Trans-omics integration of multi-omics studies for male osteoporosis

男性骨质疏松症多组学研究的跨组学整合

• 批准号: 9916677
• 负责人: HONG-WEN DENG
• 金额: $ 154.07万
• 依托单位: TULANE UNIVERSITY OF LOUISIANA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9916677
• 关键词: Affect; Age; Aging; Bioinformatics; Biometry; Bone Density; Cells; Clinical; Collaborations; Complex; DNA; DNA Methylation; Data; Data Analyses; Defect; Development; Disease; Dual-Energy X-Ray Absorptiometry; Elderly; Elements; Environment; Environmental Risk Factor; Epigenetic Process; Ethnic Origin; Etiology; Fatty acid glycerol esters; Feasibility Studies; Future; Gene Expression; Genes; Genetic; Genetic Markers; Genome; Genotype; Goals; Heritability; Human; Individual; Joints; Life; Limb structure; Measurement; Measures; Medical; Messenger RNA; Metabolic Bone Diseases; Methodology; Methylation; MicroRNAs; Molecular; Morbidity - disease rate; Multiomic Data; Obesity; Osteoporosis; Pathway interactions; Pattern; Phenotype; Population; Predisposition; Prevention; Preventive Intervention; Process; Proteins; Public Health; Publications; Regulation; Research; Risk; Risk Factors; Solid; Specialized Center; Specificity; Susceptibility Gene; Technology; Thinness; Time; Translating; Variant; Woman; Work; base; bioinformatics tool; bone; bone loss; bone quality; cost; druggable target; epigenome; expectation; fracture risk; gene environment interaction; genetic information; genetic testing; genetic variant; high risk; in vivo; innovation; insight; interest; mRNA Stability; male; member; men; mortality; multiple omics; novel; novel strategies; osteoporosis with pathological fracture; phenotypic data; programs; risk variant; sarcopenia; sex; targeted treatment; transcriptome

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.

总体摘要 骨质疏松症的主要特征是骨密度(BMD)低，其在晚年的风险最大 20-40岁达到的骨密度峰值有力地预测了这一点。尽管女性患骨质疏松症的风险更高，但男性 骨质疏松性骨折后的发病率和死亡率要高得多。(表观)遗传因素 大多数骨密度遗传性(&gt；85%)(特别是那些特定性别的遗传性)在很大程度上是未知的 主要是由于所使用的技术和方法的限制。关注男性骨质疏松症的研究很少。 我们的一般假设是：虽然个体组学研究(基因组/转录组/表观基因组)是有用的， 对多组学数据的综合跨组学分析将更加高效和强大，不仅 识别新的风险(表观)基因/变异，但最重要的是阐明它们在人类体内的功能。 该U19计划项目(PPG)的总体目标是最全面地识别/表征(epi- )男性骨质疏松风险的基因/环境因素及其作用机制。我们将开创一个 通过在基因组上同时研究骨质疏松风险因素的全面而新颖的方法-(DNA， 项目1)、转录组(mRNA和miRNA，项目2)和表观基因组(DNA甲基化，项目3)水平， 同时考虑环境因素(项目1-3)。我们将评估性别/种族/人口特异性 已鉴定(epi-)基因(Proj1-3)。此外，我们将进行深入的功能研究(如项目3所示) 有关特定新的骨质疏松症易感性的详细分子机制和功能确认 待发现的基因/变种。特别是，除了对个人组学数据的最先进分析之外， 项目1-3，我们将超越地平线，开发/应用创新的分析方法(核心C)来 描述不同组学内部和之间的相互作用(例如miRNA甲基化的相互作用，以及 通过DNA变异体和miRNA/甲基化对mRNA的调节)。我们将(在核心C中)创新地整合这些 跨不同组学的相互作用，以识别/表征男性骨质疏松症的(表观-)遗传变异(项目1-3)。 PPG有三个支持核心：A)行政核心；B)临床核心；以及C)生物统计和 生物信息学核心。每个核心服务于所有三个项目和/或其他核心。 确定(Epi)基因/环境因素及其在体内对人类骨密度变异的作用机制 尤其是对男性来说，这对于获得对基本分子的全面洞察是必要的，也是重要的 和潜在骨质疏松风险的环境机制，2)发现新的途径和可药物 治疗的目标；3)识别(表观-)遗传易感个体，以便未来的预防和 干预措施可以针对和基于个人的特定(表观)基因类型。 这一PPG有望为其创新开辟新天地，成为刺激 对其他复杂疾病的类似研究。生成的数据将对老龄化和医疗领域具有无价的价值 本项目所研究的细胞、表型和分子数据具有重要意义和相关性。