The stringent genome-wide

significance level may also inflate the false-negative rate and limit its ability to identify disease genes. Different approaches have recently been adopted to ameliorate this situation, including pathway-based and gene-based GWAS. Gene-based analysis is a complementary approach to single-locus analysis. Generally, this type of approach tests whether a set of SNPs in a given gene locus is associated with a trait selleck chemical of interest. Different approaches have been used to identify genes that are associated with trait of interest, such as multiple logistic regression for discrete trait and set-based test for discrete or continuous trait. Nonetheless, the set-based test requires heavy computation and therefore limits its application at a genome-wide level. An efficient genome-wide gene-based association method has recently been developed, based on simulations from the multivariate normal distribution. This approach has provided important biological insight into disease etiology, and a number of disease genes are expected to be identified. These genes may not contain any SNPs that meet the genome-wide significance threshold, but rather a nominal significant p value may be observed in a number of SNPs in each of these genes. In this study, we performed gene-based GWAS in a Hong Kong Southern Chinese (HKSC) cohort and

Icelandic deCODE Study (dCG) [2] and performed meta-analysis of 6,636 adults by combining the results from HKSC and dCG that examined spine and femoral neck BMD. MEK inhibitor Our findings confirmed several ICG-001 cost well-known candidate genes and discovered a number of novel candidate genes. Materials Non-specific serine/threonine protein kinase and methods Study population The current meta-analysis incorporated 6,643 individuals derived from two GWAS on BMD at the lumbar spine and femoral neck, the HKSC Study (n = 778), and dCG Study (dCG, n = 5,858) [2]. In the Hong Kong Osteoporosis Study, 800 unrelated women with extreme high or low BMD were selected from a HKSC cohort with extreme BMD. These subjects were selected from a database (>9,000 Southern Han Chinese volunteers) at the Osteoporosis

Centre of the University of Hong Kong. Low-BMD subjects are defined as those with a BMD Z-score ≤ −1.28 at either the lumbar spine (LS) or femoral neck (FN) (the lowest 10% of the total cohort). High-BMD subjects comprised individuals with BMD Z-score ≥ +1.0 at either site. Subjects who reported diseases or environmental factors that may affect BMD and bone metabolism were excluded. The recruitment procedure and exclusion criteria have been detailed elsewhere [3]. The demographic data of studied population are provided in Supplementary Table 1. BMD and anthropometric measurements BMD (grams per square centimeter) at the LS and FN was measured by dual-energy X-ray absorptiometry (Hologic QDR 4500 plus, Hologic Waltham, MA, USA) with standard protocol. The in vivo precision of the machine was 1.