Overall Abstract Osteoporosis is mainly characterized by low bone mineral density (BMD) and its risk later in life can be most powerfully predicted by peak BMD achieved at ages 20-40. Although women have higher risk to osteoporosis, men suffer much higher morbidity and mortality rates following osteoporotic fractures. The (epi-)genetic factors underlying the majority of the BMD heritability (>85%) (especially those sex-specific ones) are largely unknown mainly due to the limitation of the technology and approaches used. Studies focusing on male osteoporosis are rare. Our General Hypothesis is that: while individual omics studies (genome/transcriptome/epigenome) are useful, integrative trans-omics analyses of multi-omics data will be much more productive and more powerful, in not only identifying novel risk (epi-)genes/variants, but also most importantly illuminating their functions in vivo in humans. The Overall Goal of this U19 program project (PPG) is to most comprehensively identify/characterize (epi- )genes/environmental factors and their functional mechanisms for male osteoporosis risk. We will pioneer a comprehensive and novel approach by investigating osteoporosis risk factors simultaneously at the genome- (DNA, Proj 1), transcriptome- (mRNA and miRNA, Proj 2), and epigenome- (DNA methylation, Proj 3) levels in males, while considering environmental factors (Proj 1-3). We will assess sex/ethnicity/population specificity of the identified (epi-)genes (Proj 1-3). Furthermore, we will perform in-depth functional studies (as exemplified in Proj 3) for detailed molecular mechanisms and functional confirmation of specific novel osteoporosis susceptibility genes/variants to be discovered. Particularly, in addition to the state-of-the-art analyses of individual omics data in Proj 1-3 respectively, we will go beyond the horizon to develop/apply innovative analytical approaches (Core C) to characterize interactions within and across different omics (such as interactions for miRNA-methylation, and regulation of mRNA by DNA variants and by miRNA/methylation). We will (in Core C) innovatively integrate such interactions across various -omics to identify/characterize (epi-)genetic variants for male osteoporosis (Proj 1-3). The PPG has three supporting cores: A) Administrative Core; B) Clinical Core; and C) Biostatistics and Bioinformatics Core. Each core serves all the three projects and/or the other cores. Identifying (epi)genes/environmental factors AND their in vivo functional mechanisms for human BMD variation, especially for men, is necessary and important for 1) gaining comprehensive insights into the fundamental molecular and environmental mechanisms underlying risk of osteoporosis, 2) discovering novel pathways and druggable targets for therapeutic cures; 3) identifying (epi-)genetically susceptible individuals, so that future preventions and interventions can be targeted to and based on individuals? specific (epi-)genotypes. This PPG is expected to break new ground for its innovation, which serves as a pioneering example to stimulate similar studies of other complex diseases. The data generated will be invaluable for aging and medical fields for which the cells studied, phenotype and molecular data collected in this project are significant and relevant.

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 comprehensively identify genes and their regulatory factors that are associated with differential susceptibility to male osteoporosis. The findings will contribute to a better and more comprehensive understanding of molecular mechanisms, and thus help prevention and treatment, of osteoporosis.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Program--Cooperative Agreements (U19)
Project #
Application #
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Williams, John
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Tulane University
Biostatistics & Other Math Sci
Schools of Public Health
New Orleans
United States
Zip Code
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
Zhang, Wensheng; Flemington, Erik K; Zhang, Kun (2018) Driver gene mutations based clustering of tumors: methods and applications. Bioinformatics 34:i404-i411
Liang, Xiao; Wu, CuiYan; Zhao, Hongmou et al. (2018) Assessing the genetic correlations between early growth parameters and bone mineral density: A polygenic risk score analysis. Bone 116:301-306

Showing the most recent 10 out of 26 publications