Identification of genes for bone mineral density variation by computational disease gene identification strategy

We previously used five freely available bioinformatics tools (Prioritizer, Geneseeker, PROSPECTR and SUSPECTS, Disease Gene Prediction, and Endeavour) to analyze the thirteen well-replicated osteoporosis susceptibility loci and identify a subset of most likely candidate osteoporosis susceptibility genes (Huang et al. in J Hum Genet 53:644-655, 2008). In the current study, we experimentally tested the association between bone mineral density (BMD) and the 9 most likely candidate genes [LAMC2(1q25-q31), MATN3(2p24-p23), ITGAV(2q31-q32), ACVR1(2q23-q24), TDGF1(3p21.31), EGF(4q25), IGF1(12q22-q23), ZIC2(13q32), BMP2(20p12)] which were pinpointed by 4 or more bioinformatics tools. Forty tag SNPs in nine candidate genes were genotyped in a southern Chinese female case-control cohort consisting of 1643 subjects. Single- and multi-marker association analyses were performed using logistic regression analysis implemented by PLINK. Potential transcription factor binding sites were predicted by MatInspector. The strongest association was observed between rs10178256 (MATN3) and trochanter (P < 0.001) and total hip BMD (P = 0.002). The SNP rs6214 (IGF1) showed consistent association with BMD at all the four measured skeletal sites (P = 0.005-0.044). Prediction of transcription factor binding suggested that the minor allele G of rs10178256 might abolish the binding of MESP1 and MESP2 which play vital roles in bone homeostasis, whereas the minor allele G of rs6214 might create an additional binding site for XBP1, a constitutive regulator of endoplasmic reticulum stress response. Our data suggested that variants in MATN3 and IGF1 were involved in BMD regulation in southern Chinese women.