Sex-specific quantitative trait loci contribute to normal variation in bone structure at the proximal femur in men

Bone. 2005 Oct;37(4):467-73. doi: 10.1016/j.bone.2005.05.005.

Abstract

Bone structure is an important determinant of osteoporotic fracture. In women, bone structure is highly heritable, and several quantitative trait loci (QTL) have been reported. There are few comparable data in men. This study in men aimed at establishing the heritability of bone structure at the proximal femur, identifying QTL contributing to normal variation in bone structure, and determining which QTL might be sex-specific. Bone structure at the proximal femur was measured in 205 pairs of brothers age 18-61. Heritability was calculated, and linkage analysis performed on phenotypes at the proximal femur. Heritability estimates ranged from 0.99 to 0.39. A genome wide scan identified suggestive QTL (LOD>2.2) for femoral shaft width on chromosome 14q (LOD=2.69 at position 99 cM), calcar femorale at chromosome 2p (LOD=3.97 at position 194 cM) and at the X chromosome (LOD=3.01 at position 77 cM), femoral neck width on chromosome 5p (LOD=2.28 at position 0 cM), femoral head width on chromosome 11q (LOD=2.30 at position 131 cM) and 15q (LOD=3.11 at position 90 cM), and pelvic axis length on chromosome 4q (LOD=4.16 at position 99 cM) and 17q (LOD=2.80 at position 112 cM). Comparison with published data in 437 pairs of premenopausal sisters from the same geographical region suggested that 3 of the 7 autosomal QTL were male-specific. This study demonstrates that bone structure at the proximal femur in healthy men is highly heritable. The occurrence of sex-specific genes in humans for bone structure has important implications for the pathogenesis and treatment of osteoporosis.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Chromosomes, Human, X
  • Female
  • Femur / anatomy & histology*
  • Genetic Variation*
  • Humans
  • Lod Score
  • Male
  • Premenopause
  • Quantitative Trait Loci*
  • Sex Factors*