Xiao-Feng Chen

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.

A functional SNP regulated by miR‐196a‐3p in the 3'UTR of FGF2 is associated with bone mineral density in the Chinese Population

Previous studies have identified FGF2 as a susceptibility gene for osteoporosis in Caucasians. Evaluating the genetic associations in different ethnicities is necessary. Moreover, elucidating the functional mechanism for the susceptibility loci is important to offer new targets for therapeutic studies. Here, we genotyped 10 SNPs in FGF2 and tested for associations with bone mineral density (BMD) in a discovery sample of 1,300 Chinese subjects. Nominally significant results were subjected to replication in another sample of 1,039 Chinese subjects. We identified one SNP rs1048201:C>T in FGF2 3′untranslated region significantly associated with spine BMD (combined cohorts, P = 1.53×10−3). Expression quantitative trait locus analyses revealed that rs1048201 also affected FGF2 gene expression (P = 7.03×10−4). Bioinformatics prediction suggested that rs1048201 T allele could disrupt miRNA binding. Luciferase assay validated that the C allele had a repressive effect on FGF2 gene expression. We found that hsa‐miR‐196a‐3p affected expression on both mRNA and protein levels of FGF2. In conclusion, our study provided evidence that a functional SNP rs1048201 was associated with BMD, and SNP rs1048201:C>T variant may act by affecting binding of hsa‐miR‐196a‐3p. The SNP‐modified posttranscriptional gene regulation by miRNA could be a potentially pathogenetic mechanism of osteoporosis.

Associations of Plasma FGF2 Levels and Polymorphisms in the FGF2 Gene with Obesity Phenotypes in Han Chinese Population

Obesity is highly heritable, but the specific genes influencing obesity related traits are largely unknown. Fibroblast growth factor 2 (FGF2) could influence adipocyte differentiation. However, the association of FGF2 polymorphisms and obesity remains unclear. This study aimed to investigate the associations of both the plasma FGF2 levels and SNPs in FGF2 gene with obesity phenotypes in Han Chinese populations. Plasma FGF2 levels were measured and subjected to association analyses in 62 subjects. Eleven SNPs in FGF2 were genotyped and tested for associations in a discovery sample of 1,300 subjects. SNPs significantly associated with obesity were subjected to replication in another independent sample of 1,035 subjects. We found that plasma FGF2 levels were positively correlated with fat mass (P = 0.010). Association analyses in the discovery sample identified three SNPs (rs1449683, rs167428, rs308442) significantly associated with fat mass after multiple testing adjustments (P < 0.0045). Subsequent replication study successfully validated one SNP (rs167428) associated with fat mass (Pcombine = 3.46 × 10−5). eQTL analyses revealed that SNPs associated with obesity also affected FGF2 expression. Our findings suggested that high plasma FGF2 level correlated with increased risk of obesity, and FGF2 gene polymorphisms could affect individual variances of obesity in Han Chinese population.

Genetic Analysis Identifies DDR2 as a Novel Gene Affecting Bone Mineral Density and Osteoporotic Fractures in Chinese Population

DDR2 gene, playing an essential role in regulating osteoblast differentiation and chondrocyte maturation, may influence bone mineral density (BMD) and osteoporosis, but the genetic variations actually leading to the association remain to be elucidated. Therefore, the aim of this study was to investigate whether the genetic variants in DDR2 are associated with BMD and fracture risk. This study was performed in three samples from two ethnicities, including 1,300 Chinese Han subjects, 700 Chinese Han subjects (350 with osteoporotic hip fractures and 350 healthy controls) and 2,286 US white subjects. Twenty-eight SNPs in DDR2 were genotyped and tested for associations with hip BMD and fractures. We identified 3 SNPs in DDR2 significantly associated with hip BMD in the Chinese population after multiple testing adjustments, which were rs7521233 (P = 1.06×10−4, β: −0.018 for allele C), rs7553831 (P = 1.30×10−4, β: −0.018 for allele T), and rs6697469 (P = 1.59×10−3, β: −0.015 for allele C), separately. These three SNPs were in high linkage disequilibrium. Haplotype analyses detected two significantly associated haplotypes, including one haplotype in block 2 (P = 9.54×10−4, β: −0.016) where these three SNPs located. SNP rs6697469 was also associated with hip fractures (P = 0.043, OR: 1.42) in the Chinese population. The effect on fracture risk was consistent with its association with lower BMD. However, in the white population, we didn’t observe significant associations with hip BMD. eQTL analyses revealed that SNPs associated with BMD also affected DDR2 mRNA expression levels in Chinese. Our findings, together with the prior biological evidence, suggest that DDR2 could be a new candidate for osteoporosis in Chinese population. Our results also reveal an ethnic difference, which highlights the need for further genetic studies in each ethnic group.

Multiple functional variants at 13q14 risk locus for osteoporosis regulate RANKL expression through long-range super-enhancer†

RANKL is a key regulator involved in bone metabolism, and a drug target for osteoporosis. The clinical diagnosis and assessment of osteoporosis are mainly based on bone mineral density (BMD). Previous powerful genomewide association studies (GWASs) have identified multiple intergenic single‐nucleotide polymorphisms (SNPs) located over 100 kb upstream of RANKL and 65 kb downstream of AKAP11 at 13q14.11 for osteoporosis. Whether these SNPs exert their roles on osteoporosis through RANKL is unknown. In this study, we conducted integrative analyses combining expression quantitative trait locus (eQTL), genomic chromatin interaction (high‐throughput chromosome conformation capture [Hi‐C]), epigenetic annotation, and a series of functional assays. The eQTL analysis identified six potential functional SNPs (rs9533090, rs9594738, r8001611, rs9533094, rs9533095, and rs9594759) exclusively correlated with RANKL gene expression (p < 0.001) at 13q14.11. Co‐localization analyses suggested that eQTL signal for RANKL and BMD‐GWAS signal shared the same causal variants. Hi‐C analysis and functional annotation further validated that the first five osteoporosis SNPs are located in a super‐enhancer region to regulate the expression of RANKL via long‐range chromosomal interaction. Particularly, dual‐luciferase assay showed that the region harboring rs9533090 in the super‐enhancer has the strongest enhancer activity, and rs9533090 is an allele‐specific regulatory SNP. Furthermore, deletion of the region harboring rs9533090 using CRISPR/Cas9 genome editing significantly reduced RANKL expression in both mRNA level and protein level. Finally, we found that the rs9533090‐C robustly recruits transcription factor NFIC, which efficiently elevates the enhancer activity and increases the RANKL expression. In summary, we provided a feasible method to identify regulatory noncoding SNPs to distally regulate their target gene underlying the pathogenesis of osteoporosis by using bioinformatics data analyses and experimental validation. Our findings would be a potential and promising therapeutic target for precision medicine in osteoporosis.

An Osteoporosis Risk SNP at 1p36.12 Acts as an Allele-Specific Enhancer to Modulate LINC00339 Expression via Long-Range Loop Formation

Genome-wide association studies (GWASs) have reproducibly associated variants within intergenic regions of 1p36.12 locus with osteoporosis, but the functional roles underlying these noncoding variants are unknown. Through an integrative functional genomic and epigenomic analyses, we prioritized rs6426749 as a potential causal SNP for osteoporosis at 1p36.12. Dual-luciferase assay and CRISPR/Cas9 experiments demonstrate that rs6426749 acts as a distal allele-specific enhancer regulating expression of a lncRNA (LINC00339) (∼360 kb) via long-range chromatin loop formation and that this loop is mediated by CTCF occupied near rs6426749 and LINC00339 promoter region. Specifically, rs6426749-G allele can bind transcription factor TFAP2A, which efficiently elevates the enhancer activity and increases LINC00339 expression. Downregulation of LINC00339 significantly increases the expression of CDC42 in osteoblast cells, which is a pivotal regulator involved in bone metabolism. Our study provides mechanistic insight into how a noncoding SNP affects osteoporosis by long-range interaction, a finding that could indicate promising therapeutic targets for osteoporosis.

SNP-SNP interactions between WNT4 and WNT5A were associated with obesity related traits in Han Chinese Population

Considering the biological roles of WNT4 and WNT5A involved in adipogenesis, we aimed to investigate whether SNPs in WNT4 and WNT5A contribute to obesity related traits in Han Chinese population. Targeted genomic sequence for WNT4 and WNT5A was determined in 100 Han Chinese subjects and tag SNPs were selected. Both single SNP and SNP × SNP interaction association analyses with body mass index (BMI) were evaluated in the 100 subjects and another independent sample of 1,627 Han Chinese subjects. Meta-analyses were performed and multiple testing corrections were carried out using the Bonferroni method. Consistent with the Genetic Investigation of ANthropometric Traits (GIANT) dataset results, we didn’t detect significant association signals in single SNP association analyses. However, the interaction between rs2072920 and rs11918967, was associated with BMI after multiple testing corrections (combined P = 2.20 × 10−4). The signal was also significant in each contributing data set. SNP rs2072920 is located in the 3′-UTR of WNT4 and SNP rs11918967 is located in the intron of WNT5A. Functional annotation results revealed that both SNPs might be involved in transcriptional regulation of gene expression. Our results suggest that a combined effect of SNPs via WNT4-WNT5A interaction may affect the variation of BMI in Han Chinese population.

Runs of homozygosity associate with decreased risks of lung cancer in never-smoking East Asian females

Although genome-wide association studies (GWASs) have identified some risk single-nucleotide polymorphisms in East Asian never-smoking females, the unexplained missing heritability is still required to be investigated. Runs of homozygosity (ROHs) are thought to be a type of genetic variation acting on human complex traits and diseases. We detected ROHs in 8,881 East Asian never-smoking women. The summed ROHs were used to fit a logistic regression model which noteworthily revealed a significant association between ROHs and the decreased risk of lung cancer (P < 0.05). We identified 4 common ROHs regions located at 2p22.1, which were significantly associated with decreased risk of lung cancer (P = 2.00 × 10-4 - 1.35 × 10-4). Functional annotation was conducted to investigate the regulatory function of ROHs. The common ROHs were overlapped with potential regulatory elements, such as active epigenome elements and chromatin states in lung-derived cell lines. SOS1 and ARHGEF33 were significantly up-regulated as the putative target genes of the identified ROHs in lung cancer samples according to the analysis of differently expressed genes. Our results suggest that ROHs could act as recessive contributing factors and regulatory elements to influence the risk of lung cancer in never-smoking East Asian females.

Integrating regulatory features data for prediction of functional disease-associated SNPs.

Genome-wide association studies (GWASs) are an effective strategy to identify susceptibility loci for human complex diseases. However, missing heritability is still a big problem. Most GWASs single-nucleotide polymorphisms (SNPs) are located in noncoding regions, which has been considered to be the unexplored territory of the genome. Recently, data from the Encyclopedia of DNA Elements (ENCODE) and Roadmap Epigenomics projects have shown that many GWASs SNPs in the noncoding regions fall within regulatory elements. In this study, we developed a pipeline named functional disease-associated SNPs prediction (FDSP), to identify novel susceptibility loci for complex diseases based on the interpretation of the functional features for known disease-associated variants with machine learning. We applied our pipeline to predict novel susceptibility SNPs for type 2 diabetes (T2D) and hypertension. The predicted SNPs could explain heritability beyond that explained by GWAS-associated SNPs. Functional annotation by expression quantitative trait loci analyses showed that the target genes of the predicted SNPs were significantly enriched in T2D or hypertension-related pathways in multiple tissues. Our results suggest that combining GWASs and regulatory features data could identify additional functional susceptibility SNPs for complex diseases. We hope FDSP could help to identify novel susceptibility loci for complex diseases and solve the missing heritability problem.