Osteoporosis is the most common metabolic bone disease mainly characterized by low bone mineral density (BMD) and deteriorated bone quality/strength. Peripheral blood monocytes (PBMs) may not only act as precursors of osteoclasts but also produce cytokines important for osteoclast differentiation and function, and thus represent major systemic cells for bone metabolism. DNA methylation as an important epigenetic regulator of gene expression may have significant and potentially sex-specific effects in the etiology of human complex diseases. However, the significance of global DNA methylation profiles underlying osteoporosis risk is largely unknown, particularly in males who suffer significantly higher mortality rate upon osteoporotic fractures than females. Our Hypothesis is that altered DNA methylation profiles in PBMs and the associated changes in gene expression and osteoclastogenesis contribute to variations in peak BMD and bone quality/strength in males. Our Goal/Expectation is to i) identify significant differentially methylated regions (DMRs) in PBMs associated with osteoporosis risk in Caucasian males; ii) assess the potential sex- and ethnic-generality/specificity of the significant DMRs; and iii) ascertain the DNA methylation mediated epigenetic mechanisms of osteoporosis, that is, how the DMRs regulate the expression of the target genes and subsequent osteoclastogenesis. We will accomplish the following Specific Aims: 1) Identification and validation of DMRs significantly associated with peak BMD and bone quality/strength (QCT and FEA) in Caucasian males. We will perform PBM methylome profiling analyses with double restriction-enzyme reduced representation bisulfite sequencing (dRRBS) assays in 200 discordant Caucasian males (?Discovery cohort?) at peak bone mass ages of 20-30 years old, including half with high peak BMDs and the other half with low peak BMDs, and validate the most significant DMRs in both of the ?Discovery cohort? and an independent ?Replication cohort? of 200 Caucasian males discordant for peak BMDs. 2) Evaluation of the sex-, ethnic-, and maturation stage- generality/specificity of the significant DMRs/genes. The validated DMRs/target genes will be tested in three independent BMD-discordant samples, including a) 200 African American males, b) 160 Caucasian females, and c) 160 Chinese males, and d) in 1670 US children from the Bone Mineral Density in Childhood Study. 3) In-depth functional investigation of the roles of DMRs in regulating gene expression and osteoclastogenesis. We will identify the DMR-regulated target genes by correlating the DNA methylation and the mRNA expression levels of candidate target genes in the same sets of PBMs from the total 400 Caucasian males, and conduct in vitro cell-based assays to determine the contribution of DNA methylation at these DMRs in regulating target gene expression and subsequently influencing osteoclastogenesis. The results will reveal novel and fundamental insights into the general and sex-/ethnic-/development specific epigenetic mechanisms underlying osteoporosis. The knowledge gained may ultimately lead to novel approaches to better prevention and treatment of osteoporosis.

Public Health Relevance

Osteoporosis is a serious public health problem leading to severe bone loss and increased risk of fractures in elderly subjects. The proposed study will identify differentially methylated regions (DMRs) between subjects with discordant bone mass phenotypes and reveal fundamental underlying epigenetic mechanisms of bone mass variation and osteoporosis risk. The findings will contribute to a better and more comprehensive understanding of molecular mechanisms, and thus help efficient prevention, novel drug development, and effective treatment, of osteoporosis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR069055-03
Application #
9778514
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Nicks, Kristy
Project Start
2017-05-08
Project End
2022-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Tulane University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
053785812
City
New Orleans
State
LA
Country
United States
Zip Code
70118
Pei, Yu-Fang; Hu, Wen-Zhu; Yan, Min-Wei et al. (2018) Joint study of two genome-wide association meta-analyses identified 20p12.1 and 20q13.33 for bone mineral density. Bone 110:378-385
Lin, Xu; Peng, Cheng; Greenbaum, Jonathan et al. (2018) Identifying potentially common genes between dyslipidemia and osteoporosis using novel analytical approaches. Mol Genet Genomics 293:711-723
Dong, Shan-Shan; Yao, Shi; Chen, Yi-Xiao et al. (2018) Detecting epistasis within chromatin regulatory circuitry reveals CAND2 as a novel susceptibility gene for obesity. Int J Obes (Lond) :
Lv, Wan-Qiang; Zhang, Xue; Fan, Kun et al. (2018) Genetically driven adiposity traits increase the risk of coronary artery disease independent of blood pressure, dyslipidaemia, glycaemic traits. Eur J Hum Genet 26:1547-1553
Zhao, Qi; Shen, Hui; Su, Kuan-Jui et al. (2018) Metabolomic profiles associated with bone mineral density in US Caucasian women. Nutr Metab (Lond) 15:57
Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding et al. (2018) Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies. Hum Genet 137:247-255
Zhao, Yan; Ning, Yujie; Zhang, Feng et al. (2018) PCA-based GRS analysis enhances the effectiveness for genetic correlation detection. Brief Bioinform :
Hu, Yuan; Tan, Li-Jun; Chen, Xiang-Ding et al. (2018) Identification of Novel Potentially Pleiotropic Variants Associated With Osteoporosis and Obesity Using the cFDR Method. J Clin Endocrinol Metab 103:125-138
Zhou, Yu; Gao, Yunlong; Xu, Chao et al. (2018) A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research. Sci Rep 8:668
Liu, Hui-Min; He, Jing-Yang; Zhang, Qiang et al. (2018) Improved detection of genetic loci in estimated glomerular filtration rate and type 2 diabetes using a pleiotropic cFDR method. Mol Genet Genomics 293:225-235

Showing the most recent 10 out of 27 publications