Li-Jun Tan

An in vivo genome wide gene expression study of circulating monocytes suggested GBP1, STAT1 and CXCL10 as novel risk genes for the differentiation of peak bone mass.

Peak bone mass (PBM) is an important determinant of osteoporosis. Circulating monocytes serve as early progenitors of osteoclasts and produce important molecules for bone metabolism. To search for genes functionally important for PBM variation, we performed a whole genome gene differential expression study of circulating monocytes in human premenopausal subjects with extremely low (N=12) vs. high (N=14) PBM. We used Affymetrix HG-U133 plus2.0 GeneChip arrays. We identified 70 differential expression probe sets (p<0.01) corresponding to 49 unique genes. After false discovery rate adjustment, three genes [STAT1, signal transducer and activator of transcription 1; GBP1, guanylate binding protein 1; CXCL10, Chemokine (C-X-C motif) ligand 10] expressed significantly differentially (p<0.05). The RT-PCR results independently confirmed the significantly differential expression of GBP1 gene, and the differential expression trend of STAT1. Functional analyses suggested that the three genes are associated with the osteoclastogenic processes of proliferation, migration, differentiation, migration, chemotaxis, adhesion. Therefore, we may tentatively hypothesize that the three genes may potentially contribute to differential osteoclastogenesis, which may in the end lead to differential PBM. Our results indicate that the GBP1, STAT1 and CXCL10 may be novel risk genes for the differentiation of PBM at the monocyte stage.

Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass.

Lean body mass (LBM) is a heritable trait predicting a series of health problems, such as osteoporotic fracture and sarcopenia. We aim to identify sequence variants associated with LBM by a genome-wide association study (GWAS) of copy number variants (CNVs). We genotyped genome-wide CNVs of 1627 individuals of the Chinese population with Affymetrix SNP6.0 genotyping platform, which comprised of 9 40 000 copy number probes. We then performed a GWAS of CNVs with lean mass at seven sites: left and right arms, left and right legs, total of limb, trunk and whole body. We identified a CNV that is associated with LBM variation at the genome-wide significance level (CNV2073, Bonferroni corrected P-value 0.002 at right arm). CNV2073 locates at chromosome 15q13.3, which has been implicated as a candidate region for LBM by our previous linkage studies. The nearest gene, gremlin1, has a key role in the regulation of skeletal muscle formation and repair. Our results suggest that the gremlin1 gene is a potentially important gene for LBM variation. Our findings also show the utility and efficacy of CNV as genetic markers in association studies.

The differences of femoral neck geometric parameters: effects of age, gender and race

SummaryThis study aims at investigating the effects of age, sex, and ethnicity on five femoral neck geometric parameters (FNGPs): femoral neck periosteal diameter, cross-sectional area, cortical thickness, sectional modulus, and buckling ratio and found that the three factors would influence the FNGPs.IntroductionBone geometry is one of the most important predictors of bone strength and osteoporotic fractures. This study aims at investigating the effects of age, sex, and ethnicity on five femoral neck geometric parameters (FNGPs): femoral neck periosteal diameter (W), cross-sectional area (CSA), cortical thickness (CT), sectional modulus (Z), and buckling ratio (BR).MethodsIn the studied 861 Caucasian subjects and 3,021 Chinese individuals, CSA, CT, and Z displayed trends of decrease with age, but W and BR showed increasing trends with age in both Chinese and Caucasian females and males (p < 0.05). W, CSA, CT, and Z were significantly higher (p ≤ 0.001) in Caucasians than in Chinese and higher in males than in females except for BR between Chinese males and Chinese females.ConclusionIn conclusion, the differences of FNGPs according to gender and ethnicity provide important implications in the different prevalence of osteoporotic fracture among different gender and ethnic groups.

Establishment of peak bone mineral density in Southern Chinese males and its comparisons with other males from different regions of China

Peak bone mineral density (PBMD) is an important determinant of osteoporotic fracture and a precondition for correct diagnosis of osteoporosis. The objective of this study was to establish the reference data of PBMD at the lumber spine and hip in Southern Chinese males. Bone mineral density (BMD) was measured at the lumbar spine and hip (femoral neck, trochanter, intertrochanter, and total) in 1155 Chinese men aged 15–39 years, using dual-energy X-ray absorptiometry (DXA). We utilized a fit curve method to determine the best age range over which to calculate PBMD. Our results indicated that the PBMD was observed at the age range of 18–25 years at the various sites. The mean value and standard deviation of PBMD was 0.753 ± 0.117, 1.156 ± 0.148, 0.896 ± 0.120, 0.989 ± 0.122, and 0.980 ± 0.116 g/cm2 at the trochanter, intertrochanter, femoral neck, total hip, and spine, respectively. When the present PBMD reference was compared with the documented PBMD reference of males from other regions of China, we found great difference in standardized PBMD between Changsha males and those from other regions of China. The PBMD for Chinese males in Changsha at the various sites were 3.19%–11.33% lower than that for American Caucasian males. In conclusion, the PBMD at the spine and hip may be used as normal reference data for Southern Chinese males in Changsha instead of documented PBMD from other regions of China and the manufacturers reference data.

Anthropometric indices as the predictors of trunk obesity in Chinese young adults: receiver operating characteristic analyses.

Background: Trunk obesity has adverse health implications in adults, but valid and practical methods to correctly measure trunk obesity in China are insufficient. Aim: This study aimed to assess the validity of anthropometric indices as screening the predictors of trunk obesity in young Chinese adults. Subjects and methods: A total of 1946 (853 women, 1093 men) Chinese volunteers aged 20–40 years were recruited. Trunk fat mass was measured by dual-energy X-ray absorptiometry. Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and conicity index (C index) were measured or calculated. Receiver operating characteristic (ROC) curves were used to compare the validity of each anthropometric index to predict trunk adiposity. Results: BMI and WC performed better as the anthropometric indices defining trunk obesity than WHR and C index, and the areas under the ROC curves for BMI (0.94 in men and 0.89 in women) were similar to those for WC (0.93 in men and 0.88 in women). Conclusions: Both BMI and WC are more effective predictors of trunk obesity than WHR and C index in Chinese young adults.

Identification of IDUA and WNT16 Phosphorylation-Related Non-Synonymous Polymorphisms for Bone Mineral Density in Meta-Analyses of Genome-Wide Association Studies

Protein phosphorylation regulates a wide variety of cellular processes. Thus, we hypothesize that single‐nucleotide polymorphisms (SNPs) that may modulate protein phosphorylation could affect osteoporosis risk. Based on a previous conventional genome‐wide association (GWA) study, we conducted a three‐stage meta‐analysis targeting phosphorylation‐related SNPs (phosSNPs) for femoral neck (FN)‐bone mineral density (BMD), total hip (HIP)‐BMD, and lumbar spine (LS)‐BMD phenotypes. In stage 1, 9593 phosSNPs were meta‐analyzed in 11,140 individuals of various ancestries. Genome‐wide significance (GWS) and suggestive significance were defined by α = 5.21 × 10–6 (0.05/9593) and 1.00 × 10–4, respectively. In stage 2, nine stage 1–discovered phosSNPs (based on α = 1.00 × 10–4) were in silico meta‐analyzed in Dutch, Korean, and Australian cohorts. In stage 3, four phosSNPs that replicated in stage 2 (based on α = 5.56 × 10–3, 0.05/9) were de novo genotyped in two independent cohorts. IDUA rs3755955 and rs6831280, and WNT16 rs2707466 were associated with BMD phenotypes in each respective stage, and in three stages combined, achieving GWS for both FN‐BMD (p = 8.36 × 10–10, p = 5.26 × 10–10, and p = 3.01 × 10–10, respectively) and HIP‐BMD (p = 3.26 × 10–6, p = 1.97 × 10–6, and p = 1.63 × 10–12, respectively). Although in vitro studies demonstrated no differences in expressions of wild‐type and mutant forms of IDUA and WNT16B proteins, in silico analyses predicts that WNT16 rs2707466 directly abolishes a phosphorylation site, which could cause a deleterious effect on WNT16 protein, and that IDUA phosSNPs rs3755955 and rs6831280 could exert indirect effects on nearby phosphorylation sites. Further studies will be required to determine the detailed and specific molecular effects of these BMD‐associated non‐synonymous variants.

Integrating Epigenomic Elements and GWASs Identifies BDNF Gene Affecting Bone Mineral Density and Osteoporotic Fracture Risk

To identify susceptibility genes for osteoporosis, we conducted an integrative analysis that combined epigenomic elements and previous genome-wide association studies (GWASs) data, followed by validation at population and functional levels, which could identify common regulatory elements and predict new susceptibility genes that are biologically meaningful to osteoporosis. By this approach, we found a set of distinct epigenomic elements significantly enriched or depleted in the promoters of osteoporosis-associated genes, including 4 transcription factor binding sites, 27 histone marks, and 21 chromatin states segmentation types. Using these epigenomic marks, we performed reverse prediction analysis to prioritize the discovery of new candidate genes. Functional enrichment analysis of all the prioritized genes revealed several key osteoporosis related pathways, including Wnt signaling. Genes with high priority were further subjected to validation using available GWASs datasets. Three genes were significantly associated with spine bone mineral density, including BDNF, PDE4D, and SATB2, which all closely related to bone metabolism. The most significant gene BDNF was also associated with osteoporotic fractures. RNA interference revealed that BDNF knockdown can suppress osteoblast differentiation. Our results demonstrated that epigenomic data could be used to indicate common epigenomic marks to discover additional loci with biological functions for osteoporosis.

Integrative Analysis of Transcriptomic and Epigenomic Data to Reveal Regulation Patterns for BMD Variation.

Integration of multiple profiling data and construction of functional gene networks may provide additional insights into the molecular mechanisms of complex diseases. Osteoporosis is a worldwide public health problem, but the complex gene-gene interactions, post-transcriptional modifications and regulation of functional networks are still unclear. To gain a comprehensive understanding of osteoporosis etiology, transcriptome gene expression microarray, epigenomic miRNA microarray and methylome sequencing were performed simultaneously in 5 high hip BMD (Bone Mineral Density) subjects and 5 low hip BMD subjects. SPIA (Signaling Pathway Impact Analysis) and PCST (Prize Collecting Steiner Tree) algorithm were used to perform pathway-enrichment analysis and construct the interaction networks. Through integrating the transcriptomic and epigenomic data, firstly we identified 3 genes (FAM50A, ZNF473 and TMEM55B) and one miRNA (hsa-mir-4291) which showed the consistent association evidence from both gene expression and methylation data; secondly in network analysis we identified an interaction network module with 12 genes and 11 miRNAs including AKT1, STAT3, STAT5A, FLT3, hsa-mir-141 and hsa-mir-34a which have been associated with BMD in previous studies. This module revealed the crosstalk among miRNAs, mRNAs and DNA methylation and showed four potential regulatory patterns of gene expression to influence the BMD status. In conclusion, the integration of multiple layers of omics can yield in-depth results than analysis of individual omics data respectively. Integrative analysis from transcriptomics and epigenomic data improves our ability to identify causal genetic factors, and more importantly uncover functional regulation pattern of multi-omics for osteoporosis etiology.

A genome-wide association analysis implicates SOX6 as a candidate gene for wrist bone mass

Osteoporosis is a highly heritable common bone disease leading to fractures that severely impair the life quality of patients. Wrist fractures caused by osteoporosis are largely due to the scarcity of wrist bone mass. Here we report the results of a genome-wide association study (GWAS) of wrist bone mineral density (BMD). We examined ∼500000 SNP markers in 1000 unrelated homogeneous Caucasian subjects and found a novel allelic association with wrist BMD at rs11023787 in the SOX6 (SRY (sex determining region Y)-box 6) gene (P=9.00×10−5). Subjects carrying the C allele of rs11023787 in SOX6 had significantly higher mean wrist BMD values than those with the T allele (0.485:0.462 g cm−2 for C allele vs. T allele carriers). For validation, we performed SOX6 association for BMD in an independent Chinese sample and found that SNP rs11023787 was significantly associated with wrist BMD in the Chinese sample (P=6.41×10−3). Meta-analyses of the GWAS scan and the replication studies yielded P-values of 5.20×10−6 for rs11023787. Results of this study, together with the functional relevance of SOX6 in cartilage formation, support the SOX6 gene as an important gene for BMD variation.

A genome wide association study between copy number variation (CNV) and human height in Chinese population.

Copy number variation (CNV) is a type of genetic variation which may have important roles in phenotypic variability and disease susceptibility. To hunt for genetic variants underlying human height variation, we performed a genome wide CNV association study for human height in 618 Chinese unrelated subjects using Affymetrix 500K array set. After adjusting for age and sex, we found that four CNVs at 6p21.3, 8p23.3-23.2, 9p23 and 16p12.1 were associated with human height (with borderline significant p value: 0.013, 0.011, 0.024, 0.049; respectively). However, after multiple tests correction, none of them was associated with human height. We observed that the gain of copy number (more than 2 copies) at 8p23.3-23.2 was associated with lower height (normal copy number vs. gain of copy number: 161.2 cm vs. 153.7 cm, p = 0.011), which accounted for 0.9% of height variation. Loss of copy number (less than 2 copies) at 6p21.3 was associated with 0.8% lower height (loss of copy number vs. normal copy number: 154.5 cm vs. 161.1 cm, p = 0.013). Since no important genes influencing height located in CNVs at loci of 8p23.3-23.2 and 6p21.3, the two CNVs may cause the structural rearrangements of neighbored important candidate genes, thus regulates the variation of height. Our results expand our knowledge of the genetic factors underlying height variation and the biological regulation of human height.