4.7 Article

Evidence of association and linkage disequilibrium between a novel polymorphism in the transforming growth factor beta 1 gene and hip bone mineral density: a study of female twins

Journal

RHEUMATOLOGY
Volume 40, Issue 1, Pages 48-54

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/rheumatology/40.1.48

Keywords

genetics; osteoporosis; alleles; sibling TDT; growth factor

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Objective. Bone mineral density (BMD) in later life is a major determinant of osteoporotic fracture risk and has been shown to be under strong genetic influence. Transforming growth factor beta1 (TGF-beta1) is an important regulatory cytokine, is found in high concentrations in the bone matrix, and is a plausible candidate for the genetic regulation of BMD. Methods. This study investigated whether a novel polymorphism within the TGF-beta1 gene is associated with BMD in a large normal female population of 1706 dizygotic (DZ) twins (age range 18-76 yr). Results. A T --> C polymorphism was identified in intron 5, the C allele having a frequency of 0.25. Subjects homozygous for the presence of the TGF-beta1 C allele had a 4% reduction in femoral neck BMD compared with the other two genotype groups(P < 0.025). No effect was seen at the lumbar spine or ultradistal radius, or with calcaneal ultrasound measurements. Results were unaffected after adjustment for potential confounders. These findings were predominantly seen in pre-menopausal subjects, suggesting that this locus has an effect on the attainment of peak BMD. In pre-menopausal women, subjects who were homozygous for the C allele had a 5-fold excess risk of having osteoporosis at the femoral neck compared with the other genotype groups. A within-pair analysis using the sibling transmission disequilibrium test confirmed these findings in pre-menopausal women and supported the candidacy of the TGF-1 locus in the genetic regulation of hip BMD. Conclusions. These results indicate that allelic variation at the TGF-beta1 gene contributes to the development of osteoporosis at the hip. The study also highlights the power of candidate gene analysis in twins, in whom loci having modest effects on disease risk can be identified.

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