Dataset Information

Identification and Analysis of Genes Underlying Bone Mineral Density by Integrating Microarray Data of Osteoporosis.

ABSTRACT: Osteoporosis is a kind of brittle bone disease, which is characterized by a reduction in bone mineral density (BMD). In recent years, a number of genes and pathophysiological mechanisms have been identified for osteoporosis. However, the genes associated with BMD remain to be explored. Toward this end, we integrated multiple osteoporosis microarray datasets to identify and systematically characterize BMD-related genes. By integrating the differentially expressed genes from three osteoporosis microarray datasets, 152 genes show differentially expressed between high and low BMD osteoporosis samples in at least two of the three datasets. Among them, 88 were up-regulated in high BMD samples and 64 were up-regulated in low BMD samples. The expression of ZFP36, JUNB and TMEM8A were increased at high BMD samples in all three datasets. Hub genes were further identified by co-expression network analysis. Functional enrichment analysis showed that the gene up-regulated in high BMD were enriched in immune-related functions, suggesting that the immune system plays an important role in osteoporosis. Our study explored BMD-related genes based on the integration of osteoporosis microarray data, providing guidance to other researchers from a new perspective.

SUBMITTER: Zhang H

PROVIDER: S-EPMC7481435 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Analysis of Genes Underlying Bone Mineral Density by Integrating Microarray Data of Osteoporosis.

Zhang Haihong H Feng Jinghui J Lin Zhiguo Z Wang Shuya S Wang Yan Y Dai Siming S Kong Weisi W Wang Yanli Y Zhang Zhiyi Z

Frontiers in cell and developmental biology 20200827

Osteoporosis is a kind of brittle bone disease, which is characterized by a reduction in bone mineral density (BMD). In recent years, a number of genes and pathophysiological mechanisms have been identified for osteoporosis. However, the genes associated with BMD remain to be explored. Toward this end, we integrated multiple osteoporosis microarray datasets to identify and systematically characterize BMD-related genes. By integrating the differentially expressed genes from three osteoporosis mic ...[more]

PMID: 32974344

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Project description:Osteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by liquid chromatography with tandem mass spectrometry (LC-MS/MS) in 1552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2 to 10 years later using dual-energy X-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified 27 metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (area under the curve [AUC] = 0.74 for the model with identified metabolites and risk factors versus AUC = 0.70 with risk factors alone, p = .001; net reclassification index = 0.07, p = .03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (false discovery rate [FDR] p value = .028). Furthermore, three causally related metabolites (glycine, phosphatidylcholine [PC], and triacylglycerol [TAG]) were negatively associated with FN-BMD, whereas PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).

Project description:BackgroundOsteoporosis is diagnosed by the measurement of bone mineral density, which is a highly heritable and multifactorial trait. We aimed to identify genetic loci that are associated with bone mineral density.MethodsIn this genome-wide association study, we identified the most promising of 314 075 single nucleotide polymorphisms (SNPs) in 2094 women in a UK study. We then tested these SNPs for replication in 6463 people from three other cohorts in western Europe. We also investigated allelic expression in lymphoblast cell lines. We tested the association between the replicated SNPs and osteoporotic fractures with data from two studies.FindingsWe identified genome-wide evidence for an association between bone mineral density and two SNPs (p<5x10(-8)). The SNPs were rs4355801, on chromosome 8, near to the TNFRSF11B (osteoprotegerin) gene, and rs3736228, on chromosome 11 in the LRP5 (lipoprotein-receptor-related protein) gene. A non-synonymous SNP in the LRP5 gene was associated with decreased bone mineral density (rs3736228, p=6.3x10(-12) for lumbar spine and p=1.9x10(-4) for femoral neck) and an increased risk of both osteoporotic fractures (odds ratio [OR] 1.3, 95% CI 1.09-1.52, p=0.002) and osteoporosis (OR 1.3, 1.08-1.63, p=0.008). Three SNPs near the TNFRSF11B gene were associated with decreased bone mineral density (top SNP, rs4355801: p=7.6x10(-10) for lumbar spine and p=3.3x10(-8) for femoral neck) and increased risk of osteoporosis (OR 1.2, 95% CI 1.01-1.42, p=0.038). For carriers of the risk allele at rs4355801, expression of TNFRSF11B in lymphoblast cell lines was halved (p=3.0x10(-6)). 1883 (22%) of 8557 people were at least heterozygous for these risk alleles, and these alleles had a cumulative association with bone mineral density (trend p=2.3x10(-17)). The presence of both risk alleles increased the risk of osteoporotic fractures (OR 1.3, 1.08-1.63, p=0.006) and this effect was independent of bone mineral density.InterpretationTwo gene variants of key biological proteins increase the risk of osteoporosis and osteoporotic fracture. The combined effect of these risk alleles on fractures is similar to that of most well-replicated environmental risk factors, and they are present in more than one in five white people, suggesting a potential role in screening.

Dataset Information

Identification and Analysis of Genes Underlying Bone Mineral Density by Integrating Microarray Data of Osteoporosis.

Publications

Identification and Analysis of Genes Underlying Bone Mineral Density by Integrating Microarray Data of Osteoporosis.

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