Identification of ten loci associated with height highlights new biological pathways in human growth
By G. Lettre, A. Jackson, C. Gieger, F. Schumacher, S. Berndt, Serena Sanna, S. Eyheramendy, Benjamin F. Voight, Johannah L. Butler, C. Guiducci and 21 more. Nature Genetics, 2008
644 citations recorded by the source corpus.
Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 × 10−7 to 8 × 10−22). Together, these 12 loci account for ∼2% of the population variation in height. Individuals with ≤8 height-increasing alleles and ≥16 height-increasing alleles differ in height by ∼3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/2366cee8ccee5c7169dfbd437307f80ffd2864f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- John P. A. Ioannidis
- M. Sorrells
- Graham Coop
- Jean-Luc Jannink
- Mark J. Daly
- J. K. Pritchard
- Martin Farrall
- Chris Wallace
In Molecular Biology
- Chris Wallace
- Mark J. Daly
- Joshua T. Mendell
- E. Olson
- Joseph K. Pickrell
- David Altshuler
- Lon R. Cardon
- Shaun Purcell
Citations in the corpus
- MicroRNAs in stress signaling and human disease (2012, background): “This concept was convincingly demonstrated in a series of large genome-wide association studies designed to uncover variants associated with the age of onset of menarche, other traits associated with puberty, and height (Hartge, 2009; Lettre et al., 2008).”
- Prioritizing candidate disease genes by network-based boosting of genome-wide association data. (2011, background): “We found that the essential HMEC genes were, indeed, highly connected in HumanNet (Fig.”
- Signals of recent positive selection in a worldwide sample of human populations. (2009, background): “…(Crohn’s disease, type I and II diabetes, height, and lipid levels) from published genome-wide association studies (Scott et al. 2007; Todd et al. 2007; Gudbjartsson et al. 2008; Lettre et al. 2008; Unoki et al. 2008; Weedon et al. 2008; Willer et al. 2008; Yasuda et al. 2008; Zeggini et al. 2008).”
- Meta-analyses of genome-wide association studies identify multiple novel loci associated with pulmonary function (2009, background): “In humans, recent GWAS have linked GPR126 variants with adult height, and more specifically with trunk heigh”
- Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions (2009, methodology): “We next applied GRAIL to 42 validated SNP associations to adult height in recent GWA studies [2–4].”
- Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program (2011, background): “Despite a high h2 (~0.80) and a TP of tens of thousands of individuals, only ~5% of the phenotypic variance for human height has been accounted for with ~50 signifi - cant markers (Gudbjartsson et al., 2008; Lettre et al., 2008; Weedon et al., 2008; Visscher, 2008).”
- A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits (2009, background): “357-S1">Supplementary Table 8 ), most likely because these have been the focus of several large GWA meta-analyse”