Bioinformatics Core

生物信息学核心

基本信息

批准号：
10404414
负责人：
Yi-Hsiang Hsu
金额：
$ 9.07万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-01-01 至 2027-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10404414
关键词：
Adult Affect Anabolic Agents Antibodies Architecture Bioinformatics Biological Process Biology Biopsy Bone Density Bone Marrow Aspiration Bone structure Cells Center for Translational Science Activities Clinical Clinical Research Cloud Computing Computer Analysis Data Data Analyses Data Analytics Data Collection Data Set Development Environment FDA approved Female Femur Forteo Foundations Fracture Future Gene Expression Gene Expression Profile Genes Genetic Variation Genetic study Goals Human Human Genetics Human Genome International Knockout Mice Late Effects Modeling Molecular Molecular Mechanisms of Action Molecular Profiling Morphology Mouse Strains Mus National Heart, Lung, and Blood Institute Osteoblasts Osteocalcin Osteocytes Osteogenesis Osteoporosis Pathway interactions Pattern Pharmaceutical Preparations Phenotype Physiologic pulse Pilot Projects Postmenopausal Osteoporosis Postmenopause Process Quality Control Reporting Research Personnel Research Project Grants Resources Sampling Skeleton Techniques Time Trans-Omics for Precision Medicine Woman biobank bioinformatics pipeline bone bone cell cell type clinical phenotype computational platform data management data quality design fracture risk genetic association genetic variant genome sequencing human data inhibitor innovation long bone novel osteoporosis with pathological fracture parathyroid hormone (1-34)phenotypic data pre-clinical preclinical study precursor cell prevent progenitor response side effect single-cell RNA sequencing skeletal stem cell biology tibia time use transcriptome transcriptome sequencing transcriptomics treatment effect treatment strategy whole genome

项目摘要

Project Summary – Bioinformatics Core The objective of this Bioinformatics Core is to support statistical and bioinformatics analyses to study the effects of osteoporosis anabolic therapies (romosozumab, a sclerostin inhibitor, Scl- Ab) on osteoblast progenitors as well as osteocytes in clinical and pre-clinical studies with anabolic therapies. A short anabolic treatment window from Scl-Ab has been reported; in contrast to teriparatide (PTH) that has a longer anabolic window. This Bioinformatics Core will serve as the critical foundation for the research projects by analyzing cross-species data from single cell RNA-seq (scRNA-seq) and bulk RNA-seq using innovative techniques and approaches. The capabilities of the Bioinformatics Core will be enhanced by being able to leverage existing datasets of whole genome sequencing in tens thousands of human samples; and osteocyte gene expression signatures and deeply skeletal phenotyping from a unique mouse knockout dataset from our collaborators. To support Project #1, Project #2 as well as pilot projects, the Bioinformatics Core will provide statistical design, computational analysis, data quality control and management support as well as accessing to other external human genetics and bioinformatics data and resource. Specifically, in Aim 1, the Bioinformatics Core seeks to build a synergistic data management, data analytical and bioinformatics pipelines over cloud computing environment which allows interaction within investigators through data collection, data analyses, information sharing and data interpretation. In Aim 2, the Core will provide statistical and bioinformatics analyses for scRNA-seq and bulk RNA-seq generated from clinical and pre-clinical studies to identify osteoblast precursor cell clusters over time with either Scl-Ab or PTH treatments; osteoblast lineage tracing; osteoblast progenitors and osteocytes gene expression patterns; and co-expression pattern over time. In addition, cross-species integrating analysis will be conducted to identify homologous and divergent cell types between human and mice. In Aim 3, we will prioritize genes regulating bone formation and Identify molecular signatures affecting treatment effect via human gene expression (in bone biopsies) and genetic variation associated with bone phenotypes (BMD, HR-PQCT derived bone structure, fracture) in large-scale whole genome sequenced studies. In Aim 4, To further characterize skeletal function and phenotypes of the genes identified from project# and project#2 transcriptome analyses, we will utilize the existing KO mice deep phenotyping data; and generate a new KO mice strain. Ultimately, these merged analyses will generate powerfully informed, novel hypotheses regarding bone stem cell biology and responses to bone anabolic agents.

项目摘要 - 生物信息学核心该生物信息学核心的目标是支持统计和生物信息学分析研究骨质疏松症合成代谢疗法（romosozumab，一种硬化素抑制剂，Scl- Ab) 在临床和临床前研究中对成骨细胞祖细胞以及骨细胞的影响据报道，Scl-Ab 的合成代谢治疗窗口较短；与具有较长合成代谢窗口的特立帕肽 (PTH) 相比，该生物信息学核心将。通过分析跨物种数据作为研究项目的关键基础使用创新技术和方法的单细胞 RNA-seq (scRNA-seq) 和批量 RNA-seq。通过利用现有的生物信息学核心的能力将得到增强数以万计的人类样本和骨细胞的全基因组测序数据集；来自独特小鼠敲除的基因表达特征和深层骨骼表型为了支持项目 #1、项目 #2 以及试点项目，生物信息学核心将提供统计设计、计算分析、数据质量控制和管理支持以及获取其他外部人类遗传学和具体来说，在目标 1 中，生物信息学核心旨在建立一个通过云进行协同数据管理、数据分析和生物信息学管道允许研究人员通过数据收集进行交互的计算环境，在目标 2 中，核心将提供数据分析、信息共享和数据解释。对临床生成的 scRNA-seq 和bulk RNA-seq 进行统计和生物信息学分析以及临床前研究，以使用 Scl-Ab 随着时间的推移识别成骨细胞前体细胞簇或 PTH 治疗；成骨细胞谱系追踪；此外，跨物种整合。将进行分析以确定人类和不同细胞之间的同源和不同细胞类型在目标 3 中，我们将优先考虑调节骨形成的基因并识别分子。通过人类基因表达（骨活检）和遗传影响治疗效果的特征与骨表型（BMD、HR-PQCT 衍生的骨结构、骨折）相关的变异目标 4：大规模全基因组测序研究，进一步表征骨骼功能。以及从项目#和项目#2转录组分析中鉴定出的基因的表型，我们将利用现有的 KO 小鼠深度表型数据，并生成新的 KO 小鼠品系。最终，这些合并分析将产生强有力的新颖假设关于骨干细胞生物学和对骨合成代谢剂的反应。