Abstract

Phenotypic correlations among partners for traits such as longevity or late-onset disease have been found to be comparable to phenotypic correlations in first-degree relatives. How these correlations arise in late life is poorly understood. Here we introduce a novel paradigm to establish the presence of indirect assortment on factors correlated across generations, by examining correlations between parents of couples, i.e., in-laws. Using correlations in additive genetic values we further corroborate the presence of indirect assortment on heritable factors. Specifically, using couples from the UK Biobank cohort, we show that longevity and disease history of the parents of White British couples are correlated, with correlations of up to 0.09. The correlations in parental longevity are replicated in the FamiLinx cohort, a larger and geographically more diverse historical ancestry dataset spanning a broader time frame. These correlations in parental longevity significantly (pval < 0.0093 for all pairs of parents) exceed what would be expected due to variations in lifespan based on year and location of birth. For cardiovascular diseases, in particular hypertension, we find significant correlations (r = 0.028, pval = 0.005) in genetic values among partners, supporting a model where partners assort for risk factors to some extent genetically correlated with cardiovascular disease. Partitioning the relative importance of indirect assortative mating and shared common environment will require large, well-characterized longitudinal cohorts aimed at understanding phenotypic correlations among none-blood relatives. Identifying the factors that mediate indirect assortment on longevity and human disease risk will help to unravel factors affecting human disease and ultimately longevity.

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Data availability

Required data can be accessed through the UK Biobank (http://www.ukbiobank.ac.uk/) and the FamiLinx website (http://www.familinx.org/), respectively. For analyses involving genotypes, we used the individuals genotyped in phase 1 of the UK Biobank genotyping project, which were released by the UK Biobank in June 2015. The genotype data were downloaded on 5 June 2015. The DISSECT software used to perform the analysis based on genetic values is freely available from http://www.dissect.ed.ac.uk/.

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Acknowledgements

This work was mainly supported by The Roslin Institute Strategic Grant funding from the BBSRC. AT also acknowledges funding from the Medical Research Council Human Genetics Unit. This work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk) and the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/). This research has been conducted using the UK Biobank Resource under project 6684.

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  1. The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, Edinburgh, EH25 9RG, Scotland

    • Konrad Rawlik
    • , Oriol Canela-Xandri
    •  & Albert Tenesa
  2. MRC HGU at the MRC IGMM, Western General Hospital, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK

    • Oriol Canela-Xandri
    •  & Albert Tenesa

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The authors declare that they have no conflict of interest.

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Correspondence to Albert Tenesa.

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https://doi.org/10.1038/s41437-019-0185-3