Evidence of horizontal indirect genetic effects in humans.
Journal
Nature human behaviour
ISSN: 2397-3374
Titre abrégé: Nat Hum Behav
Pays: England
ID NLM: 101697750
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
24
08
2019
accepted:
29
09
2020
pubmed:
16
12
2020
medline:
2
4
2021
entrez:
15
12
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33318663
doi: 10.1038/s41562-020-00991-9
pii: 10.1038/s41562-020-00991-9
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
399-406Subventions
Organisme : Medical Research Council
ID : MR/R025851/1
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BBS/E/D/30002275
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BBS/E/D/10002070
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P015514/1
Pays : United Kingdom
Références
Bijma, P. The quantitative genetics of indirect genetic effects: a selective review of modelling issues. Heredity 112, 61–69 (2014).
doi: 10.1038/hdy.2013.15
Wolf, J. B., Brodie, E. D. III, Cheverud, J. M., Moore, A. J. & Wade, M. J. Evolutionary consequences of indirect genetic effects. Trends Ecol. Evol. 13, 64–69 (1998).
doi: 10.1016/S0169-5347(97)01233-0
Moore, A. J., Brodie, E. D. III & Wolf, J. B. Interacting phenotypes and the evolutionary process: I. Direct and indirect genetic effects of social interactions. Evolution 51, 1352–1362 (1997).
doi: 10.1111/j.1558-5646.1997.tb01458.x
Mousseau, T. A. & Fox, C. W. The adaptive significance of maternal effects. Trends Ecol. Evol. 13, 403–407 (1998).
doi: 10.1016/S0169-5347(98)01472-4
Willham, R. L. The covariance between relatives for characters composed of components contributed by related individuals. Biometrics 19, 18–27 (1963).
doi: 10.2307/2527570
Santostefano, F., Wilson, A. J., Niemelä, P. T. & Dingemanse, N. J. Indirect genetic effects: a key component of the genetic architecture of behaviour. Sci. Rep. 7, 10235 (2017).
doi: 10.1038/s41598-017-08258-6
Brotherstone, S. et al. Competition effects in a young Sitka spruce (Picea sitchensis, Bong. Carr) clonal trial. Silvae Genet. 60, 149–155 (2011).
doi: 10.1515/sg-2011-0020
Camerlink, I., Ursinus, W. W., Bijma, P., Kemp, B. & Bolhuis, J. E. Indirect genetic effects for growth rate in domestic pigs alter aggressive and manipulative biting behaviour. Behav. Genet. 45, 117–126 (2015).
doi: 10.1007/s10519-014-9671-9
Warrington, N. M. et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat. Genet. 51, 804–814 (2019).
doi: 10.1038/s41588-019-0403-1
Kong, A. et al. The nature of nurture: effects of parental genotypes. Science 359, 424–428 (2018).
doi: 10.1126/science.aan6877
Domingue, B. W. et al. The social genome of friends and schoolmates in the national longitudinal study of adolescent to adult health. Proc. Natl Acad. Sci. USA 115, 702–707 (2018).
doi: 10.1073/pnas.1711803115
Baud, A., Casale, F. P., Nicod, J. & Stegle, O. Comparative architectures of direct and social genetic effects from the genome-wide association study of 170 phenotypes in laboratory mice. Preprint at bioRxiv https://doi.org/10.1101/302349 (2019).
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
doi: 10.1371/journal.pmed.1001779
Lee, S. H., Wray, N. R., Goddard, M. E. & Visscher, P. M. Estimating missing heritability for disease from genome-wide association studies. Am. J. Hum. Genet. 88, 294–305 (2011).
doi: 10.1016/j.ajhg.2011.02.002
Dempster, E. R. & Lerner, I. M. Heritability of threshold characters. Genetics 35, 212–236 (1950).
pubmed: 17247344
pmcid: 1209482
Tenesa, A., Rawlik, K., Navarro, P. & Canela-Xandri, O. Genetic determination of height-mediated mate choice. Genome Biol. 16, 269 (2016).
doi: 10.1186/s13059-015-0833-8
Hugh-Jones, D., Verweij, K. J. H., St Pourcain, B. & Abdellaoui, A. Assortative mating on educational attainment leads to genetic spousal resemblance for polygenic scores. Intelligence 59, 103–108 (2016).
doi: 10.1016/j.intell.2016.08.005
Stulp, G., Simons, M. J. P., Grasman, S. & Pollet, T. V. Assortative mating for human height: a meta-analysis. Am. J. Hum. Biol. 29, e22917 (2017).
doi: 10.1002/ajhb.22917
Canela-Xandri, O., Law, A., Gray, A., Woolliams, J. A. & Tenesa, A. A new tool called DISSECT for analysing large genomic data sets using a big data approach. Nat. Commun. 6, 10162 (2015).
doi: 10.1038/ncomms10162
Fisher, R. A. Statistical Methods for Research Workers 4th edn (Oliver and Boyd, 1932).
Cheesman, R. et al. Comparison of adopted and non-adopted individuals reveals gene-environment interplay for education in the UK Biobank. Psychol. Sci. 31, 582–591 (2019).
doi: 10.1177/0956797620904450
Canela-Xandri, O., Rawlik, K. & Tenesa, A. An atlas of genetic associations in UK Biobank. Nat. Genet. 50, 1593–1599 (2018).
doi: 10.1038/s41588-018-0248-z
Bycroft, C. et al. Genome-wide genetic data on ~500,000 UK Biobank participants. Preprint at bioRxiv https://doi.org/10.1101/166298 (2017).
Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).
doi: 10.1038/ng.608
Visscher, P. M. A note on the asymptotic distribution of likelihood ratio tests to test variance components. Twin Res. Hum. Genet. 9, 490–495 (2006).
doi: 10.1375/twin.9.4.490
Sing, T., Sander, O., Beerenwinkel, N. & Lengauer, T. ROCR: visualizing classifier performance in R. Bioinformatics 21, 3940–3941 (2005).
doi: 10.1093/bioinformatics/bti623
Hanley, J. A. & McNeil, B. J. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143, 29–36 (1982).
doi: 10.1148/radiology.143.1.7063747