Inference of the Genetic Architecture Underlying BMI and Height with the Use of 20,240 Sibling Pairs

Hemani, Gibran, Yang, Jian, Vinkhuyzen, Anna, Powell, Joseph E., Willemsen, Gonneke, Hottenga, Jouke-Jan, Abdellaoui, Abdel, Mangino, Massimo, Valdes, Ana M., Medland, Sarah E., Madden, Pamela A., Heath, Andrew C., Henders, Anjali K., Nyholt, Dale R., de Geus, Eco J. C., Magnusson, Patrik K. E., Ingelsson, Erik, Montgomery, Grant W., Spector, Timothy D., Boomsma, Dorret I., Pedersen, Nancy L., Martin, Nicholas G. and Visscher, Peter M. (2013) Inference of the Genetic Architecture Underlying BMI and Height with the Use of 20,240 Sibling Pairs. American Journal of Human Genetics, 93 5: 865-875. doi:10.1016/j.ajhg.2013.10.005


Author Hemani, Gibran
Yang, Jian
Vinkhuyzen, Anna
Powell, Joseph E.
Willemsen, Gonneke
Hottenga, Jouke-Jan
Abdellaoui, Abdel
Mangino, Massimo
Valdes, Ana M.
Medland, Sarah E.
Madden, Pamela A.
Heath, Andrew C.
Henders, Anjali K.
Nyholt, Dale R.
de Geus, Eco J. C.
Magnusson, Patrik K. E.
Ingelsson, Erik
Montgomery, Grant W.
Spector, Timothy D.
Boomsma, Dorret I.
Pedersen, Nancy L.
Martin, Nicholas G.
Visscher, Peter M.
Title Inference of the Genetic Architecture Underlying BMI and Height with the Use of 20,240 Sibling Pairs
Journal name American Journal of Human Genetics   Check publisher's open access policy
ISSN 0002-9297
1537-6605
Publication date 2013-11-01
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.ajhg.2013.10.005
Volume 93
Issue 5
Start page 865
End page 875
Total pages 11
Place of publication Cambridge, United States
Publisher Cell Press
Collection year 2014
Language eng
Formatted abstract
Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10−7) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10−10) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.
Keyword Genomewide association
Major depressive disorders
Swedish Twin Registry
De-Novo mutations
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2014 Collection
UQ Diamantina Institute Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 24 times in Thomson Reuters Web of Science Article | Citations
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