Functional relevance for associations between osteoporosis and genetic variants

<div><p>Osteoporosis is characterized by increased bone loss and deterioration of bone microarchitecture, which will lead to reduced bone strength and increased risk of fragility fractures. Previous studies have identified many genetic loci associated with osteoporosis, but functional mechanisms underlying the associations have rarely been explored. In order to explore the potential molecular functional mechanisms underlying the associations for osteoporosis, we performed integrative analyses by using the publically available datasets and resources. We searched 128 identified osteoporosis associated SNPs (<i>P</i><10⁻⁶), and 8 SNPs exert cis-regulation effects on 11 eQTL target genes. Among the 8 SNPs, 2 SNPs (<i>RPL31</i> rs2278729 and <i>LRP5</i> rs3736228) were confirmed to impact the expression of 3 genes (<i>RPL31</i>, <i>CPT1A</i> and <i>MTL5</i>) that were differentially expressed between human subjects of high BMD group and low BMD group. All of the functional evidence suggested the important functional mechanisms underlying the associations of the 2 SNPs (rs2278729 and rs3736228) and 3 genes (<i>RPL31</i>, <i>CPT1A</i> and <i>MTL5</i>) with osteoporosis. This study may provide novel insights into the functional mechanisms underlying the osteoporosis associated genetic variants, which will help us to comprehend the potential mechanisms underlying the genetic association for osteoporosis.</p></div

Differential expression analysis for eQTL target genes in OP-related cells groups.

<p>Differential expression analysis for eQTL target genes in OP-related cells groups.</p

Expression quantitative trait locus (eQTL) analysis results between SNPs and the corresponding eQTL target genes.

<p>Expression quantitative trait locus (eQTL) analysis results between SNPs and the corresponding eQTL target genes.</p

Functional relevance for associations between osteoporosis and genetic variants - Fig 1

<p><b>Predicted secondary structure of protein carrying either (A) rs3736228-C allele or (B) rs3736228-T allele.</b> A:before missense mutation; B: after missense mutation. NOTE: The arrows point the position of the missense mutation. The 50 amino acids before and after missense mutations, which are: cdgfpecddqsdeegcpvcsaaqfpcargqcvdlrlrcdgeadcqdrsdeadcdaiclpnqfrcasgqcvlikqqcdsfpdcidgsdelmceitkppsdds and cdgfpecddqsdeegcpvcsaaqfpcargqcvdlrlrcdgeadcqdrsdevdcdaiclpnqfrcasgqcvlikqqcdsfpdcidgsdelmceitkppsdds, respectively.</p

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

<div><p>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 (<i>FAM50A</i>, <i>ZNF473</i> and <i>TMEM55B</i>) 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 <i>AKT1</i>, <i>STAT3</i>, <i>STAT5A</i>, <i>FLT3</i>, 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.</p></div

The interaction module inferred in network analysis.

<p>Genes were represented by squares and connected each other with solid lines. miRNAs were represented by circles. Node size was proportional to the absolute value of the combined <i>S</i> score of integration analysis. Node color represented the strength of negative correlation between gene expression profile and DNA methylation level. The direct gene interactions using dot-dash lines between genes based on annotation from STRING database. Abbreviations: PCST (Prize Collecting Steiner Tree); STRING (Search Tool for the Retrieval of Interacting Genes).</p

Basic characteristics of study subjects.

<p>Note: BMD, bone mineral density.</p><p>Basic characteristics of study subjects.</p

Top three pathways identified by SPIA.

<p>Notes: SPIA: Signaling Pathway Impact Analysis. <i>P</i>_NDE is the <i>P</i> value of over-representation evidence, <i>P</i>_PERT is the <i>P</i> value of perturbation evidenceand P_G is the P value of combined over-representation evidence and perturbation evidence.</p><p>Top three pathways identified by SPIA.</p

9 protein coding genes and 2 miRNAs identified in integration analysis.

<p>Notes: <i>P</i>_exp is <i>P</i>-value of expression data; FDR_exp is FDR-value of expression data; <i>P</i> _methy is <i>P</i>-value of methylation data; FDR_methy is FDR-value of methylation data; <i>P</i> _inte is <i>P</i>-value of integration analysis; FDR_inte is FDR-value of integration analysis.</p><p>9 protein coding genes and 2 miRNAs identified in integration analysis.</p

Difference in height between Chinese female carriers of two vs. three copies at CNP12587.

<p>2 and 3 stands for normal and gain state, respectively.</p