Debunking a myopic view of nature versus nurture

Hopper, John L.

doi:10.1111/cxo.12850

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…This has caused some controversy in interpreting heritability estimates for binary traits within the literature. 30 , 31 …”

Section: Genomic Methods: Related Individualsmentioning

confidence: 99%

“… 23 Further, some argue that setting an artificial risk threshold to determine the disease status may create mathematically meaningless results. 30 , 31 …”

Section: Genomic Methods: Related Individualsmentioning

confidence: 99%

“…This has caused some controversy in interpreting heritability estimates for binary traits within the literature. 30,31 ii. The 'estimate of the variance' that may be 'apportioned to the SNPs' on the 'binary scale' may be 'linearly transformed to a continuous liability scale'.…”

Section: Sibling Regressionmentioning

confidence: 99%

“…23 Further, some argue that setting an artificial risk threshold to determine the disease status may create mathematically meaningless results. 30,31 The following four methods-GREML-kinship (GREML-KIN), maternal-genome-wide complex trait analysis (M-GCTA), Trio-GCTA and relatedness disequilibrium regression (RDR)-are extensions to GREML using related individuals. GREML-KIN estimates heritability whilst controlling for the shared environment by including relatives.…”

Section: Ethics Approvalmentioning

confidence: 99%

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How to estimate heritability: a guide for genetic epidemiologists

Barry

Walker

Cheesman

et al. 2022

International Journal of Epidemiology

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Background Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Methods Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). Results We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Conclusions Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.

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“…This has caused some controversy in interpreting heritability estimates for binary traits within the literature. 30 , 31 …”

Section: Genomic Methods: Related Individualsmentioning

confidence: 99%

“… 23 Further, some argue that setting an artificial risk threshold to determine the disease status may create mathematically meaningless results. 30 , 31 …”

Section: Genomic Methods: Related Individualsmentioning

confidence: 99%

Section: Sibling Regressionmentioning

confidence: 99%