Gloria H.Y. Li

The -9247 T/C polymorphism in the SOST upstream regulatory region that potentially affects C/EBPα and FOXA1 binding is associated with osteoporosis.

Accumulating evidence shows that genes that cause monogenic diseases also contribute to similar complex disease in the general population. We sought to determine whether the allelic variation in seven monogenic bone disease genes (CLCN7, TCIRGI, SOST, CA2, CSTK, TGFB1 and SLC26A2) contributes to osteoporosis/bone mineral density (BMD) variation in the normal Chinese population. We conducted a gene-wide tag SNP-based association study in 1243 Chinese subjects with low BMD (Z-scores < or = -1.28, equivalent to the lowest 10% of the population) and high BMD (Z-score > or = +1.0). Twenty-two tag SNPs were selected and genotyped by using the high-throughput Sequenom genotyping platform. Allelic and haplotype association tests were conducted by Haploview and binary logistic regression analyses. The -9247 polymorphism rs1230399 in the upstream regulatory region of the sclerostin gene showed significant genotypic/allelic associations with spine, femoral neck, trochanter and total hip BMD (P=0.03-0.004). The T-allele of rs1230399 increased the risk of osteoporosis (OR=1.52, P=0.005). Computational analysis showed that rs1230399 is located at the core consensus recognition site of two cooperating transcription factors C/EBPalpha and FOXA1 that modulate estrogen receptor function. T-->C polymorphism abolishes the binding of both C/EBPalpha and FOXA1 to the sclerostin gene. Our data suggest a mechanistic link between rs1230399 and BMD through estrogen ERalpha/FOXA1 signaling pathways driven by long-distance enhancers.

Multiple osteoporosis susceptibility genes on chromosome 1p36 in Chinese

INTRODUCTION Chromosome 1p36 is a region that has previously shown good evidence of linkage to bone mineral density (BMD) in multiple studies, but the genes that are responsible for the linkage signals are unknown. MATERIALS AND METHODS We performed a gene-wide and tag SNP-based association study of four positional and functional candidate genes (TNFRSF1B, PLOD, CNR2, and MTHFR) at 1p36 in 1, 243 case-control Chinese subjects. Twenty-three tag SNPs were selected and genotyped using the high-throughput Sequenom genotyping platform. Binary logistic regression analyses were performed to test for genotype associations between each SNP and BMD. Allelic and haplotype association analyses were conducted by Haploview. Gene-gene interactions were investigated using multifactor dimensionality reduction method. RESULTS The PLOD rs7529452 (C385T; F98F) and MTHFR rs1801133 (C677T; A429E) showed significant genotypic/allelic associations with BMDs at all sites measured (P=0.08-0.001), and a promising two-locus gene-gene interaction for femoral neck BMD. The CNR2 rs2501431 (A592G; G155G) showed nominally significant allelic associations with trochanter and hip BMD. The TNFRSF1B rs976881 showed genotypic associations with BMDs (P=0.08-0.04). CONCLUSIONS Our results suggest that multiple genes at 1p36, individually or in different combinations, contribute to osteoporosis susceptibility in Chinese.

Prediction of osteoporosis candidate genes by computational disease-gene identification strategy

AbstractOsteoporosis is a complex disease with a strong genetic component. To date, more than 20 genome-wide linkage scans across multiple populations have been launched to hunt for osteoporosis susceptibility genes. Some significant or suggestive chromosomal regions of linkage to bone mineral density have been identified and replicated in genome-wide linkage screens. However, identification of key candidate genes within these confirmed regions is challenging. We used five freely available bioinformatics tools (Prioritizer, GeneSeeker, PROSPECTR and SUSPECTS, Disease Gene Prediction, and Endeavor) to analyze the 13 well-replicated osteoporosis susceptibility loci: 1p36, 1q21–25, 2p22–24, 3p14–25, 4q25–34, 6p21, 7p14–21, 11q14–25, 12q23–24, 13q14–34, 20p12, 2q24–32, and 5q12–21. Pathways and regulatory network analyses were performed using the Ingenuity Pathways Analysis (IPA) software. We identified a subset of most likely candidate osteoporosis susceptibility genes that are largely involved in transforming growth factor (TGF)-β signaling, granulocyte-macrophage colony-stimulating factor (GM-CSF) signaling, axonal guidance signaling, peroxisome proliferator-activated receptor (PPAR) signaling, and Wnt/β-catenin signaling pathway. Six nonoverlapping networks were generated by IPA 5.0 from 88 out of the 91 candidate genes. The list of most likely candidate genes and the associated pathway identified will assist researchers in prioritizing candidate disease genes for further empirical analysis and understanding the pathogenesis of osteoporosis.