Human Genetics

, Volume 133, Issue 5, pp 587–597

Common DNA variants predict tall stature in Europeans

  • Fan Liu
  • A. Emile J. Hendriks
  • Arwin Ralf
  • Annemieke M. Boot
  • Emelie Benyi
  • Lars Sävendahl
  • Ben A. Oostra
  • Cornelia van Duijn
  • Albert Hofman
  • Fernando Rivadeneira
  • André G. Uitterlinden
  • Stenvert L. S. Drop
  • Manfred Kayser
Original Investigation

DOI: 10.1007/s00439-013-1394-0

Cite this article as:
Liu, F., Hendriks, A.E.J., Ralf, A. et al. Hum Genet (2014) 133: 587. doi:10.1007/s00439-013-1394-0

Abstract

Genomic prediction of the extreme forms of adult body height or stature is of practical relevance in several areas such as pediatric endocrinology and forensic investigations. Here, we examine 770 extremely tall cases and 9,591 normal height controls in a population-based Dutch European sample to evaluate the capability of known height-associated DNA variants in predicting tall stature. Among the 180 normal height-associated single nucleotide polymorphisms (SNPs) previously reported by the Genetic Investigation of ANthropocentric Traits (GIANT) genome-wide association study on normal stature, in our data 166 (92.2 %) showed directionally consistent effects and 75 (41.7 %) showed nominally significant association with tall stature, indicating that the 180 GIANT SNPs are informative for tall stature in our Dutch sample. A prediction analysis based on the weighted allele sums method demonstrated a substantially improved potential for predicting tall stature (AUC = 0.75; 95 % CI 0.72–0.79) compared to a previous attempt using 54 height-associated SNPs (AUC = 0.65). The achieved accuracy is approaching practical relevance such as in pediatrics and forensics. Furthermore, a reanalysis of all SNPs at the 180 GIANT loci in our data identified novel secondary association signals for extreme tall stature at TGFB2 (P = 1.8 × 10−13) and PCSK5 (P = 7.8 × 10−11) suggesting the existence of allelic heterogeneity and underlining the importance of fine analysis of already discovered loci. Extrapolating from our results suggests that the genomic prediction of at least the extreme forms of common complex traits in humans including common diseases are likely to be informative if large numbers of trait-associated common DNA variants are available.

Supplementary material

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Supplementary material 1 (DOCX 34 kb)
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Supplementary material 2 (XLSX 65 kb)
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Supplementary Fig. 1a Association result of the case–control designed GWAS for tall stature in 770 tall and 9,591 non-tall Dutch Europeans. A, Manhattan plot. (TIFF 1321 kb)
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Supplementary Fig. 1b B, QQ plot. (TIFF 1321 kb)
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Supplementary Fig. 2. Performance of six classifiers in predicting tall stature from DNA variants. Box plots of AUC values were generated for weighted allele sums (WAS); least absolute shrinkage and selection operator (LASSO); support vector machine (SVM), neuron networks (NN); classification and regression trees (CART); and random forest (RF). For each method, 1,000 AUC values were derived from cross-validations using randomly split training–testing samples (80 % - 20 %). Summary statistics in the box plots include median (black line), 25-75 % quartiles (grey box), minimum and maximum (dashed interval), and outliers (dots). A. using randomly selected 180 SNPs over the genome. B. using the 180 SNPs from the GIANT paper (Lango Allen et al. 2010). Note that this analysis included 20 % of controls and all cases because the computational burden of SVM scales with sample size. (TIFF 714 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fan Liu
    • 1
  • A. Emile J. Hendriks
    • 2
  • Arwin Ralf
    • 1
  • Annemieke M. Boot
    • 3
  • Emelie Benyi
    • 4
  • Lars Sävendahl
    • 4
  • Ben A. Oostra
    • 5
  • Cornelia van Duijn
    • 6
  • Albert Hofman
    • 6
  • Fernando Rivadeneira
    • 6
    • 7
  • André G. Uitterlinden
    • 6
    • 7
  • Stenvert L. S. Drop
    • 2
  • Manfred Kayser
    • 1
  1. 1.Department of Forensic Molecular BiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
  2. 2.Division of Endocrinology, Department of PediatricsSophia Children’s Hospital, Erasmus MC University Medical Center RotterdamRotterdamThe Netherlands
  3. 3.Division of Endocrinology, Department of PediatricsUniversity Medical Center GroningenGroningenThe Netherlands
  4. 4.Department of Women’s and Children’s HealthKarolinska InstituteStockholmSweden
  5. 5.Department of Clinical GeneticsErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
  6. 6.Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
  7. 7.Department of Internal MedicineErasmus MC University Medical Center RotterdamRotterdamThe Netherlands