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Cited by 28Genetic Associations and EpidemiologyGenetic and phenotypic traits in livestockGenetic diversity and population structure

Genetic nurturing, missing heritability, and causal analysis in genetic statistics

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Shen, Hao, Feldman, Marcus W.·2020·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.2015869117PMC PMC7568332
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Abstract

Significance: Correlation between genotypes and phenotypes can be produced by genetic nurturing, namely the effect of parents’ genotypes on their offspring’s phenotypes through the parents’ phenotypes. Population subdivision and assortative mating can give rise to correlations between genotypes and phenotypes similar to those due to genetic nurturing. Variances and correlations may not reveal causal relationships in the presence of these complexities. We analyze mechanistic models of genetic nurturing, population subdivision, and assortative mating and compare these with results obtained within the framework of modern causal analysis. Our results clarify statistical signals emanating from correlations between nontransmitted alleles and offspring phenotypes and reveal difficulties with standard linear models in the interpretation of heritability, in particular, the concept of missing heritability.

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  • Some, but not all, methods using genome-wide summary statistics have been shown to be particularly vulnerable to biased inferences due to uncorrected population stratification confounding.

    “Some, but not all, of these methods have been shown to be particularly vulnerable to biased inferences due to uncorrected population stratification confounding: for example, measuring the strength of AM23, assessing evidence for IGEs11,42,43, assessing evidence for polygenic selection using ancient and modern DNA4,5,9, and Mendelian Randomisation13.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [42]

    The ‘Effect of Population Subdivision’ section (page unavailable) shows that population subdivision can create a misleading genetic-nurturing signal unless corrected. The ‘Effect of Assortative Mating’ section treats assortative mating as a form of subdivision, but does not show that measuring the strength of assortative mating is particularly vulnerable to uncorrected population stratification—the example to which this citation is attached. (LLM, conf=0.78)

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  • GWAS associations for some phenotypes estimated from samples of unrelated individuals also capture effects of demography (assortative mating and population stratification) and indirect genetic effects of relatives.

    “However, there is growing evidence that GWAS associations for some phenotypes estimated from samples of unrelated individuals also capture effects of demography7,8 (assortative mating9–11 and population stratification12) and indirect genetic effects of relatives13–19 (Fig. 1).”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [8]

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Research works printed but not linked: 7

  1. [1]J. L. Lush, Animal Breeding Plans (Iowa State College Press, ed. 2, 1943).
  2. [5]L. J. Kamin, The Science and Politics of IQ (Routledge, 2012).
  3. [31]M. R. Robinson, Genetic evidence of assortative mating in humans. Nat. Hum. Behav. 1, 0016 (2017).
  4. [39]J. Pearl, Causality: Models, Reasoning and Inference (Cambridge University Press, ed. 2, 2009).
  5. [41]J. Tian, J. Pearl, “ A general identification condition for causal effects” in Proceedings of the Eighteenth National Conference on Artificial Intelligence, R. Dechter, R. Sutton, program cochairs (AAAI Press/MIT Press, Menlo Park, CA, 2002), pp. 567– 573.
  6. [42]I. Shpitser, J. Pearl, “ Identification of joint interventional distributions in recursive semi-Markovian causal models” in Proceedings of the National Conference on Artificial Intelligence, Y. Gil, R. J. Mooney, cochairs (AAAI, Boston, MA, 2006), vol. 2, pp. 1219– 1226.
  7. [43]C. Avin, I. Shpitser, J. Pearl, “ Identifiability of path-specific effects” in Proceedings of Nineteenth International Joint Conference on Artificial Intelligence, L. P. Kaelbling, program chair (Morgan Kaufmann Publishers, San Francisco, CA, 2005), pp. 357– 363.

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Authors
Shen, H., & Feldman, M. W.
Affiliations
Stanford University (US)
Corresponding author
Feldman, Marcus W.
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2020-09-28
Volume
117
Issue
41
Pages
25646-25654
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.2015869117
PMC
PMC7568332
OpenAlex
W3090312868
Cited by
28
References
34
Citations by year
2026: 4 · 2025: 4 · 2024: 5 · 2023: 3 · 2022: 5 · 2021: 7
FWCI
2.20
Type
journal article
Language
en
Update notices
correction (2021-09-01)
Open access
Licence
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Keywords
missing heritability, heritability, population subdivision, assortative mating, causal analysis, offspring phenotype
MeSH terms
Correlation of Data, Child, Culture, Genotype, Humans, Models, Genetic, Parents, Phenotype, Causality

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