Heritability: What's the point? What is it not for? A human genetics perspective View Full Text


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Article Info

DATE

2022-01-29

AUTHORS

Nicolas Robette, Emmanuelle Génin, Françoise Clerget-Darpoux

ABSTRACT

In this paper, we explain the concept of heritability and describe the different methods and the genotype–phenotype correspondences used to estimate heritability in the specific field of human genetics. Heritability studies are conducted on extremely diverse human traits: quantitative traits (physical, biological, but also cognitive and behavioral measurements) and binary traits (as is the case of most human diseases). Instead of variables such as education and socio-economic status as covariates in genetic studies, they are now the direct object of genetic analysis. We make a review of the different assumptions underlying heritability estimates and dispute the validity of most of them. Moreover, and maybe more importantly, we show that they are very often misinterpreted. These erroneous interpretations lead to a vision of a genetic determinism of human traits. This vision is currently being widely disseminated not only by the mass media and the mainstream press, but also by the scientific press. We caution against the dangerous implication it has both medically and socially. Contrarily to the field of animal and plant genetics for which the polygenic model and the concept of heritability revolutionized selection methods, we explain why it does not provide answer in human genetics. More... »

PAGES

199-208

References to SciGraph publications

  • 2001-02-15. A physical map of the human genome in NATURE
  • 2011-07-30. Field Analysis and Interdisciplinary Science: Scientific Capital Exchange in Behavior Genetics in MINERVA
  • 2014-06-09. Why epistasis is important for tackling complex human disease genetics in GENOME MEDICINE
  • 2012-07-31. The continuing value of twin studies in the omics era in NATURE REVIEWS GENETICS
  • 2004-08. Epistasis: too often neglected in complex trait studies? in NATURE REVIEWS GENETICS
  • 2019-06-04. Missing heritability of complex diseases: case solved? in HUMAN GENETICS
  • 2013-01-18. The heritability of human disease: estimation, uses and abuses in NATURE REVIEWS GENETICS
  • 2018-08-13. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations in NATURE GENETICS
  • 2008-05. Sizing up human height variation in NATURE GENETICS
  • 2010-06-20. Common SNPs explain a large proportion of the heritability for human height in NATURE GENETICS
  • 1877-04. Typical Laws of Heredity1 in NATURE
  • 2008-11-05. Personal genomes: The case of the missing heritability in NATURE
  • 1997-06. Coming to terms with heritability in GENETICA
  • 2019-01-12. The illusion of polygenic disease risk prediction in GENETICS IN MEDICINE
  • 2018-01-08. The new genetics of intelligence in NATURE REVIEWS GENETICS
  • 2017-09-01. Concepts, estimation and interpretation of SNP-based heritability in NATURE GENETICS
  • 2009-10. Finding the missing heritability of complex diseases in NATURE
  • 2015-02-02. Efficient Bayesian mixed-model analysis increases association power in large cohorts in NATURE GENETICS
  • 2006-12-13. Are genome-wide association studies all that we need to dissect the genetic component of complex human diseases? in EUROPEAN JOURNAL OF HUMAN GENETICS
  • 2020-03-23. Evaluating and improving heritability models using summary statistics in NATURE GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10709-022-00149-7

    DOI

    http://dx.doi.org/10.1007/s10709-022-00149-7

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/35092541


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