to disease risk is known as the heritability. Heritability is often estimated using twin pairs. However, heritability estimates obtained from twins have limitations that could be overcome by using sibling and parental information on disease. That is, a person's family history. We will calculate heritability by comparing the disease frequency among relatives to the frequency in the general population. We will use the full UKbiobank cohort data on family history to estimate the heritability of a broad range of medical conditions. We will use information on smoking, anthropometric and reproductive factors to understand to what degree these risk factors are determined by genetics; and to what degree genes influencing risky behaviours (e.g. smoking) and diseases are shared. In addition, we will estimate the heritability of reproductive fitness (a measure of natural selection). Estimates of heritability are important because they set the potential utility of genetics to predict disease risk. Stratification of the population by their level of risk would allow tailoring the level of medical intervention to the level of risk and facilitate early diagnosis.