PT - JOURNAL ARTICLE AU - Liu, P-Y AU - Lu, Y AU - Long, J-R AU - Xu, F-H AU - Shen, H AU - Recker, R R AU - Deng, H-W TI - Common variants at the PCOL2 and Sp1 binding sites of the <em>COL1A1</em> gene and their interactive effect influence bone mineral density in Caucasians AID - 10.1136/jmg.2004.019851 DP - 2004 Oct 01 TA - Journal of Medical Genetics PG - 752--757 VI - 41 IP - 10 4099 - http://jmg.bmj.com/content/41/10/752.short 4100 - http://jmg.bmj.com/content/41/10/752.full SO - J Med Genet2004 Oct 01; 41 AB - Background: Osteoporosis, mainly characterised by low bone mineral density (BMD), is a serious public health problem. The collagen type I alpha 1 (COL1A1) gene is a prominent candidate gene for osteoporosis. Here, we examined whether genetic variants at the COL1A1 gene can influence BMD variation. Methods: BMD was measured at nine skeletal sites in 313 Caucasian males and 308 Caucasian females. We screened four single nucleotide polymorphisms (SNPs) at the COL1A1 gene: PCOL2 (-1997 G/T) in the promoter, Sp1 (1546 G/T) in the intron 1, Gly19Cys (3911 G/A) in exon 8, and Ala897Thr (13 773 G/A) in exon 45. Univariate and multivariate association approaches were used in the analyses. Results: In multivariate analyses, we found a strong association between the PCOL2 SNP and BMD (p = 0.007 to 0.024) and a suggestive association between the Sp1 SNP and BMD (p = 0.023 to 0.048) in elderly Caucasian females. Interestingly, the interaction of these two SNPs was highly significantly associated with BMD variation (p = 0.001 to 0.003). The haplotype GG at the two SNPs had, on average, 2.7% higher BMD than non-carriers (p = 0.006 to 0.026). Conclusions: Our data suggested that the common genetic variants at the PCOL2 and Sp1 sites, and importantly, their interactive effects, may contribute to BMD variation in elderly Caucasian females. Further studies are necessary to delineate the mechanisms underlying the effects of these common variants on BMD variation and to test their clinical relevance for general populations. In addition, our study highlighted the importance of multivariate analyses when multiple correlated phenotypes are under study.