Robust and Comprehensive Analysis of 20 Osteoporosis Candidate Genes by Very High-Density Single-Nucleotide Polymorphism Screen Among 405 White Nuclear Families Identified Significant Association and Gene–Gene Interaction

Authors

  • Dong-Hai Xiong,

    1. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, Nebraska, USA
    Search for more papers by this author
  • Hui Shen,

    1. Departments of Orthopedic Surgery and Basic Medical Sciences, University of Missouri–Kansas City, Kansas City, Missouri, USA
    Search for more papers by this author
  • Lan-Juan Zhao,

    1. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, Nebraska, USA
    Search for more papers by this author
  • Peng Xiao,

    1. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, Nebraska, USA
    Search for more papers by this author
  • Tie-Lin Yang,

    1. The Key Laboratory of Biomedical Information Engineering, Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    Search for more papers by this author
  • Yan Guo,

    1. The Key Laboratory of Biomedical Information Engineering, Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    Search for more papers by this author
  • Wei Wang,

    1. The Key Laboratory of Biomedical Information Engineering, Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    Search for more papers by this author
  • Yan-Fang Guo,

    1. Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
    Search for more papers by this author
  • Yong-Jun Liu,

    1. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, Nebraska, USA
    Search for more papers by this author
  • Robert R Recker,

    1. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, Nebraska, USA
    Search for more papers by this author
  • Hong-Wen Deng PhD

    Corresponding author
    1. Departments of Orthopedic Surgery and Basic Medical Sciences, University of Missouri–Kansas City, Kansas City, Missouri, USA
    2. The Key Laboratory of Biomedical Information Engineering, Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    3. Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
    • Hong-Wen Deng, PhD, Departments of Orthopedic Surgery and Basic Medical Sciences, University of Missouri–Kansas City, 2411 Holmes Street, Room M3-C03, Kansas City, MO 64108-2792, USA
    Search for more papers by this author

  • The authors state that they have no conflicts of interest.

Abstract

Many “novel” osteoporosis candidate genes have been proposed in recent years. To advance our knowledge of their roles in osteoporosis, we screened 20 such genes using a set of high-density SNPs in a large family-based study. Our efforts led to the prioritization of those osteoporosis genes and the detection of gene–gene interactions.

Introduction: We performed large-scale family-based association analyses of 20 novel osteoporosis candidate genes using 277 single nucleotide polymorphisms (SNPs) for the quantitative trait BMD variation and the qualitative trait osteoporosis (OP) at three clinically important skeletal sites: spine, hip, and ultradistal radius (UD).

Materials and Methods: One thousand eight hundred seventy-three subjects from 405 white nuclear families were genotyped and analyzed with an average density of one SNP per 4 kb across the 20 genes. We conducted association analyses by SNP- and haplotype-based family-based association test (FBAT) and performed gene–gene interaction analyses using multianalytic approaches such as multifactor-dimensionality reduction (MDR) and conditional logistic regression.

Results and Conclusions: We detected four genes (DBP, LRP5, CYP17, and RANK) that showed highly suggestive associations (10,000-permutation derived empirical global p ≤ 0.01) with spine BMD/OP; four genes (CYP19, RANK, RANKL, and CYP17) highly suggestive for hip BMD/OP; and four genes (CYP19, BMP2, RANK, and TNFR2) highly suggestive for UD BMD/OP. The associations between BMP2 with UD BMD and those between RANK with OP at the spine, hip, and UD also met the experiment-wide stringent criterion (empirical global p ≤ 0.0007). Sex-stratified analyses further showed that some of the significant associations in the total sample were driven by either male or female subjects. In addition, we identified and validated a two-locus gene–gene interaction model involving GCR and ESR2, for which prior biological evidence exists. Our results suggested the prioritization of osteoporosis candidate genes from among the many proposed in recent years and revealed the significant gene–gene interaction effects influencing osteoporosis risk.

Ancillary